Learning Kinetic Monte Carlo Models of Condensed Phase High Temperature Chemistry from Molecular Dynamics

NASA Astrophysics Data System (ADS)

Yang, Qian; Sing-Long, Carlos; Chen, Enze; Reed, Evan

2017-06-01

Complex chemical processes, such as the decomposition of energetic materials and the chemistry of planetary interiors, are typically studied using large-scale molecular dynamics simulations that run for weeks on high performance parallel machines. These computations may involve thousands of atoms forming hundreds of molecular species and undergoing thousands of reactions. It is natural to wonder whether this wealth of data can be utilized to build more efficient, interpretable, and predictive models. In this talk, we will use techniques from statistical learning to develop a framework for constructing Kinetic Monte Carlo (KMC) models from molecular dynamics data. We will show that our KMC models can not only extrapolate the behavior of the chemical system by as much as an order of magnitude in time, but can also be used to study the dynamics of entirely different chemical trajectories with a high degree of fidelity. Then, we will discuss three different methods for reducing our learned KMC models, including a new and efficient data-driven algorithm using L1-regularization. We demonstrate our framework throughout on a system of high-temperature high-pressure liquid methane, thought to be a major component of gas giant planetary interiors.

Building a kinetic Monte Carlo model with a chosen accuracy.

PubMed

Bhute, Vijesh J; Chatterjee, Abhijit

2013-06-28

The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials length and time scales. The KMC dynamics is erroneous when atomic processes that are relevant to the dynamics are missing from the KMC model. Recently, we had developed for the first time an error measure for KMC in Bhute and Chatterjee [J. Chem. Phys. 138, 084103 (2013)]. The error measure, which is given in terms of the probability that a missing process will be selected in the correct dynamics, requires estimation of the missing rate. In this work, we present an improved procedure for estimating the missing rate. The estimate found using the new procedure is within an order of magnitude of the correct missing rate, unlike our previous approach where the estimate was larger by orders of magnitude. This enables one to find the error in the KMC model more accurately. In addition, we find the time for which the KMC model can be used before a maximum error in the dynamics has been reached.

Effect of nonlinearity in hybrid kinetic Monte Carlo-continuum models.

PubMed

Balter, Ariel; Lin, Guang; Tartakovsky, Alexandre M

2012-01-01

Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a kinetic Monte Carlo (KMC) model for a surface to a finite-difference model for bulk diffusion in a continuous domain. We consider two representative problems that validate a hybrid method and show that this method captures the combined effects of nonlinearity and stochasticity. We first validate a simple deposition-dissolution model with a linear rate showing that the KMC-continuum hybrid agrees with both a fully deterministic model and its analytical solution. We then study a deposition-dissolution model including competitive adsorption, which leads to a nonlinear rate, and show that in this case the KMC-continuum hybrid and fully deterministic simulations do not agree. However, we are able to identify the difference as a natural result of the stochasticity coming from the KMC surface process. Because KMC captures inherent fluctuations, we consider it to be more realistic than a purely deterministic model. Therefore, we consider the KMC-continuum hybrid to be more representative of a real system.

On-the-Fly Kinetic Monte Carlo Simulation of Aqueous Phase Advanced Oxidation Processes.

PubMed

Guo, Xin; Minakata, Daisuke; Crittenden, John

2015-08-04

We have developed an on-the-fly kinetic Monte Carlo (KMC) model to predict the degradation mechanisms and fates of intermediates and byproducts that are produced during aqueous-phase advanced oxidation processes (AOPs). The on-the-fly KMC model is composed of a reaction pathway generator, a reaction rate constant estimator, a mechanistic reduction module, and a KMC solver. The novelty of this work is that we develop the pathway as we march forward in time rather than developing the pathway before we use the KMC method to solve the equations. As a result, we have fewer reactions to consider, and we have greater computational efficiency. We have verified this on-the-fly KMC model for the degradation of polyacrylamide (PAM) using UV light and titanium dioxide (i.e., UV/TiO2). Using the on-the-fly KMC model, we were able to predict the time-dependent profiles of the average molecular weight for PAM. The model provided detailed and quantitative insights into the time evolution of the molecular weight distribution and reaction mechanism. We also verified our on-the-fly KMC model for the destruction of (1) acetone, (2) trichloroethylene (TCE), and (3) polyethylene glycol (PEG) for the ultraviolet light and hydrogen peroxide AOP. We demonstrated that the on-the-fly KMC model can achieve the same accuracy as the computer-based first-principles KMC (CF-KMC) model, which has already been validated in our earlier work. The on-the-fly KMC is particularly suitable for molecules with large molecular weights (e.g., polymers) because the degradation mechanisms for large molecules can result in hundreds of thousands to even millions of reactions. The ordinary differential equations (ODEs) that describe the degradation pathways cannot be solved using traditional numerical methods, but the KMC can solve these equations.

Numerical simulation of photocurrent generation in bilayer organic solar cells: Comparison of master equation and kinetic Monte Carlo approaches

NASA Astrophysics Data System (ADS)

Casalegno, Mosè; Bernardi, Andrea; Raos, Guido

2013-07-01

Numerical approaches can provide useful information about the microscopic processes underlying photocurrent generation in organic solar cells (OSCs). Among them, the Kinetic Monte Carlo (KMC) method is conceptually the simplest, but computationally the most intensive. A less demanding alternative is potentially represented by so-called Master Equation (ME) approaches, where the equations describing particle dynamics rely on the mean-field approximation and their solution is attained numerically, rather than stochastically. The description of charge separation dynamics, the treatment of electrostatic interactions and numerical stability are some of the key issues which have prevented the application of these methods to OSC modelling, despite of their successes in the study of charge transport in disordered system. Here we describe a three-dimensional ME approach to photocurrent generation in OSCs which attempts to deal with these issues. The reliability of the proposed method is tested against reference KMC simulations on bilayer heterojunction solar cells. Comparison of the current-voltage curves shows that the model well approximates the exact result for most devices. The largest deviations in current densities are mainly due to the adoption of the mean-field approximation for electrostatic interactions. The presence of deep traps, in devices characterized by strong energy disorder, may also affect result quality. Comparison of the simulation times reveals that the ME algorithm runs, on the average, one order of magnitude faster than KMC.

Prediction of La0.6Sr0.4Co0.2Fe0.8O3 cathode microstructures during sintering: Kinetic Monte Carlo (KMC) simulations calibrated by artificial neural networks

NASA Astrophysics Data System (ADS)

Yan, Zilin; Kim, Yongtae; Hara, Shotaro; Shikazono, Naoki

2017-04-01

The Potts Kinetic Monte Carlo (KMC) model, proven to be a robust tool to study all stages of sintering process, is an ideal tool to analyze the microstructure evolution of electrodes in solid oxide fuel cells (SOFCs). Due to the nature of this model, the input parameters of KMC simulations such as simulation temperatures and attempt frequencies are difficult to identify. We propose a rigorous and efficient approach to facilitate the input parameter calibration process using artificial neural networks (ANNs). The trained ANN reduces drastically the number of trial-and-error of KMC simulations. The KMC simulation using the calibrated input parameters predicts the microstructures of a La0.6Sr0.4Co0.2Fe0.8O3 cathode material during sintering, showing both qualitative and quantitative congruence with real 3D microstructures obtained by focused ion beam scanning electron microscopy (FIB-SEM) reconstruction.

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.

A kinetic Monte Carlo simulation method of van der Waals epitaxy for atomistic nucleation-growth processes of transition metal dichalcogenides.

PubMed

Nie, Yifan; Liang, Chaoping; Cha, Pil-Ryung; Colombo, Luigi; Wallace, Robert M; Cho, Kyeongjae

2017-06-07

Controlled growth of crystalline solids is critical for device applications, and atomistic modeling methods have been developed for bulk crystalline solids. Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW) heterostructures has not yet been developed. Specifically, the growth of single-layered transition metal dichalcogenides (TMDs) is currently facing tremendous challenges, and a detailed understanding based on KMC simulations would provide critical guidance to enable controlled growth of vdW heterostructures. In this work, a KMC simulation method is developed for the growth modeling on the vdW epitaxy of TMDs. The KMC method has introduced full material parameters for TMDs in bottom-up synthesis: metal and chalcogen adsorption/desorption/diffusion on substrate and grown TMD surface, TMD stacking sequence, chalcogen/metal ratio, flake edge diffusion and vacancy diffusion. The KMC processes result in multiple kinetic behaviors associated with various growth behaviors observed in experiments. Different phenomena observed during vdW epitaxy process are analysed in terms of complex competitions among multiple kinetic processes. The KMC method is used in the investigation and prediction of growth mechanisms, which provide qualitative suggestions to guide experimental study.

Information criteria for quantifying loss of reversibility in parallelized KMC

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

Gourgoulias, Konstantinos, E-mail: gourgoul@math.umass.edu; Katsoulakis, Markos A., E-mail: markos@math.umass.edu; Rey-Bellet, Luc, E-mail: luc@math.umass.edu

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot bemore » computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.« less

Information criteria for quantifying loss of reversibility in parallelized KMC

NASA Astrophysics Data System (ADS)

Gourgoulias, Konstantinos; Katsoulakis, Markos A.; Rey-Bellet, Luc

2017-01-01

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

Kinetic Monte Carlo simulations of thermally activated magnetization reversal in dual-layer Exchange Coupled Composite recording media

NASA Astrophysics Data System (ADS)

Plumer, M. L.; Almudallal, A. M.; Mercer, J. I.; Whitehead, J. P.; Fal, T. J.

The kinetic Monte Carlo (KMC) method developed for thermally activated magnetic reversal processes in single-layer recording media has been extended to study dual-layer Exchange Coupled Composition (ECC) media used in current and next generations of disc drives. The attempt frequency is derived from the Langer formalism with the saddle point determined using a variant of Bellman Ford algorithm. Complication (such as stagnation) arising from coupled grains having metastable states are addressed. MH-hysteresis loops are calculated over a wide range of anisotropy ratios, sweep rates and inter-layer coupling parameter. Results are compared with standard micromagnetics at fast sweep rates and experimental results at slow sweep rates.

Simulations of Quantum Dot Growth on Semiconductor Surfaces: Morphological Design of Sensor Concepts

DTIC Science & Technology

2008-12-01

size equalization can be clearly illustrated during the growth process. In this work we develop a fast multiscale 3D kinetic Monte Carlo ( KMC ) QD...model will provide an attractive means for producing predictably ordered nanostructures. MODEL DESCRIPTION The 3D layer-by-layer KMC growth model...Voter, 2001) and KMC simulation experience (Pan et al., 2004; Pan et al., 2006; Meixner et al, 2003) in 2D, we therefore propose the following simple

Empirical force field-based kinetic Monte Carlo simulation of precipitate evolution and growth in Al-Cu alloys

NASA Astrophysics Data System (ADS)

Joshi, Kaushik; Chaudhuri, Santanu

2016-10-01

Ability to accelerate the morphological evolution of nanoscale precipitates is a fundamental challenge for atomistic simulations. Kinetic Monte Carlo (KMC) methodology is an effective approach for accelerating the evolution of nanoscale systems that are dominated by so-called rare events. The quality and accuracy of energy landscape used in KMC calculations can be significantly improved using DFT-informed interatomic potentials. Using newly developed computational framework that uses molecular simulator LAMMPS as a library function inside KMC solver SPPARKS, we investigated formation and growth of Guiner-Preston (GP) zones in dilute Al-Cu alloys at different temperature and copper concentrations. The KMC simulations with angular dependent potential (ADP) predict formation of coherent disc-shaped monolayers of copper atoms (GPI zones) in early stage. Such monolayers are then gradually transformed into energetically favored GPII phase that has two aluminum layers sandwiched between copper layers. We analyzed the growth kinetics of KMC trajectory using Johnson-Mehl-Avrami (JMA) theory and obtained a phase transformation index close to 1.0. In the presence of grain boundaries, the KMC calculations predict the segregation of copper atoms near the grain boundaries instead of formation of GP zones. The computational framework presented in this work is based on open source potentials and MD simulator and can predict morphological changes during the evolution of the alloys in the bulk and around grain boundaries.

A statistical approach to develop a detailed soot growth model using PAH characteristics

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

Raj, Abhijeet; Celnik, Matthew; Shirley, Raphael

A detailed PAH growth model is developed, which is solved using a kinetic Monte Carlo algorithm. The model describes the structure and growth of planar PAH molecules, and is referred to as the kinetic Monte Carlo-aromatic site (KMC-ARS) model. A detailed PAH growth mechanism based on reactions at radical sites available in the literature, and additional reactions obtained from quantum chemistry calculations are used to model the PAH growth processes. New rates for the reactions involved in the cyclodehydrogenation process for the formation of 6-member rings on PAHs are calculated in this work based on density functional theory simulations. Themore » KMC-ARS model is validated by comparing experimentally observed ensembles on PAHs with the computed ensembles for a C{sub 2}H{sub 2} and a C{sub 6}H{sub 6} flame at different heights above the burner. The motivation for this model is the development of a detailed soot particle population balance model which describes the evolution of an ensemble of soot particles based on their PAH structure. However, at present incorporating such a detailed model into a population balance is computationally unfeasible. Therefore, a simpler model referred to as the site-counting model has been developed, which replaces the structural information of the PAH molecules by their functional groups augmented with statistical closure expressions. This closure is obtained from the KMC-ARS model, which is used to develop correlations and statistics in different flame environments which describe such PAH structural information. These correlations and statistics are implemented in the site-counting model, and results from the site-counting model and the KMC-ARS model are in good agreement. Additionally the effect of steric hindrance in large PAH structures is investigated and correlations for sites unavailable for reaction are presented. (author)« less

Generating relevant kinetic Monte Carlo catalogs using temperature accelerated dynamics with control over the accuracy

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

Chatterjee, Abhijit; Voter, Arthur

2009-01-01

We develop a variation of the temperature accelerated dynamics (TAD) method, called the p-TAD method, that efficiently generates an on-the-fly kinetic Monte Carlo (KMC) process catalog with control over the accuracy of the catalog. It is assumed that transition state theory is valid. The p-TAD method guarantees that processes relevant at the timescales of interest to the simulation are present in the catalog with a chosen confidence. A confidence measure associated with the process catalog is derived. The dynamics is then studied using the process catalog with the KMC method. Effective accuracy of a p-TAD calculation is derived when amore » KMC catalog is reused for conditions different from those the catalog was originally generated for. Different KMC catalog generation strategies that exploit the features of the p-TAD method and ensure higher accuracy and/or computational efficiency are presented. The accuracy and the computational requirements of the p-TAD method are assessed. Comparisons to the original TAD method are made. As an example, we study dynamics in sub-monolayer Ag/Cu(110) at the time scale of seconds using the p-TAD method. It is demonstrated that the p-TAD method overcomes several challenges plaguing the conventional KMC method.« less

Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

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

Chatterjee, Abhijit; Vlachos, Dionisios G.

The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less

Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling

NASA Astrophysics Data System (ADS)

Núñez, M.; Robie, T.; Vlachos, D. G.

2017-10-01

Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111).

Enabling Microscopic Simulators to Perform System Level Tasks: A System-Identification Based, Closure-on-Demand Toolkit for Multiscale Simulation Stability/Bifurcation Analysis, Optimization and Control

DTIC Science & Technology

2006-10-01

The objective was to construct a bridge between existing and future microscopic simulation codes ( kMC , MD, MC, BD, LB etc.) and traditional, continuum...kinetic Monte Carlo, kMC , equilibrium MC, Lattice-Boltzmann, LB, Brownian Dynamics, BD, or general agent-based, AB) simulators. It also, fortuitously...cond-mat/0310460 at arXiv.org. 27. Coarse Projective kMC Integration: Forward/Reverse Initial and Boundary Value Problems", R. Rico-Martinez, C. W

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

PubMed

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

PubMed Central

Sing-Long, Carlos A.

2017-01-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates. PMID:28989618

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

DOE PAGES

Yang, Qian; Sing-Long, Carlos A.; Reed, Evan J.

2017-06-19

Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our methodmore » on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.« less

Integrated Multiscale Modeling of Molecular Computing Devices. Final Report

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

Tim Schulze

2012-11-01

The general theme of this research has been to expand the capabilities of a simulation technique, Kinetic Monte Carlo (KMC) and apply it to study self-assembled nano-structures on epitaxial thin films. KMC simulates thin film growth and evolution by replacing the detailed dynamics of the system's evolution, which might otherwise be studied using molecular dynamics, with an appropriate stochastic process.

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

KMC 3: counting and manipulating k-mer statistics.

PubMed

Kokot, Marek; Dlugosz, Maciej; Deorowicz, Sebastian

2017-09-01

Counting all k -mers in a given dataset is a standard procedure in many bioinformatics applications. We introduce KMC3, a significant improvement of the former KMC2 algorithm together with KMC tools for manipulating k -mer databases. Usefulness of the tools is shown on a few real problems. Program is freely available at http://sun.aei.polsl.pl/REFRESH/kmc . sebastian.deorowicz@polsl.pl. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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.

kmos: A lattice kinetic Monte Carlo framework

NASA Astrophysics Data System (ADS)

Hoffmann, Max J.; Matera, Sebastian; Reuter, Karsten

2014-07-01

Kinetic Monte Carlo (kMC) simulations have emerged as a key tool for microkinetic modeling in heterogeneous catalysis and other materials applications. Systems, where site-specificity of all elementary reactions allows a mapping onto a lattice of discrete active sites, can be addressed within the particularly efficient lattice kMC approach. To this end we describe the versatile kmos software package, which offers a most user-friendly implementation, execution, and evaluation of lattice kMC models of arbitrary complexity in one- to three-dimensional lattice systems, involving multiple active sites in periodic or aperiodic arrangements, as well as site-resolved pairwise and higher-order lateral interactions. Conceptually, kmos achieves a maximum runtime performance which is essentially independent of lattice size by generating code for the efficiency-determining local update of available events that is optimized for a defined kMC model. For this model definition and the control of all runtime and evaluation aspects kmos offers a high-level application programming interface. Usage proceeds interactively, via scripts, or a graphical user interface, which visualizes the model geometry, the lattice occupations and rates of selected elementary reactions, while allowing on-the-fly changes of simulation parameters. We demonstrate the performance and scaling of kmos with the application to kMC models for surface catalytic processes, where for given operation conditions (temperature and partial pressures of all reactants) central simulation outcomes are catalytic activity and selectivities, surface composition, and mechanistic insight into the occurrence of individual elementary processes in the reaction network.

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.

Effect of Nonlinearity in Hybrid Kinetic Monte Carlo-Continuum Models

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

Balter, Ariel I.; Lin, Guang; Tartakovsky, Alexandre M.

2012-04-23

Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a KMC model for a surface to a finite difference model for bulk diffusion in a continuous domain. We consider two representative problems that validate a hybrid method and also show that this method captures the combined effects of nonlinearity and stochasticity. We first validate a simple deposition/dissolution model with a linear rate showing that the KMC-continuum hybrid agrees with both a fully deterministic model and its analytical solution. We then study a deposition/dissolution model including competitive adsorption, which leadsmore » to a nonlinear rate, and show that, in this case, the KMC-continuum hybrid and fully deterministic simulations do not agree. However, we are able to identify the difference as a natural result of the stochasticity coming from the KMC surface process. Because KMC captures inherent fluctuations, we consider it to be more realistic than a purely deterministic model. Therefore, we consider the KMC-continuum hybrid to be more representative of a real system.« less

Theoretical study of the ammonia nitridation rate on an Fe (100) surface: a combined density functional theory and kinetic Monte Carlo study.

PubMed

Yeo, Sang Chul; Lo, Yu Chieh; Li, Ju; Lee, Hyuck Mo

2014-10-07

Ammonia (NH3) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (Eb) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (Eb) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH3 nitridation rate on the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH3 nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH3 nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH3 nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.

Comparing kinetic Monte Carlo and thin-film modeling of transversal instabilities of ridges on patterned substrates

NASA Astrophysics Data System (ADS)

Tewes, Walter; Buller, Oleg; Heuer, Andreas; Thiele, Uwe; Gurevich, Svetlana V.

2017-03-01

We employ kinetic Monte Carlo (KMC) simulations and a thin-film continuum model to comparatively study the transversal (i.e., Plateau-Rayleigh) instability of ridges formed by molecules on pre-patterned substrates. It is demonstrated that the evolution of the occurring instability qualitatively agrees between the two models for a single ridge as well as for two weakly interacting ridges. In particular, it is shown for both models that the instability occurs on well defined length and time scales which are, for the KMC model, significantly larger than the intrinsic scales of thermodynamic fluctuations. This is further evidenced by the similarity of dispersion relations characterizing the linear instability modes.

Kinetic Activation-Relaxation Technique and Self-Evolving Atomistic Kinetic Monte Carlo: Comparison of on-the-fly kinetic Monte Carlo algorithms

DOE PAGES

Beland, Laurent Karim; Osetskiy, Yury N.; Stoller, Roger E.; ...

2015-02-07

Here, we present a comparison of the Kinetic Activation–Relaxation Technique (k-ART) and the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC), two off-lattice, on-the-fly Kinetic Monte Carlo (KMC) techniques that were recently used to solve several materials science problems. We show that if the initial displacements are localized the dimer method and the Activation–Relaxation Technique nouveau provide similar performance. We also show that k-ART and SEAKMC, although based on different approximations, are in agreement with each other, as demonstrated by the examples of 50 vacancies in a 1950-atom Fe box and of interstitial loops in 16,000-atom boxes. Generally speaking, k-ART’s treatment ofmore » geometry and flickers is more flexible, e.g. it can handle amorphous systems, and rigorous than SEAKMC’s, while the later’s concept of active volumes permits a significant speedup of simulations for the systems under consideration and therefore allows investigations of processes requiring large systems that are not accessible if not localizing calculations.« less

An exact and efficient first passage time algorithm for reaction-diffusion processes on a 2D-lattice

NASA Astrophysics Data System (ADS)

Bezzola, Andri; Bales, Benjamin B.; Alkire, Richard C.; Petzold, Linda R.

2014-01-01

We present an exact and efficient algorithm for reaction-diffusion-nucleation processes on a 2D-lattice. The algorithm makes use of first passage time (FPT) to replace the computationally intensive simulation of diffusion hops in KMC by larger jumps when particles are far away from step-edges or other particles. Our approach computes exact probability distributions of jump times and target locations in a closed-form formula, based on the eigenvectors and eigenvalues of the corresponding 1D transition matrix, maintaining atomic-scale resolution of resulting shapes of deposit islands. We have applied our method to three different test cases of electrodeposition: pure diffusional aggregation for large ranges of diffusivity rates and for simulation domain sizes of up to 4096×4096 sites, the effect of diffusivity on island shapes and sizes in combination with a KMC edge diffusion, and the calculation of an exclusion zone in front of a step-edge, confirming statistical equivalence to standard KMC simulations. The algorithm achieves significant speedup compared to standard KMC for cases where particles diffuse over long distances before nucleating with other particles or being captured by larger islands.

An exact and efficient first passage time algorithm for reaction–diffusion processes on a 2D-lattice

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

Bezzola, Andri, E-mail: andri.bezzola@gmail.com; Bales, Benjamin B., E-mail: bbbales2@gmail.com; Alkire, Richard C., E-mail: r-alkire@uiuc.edu

2014-01-01

We present an exact and efficient algorithm for reaction–diffusion–nucleation processes on a 2D-lattice. The algorithm makes use of first passage time (FPT) to replace the computationally intensive simulation of diffusion hops in KMC by larger jumps when particles are far away from step-edges or other particles. Our approach computes exact probability distributions of jump times and target locations in a closed-form formula, based on the eigenvectors and eigenvalues of the corresponding 1D transition matrix, maintaining atomic-scale resolution of resulting shapes of deposit islands. We have applied our method to three different test cases of electrodeposition: pure diffusional aggregation for largemore » ranges of diffusivity rates and for simulation domain sizes of up to 4096×4096 sites, the effect of diffusivity on island shapes and sizes in combination with a KMC edge diffusion, and the calculation of an exclusion zone in front of a step-edge, confirming statistical equivalence to standard KMC simulations. The algorithm achieves significant speedup compared to standard KMC for cases where particles diffuse over long distances before nucleating with other particles or being captured by larger islands.« less

"First-principles" kinetic Monte Carlo simulations revisited: CO oxidation over RuO2 (110).

PubMed

Hess, Franziska; Farkas, Attila; Seitsonen, Ari P; Over, Herbert

2012-03-15

First principles-based kinetic Monte Carlo (kMC) simulations are performed for the CO oxidation on RuO(2) (110) under steady-state reaction conditions. The simulations include a set of elementary reaction steps with activation energies taken from three different ab initio density functional theory studies. Critical comparison of the simulation results reveals that already small variations in the activation energies lead to distinctly different reaction scenarios on the surface, even to the point where the dominating elementary reaction step is substituted by another one. For a critical assessment of the chosen energy parameters, it is not sufficient to compare kMC simulations only to experimental turnover frequency (TOF) as a function of the reactant feed ratio. More appropriate benchmarks for kMC simulations are the actual distribution of reactants on the catalyst's surface during steady-state reaction, as determined by in situ infrared spectroscopy and in situ scanning tunneling microscopy, and the temperature dependence of TOF in the from of Arrhenius plots. Copyright © 2012 Wiley Periodicals, Inc.

Theoretical study of the ammonia nitridation rate on an Fe (100) surface: A combined density functional theory and kinetic Monte Carlo study

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

Yeo, Sang Chul; Lee, Hyuck Mo, E-mail: hmlee@kaist.ac.kr; Lo, Yu Chieh

2014-10-07

Ammonia (NH{sub 3}) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (E{sub b}) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (E{sub b}) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH{sub 3} nitridation rate onmore » the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH{sub 3} nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH{sub 3} nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH{sub 3} nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.« less

A new class of accelerated kinetic Monte Carlo algorithms

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

Bulatov, V V; Oppelstrup, T; Athenes, M

2011-11-30

Kinetic (aka dynamic) Monte Carlo (KMC) is a powerful method for numerical simulations of time dependent evolution applied in a wide range of contexts including biology, chemistry, physics, nuclear sciences, financial engineering, etc. Generally, in a KMC the time evolution takes place one event at a time, where the sequence of events and the time intervals between them are selected (or sampled) using random numbers. While details of the method implementation vary depending on the model and context, there exist certain common issues that limit KMC applicability in almost all applications. Among such is the notorious 'flicker problem' where themore » same states of the systems are repeatedly visited but otherwise no essential evolution is observed. In its simplest form the flicker problem arises when two states are connected to each other by transitions whose rates far exceed the rates of all other transitions out of the same two states. In such cases, the model will endlessly hop between the two states otherwise producing no meaningful evolution. In most situation of practical interest, the trapping cluster includes more than two states making the flicker somewhat more difficult to detect and to deal with. Several methods have been proposed to overcome or mitigate the flicker problem, exactly [1-3] or approximately [4,5]. Of the exact methods, the one proposed by Novotny [1] is perhaps most relevant to our research. Novotny formulates the problem of escaping from a trapping cluster as a Markov system with absorbing states. Given an initial state inside the cluster, it is in principle possible to solve the Master Equation for the time dependent probabilities to find the walker in a given state (transient or absorbing) of the cluster at any time in the future. Novotny then proceeds to demonstrate implementation of his general method to trapping clusters containing the initial state plus one or two transient states and all of their absorbing states. Similar methods have been subsequently proposed in [refs] but applied in a different context. The most serious deficiency of the earlier methods is that size of the trapping cluster size is fixed and often too small to bring substantial simulation speedup. Furthermore, the overhead associated with solving for the probability distribution on the trapping cluster sometimes makes such simulations less efficient than the standard KMC. Here we report on a general and exact accelerated kinetic Monte Carlo algorithm generally applicable to arbitrary Markov models1. Two different implementations are attempted both based on incremental expansion of trapping sub-set of Markov states: (1) numerical solution of the Master Equation with absorbing states and (2) incremental graph reduction followed by randomization. Of the two implementations, the 2nd one performs better allowing, for the first time, to overcome trapping basins spanning several million Markov states. The new method is used for simulations of anomalous diffusion on a 2D substrate and of the kinetics of diffusive 1st order phase transformations in binary alloys. Depending on temperature and (alloy) super-saturation conditions, speedups of 3 to 7 orders of magnitude are demonstrated, with no compromise of simulation accuracy.« less

Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions

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

Nielsen, Jens; D’Avezac, Mayeul; Hetherington, James

2013-12-14

Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. Moremore » recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.« less

Simulating complex atomistic processes: On-the-fly kinetic Monte Carlo scheme with selective active volumes

NASA Astrophysics Data System (ADS)

Xu, Haixuan; Osetsky, Yury N.; Stoller, Roger E.

2011-10-01

An accelerated atomistic kinetic Monte Carlo (KMC) approach for evolving complex atomistic structures has been developed. The method incorporates on-the-fly calculations of transition states (TSs) with a scheme for defining active volumes (AVs) in an off-lattice (relaxed) system. In contrast to conventional KMC models that require all reactions to be predetermined, this approach is self-evolving and any physically relevant motion or reaction may occur. Application of this self-evolving atomistic kinetic Monte Carlo (SEAK-MC) approach is illustrated by predicting the evolution of a complex defect configuration obtained in a molecular dynamics (MD) simulation of a displacement cascade in Fe. Over much longer times, it was shown that interstitial clusters interacting with other defects may change their structure, e.g., from glissile to sessile configuration. The direct comparison with MD modeling confirms the atomistic fidelity of the approach, while the longer time simulation demonstrates the unique capability of the model.

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.

Kinetic Monte Carlo simulations of excitation density dependent scintillation in CsI and CsI(Tl)

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

Wang, Zhiguo; Williams, Richard; Grim, Joel

2013-08-15

Nonlinear quenching of electron-hole pairs in the denser regions of ionization tracks created by γ-ray and high-energy electrons is a likely cause of the light yield nonproportionality of many inorganic scintillators. Therefore, kinetic Monte Carlo (KMC) simulations were carried out to investigate the scintillation properties of pure and thallium-doped CsI as a function of electron-hole pair density. The availability of recent experimental data on the excitation density dependence of the light yield of CsI following ultraviolet excitation allowed for an improved parameterization of the interactions between self-trapped excitons (STE) in the KMC model via dipole-dipole Förster transfer. The KMC simulationsmore » reveal that nonlinear quenching occurs very rapidly (within a few picoseconds) in the early stages of the scintillation process. In addition, the simulations predict that the concentration of thallium activators can affect the extent of nonlinear quenching as it has a direct influence on the STE density through STE dissociation and electron scavenging. This improved model will enable more realistic simulations of the nonproportional γ-ray and electron response of inorganic scintillators.« less

Kinetic Monte Carlo simulation of dopant-defect systems under submicrosecond laser thermal processes

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

Fisicaro, G.; Pelaz, Lourdes; Lopez, P.

2012-11-06

An innovative Kinetic Monte Carlo (KMC) code has been developed, which rules the post-implant kinetics of the defects system in the extremely far-from-the equilibrium conditions caused by the laser irradiation close to the liquid-solid interface. It considers defect diffusion, annihilation and clustering. The code properly implements, consistently to the stochastic formalism, the fast varying local event rates related to the thermal field T(r,t) evolution. This feature of our numerical method represents an important advancement with respect to current state of the art KMC codes. The reduction of the implantation damage and its reorganization in defect aggregates are studied as amore » function of the process conditions. Phosphorus activation efficiency, experimentally determined in similar conditions, has been related to the emerging damage scenario.« less

Determination of the effective diffusivity of water in a poly (methyl methacrylate) membrane containing carbon nanotubes using kinetic Monte Carlo simulations.

PubMed

Mermigkis, Panagiotis G; Tsalikis, Dimitrios G; Mavrantzas, Vlasis G

2015-10-28

A kinetic Monte Carlo (kMC) simulation algorithm is developed for computing the effective diffusivity of water molecules in a poly(methyl methacrylate) (PMMA) matrix containing carbon nanotubes (CNTs) at several loadings. The simulations are conducted on a cubic lattice to the bonds of which rate constants are assigned governing the elementary jump events of water molecules from one lattice site to another. Lattice sites belonging to PMMA domains of the membrane are assigned different rates than lattice sites belonging to CNT domains. Values of these two rate constants are extracted from available numerical data for water diffusivity within a PMMA matrix and a CNT pre-computed on the basis of independent atomistic molecular dynamics simulations, which show that water diffusivity in CNTs is 3 orders of magnitude faster than in PMMA. Our discrete-space, continuum-time kMC simulation results for several PMMA-CNT nanocomposite membranes (characterized by different values of CNT length L and diameter D and by different loadings of the matrix in CNTs) demonstrate that the overall or effective diffusivity, D(eff), of water in the entire polymeric membrane is of the same order of magnitude as its diffusivity in PMMA domains and increases only linearly with the concentration C (vol. %) in nanotubes. For a constant value of the concentration C, D(eff) is found to vary practically linearly also with the CNT aspect ratio L/D. The kMC data allow us to propose a simple bilinear expression for D(eff) as a function of C and L/D that can describe the numerical data for water mobility in the membrane extremely accurately. Additional simulations with two different CNT configurations (completely random versus aligned) show that CNT orientation in the polymeric matrix has only a minor effect on D(eff) (as long as CNTs do not fully penetrate the membrane). We have also extensively analyzed and quantified sublinear (anomalous) diffusive phenomena over small to moderate times and correlated them with the time needed for penetrant water molecules to explore the available large, fast-diffusing CNT pores before Fickian diffusion is reached.

Determination of the effective diffusivity of water in a poly (methyl methacrylate) membrane containing carbon nanotubes using kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Mermigkis, Panagiotis G.; Tsalikis, Dimitrios G.; Mavrantzas, Vlasis G.

2015-10-01

A kinetic Monte Carlo (kMC) simulation algorithm is developed for computing the effective diffusivity of water molecules in a poly(methyl methacrylate) (PMMA) matrix containing carbon nanotubes (CNTs) at several loadings. The simulations are conducted on a cubic lattice to the bonds of which rate constants are assigned governing the elementary jump events of water molecules from one lattice site to another. Lattice sites belonging to PMMA domains of the membrane are assigned different rates than lattice sites belonging to CNT domains. Values of these two rate constants are extracted from available numerical data for water diffusivity within a PMMA matrix and a CNT pre-computed on the basis of independent atomistic molecular dynamics simulations, which show that water diffusivity in CNTs is 3 orders of magnitude faster than in PMMA. Our discrete-space, continuum-time kMC simulation results for several PMMA-CNT nanocomposite membranes (characterized by different values of CNT length L and diameter D and by different loadings of the matrix in CNTs) demonstrate that the overall or effective diffusivity, Deff, of water in the entire polymeric membrane is of the same order of magnitude as its diffusivity in PMMA domains and increases only linearly with the concentration C (vol. %) in nanotubes. For a constant value of the concentration C, Deff is found to vary practically linearly also with the CNT aspect ratio L/D. The kMC data allow us to propose a simple bilinear expression for Deff as a function of C and L/D that can describe the numerical data for water mobility in the membrane extremely accurately. Additional simulations with two different CNT configurations (completely random versus aligned) show that CNT orientation in the polymeric matrix has only a minor effect on Deff (as long as CNTs do not fully penetrate the membrane). We have also extensively analyzed and quantified sublinear (anomalous) diffusive phenomena over small to moderate times and correlated them with the time needed for penetrant water molecules to explore the available large, fast-diffusing CNT pores before Fickian diffusion is reached.

A computational atomistic study of the relaxation of ion-bombarded c-Si on experimental time-scales: an application of the kinetic Activation Relaxation Technique

NASA Astrophysics Data System (ADS)

Béland, Laurent Karim; Mousseau, Normand

2012-02-01

The kinetic activation relaxation technique (kinetic ART) method, an off-lattice, self-learning kinetic Monte Carlo (KMC) algorithm with on-the-fly event search,ootnotetextL. K. B'eland, P. Brommer, F. El-Mellouhi, J.-F. Joly and N. Mousseau, Phys. Rev. E 84, 046704 (2011). is used to study the relaxation of c-Si after Si^- bombardment at 3 keV. We describe the evolution of the damaged areas at room-temperature and above for periods of the order of seconds, treating long-range elastic deformations exactly. We assess the stability of the nanoscale structures formed by the damage cascade and the mechanisms that govern post-implantation annealing.

Kinetic Monte Carlo Simulations of Scintillation Processes in NaI(Tl)

NASA Astrophysics Data System (ADS)

Kerisit, Sebastien; Wang, Zhiguo; Williams, Richard T.; Grim, Joel Q.; Gao, Fei

2014-04-01

Developing a comprehensive understanding of the processes that govern the scintillation behavior of inorganic scintillators provides a pathway to optimize current scintillators and allows for the science-driven search for new scintillator materials. Recent experimental data on the excitation density dependence of the light yield of inorganic scintillators presents an opportunity to incorporate parameterized interactions between excitations in scintillation models and thus enable more realistic simulations of the nonproportionality of inorganic scintillators. Therefore, a kinetic Monte Carlo (KMC) model of elementary scintillation processes in NaI(Tl) is developed in this paper to simulate the kinetics of scintillation for a range of temperatures and Tl concentrations as well as the scintillation efficiency as a function of excitation density. The ability of the KMC model to reproduce available experimental data allows for elucidating the elementary processes that give rise to the kinetics and efficiency of scintillation observed experimentally for a range of conditions.

Towards the reliable calculation of residence time for off-lattice kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Alexander, Kathleen C.; Schuh, Christopher A.

2016-08-01

Kinetic Monte Carlo (KMC) methods have the potential to extend the accessible timescales of off-lattice atomistic simulations beyond the limits of molecular dynamics by making use of transition state theory and parallelization. However, it is a challenge to identify a complete catalog of events accessible to an off-lattice system in order to accurately calculate the residence time for KMC. Here we describe possible approaches to some of the key steps needed to address this problem. These include methods to compare and distinguish individual kinetic events, to deterministically search an energy landscape, and to define local atomic environments. When applied to the ground state  ∑5(2 1 0) grain boundary in copper, these methods achieve a converged residence time, accounting for the full set of kinetically relevant events for this off-lattice system, with calculable uncertainty.

Kinetic Monte Carlo study of vinyl acetate synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100)

NASA Astrophysics Data System (ADS)

Huang, Yanping; Dong, Xiuqin; Yu, Yingzhe; Zhang, Minhua

2017-11-01

On the basis of the activation barriers and reaction energies from DFT calculations, kinetic Monte Carlo (kMC) simulations of vinyl acetate (VA) synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100) were carried out. Through kMC simulation, it was found that VA synthesis from ethylene acetoxylation proceeds via Moiseev mechanism on both Pd(100) and Pd/Au(100). The addition of Au into Pd can suppress ethylene dehydrogenation while it can promote acetic acid dehydrogenation, which can eventually facilitate VA synthesis as a whole. The addition of Au into Pd can further improve the conversion and selectivity of VA synthesis from ethylene acetoxylation. When the reaction network is analyzed, besides the energetics of each elementary reaction, the surface coverage of each species and the occupancy of the surface sites on the catalyst should also be taken into consideration.

On the gas phase fragmentation of protonated uracil: a statistical perspective.

PubMed

Rossich Molina, Estefanía; Salpin, Jean-Yves; Spezia, Riccardo; Martínez-Núñez, Emilio

2016-06-01

The potential energy surface of protonated uracil has been explored by an automated transition state search procedure, resulting in the finding of 1398 stationary points and 751 reactive channels, which can be categorized into isomerizations between pairs of isomers, unimolecular fragmentations and bimolecular reactions. The use of statistical Rice-Ramsperger-Kassel-Marcus (RRKM) theory and Kinetic Monte Carlo (KMC) simulations allowed us to determine the relative abundances of each fragmentation channel as a function of the ion's internal energy. The KMC/RRKM product abundances are compared with novel mass spectrometry (MS) experiments in the collision energy range 1-6 eV. To facilitate the comparison between theory and experiments, further dynamics simulations are carried out to determine the fraction of collision energy converted into the ion's internal energy. The KMC simulations show that the major fragmentation channels are isocyanic acid and ammonia losses, in good agreement with experiments. The third predominant channel is water loss according to both theory and experiments, although the abundance obtained in the KMC simulations is very low, suggesting that non-statistical dynamics might play an important role in this channel. Isocyanic acid (HNCOH(+)) is also an important product in the KMC simulations, although its abundance is only significant at internal energies not accessible in the MS experiments.

Centrality measures highlight proton traps and access points to proton highways in kinetic Monte Carlo trajectories

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

Krueger, Rachel A.; Haibach, Frederick G.; Fry, Dana L.

2015-04-21

A centrality measure based on the time of first returns rather than the number of steps is developed and applied to finding proton traps and access points to proton highways in the doped perovskite oxides: AZr{sub 0.875}D{sub 0.125}O{sub 3}, where A is Ba or Sr and the dopant D is Y or Al. The high centrality region near the dopant is wider in the SrZrO{sub 3} systems than the BaZrO{sub 3} systems. In the aluminum-doped systems, a region of intermediate centrality (secondary region) is found in a plane away from the dopant. Kinetic Monte Carlo (kMC) trajectories show that thismore » secondary region is an entry to fast conduction planes in the aluminum-doped systems in contrast to the highest centrality area near the dopant trap. The yttrium-doped systems do not show this secondary region because the fast conduction routes are in the same plane as the dopant and hence already in the high centrality trapped area. This centrality measure complements kMC by highlighting key areas in trajectories. The limiting activation barriers found via kMC are in very good agreement with experiments and related to the barriers to escape dopant traps.« less

CO adsorption on W(100) during temperature-programmed desorption: A combined density functional theory and kinetic Monte Carlo study

NASA Astrophysics Data System (ADS)

Albao, Marvin A.; Padama, Allan Abraham B.

2017-02-01

Using a combined density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations, we study the adsorption at 800 K and subsequent desorption of CO on W(100) at higher temperatures. The resulting TPD profiles are known experimentally to exhibit three desorption peaks β1, β2, and β3 at 930 K, 1070 K, and 1375 K, respectively. Unlike more recent theoretical studies that propose that all three aforementioned peaks are molecularly rather than associatively desorbed, our KMC analyses are in support of the latter, since at 800 K dissociation is facile and that CO exists as dissociation fragments C and O. We show that these peaks arise from desorption from the same adsorption site but whose binding energy varies depending on local environment, that is, the presence of CO as well as dissociation fragments C and O nearby. Furthermore we show that several key parameters, such as desorption, dissociation and recombination barriers all play a key role in the TPD spectra-these parameter effectively controls not only the location of the TPD peaks but the shape and width of the desorption peaks as well. Moreover, our KMC simulations reveal that varying the heating rate shifts the peaks but leaves their shape intact.

Simulation of gas adsorption on a surface and in slit pores with grand canonical and canonical kinetic Monte Carlo methods.

PubMed

Ustinov, E A; Do, D D

2012-08-21

We present for the first time in the literature a new scheme of kinetic Monte Carlo method applied on a grand canonical ensemble, which we call hereafter GC-kMC. It was shown recently that the kinetic Monte Carlo (kMC) scheme is a very effective tool for the analysis of equilibrium systems. It had been applied in a canonical ensemble to describe vapor-liquid equilibrium of argon over a wide range of temperatures, gas adsorption on a graphite open surface and in graphitic slit pores. However, in spite of the conformity of canonical and grand canonical ensembles, the latter is more relevant in the correct description of open systems; for example, the hysteresis loop observed in adsorption of gases in pores under sub-critical conditions can only be described with a grand canonical ensemble. Therefore, the present paper is aimed at an extension of the kMC to open systems. The developed GC-kMC was proved to be consistent with the results obtained with the canonical kMC (C-kMC) for argon adsorption on a graphite surface at 77 K and in graphitic slit pores at 87.3 K. We showed that in slit micropores the hexagonal packing in the layers adjacent to the pore walls is observed at high loadings even at temperatures above the triple point of the bulk phase. The potential and applicability of the GC-kMC are further shown with the correct description of the heat of adsorption and the pressure tensor of the adsorbed phase.

Multi-scale simulation of quantum dot formation in Al/Al (110) homoepitaxy

NASA Astrophysics Data System (ADS)

Tiwary, Yogesh; Fichthorn, Kristen

2007-03-01

In experimental studies of Al(110) homoepitaxy, it is observed that over a certain temperature window (330-500K), 3D huts, up to 50 nm high with well defined and smooth (111) and (100) facets, form and self-organize over the micron scale [1]. The factors leading to this kinetic self-organization are currently unclear. To understand how these structures form and evolve, we simulated multi-layer, homoepitaxial growth on Al(110) using ab initio kinetic Monte Carlo (KMC). At the high temperatures, where nano-huts form, the KMC simulations are slow. To tackle this problem, we use a technique developed by Devita & Sander [2], in which isolated adatoms make multiple moves in one step. We achieve high efficiency with this algorithm and we explore very high temperatures on large simulation lattices. We uncover a variety of interesting morphologies (Ripples, mounds, smooth surface, huts) that depend on the growth temperature. By varying the barriers for various rate processes, we discern the factors that determine hut sizes, aspect ratios, and self-organization. [1] F. Buatier de Mongeot, W. Zhu, A. Molle, R. Buzio, C. Boragno, U. Valbusa, E. Wang, and Z. Zhang, Phys. Rev. Lett. 91, 016102 (2003). [2] J.P. Devita & L.M. Sander, Phys. Rev. B 72, 205421 (2005).

Does phenomenological kinetics provide an adequate description of heterogeneous catalytic reactions?

PubMed

Temel, Burcin; Meskine, Hakim; Reuter, Karsten; Scheffler, Matthias; Metiu, Horia

2007-05-28

Phenomenological kinetics (PK) is widely used in the study of the reaction rates in heterogeneous catalysis, and it is an important aid in reactor design. PK makes simplifying assumptions: It neglects the role of fluctuations, assumes that there is no correlation between the locations of the reactants on the surface, and considers the reacting mixture to be an ideal solution. In this article we test to what extent these assumptions damage the theory. In practice the PK rate equations are used by adjusting the rate constants to fit the results of the experiments. However, there are numerous examples where a mechanism fitted the data and was shown later to be erroneous or where two mutually exclusive mechanisms fitted well the same set of data. Because of this, we compare the PK equations to "computer experiments" that use kinetic Monte Carlo (kMC) simulations. Unlike in real experiments, in kMC the structure of the surface, the reaction mechanism, and the rate constants are known. Therefore, any discrepancy between PK and kMC must be attributed to an intrinsic failure of PK. We find that the results obtained by solving the PK equations and those obtained from kMC, while using the same rate constants and the same reactions, do not agree. Moreover, when we vary the rate constants in the PK model to fit the turnover frequencies produced by kMC, we find that the fit is not adequate and that the rate constants that give the best fit are very different from the rate constants used in kMC. The discrepancy between PK and kMC for the model of CO oxidation used here is surprising since the kMC model contains no lateral interactions that would make the coverage of the reactants spatially inhomogeneous. Nevertheless, such inhomogeneities are created by the interplay between the rate of adsorption, of desorption, and of vacancy creation by the chemical reactions.

Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär

2017-02-01

The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.

Thermodynamics and simulation of hard-sphere fluid and solid: Kinetic Monte Carlo method versus standard Metropolis scheme

NASA Astrophysics Data System (ADS)

Ustinov, E. A.

2017-01-01

The paper aims at a comparison of techniques based on the kinetic Monte Carlo (kMC) and the conventional Metropolis Monte Carlo (MC) methods as applied to the hard-sphere (HS) fluid and solid. In the case of the kMC, an alternative representation of the chemical potential is explored [E. A. Ustinov and D. D. Do, J. Colloid Interface Sci. 366, 216 (2012)], which does not require any external procedure like the Widom test particle insertion method. A direct evaluation of the chemical potential of the fluid and solid without thermodynamic integration is achieved by molecular simulation in an elongated box with an external potential imposed on the system in order to reduce the particle density in the vicinity of the box ends. The existence of rarefied zones allows one to determine the chemical potential of the crystalline phase and substantially increases its accuracy for the disordered dense phase in the central zone of the simulation box. This method is applicable to both the Metropolis MC and the kMC, but in the latter case, the chemical potential is determined with higher accuracy at the same conditions and the number of MC steps. Thermodynamic functions of the disordered fluid and crystalline face-centered cubic (FCC) phase for the hard-sphere system have been evaluated with the kinetic MC and the standard MC coupled with the Widom procedure over a wide range of density. The melting transition parameters have been determined by the point of intersection of the pressure-chemical potential curves for the disordered HS fluid and FCC crystal using the Gibbs-Duhem equation as a constraint. A detailed thermodynamic analysis of the hard-sphere fluid has provided a rigorous verification of the approach, which can be extended to more complex systems.

Kinetic Monte Carlo Simulations of Rod Eutectics and the Surface Roughening Transition in Binary Alloys

NASA Technical Reports Server (NTRS)

Bentz, Daniel N.; Betush, William; Jackson, Kenneth A.

2003-01-01

In this paper we report on two related topics: Kinetic Monte Carlo simulations of the steady state growth of rod eutectics from the melt, and a study of the surface roughness of binary alloys. We have implemented a three dimensional kinetic Monte Carlo (kMC) simulation with diffusion by pair exchange only in the liquid phase. Entropies of fusion are first chosen to fit the surface roughness of the pure materials, and the bond energies are derived from the equilibrium phase diagram, by treating the solid and liquid as regular and ideal solutions respectively. A simple cubic lattice oriented in the {100} direction is used. Growth of the rods is initiated from columns of pure B material embedded in an A matrix, arranged in a close packed array with semi-periodic boundary conditions. The simulation cells typically have dimensions of 50 by 87 by 200 unit cells. Steady state growth is compliant with the Jackson-Hunt model. In the kMC simulations, using the spin-one Ising model, growth of each phase is faceted or nonfaceted phases depending on the entropy of fusion. There have been many studies of the surface roughening transition in single component systems, but none for binary alloy systems. The location of the surface roughening transition for the phases of a eutectic alloy determines whether the eutectic morphology will be regular or irregular. We have conducted a study of surface roughness on the spin-one Ising Model with diffusion using kMC. The surface roughness was found to scale with the melting temperature of the alloy as given by the liquidus line on the equilibrium phase diagram. The density of missing lateral bonds at the surface was used as a measure of surface roughness.

Kinetic Monte Carlo simulations of scintillation processes in NaI(Tl)

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

Kerisit, Sebastien N.; Wang, Zhiguo; Williams, Richard

2014-04-26

Developing a comprehensive understanding of the processes that govern the scintillation behavior of inorganic scintillators provides a pathway to optimize current scintillators and allows for the science-driven search for new scintillator materials. Recent experimental data on the excitation density dependence of the light yield of inorganic scintillators presents an opportunity to incorporate parameterized interactions between excitations in scintillation models and thus enable more realistic simulations of the nonproportionality of inorganic scintillators. Therefore, a kinetic Monte Carlo (KMC) model of elementary scintillation processes in NaI(Tl) is developed in this work to simulate the kinetics of scintillation for a range of temperaturesmore » and Tl concentrations as well as the scintillation efficiency as a function of excitation density. The ability of the KMC model to reproduce available experimental data allows for elucidating the elementary processes that give rise to the kinetics and efficiency of scintillation observed experimentally for a range of conditions.« less

Kinetic Monte Carlo and cellular particle dynamics simulations of multicellular systems

NASA Astrophysics Data System (ADS)

Flenner, Elijah; Janosi, Lorant; Barz, Bogdan; Neagu, Adrian; Forgacs, Gabor; Kosztin, Ioan

2012-03-01

Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Here we formulate two computer simulation methods: (1) a kinetic Monte Carlo (KMC) and (2) a cellular particle dynamics (CPD) method, which are capable of describing and predicting the shape evolution in time of three-dimensional multicellular systems during their biomechanical relaxation. Our work is motivated by the need of developing quantitative methods for optimizing postprinting structure formation in bioprinting-assisted tissue engineering. The KMC and CPD model parameters are determined and calibrated by using an original computational-theoretical-experimental framework applied to the fusion of two spherical cell aggregates. The two methods are used to predict the (1) formation of a toroidal structure through fusion of spherical aggregates and (2) cell sorting within an aggregate formed by two types of cells with different adhesivities.

Kinetic Monte Carlo Simulation of the Growth of Various Nanostructures through Atomic and Cluster Deposition: Application to Gold Nanostructure Growth on Graphite

NASA Astrophysics Data System (ADS)

Claassens, C. H.; Hoffman, M. J. H.; Terblans, J. J.; Swart, H. C.

2006-01-01

A Kinetic Monte Carlo (KMC) method is presented to describe the growth of metallic nanostructures through atomic and cluster deposition in the mono -and multilayer regime. The model makes provision for homo- and heteroepitaxial systems with small lattice mismatch. The accuracy of the model is tested with simulations of the growth of gold nanostructures on HOPG and comparisons are made with existing experimental data.

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

Ye Jia; Lawrence Berkeley Laboratory, Berkeley, California 94720-8250; Li Youhong

Theoretical predictions indicate that ordered alloys can spontaneously develop a steady-state nanoscale microstructure when irradiated with energetic particles. This behavior derives from a dynamical competition between disordering in cascades and thermally activated reordering, which leads to self-organization of the chemical order parameter. We test this possibility by combining molecular dynamics (MD) and kinetic Monte Carlo (KMC) simulations. We first generate realistic distributions of disordered zones for Ni{sub 3}Al irradiated with 70 keV He and 1 MeV Kr ions using MD and then input this data into KMC to obtain predictions of steady state microstructures as a function of the irradiationmore » flux. Nanoscale patterning is observed for Kr ion irradiations but not for He ion irradiations. We illustrate, moreover, using image simulations of these KMC microstructures, that high-resolution transmission electron microscopy can be employed to identify nanoscale patterning. Finally, we indicate how this method could be used to synthesize functional thin films, with potential for magnetic applications.« less

Analysis of Radiation Effects in Silicon using Kinetic Monte Carlo Methods

DOE PAGES

Hehr, Brian Douglas

2014-11-25

The transient degradation of semiconductor device performance under irradiation has long been an issue of concern. Neutron irradiation can instigate the formation of quasi-stable defect structures, thereby introducing new energy levels into the bandgap that alter carrier lifetimes and give rise to such phenomena as gain degradation in bipolar junction transistors. Normally, the initial defect formation phase is followed by a recovery phase in which defect-defect or defect-dopant interactions modify the characteristics of the damaged structure. A kinetic Monte Carlo (KMC) code has been developed to model both thermal and carrier injection annealing of initial defect structures in semiconductor materials.more » The code is employed to investigate annealing in electron-irradiated, p-type silicon as well as the recovery of base current in silicon transistors bombarded with neutrons at the Los Alamos Neutron Science Center (LANSCE) “Blue Room” facility. Our results reveal that KMC calculations agree well with these experiments once adjustments are made, within the appropriate uncertainty bounds, to some of the sensitive defect parameters.« less

Dewetting of patterned solid films: Towards a predictive modelling approach

NASA Astrophysics Data System (ADS)

Trautmann, M.; Cheynis, F.; Leroy, F.; Curiotto, S.; Pierre-Louis, O.; Müller, P.

2017-06-01

Owing to its ability to produce an assembly of nanoislands with controllable size and locations, the solid state dewetting of patterned films has recently received great attention. A simple Kinetic Monte Carlo model based on two reduced energetic parameters allows one to reproduce experimental observations of the dewetting morphological evolution of patterned films of Si(001) on SiO2 (or SOI for Silicon-on-Insulator) with various pattern designs. Thus, it is now possible to use KMC to drive further experiments and to optimize the pattern shapes to reach a desired dewetted structure. Comparisons between KMC simulations and dewetting experiments, at least for wire-shaped patterns, show that the prevailing dewetting mechanism depends on the wire width.

InAs wetting layer and quantum dots on GaAs(001) surface studied by in situ STM placed inside MBE growth chamber and kMC simulations based on first-principles calculations

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

Tsukamoto, S.; Arakawa, Y.; Bell, G. R.

2007-04-10

Dynamic images of InAs quantum dots (QDs) formation are obtained using a unique scanning tunneling microscope (STM) placed within the growth chamber. These images are interpreted with the aid of kinetic Monte Carlo (kMC) simulations of the QD nucleation process. Alloy fluctuations in the InGaAs wetting layer prior to QD formation assist in the nucleation of stable InAs islands containing tens of atoms which grow extremely rapidly to form QDs. Furthermore, not all deposited In is initially incorporated into the lattice, providing a large supply of material to rapidly form QDs at the critical thickness.

Multiscale Investigations of the Early Stage Oxidation on Cu Surfaces

NASA Astrophysics Data System (ADS)

Zhu, Qing; Xiao, Penghao; Lian, Xin; Yang, Shen-Che; Henkelman, Grame; Saidi, Wissam; Yang, Judith; University of Pittsburgh Team; University of Texas at Austin Team

Previous in situ TEM experiments have shown that the oxidation of the three low index Cu surfaces (100), (110) and (111) exhibit different oxide nucleation rates, and the resulting oxides have 3-dimensional (3D) island shapes or 2D rafts under different conditions. In order to better understand these results, we have investigated the early stages of Cu oxidation using a multiscale computational approach that employs density functional theory (DFT), reactive force field (ReaxFF), and kinetic Mote Carlo (KMC). With DFT calculation, we have compared O2 dissociation barriers on Cu (100), (110) and (111) surfaces at high oxygen coverage to evaluate the kinetic barrier of sublayer oxidization. We found that O2 dissociation barriers on Cu(111) surface are all lower than those on (110) and (100) surfaces. This trend agrees with experimental observations that (111) surface is easier to oxidize. These DFT calculated energy barriers are then incorporated into KMC simulations. The large scale ReaxFF molecular dynamics and KMC simulations detail the oxidation dynamics of the different Cu surfaces, and show the formation of various oxide morphologies that are consistent with experimental observations.

KMCThinFilm: A C++ Framework for the Rapid Development of Lattice Kinetic Monte Carlo (kMC) Simulations of Thin Film Growth

DTIC Science & Technology

2015-09-01

direction, so if the simulation domain is set to be a certain size, then that presents a hard ceiling on the thickness of a film that may be grown in...FFA, Los J, Cuppen HM, Bennema P, Meekes H. MONTY:  Monte Carlo crystal growth on any crystal structure in any crystallographic orientation...mhoffman.github.io/kmos/. 23. Kiravittaya S, Schmidt OG. Quantum-dot crystal defects. Applied Physics Letters. 2008;93:173109. 24. Leetmaa M

Multiscale simulations of the early stages of the growth of graphene on copper

NASA Astrophysics Data System (ADS)

Gaillard, P.; Chanier, T.; Henrard, L.; Moskovkin, P.; Lucas, S.

2015-07-01

We have performed multiscale simulations of the growth of graphene on defect-free copper (111) in order to model the nucleation and growth of graphene flakes during chemical vapour deposition and potentially guide future experimental work. Basic activation energies for atomic surface diffusion were determined by ab initio calculations. Larger scale growth was obtained within a kinetic Monte Carlo approach (KMC) with parameters based on the ab initio results. The KMC approach counts the first and second neighbours to determine the probability of surface diffusion. We report qualitative results on the size and shape of the graphene islands as a function of deposition flux. The dominance of graphene zigzag edges for low deposition flux, also observed experimentally, is explained by its larger dynamical stability that the present model fully reproduced.

Kinetic Monte Carlo simulations for transient thermal fields: Computational methodology and application to the submicrosecond laser processes in implanted silicon.

PubMed

Fisicaro, G; Pelaz, L; Lopez, P; La Magna, A

2012-09-01

Pulsed laser irradiation of damaged solids promotes ultrafast nonequilibrium kinetics, on the submicrosecond scale, leading to microscopic modifications of the material state. Reliable theoretical predictions of this evolution can be achieved only by simulating particle interactions in the presence of large and transient gradients of the thermal field. We propose a kinetic Monte Carlo (KMC) method for the simulation of damaged systems in the extremely far-from-equilibrium conditions caused by the laser irradiation. The reference systems are nonideal crystals containing point defect excesses, an order of magnitude larger than the equilibrium density, due to a preirradiation ion implantation process. The thermal and, eventual, melting problem is solved within the phase-field methodology, and the numerical solutions for the space- and time-dependent thermal field were then dynamically coupled to the KMC code. The formalism, implementation, and related tests of our computational code are discussed in detail. As an application example we analyze the evolution of the defect system caused by P ion implantation in Si under nanosecond pulsed irradiation. The simulation results suggest a significant annihilation of the implantation damage which can be well controlled by the laser fluence.

Kinetic Monte Carlo simulations of nucleation and growth in electrodeposition.

PubMed

Guo, Lian; Radisic, Aleksandar; Searson, Peter C

2005-12-22

Nucleation and growth during bulk electrodeposition is studied using kinetic Monte Carlo (KMC) simulations. Ion transport in solution is modeled using Brownian dynamics, and the kinetics of nucleation and growth are dependent on the probabilities of metal-on-substrate and metal-on-metal deposition. Using this approach, we make no assumptions about the nucleation rate, island density, or island distribution. The influence of the attachment probabilities and concentration on the time-dependent island density and current transients is reported. Various models have been assessed by recovering the nucleation rate and island density from the current-time transients.

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.

A divide-conquer-recombine algorithmic paradigm for large spatiotemporal quantum molecular dynamics simulations

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

Shimojo, Fuyuki; Hattori, Shinnosuke; Department of Physics, Kumamoto University, Kumamoto 860-8555

We introduce an extension of the divide-and-conquer (DC) algorithmic paradigm called divide-conquer-recombine (DCR) to perform large quantum molecular dynamics (QMD) simulations on massively parallel supercomputers, in which interatomic forces are computed quantum mechanically in the framework of density functional theory (DFT). In DCR, the DC phase constructs globally informed, overlapping local-domain solutions, which in the recombine phase are synthesized into a global solution encompassing large spatiotemporal scales. For the DC phase, we design a lean divide-and-conquer (LDC) DFT algorithm, which significantly reduces the prefactor of the O(N) computational cost for N electrons by applying a density-adaptive boundary condition at themore » peripheries of the DC domains. Our globally scalable and locally efficient solver is based on a hybrid real-reciprocal space approach that combines: (1) a highly scalable real-space multigrid to represent the global charge density; and (2) a numerically efficient plane-wave basis for local electronic wave functions and charge density within each domain. Hybrid space-band decomposition is used to implement the LDC-DFT algorithm on parallel computers. A benchmark test on an IBM Blue Gene/Q computer exhibits an isogranular parallel efficiency of 0.984 on 786 432 cores for a 50.3 × 10{sup 6}-atom SiC system. As a test of production runs, LDC-DFT-based QMD simulation involving 16 661 atoms is performed on the Blue Gene/Q to study on-demand production of hydrogen gas from water using LiAl alloy particles. As an example of the recombine phase, LDC-DFT electronic structures are used as a basis set to describe global photoexcitation dynamics with nonadiabatic QMD (NAQMD) and kinetic Monte Carlo (KMC) methods. The NAQMD simulations are based on the linear response time-dependent density functional theory to describe electronic excited states and a surface-hopping approach to describe transitions between the excited states. A series of techniques are employed for efficiently calculating the long-range exact exchange correction and excited-state forces. The NAQMD trajectories are analyzed to extract the rates of various excitonic processes, which are then used in KMC simulation to study the dynamics of the global exciton flow network. This has allowed the study of large-scale photoexcitation dynamics in 6400-atom amorphous molecular solid, reaching the experimental time scales.« less

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

Mermigkis, Panagiotis G.; Tsalikis, Dimitrios G.; Institute of Chemical Engineering and High Temperature Chemical Processes, GR 26500 Patras

A kinetic Monte Carlo (kMC) simulation algorithm is developed for computing the effective diffusivity of water molecules in a poly(methyl methacrylate) (PMMA) matrix containing carbon nanotubes (CNTs) at several loadings. The simulations are conducted on a cubic lattice to the bonds of which rate constants are assigned governing the elementary jump events of water molecules from one lattice site to another. Lattice sites belonging to PMMA domains of the membrane are assigned different rates than lattice sites belonging to CNT domains. Values of these two rate constants are extracted from available numerical data for water diffusivity within a PMMA matrixmore » and a CNT pre-computed on the basis of independent atomistic molecular dynamics simulations, which show that water diffusivity in CNTs is 3 orders of magnitude faster than in PMMA. Our discrete-space, continuum-time kMC simulation results for several PMMA-CNT nanocomposite membranes (characterized by different values of CNT length L and diameter D and by different loadings of the matrix in CNTs) demonstrate that the overall or effective diffusivity, D{sub eff}, of water in the entire polymeric membrane is of the same order of magnitude as its diffusivity in PMMA domains and increases only linearly with the concentration C (vol. %) in nanotubes. For a constant value of the concentration C, D{sub eff} is found to vary practically linearly also with the CNT aspect ratio L/D. The kMC data allow us to propose a simple bilinear expression for D{sub eff} as a function of C and L/D that can describe the numerical data for water mobility in the membrane extremely accurately. Additional simulations with two different CNT configurations (completely random versus aligned) show that CNT orientation in the polymeric matrix has only a minor effect on D{sub eff} (as long as CNTs do not fully penetrate the membrane). We have also extensively analyzed and quantified sublinear (anomalous) diffusive phenomena over small to moderate times and correlated them with the time needed for penetrant water molecules to explore the available large, fast-diffusing CNT pores before Fickian diffusion is reached.« less

Combining DFT, Cluster Expansions, and KMC to Model Point Defects in Alloys

NASA Astrophysics Data System (ADS)

Modine, N. A.; Wright, A. F.; Lee, S. R.; Foiles, S. M.; Battaile, C. C.; Thomas, J. C.; van der Ven, A.

In an alloy, defect energies are sensitive to the occupations of nearby atomic sites, which leads to a distribution of defect properties. When radiation-induced defects diffuse from their initially non-equilibrium locations, this distribution becomes time-dependent. The defects can become trapped in energetically favorable regions of the alloy leading to a diffusion rate that slows dramatically with time. Density Functional Theory (DFT) allows the accurate determination of ground state and transition state energies for a defect in a particular alloy environment but requires thousands of processing hours for each such calculation. Kinetic Monte-Carlo (KMC) can be used to model defect diffusion and the changing distribution of defect properties but requires energy evaluations for millions of local environments. We have used the Cluster Expansion (CE) formalism to ``glue'' together these seemingly incompatible methods. The occupation of each alloy site is represented by an Ising-like variable, and products of these variables are used to expand quantities of interest. Once a CE is fit to a training set of DFT energies, it allows very rapid evaluation of the energy for an arbitrary configuration, while maintaining the accuracy of the underlying DFT calculations. These energy evaluations are then used to drive our KMC simulations. We will demonstrate the application of our DFT/MC/KMC approach to model thermal and carrier-induced diffusion of intrinsic point defects in III-V alloys. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under Contract DE.

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.

TiOx deposited by magnetron sputtering: a joint modelling and experimental study

NASA Astrophysics Data System (ADS)

Tonneau, R.; Moskovkin, P.; Pflug, A.; Lucas, S.

2018-05-01

This paper presents a 3D multiscale simulation approach to model magnetron reactive sputter deposition of TiOx⩽2 at various O2 inlets and its validation against experimental results. The simulation first involves the transport of sputtered material in a vacuum chamber by means of a three-dimensional direct simulation Monte Carlo (DSMC) technique. Second, the film growth at different positions on a 3D substrate is simulated using a kinetic Monte Carlo (kMC) method. When simulating the transport of species in the chamber, wall chemistry reactions are taken into account in order to get the proper content of the reactive species in the volume. Angular and energy distributions of particles are extracted from DSMC and used for film growth modelling by kMC. Along with the simulation, experimental deposition of TiOx coatings on silicon samples placed at different positions on a curved sample holder was performed. The experimental results are in agreement with the simulated ones. For a given coater, the plasma phase hysteresis behaviour, film composition and film morphology are predicted. The used methodology can be applied to any coater and any films. This paves the way to the elaboration of a virtual coater allowing a user to predict composition and morphology of films deposited in silico.

Markov-chain model of classified atomistic transition states for discrete kinetic Monte Carlo simulations.

PubMed

Numazawa, Satoshi; Smith, Roger

2011-10-01

Classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The scheme is then used to determine transitions that can be applied in a lattice-based kinetic Monte Carlo (KMC) atomistic simulation model. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multidimensional Boolean valued functions in three-dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology-dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. Excellent agreement with observed experimental results is obtained.

In-silico analysis on biofabricating vascular networks using kinetic Monte Carlo simulations.

PubMed

Sun, Yi; Yang, Xiaofeng; Wang, Qi

2014-03-01

We present a computational modeling approach to study the fusion of multicellular aggregate systems in a novel scaffold-less biofabrication process, known as 'bioprinting'. In this novel technology, live multicellular aggregates are used as fundamental building blocks to make tissues or organs (collectively known as the bio-constructs,) via the layer-by-layer deposition technique or other methods; the printed bio-constructs embedded in maturogens, consisting of nutrient-rich bio-compatible hydrogels, are then placed in bioreactors to undergo the cellular aggregate fusion process to form the desired functional bio-structures. Our approach reported here is an agent-based modeling method, which uses the kinetic Monte Carlo (KMC) algorithm to evolve the cellular system on a lattice. In this method, the cells and the hydrogel media, in which cells are embedded, are coarse-grained to material's points on a three-dimensional (3D) lattice, where the cell-cell and cell-medium interactions are quantified by adhesion and cohesion energies. In a multicellular aggregate system with a fixed number of cells and fixed amount of hydrogel media, where the effect of cell differentiation, proliferation and death are tactically neglected, the interaction energy is primarily dictated by the interfacial energy between cell and cell as well as between cell and medium particles on the lattice, respectively, based on the differential adhesion hypothesis. By using the transition state theory to track the time evolution of the multicellular system while minimizing the interfacial energy, KMC is shown to be an efficient time-dependent simulation tool to study the evolution of the multicellular aggregate system. In this study, numerical experiments are presented to simulate fusion and cell sorting during the biofabrication process of vascular networks, in which the bio-constructs are fabricated via engineering designs. The results predict the feasibility of fabricating the vascular structures via the bioprinting technology and demonstrate the morphological development process during cellular aggregate fusion in various engineering designed structures. The study also reveals that cell sorting will perhaps not significantly impact the final fabricated products, should the maturation process be well-controlled in bioprinting.

Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

NASA Astrophysics Data System (ADS)

Pineda, M.; Stamatakis, M.

2017-07-01

Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.

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

Cascade Defect Evolution Processes: Comparison of Atomistic Methods

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

Xu, Haixuan; Stoller, Roger E; Osetskiy, Yury N

2013-11-01

Determining the defect evolution beyond the molecular dynamics (MD) time scale is critical in bridging the gap between atomistic simulations and experiments. The recently developed self-evolving atomistic kinetic Monte Carlo (SEAKMC) method provides new opportunities to simulate long-term defect evolution with MD-like fidelity. In this study, SEAKMC is applied to investigate the cascade defect evolution in bcc iron. First, the evolution of a vacancy rich region is simulated and compared with results obtained using autonomous basin climbing (ABC) +KMC and kinetic activation-relaxation technique (kART) simulations. Previously, it is found the results from kART are orders of magnitude faster than ABC+KMC.more » The results obtained from SEAKMC are similar to kART but the time predicted is about one order of magnitude faster than kART. The fidelity of SEAKMC is confirmed by statistically relevant MD simulations at multiple higher temperatures, which proves that the saddle point sampling is close to complete in SEAKMC. The second is the irradiation-induced formation of C15 Laves phase nano-size defect clusters. In contrast to previous studies, which claim the defects can grow by capturing self-interstitials, we found these highly stable clusters can transform to <111> glissile configuration on a much longer time scale. Finally, cascade-annealing simulations using SEAKMC is compared with traditional object KMC (OKMC) method. SEAKMC predicts substantially fewer surviving defects compared with OKMC. The possible origin of this difference is discussed and a possible way to improve the accuracy of OKMC based on SEAKMC results is outlined. These studies demonstrate the atomistic fidelity of SEAKMC in comparison with other on-the-fly KMC methods and provide new information on long-term defect evolution in iron.« less

Readiness of hospitals to provide Kangaroo Mother Care (KMC) and documentation of KMC service delivery: Analysis of Malawi 2014 Emergency Obstetric and Newborn Care (EmONC) survey data.

PubMed

Chavula, Kondwani; Likomwa, Dyson; Valsangkar, Bina; Luhanga, Richard; Chimtembo, Lydia; Dube, Queen; Gobezie, Wasihun Andualem; Guenther, Tanya

2017-12-01

Malawi introduced Kangaroo Mother Care (KMC) in 1999 as part of its efforts to address newborn morbidity and mortality and has continued to expand KMC services across the country. Yet, data on availability of KMC services and routine service provision are limited. Data from the 2014 Emergency Obstetric Newborn Care (EmONC) survey, which was a census of all 87 hospitals in Malawi, were analyzed. The WHO service availability and readiness domains were used to generate indicators for KMC service readiness and an additional domain for documentation of KMC services was included. Levels of KMC service delivery were quantified using data extracted from a 12-month register review and a KMC initiation rate was calculated for each facility by dividing the reported number of babies initiated on KMC by the number of live births at facility. We defined three levels of KMC readiness and two levels of KMC operational status. 79% of hospitals (69/87) reported providing inpatient KMC services. More than half of the hospitals (62%; 54/87) met the most basic definition of readiness (staff, space for KMC and functional weighing scale) and 35% (30/87) met an expanded definition of readiness (guidelines, staff, space, scale and register in use). Only 15 % (13/87) of hospitals had all KMC tracer items. Less than half of the hospitals (43%; 37/87) met criteria for KMC operational status at minimum levels (≥1/100 live births), and just 16% (14/87) met criteria for KMC operational status at routine levels (≥5/100 live births). Our study found large differences between reported levels of KMC services and documented levels of KMC readiness and service provision among hospitals in Malawi. It is recommended that facility assessments of services such as KMC include record reviews to better estimate service availability and delivery. Further efforts to strengthen the capacity of Malawian hospitals to deliver KMC are needed.

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.

Ab initio and kinetic Monte Carlo study of lithium diffusion in LiSi, Li12Si7, Li13Si5 and Li15Si4

NASA Astrophysics Data System (ADS)

Moon, Janghyuk; Lee, Byeongchan; Cho, Maenghyo; Cho, Kyeongjae

2016-10-01

The kinetics of lithium atoms in various Li-Si binary compounds are investigated using density functional theory calculations and kinetic Monte Carlo calculations. The values of the Li migration energy barriers are identified by NEB calculations with vacancy-mediated, interstitial and exchange migration mechanisms in crystalline LiSi, Li12Si7, Li13Si4, and Li15Si4. A comparison of these NEB results shows that the vacancy-mediated Li migration is identified as the dominant diffusion mechanisms in Li-Si compounds. The diffusion coefficients of Li in Li-Si compounds at room temperature are determined by KMC simulation. From the KMC results, the recalculated migration energy barriers in LiSi, Li12Si7, Li13Si4, and Li15Si4 correspond to 0.306, 0.301, 0.367 and 0.320 eV, respectively. Compared to the Li migration energy barrier of 0.6 eV in crystalline Si, the drastic reduction in the Li migration energy barriers in the lithiated silicon indicates that the initial lithiation of the Si anode is the rate-limiting step. Furthermore, it is also found that Si migration is possible in Li-rich configurations. On the basis of these findings, the underlying mechanisms of kinetics on the atomic scale details are elucidated.

Readiness of hospitals to provide Kangaroo Mother Care (KMC) and documentation of KMC service delivery: Analysis of Malawi 2014 Emergency Obstetric and Newborn Care (EmONC) survey data

PubMed Central

Chavula, Kondwani; Likomwa, Dyson; Valsangkar, Bina; Luhanga, Richard; Chimtembo, Lydia; Dube, Queen; Gobezie, Wasihun Andualem; Guenther, Tanya

2017-01-01

Background Malawi introduced Kangaroo Mother Care (KMC) in 1999 as part of its efforts to address newborn morbidity and mortality and has continued to expand KMC services across the country. Yet, data on availability of KMC services and routine service provision are limited. Methods Data from the 2014 Emergency Obstetric Newborn Care (EmONC) survey, which was a census of all 87 hospitals in Malawi, were analyzed. The WHO service availability and readiness domains were used to generate indicators for KMC service readiness and an additional domain for documentation of KMC services was included. Levels of KMC service delivery were quantified using data extracted from a 12–month register review and a KMC initiation rate was calculated for each facility by dividing the reported number of babies initiated on KMC by the number of live births at facility. We defined three levels of KMC readiness and two levels of KMC operational status. Results 79% of hospitals (69/87) reported providing inpatient KMC services. More than half of the hospitals (62%; 54/87) met the most basic definition of readiness (staff, space for KMC and functional weighing scale) and 35% (30/87) met an expanded definition of readiness (guidelines, staff, space, scale and register in use). Only 15% (13/87) of hospitals had all KMC tracer items. Less than half of the hospitals (43%; 37/87) met criteria for KMC operational status at minimum levels (≥1/100 live births), and just 16% (14/87) met criteria for KMC operational status at routine levels (≥5/100 live births). Conclusions Our study found large differences between reported levels of KMC services and documented levels of KMC readiness and service provision among hospitals in Malawi. It is recommended that facility assessments of services such as KMC include record reviews to better estimate service availability and delivery. Further efforts to strengthen the capacity of Malawian hospitals to deliver KMC are needed. PMID:29085623

Predictive process simulation of cryogenic implants for leading edge transistor design

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

Gossmann, Hans-Joachim; Zographos, Nikolas; Park, Hugh

2012-11-06

Two cryogenic implant TCAD-modules have been developed: (i) A continuum-based compact model targeted towards a TCAD production environment calibrated against an extensive data-set for all common dopants. Ion-specific calibration parameters related to damage generation and dynamic annealing were used and resulted in excellent fits to the calibration data-set. (ii) A Kinetic Monte Carlo (kMC) model including the full time dependence of ion-exposure that a particular spot on the wafer experiences, as well as the resulting temperature vs. time profile of this spot. It was calibrated by adjusting damage generation and dynamic annealing parameters. The kMC simulations clearly demonstrate the importancemore » of the time-structure of the beam for the amorphization process: Assuming an average dose-rate does not capture all of the physics and may lead to incorrect conclusions. The model enables optimization of the amorphization process through tool parameters such as scan speed or beam height.« less

Knowledge and awareness about benefits of Kangaroo Mother Care.

PubMed

Muddu, Gopi Krishna; Boju, Sangeetha Lakshmi; Chodavarapu, Ravikumar

2013-10-01

To determine mothers' prior knowledge of Kangaroo Mother Care (KMC) and awareness about benefits of KMC for preterm babies. Mothers of a consecutive sample of 46 preterm babies, eligible for KMC admitted to a teaching hospital, from June through August 2009, were studied to determine the attitude and knowledge about KMC. A structured questionnaire was prepared. Mothers were asked questions to determine their baseline knowledge about KMC. Then each mother was explained about KMC and instructed to do KMC. After one hour of KMC, mothers were asked questions again to know their feelings and difficulties regarding KMC and feasibility of breast feeding during KMC. Most of the mothers could understand what was explained to them (97.8 %; 95 % CI 88.5-99.9 %) in a single session. Positive feelings like closeness to baby (93.5 %) and sense of goodness (97.8 %) were noted amongst mothers. Though statistically not significant, the proportion of mothers who felt it impracticable to give breast feeding while doing KMC was considerable (39.1 %; 95 % CI 25.1-54.6 %) compared to those who felt no difficulty in breast feeding (60.9 %; 95 % CI 45.4-74.9 %). Practicable duration of KMC is 1, 2 and 12 h as felt by 52 %, 19.6 % and 6.5 % of mothers respectively. All the mothers expressed their willingness to continue KMC at home. Mothers can understand and implement KMC with simple and clear oral instructions in local language. Positive feelings arise in mothers even with 1 h of KMC. KMC of 24 h is not practicable to almost all of the mothers. There is a need for special emphasis on breast feeding the child while doing the KMC.

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.

KMCLib 1.1: Extended random number support and technical updates to the KMCLib general framework for kinetic Monte-Carlo simulations

NASA Astrophysics Data System (ADS)

Leetmaa, Mikael; Skorodumova, Natalia V.

2015-11-01

We here present a revised version, v1.1, of the KMCLib general framework for kinetic Monte-Carlo (KMC) simulations. The generation of random numbers in KMCLib now relies on the C++11 standard library implementation, and support has been added for the user to choose from a set of C++11 implemented random number generators. The Mersenne-twister, the 24 and 48 bit RANLUX and a 'minimal-standard' PRNG are supported. We have also included the possibility to use true random numbers via the C++11 std::random_device generator. This release also includes technical updates to support the use of an extended range of operating systems and compilers.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent.

PubMed

Peter, Emanuel K; Shea, Joan-Emma; Pivkin, Igor V

2016-05-14

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC). The new development significantly can reduce the amount of replicas and the computational cost needed to enhance sampling in protein simulations. We introduce 2 different methods which primarily differ in the exchange scheme between the parallel ensembles. We apply this approach on folding of 2 different β-stranded peptides: the C-terminal β-hairpin fragment of GB1 and TrpZip4. Additionally, we use the new simulation technique to study the folding of TrpCage, a small fast folding α-helical peptide. Subsequently, we apply the new methodology on conformation changes in signaling of the light-oxygen voltage (LOV) sensitive domain from Avena sativa (AsLOV2). Our results agree well with data reported in the literature. In simulations of dialanine, we compare the statistical sampling of the 2 techniques with conventional REMD and analyze their performance. The new techniques can reduce the computational cost of REMD significantly and can be used in enhanced sampling simulations of biomolecules.

Nucleation and growth studies of crystalline carbon phases at nanoscale

NASA Astrophysics Data System (ADS)

Mani, Radhika C.

Understanding the nucleation and early stage growth of crystals from the vapor phase is important for realizing large-area single-crystal quality films, controlled synthesis of nanocrystals, and the possible discovery of new phases of materials. Carbon provides the most interesting system because all its known crystalline phases (diamond, graphite and carbon nanotubes) are technologically important materials. Hence, this dissertation is focused on studying the nucleation and growth of carbon phases synthesized from the vapor phase. Nucleation experiments were performed in a microwave plasma chemical vapor deposition (CVD) reactor, and the resulting carbon nanocrystals were analyzed primarily using electron nanodiffraction and Raman spectroscopy. These studies led to the discovery of two new crystalline phases of sp 3 carbon other than diamond: face-centered and body-centered cubic carbon. Nanodiffraction results revealed possible hydrogen substitution into diamond-cubic lattices, indicating that these new phases probably act as intermediates in diamond nucleation. Nucleation experiments also led to the discovery of two new morphologies for sp2 carbon: nanocrystals of graphite and tapered, hollow 1-D structures termed here as "carbon nanopipettes". A Kinetic Monte Carlo (KMC) algorithm was developed to simulate the growth of individual diamond crystals from the vapor phase, starting with small clusters of carbon atoms (or seeds). Specifically, KMC simulations were used to distinguish the kinetic rules that give rise to a star-shaped decahedral morphology compared to decahedral crystals. KMC simulations revealed that slow adsorption on the {111} step-propagation sites compared to kink sites leads to star-decahedral crystals, and higher adsorption leads to decahedral crystals. Since the surfaces of the nanocrystals of graphite and nanopipettes were expected to be composed primarily of edge-plane sites, the electrochemical behavior of both these materials were investigated with compounds requiring chemisorption, specifically biologically important species. Both these materials exhibited a stable and reversible voltammetric behavior for dopamine (a neurotransmitter) similar to that of graphite edge planes. Furthermore, a simple bottom-up concept utilizing the tapered morphology of the nanopipettes was developed to assemble a nanoarray sensor for fast cyclic voltammetry. In summary, the main outcomes of this dissertation include: the discovery of new crystalline carbon phases, understanding kinetic faceting of multiply twinned diamond crystals and tapered morphologies of carbon nanotubes, and development of new electrode materials based on sp2 carbon nanocrystals for sensing biologically important analytes.

What is kangaroo mother care? Systematic review of the literature

PubMed Central

Chan, Grace J; Valsangkar, Bina; Kajeepeta, Sandhya; Boundy, Ellen O; Wall, Stephen

2016-01-01

Background Kangaroo mother care (KMC), often defined as skin–to–skin contact between a mother and her newborn, frequent or exclusive breastfeeding, and early discharge from the hospital has been effective in reducing the risk of mortality among preterm and low birth weight infants. Research studies and program implementation of KMC have used various definitions. Objectives To describe the current definitions of KMC in various settings, analyze the presence or absence of KMC components in each definition, and present a core definition of KMC based on common components that are present in KMC literature. Methods We conducted a systematic review and searched PubMed, Embase, Scopus, Web of Science, and the World Health Organization Regional Databases for studies with key words “kangaroo mother care”, “kangaroo care” or “skin to skin care” from 1 January 1960 to 24 April 2014. Two independent reviewers screened articles and abstracted data. Findings We screened 1035 articles and reports; 299 contained data on KMC and neonatal outcomes or qualitative information on KMC implementation. Eighty–eight of the studies (29%) did not define KMC. Two hundred and eleven studies (71%) included skin–to–skin contact (SSC) in their KMC definition, 49 (16%) included exclusive or nearly exclusive breastfeeding, 22 (7%) included early discharge criteria, and 36 (12%) included follow–up after discharge. One hundred and sixty–seven studies (56%) described the duration of SSC. Conclusions There exists significant heterogeneity in the definition of KMC. A large number of studies did not report definitions of KMC. Skin–to–skin contact is the core component of KMC, whereas components such as breastfeeding, early discharge, and follow–up care are context specific. To implement KMC effectively development of a global standardized definition of KMC is needed. PMID:27231546

Does kangaroo mother care save lives?

PubMed

Pattinson, R C; Bergh, A-M; Malan, A F; Prinsloo, R

2006-12-01

To assess the impact of the introduction of kangaroo mother care (KMC) in hospitals using the Perinatal Problem Identification Programme (PPIP) in South Africa, a survey was conducted of the PPIP sentinel sites in South Africa requesting information on the practice of KMC in the hospital and if practised, when it had been initiated. Data on live births and the neonatal deaths of infants weighing between 1000 and 1999 g for each institution were obtained from the national PPIP database and, where applicable, divided into two periods, before and after the introduction of KMC. The practice of KMC and PPIP data could be combined for 40 of the hospitals that had responded to the survey. Of these, eight hospitals had not initiated KMC by January 2005, 21 had PPIP data for a period after KMC had commenced and 11 had PPIP data for periods before and after the introduction of KMC. The neonatal death rate (NNDR) for all hospitals with no KMC or before the introduction of KMC was 88.14/1000 live births, whereas the NNDR for hospitals with KMC or after the introduction of KMC was 71.43/1000 live births [relative risk (RR) 0.81; 95% confidence interval (CI) 0.72-0.91]. For the 11 hospitals that had reliable PPIP data for periods before and after the initiation of KMC, the NNDR was 87.72/1000 live births before KMC and 60.76/1000 live births after KMC had been introduced (RR 0.62; 95% CI 0.53-0.73). The large and significant reduction in the NNDR of neonates weighing between 1000 and 1999 g was associated with the introduction of KMC.

What is kangaroo mother care? Systematic review of the literature.

PubMed

Chan, Grace J; Valsangkar, Bina; Kajeepeta, Sandhya; Boundy, Ellen O; Wall, Stephen

2016-06-01

Kangaroo mother care (KMC), often defined as skin-to-skin contact between a mother and her newborn, frequent or exclusive breastfeeding, and early discharge from the hospital has been effective in reducing the risk of mortality among preterm and low birth weight infants. Research studies and program implementation of KMC have used various definitions. To describe the current definitions of KMC in various settings, analyze the presence or absence of KMC components in each definition, and present a core definition of KMC based on common components that are present in KMC literature. We conducted a systematic review and searched PubMed, Embase, Scopus, Web of Science, and the World Health Organization Regional Databases for studies with key words "kangaroo mother care", "kangaroo care" or "skin to skin care" from 1 January 1960 to 24 April 2014. Two independent reviewers screened articles and abstracted data. We screened 1035 articles and reports; 299 contained data on KMC and neonatal outcomes or qualitative information on KMC implementation. Eighty-eight of the studies (29%) did not define KMC. Two hundred and eleven studies (71%) included skin-to-skin contact (SSC) in their KMC definition, 49 (16%) included exclusive or nearly exclusive breastfeeding, 22 (7%) included early discharge criteria, and 36 (12%) included follow-up after discharge. One hundred and sixty-seven studies (56%) described the duration of SSC. There exists significant heterogeneity in the definition of KMC. A large number of studies did not report definitions of KMC. Skin-to-skin contact is the core component of KMC, whereas components such as breastfeeding, early discharge, and follow-up care are context specific. To implement KMC effectively development of a global standardized definition of KMC is needed.

A kinetic Monte Carlo approach to study fluid transport in pore networks

NASA Astrophysics Data System (ADS)

Apostolopoulou, M.; Day, R.; Hull, R.; Stamatakis, M.; Striolo, A.

2017-10-01

The mechanism of fluid migration in porous networks continues to attract great interest. Darcy's law (phenomenological continuum theory), which is often used to describe macroscopically fluid flow through a porous material, is thought to fail in nano-channels. Transport through heterogeneous and anisotropic systems, characterized by a broad distribution of pores, occurs via a contribution of different transport mechanisms, all of which need to be accounted for. The situation is likely more complicated when immiscible fluid mixtures are present. To generalize the study of fluid transport through a porous network, we developed a stochastic kinetic Monte Carlo (KMC) model. In our lattice model, the pore network is represented as a set of connected finite volumes (voxels), and transport is simulated as a random walk of molecules, which "hop" from voxel to voxel. We simulated fluid transport along an effectively 1D pore and we compared the results to those expected by solving analytically the diffusion equation. The KMC model was then implemented to quantify the transport of methane through hydrated micropores, in which case atomistic molecular dynamic simulation results were reproduced. The model was then used to study flow through pore networks, where it was able to quantify the effect of the pore length and the effect of the network's connectivity. The results are consistent with experiments but also provide additional physical insights. Extension of the model will be useful to better understand fluid transport in shale rocks.

Starting the conversation: community perspectives on preterm birth and kangaroo mother care in southern Malawi.

PubMed

Lydon, Megan; Longwe, Monica; Likomwa, Dyson; Lwesha, Victoria; Chimtembo, Lydia; Donohue, Pamela; Guenther, Tanya; Valsangar, Bina

2018-06-01

Despite introduction of Kangaroo Mother Care (KMC) in Malawi over a decade ago, preterm birth remains the leading cause of neonatal mortality. Although KMC is initiated in the health care facility, robust community follow-up is critical for survival and optimal development of preterm and low birth weight infants post-discharge. The objective of this qualitative study was to gain insight into community and health worker understanding, attitudes, beliefs and practices around preterm and low birth weight babies and KMC in Malawi. A total of 152 participants were interviewed in two districts in southern Malawi, Machinga and Thyolo, in April 2015. Focus group discussions (groups = 11, n = 132) were conducted with pregnant women, community members and women who have practiced KMC. In-depth interviews (n = 20) were conducted with fathers who have practiced KMC, community and religious leaders, and health workers. Purposive and snowball sampling were employed to identify participants. Thematic content analysis was conducted. KMC mothers and fathers only learned about KMC and care for preterm newborns after delivery of a child in need of this care. Men typically were not included in KMC counseling due to societal gender roles. Health facilities were the main source of information on KMC, however informal networks among women provided some degree of knowledge exchange. Community leaders were regarded as major facilitators of health information, conveners, key influencers, and policy-makers. Religious leaders were regarded as advocates and emotional support for families with preterm infants. Finally, while many participants initially had negative feelings towards preterm births and KMC, the large majority saw a shift in their perceptions through health counseling, peer modeling, and personal success with KMC. The findings offer several opportunities to improve KMC implementation including 1) earlier introduction of KMC to pregnant women and their families that are at-risk for preterm birth, 2) greater involvement of men in KMC counselling, practice and care for preterm infants, and 3) strengthening and defining partnerships with community and religious leaders. Finally, as parental perceptions of preterm infants and KMC improved with successful KMC practice, it is hopeful that KMC itself can positively affect social norms surrounding preterm infants, leading to a virtuous cycle of improved perceptions of preterm infants and increased uptake of KMC.

Starting the conversation: community perspectives on preterm birth and kangaroo mother care in southern Malawi

PubMed Central

Lydon, Megan; Longwe, Monica; Likomwa, Dyson; Lwesha, Victoria; Chimtembo, Lydia; Donohue, Pamela; Guenther, Tanya; Valsangar, Bina

2018-01-01

Background Despite introduction of Kangaroo Mother Care (KMC) in Malawi over a decade ago, preterm birth remains the leading cause of neonatal mortality. Although KMC is initiated in the health care facility, robust community follow-up is critical for survival and optimal development of preterm and low birth weight infants post-discharge. The objective of this qualitative study was to gain insight into community and health worker understanding, attitudes, beliefs and practices around preterm and low birth weight babies and KMC in Malawi. Methods A total of 152 participants were interviewed in two districts in southern Malawi, Machinga and Thyolo, in April 2015. Focus group discussions (groups = 11, n = 132) were conducted with pregnant women, community members and women who have practiced KMC. In-depth interviews (n = 20) were conducted with fathers who have practiced KMC, community and religious leaders, and health workers. Purposive and snowball sampling were employed to identify participants. Thematic content analysis was conducted. Findings KMC mothers and fathers only learned about KMC and care for preterm newborns after delivery of a child in need of this care. Men typically were not included in KMC counseling due to societal gender roles. Health facilities were the main source of information on KMC, however informal networks among women provided some degree of knowledge exchange. Community leaders were regarded as major facilitators of health information, conveners, key influencers, and policy-makers. Religious leaders were regarded as advocates and emotional support for families with preterm infants. Finally, while many participants initially had negative feelings towards preterm births and KMC, the large majority saw a shift in their perceptions through health counseling, peer modeling, and personal success with KMC. Conclusions The findings offer several opportunities to improve KMC implementation including 1) earlier introduction of KMC to pregnant women and their families that are at-risk for preterm birth, 2) greater involvement of men in KMC counselling, practice and care for preterm infants, and 3) strengthening and defining partnerships with community and religious leaders. Finally, as parental perceptions of preterm infants and KMC improved with successful KMC practice, it is hopeful that KMC itself can positively affect social norms surrounding preterm infants, leading to a virtuous cycle of improved perceptions of preterm infants and increased uptake of KMC. PMID:29904606

Community based kangaroo mother care for low birth weight babies: A pilot study

PubMed Central

Rasaily, Reeta; Ganguly, K. K.; Roy, M.; Vani, S. N.; Kharood, N.; Kulkarni, R.; Chauhan, S.; Swain, S.; Kanugo, L.

2017-01-01

Background & objectives: Kangaroo mother care (KMC - early continuous skin-to-skin contact between mother and infants) has been recommended as an alternative care for low birth weight infants. There is limited evidence in our country on KMC initiated at home. The present study was undertaken to study acceptability of KMC in different community settings. Methods: A community-based pilot study was carried out at three sites in the States of Odisha, Gujarat and Maharashtra covering rural, urban and rural tribal population, respectively. Trained health workers provided IEC (information, education and communication) on KMC during antenatal period along with essential newborn care messages. These messages were reinforced during the postnatal period. Outcome measures were the proportion of women accepting KMC, duration of KMC/day and total number of days continuing KMC. Focus group discussions and in-depth interviews were also carried out. Results: KMC was provided to 101 infants weighing 1500-2000 g; 57.4 per cent were preterm. Overall, 80.2 per cent mothers received health education on KMC during antenatal period, family members (68.3%) also attended KMC sessions along with pregnant women and 55.4 per cent of the women initiated KMC within 72 h of birth. KMC was provided on an average for five hours per day. Qualitative survey data indicated that the method was acceptable to mothers and family members; living in nuclear family, household work, twin pregnancy, hot weather, etc., were cited as reasons for not being able to practice KMC for a longer duration. Interpretation & conclusions: It was feasible to provide KMC using existing infrastructure, and the method was acceptable to most mothers of low birth infants. PMID:28574014

Community based kangaroo mother care for low birth weight babies: A pilot study.

PubMed

Rasaily, Reeta; Ganguly, K K; Roy, M; Vani, S N; Kharood, N; Kulkarni, R; Chauhan, S; Swain, S; Kanugo, L

2017-01-01

Kangaroo mother care (KMC - early continuous skin-to-skin contact between mother and infants) has been recommended as an alternative care for low birth weight infants. There is limited evidence in our country on KMC initiated at home. The present study was undertaken to study acceptability of KMC in different community settings. A community-based pilot study was carried out at three sites in the States of Odisha, Gujarat and Maharashtra covering rural, urban and rural tribal population, respectively. Trained health workers provided IEC (information, education and communication) on KMC during antenatal period along with essential newborn care messages. These messages were reinforced during the postnatal period. Outcome measures were the proportion of women accepting KMC, duration of KMC/day and total number of days continuing KMC. Focus group discussions and in-depth interviews were also carried out. KMC was provided to 101 infants weighing 1500-2000 g; 57.4 per cent were preterm. Overall, 80.2 per cent mothers received health education on KMC during antenatal period, family members (68.3%) also attended KMC sessions along with pregnant women and 55.4 per cent of the women initiated KMC within 72 h of birth. KMC was provided on an average for five hours per day. Qualitative survey data indicated that the method was acceptable to mothers and family members; living in nuclear family, household work, twin pregnancy, hot weather, etc., were cited as reasons for not being able to practice KMC for a longer duration. It was feasible to provide KMC using existing infrastructure, and the method was acceptable to most mothers of low birth infants.

State of the art and recommendations. Kangaroo mother care: application in a high-tech environment.

PubMed

Nyqvist, K H; Anderson, G C; Bergman, N; Cattaneo, A; Charpak, N; Davanzo, R; Ewald, U; Ludington-Hoe, S; Mendoza, S; Pallás-Allonso, C; Peláez, J G; Sizun, J; Widström, A-M

2010-06-01

Since Kangaroo Mother Care (KMC) was developed in Colombia in the 1970s, two trends in clinical application emerged. In low income settings, the original KMC model is implemented. This consists of continuous (24 h/day, 7 days/week) and prolonged mother/parent-infant skin-to-skin contact; early discharge with the infant in the kangaroo position; (ideally) exclusive breastfeeding; and, adequate follow-up. In affluent settings, intermittent KMC with sessions of one or a few hours skin-to-skin contact for a limited period is common. As a result of the increasing evidence of the benefits of KMC for both infants and families in all intensive care settings, KMC in a high-tech environment was chosen as the topic for the first European Conference on KMC, and the clinical implementation of the KMC model in all types of settings was discussed at the 7th International Workshop on KMC. Kangaroo Mother Care protocols in high-tech Neonatal Intensive Care Units (NICU) should specify criteria for initiation, kangaroo position, transfer to/from KMC, transport in kangaroo position, kangaroo nutrition, parents' role, modification of the NICU environment, performance of care in KMC, and KMC in case of infant instability. Implementation of the original KMC method, with continuous skin-to-skin contact whenever possible, is recommended for application in high-tech environments, although scientific evaluation should continue.

Comparison of Various Kangaroo Mother Care Carriers on Maternal Comfort: A Pilot Study.

PubMed

Amaliya, Sholihatul; Rustina, Yeni; Agustini, Nur

Kangaroo mother care (KMC) is an evidence-based approach that has been scientifically proven to have a positive effect on mothers and infants. One of the barriers to performing KMC at home is the absence of a special KMC carrier. The most widely used KMC carriers in Indonesia are kangaroo pouch, thari, wrap and traditional wraps in the form of a long strip of fabric. This study's aim was to compare the level of maternal comfort when performing KMC with three different KMC carriers. The study used crossover design involving 20 mothers with low birth weight (LBW) infants as responders, selected through a consecutive sampling method. Data were collected using a maternal comfort questionnaire, maternal anxiety questionnaire, and KMC observation sheet. The results of repeated analysis of variance (ANOVA) showed that there was no significant difference in maternal comfort when performing KMC with any of three KMC carriers (maternal comfort p = .366, α = .05). Therefore, KMC can be implemented using any of the types of carriers including kangaroo pouch, thari wrap, and traditional wrap.

Multiscale Simulation and Modeling of Multilayer Heteroepitactic Growth of C60 on Pentacene.

PubMed

Acevedo, Yaset M; Cantrell, Rebecca A; Berard, Philip G; Koch, Donald L; Clancy, Paulette

2016-03-29

We apply multiscale methods to describe the strained growth of multiple layers of C60 on a thin film of pentacene. We study this growth in the presence of a monolayer pentacene step to compare our simulations to recent experimental studies by Breuer and Witte of submonolayer growth in the presence of monolayer steps. The molecular-level details of this organic semiconductor interface have ramifications on the macroscale structural and electronic behavior of this system and allow us to describe several unexplained experimental observations for this system. The growth of a C60 thin film on a pentacene surface is complicated by the differing crystal habits of the two component species, leading to heteroepitactical growth. In order to probe this growth, we use three computational methods that offer different approaches to coarse-graining the system and differing degrees of computational efficiency. We present a new, efficient reaction-diffusion continuum model for 2D systems whose results compare well with mesoscale kinetic Monte Carlo (KMC) results for submonolayer growth. KMC extends our ability to simulate multiple layers but requires a library of predefined rates for event transitions. Coarse-grained molecular dynamics (CGMD) circumvents KMC's need for predefined lattices, allowing defects and grain boundaries to provide a more realistic thin film morphology. For multilayer growth, in this particularly suitable candidate for coarse-graining, CGMD is a preferable approach to KMC. Combining the results from these three methods, we show that the lattice strain induced by heteroepitactical growth promotes 3D growth and the creation of defects in the first monolayer. The CGMD results are consistent with experimental results on the same system by Conrad et al. and by Breuer and Witte in which C60 aggregates change from a 2D structure at low temperature to 3D clusters along the pentacene step edges at higher temperatures.

Barriers and enablers of kangaroo mother care practice: a systematic review.

PubMed

Seidman, Gabriel; Unnikrishnan, Shalini; Kenny, Emma; Myslinski, Scott; Cairns-Smith, Sarah; Mulligan, Brian; Engmann, Cyril

2015-01-01

Kangaroo mother care (KMC) is an evidence-based approach to reducing mortality and morbidity in preterm infants. Although KMC is a key intervention package in newborn health initiatives, there is limited systematic information available on the barriers to KMC practice that mothers and other stakeholders face while practicing KMC. This systematic review sought to identify the most frequently reported barriers to KMC practice for mothers, fathers, and health practitioners, as well as the most frequently reported enablers to practice for mothers. We searched nine electronic databases and relevant reference lists for publications reporting barriers or enablers to KMC practice. We identified 1,264 unique publications, of which 103 were included based on pre-specified criteria. Publications were scanned for all barriers / enablers. Each publication was also categorized based on its approach to identification of barriers / enablers, and more weight was assigned to publications which had systematically sought to understand factors influencing KMC practice. Four of the top five ranked barriers to KMC practice for mothers were resource-related: "Issues with the facility environment / resources," "negative impressions of staff attitudes or interactions with staff," "lack of help with KMC practice or other obligations," and "low awareness of KMC / infant health." Considering only publications from low- and middle-income countries, "pain / fatigue" was ranked higher than when considering all publications. Top enablers to practice were included "mother-infant attachment" and "support from family, friends, and other mentors." Our findings suggest that mother can understand and enjoy KMC, and it has benefits for mothers, infants, and families. However, continuous KMC may be physically and emotionally difficult, and often requires support from family members, health practitioners, or other mothers. These findings can serve as a starting point for researchers and program implementers looking to improve KMC programs.

A neonatal nurse training program in kangaroo mother care (KMC) decreases barriers to KMC utilization in the NICU.

PubMed

Hendricks-Munoz, Karen D; Mayers, Roslyn M

2014-11-01

This study assessed the impact of a nurse simulation training program on perception of kangaroo mother care (KMC) value and transfer skill competency. An 8-item Likert scale skill survey tool and a 24-item Likert developmental care survey tool were used in a prospective cohort study to analyze perceptions of 30 neonatal nurses who underwent a comprehensive KMC simulation-based training program. Competency skills were evaluated pretraining and tracked by direct observation for 6 months posttraining. Pre- and postsurvey data were analyzed and KMC utilization for preterm infants born at ≤ 34 weeks' gestation was determined. Nurses' competency in infant transfer improved, especially in infants receiving nasal continuous positive airway pressure or ventilator support, from 30 to 93% or 10 to 50%, respectively, p < 0.0001. Neonatal nurses' perceived KMC value increased from 50 to 100%, p < 0.001, and parent KMC utilization increased from 26.5 to 85.9%, p < 0.0001. Nurses' support for parental visitation improved from 38 to 73%, p < 0.001; discussion of KMC with parents on the 1st day increased from 5 to 45%, p < 0.001; and initial day of KMC provision improved from 18.0 ± 2.7 to 5.6 ± 1.2 days, p < 0.001. A comprehensive simulation-based KMC education program improved nurses' perception of KMC value, their competency and comfort in infant transfer for KMC care, and successfully promoted KMC parent utilization for the preterm infant in the neonatal intensive care unit. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Energetic fluctuations in amorphous semiconducting polymers: Impact on charge-carrier mobility

NASA Astrophysics Data System (ADS)

Gali, Sai Manoj; D'Avino, Gabriele; Aurel, Philippe; Han, Guangchao; Yi, Yuanping; Papadopoulos, Theodoros A.; Coropceanu, Veaceslav; Brédas, Jean-Luc; Hadziioannou, Georges; Zannoni, Claudio; Muccioli, Luca

2017-10-01

We present a computational approach to model hole transport in an amorphous semiconducting fluorene-triphenylamine copolymer (TFB), which is based on the combination of molecular dynamics to predict the morphology of the oligomeric system and Kinetic Monte Carlo (KMC), parameterized with quantum chemistry calculations, to simulate hole transport. Carrying out a systematic comparison with available experimental results, we discuss the role that different transport parameters play in the KMC simulation and in particular the dynamic nature of positional and energetic disorder on the temperature and electric field dependence of charge mobility. It emerges that a semi-quantitative agreement with experiments is found only when the dynamic nature of the disorder is taken into account. This study establishes a clear link between microscopic quantities and macroscopic hole mobility for TFB and provides substantial evidence of the importance of incorporating fluctuations, at the molecular level, to obtain results that are in good agreement with temperature and electric field-dependent experimental mobilities. Our work makes a step forward towards the application of nanoscale theoretical schemes as a tool for predictive material screening.

A framework for stochastic simulations and visualization of biological electron-transfer dynamics

NASA Astrophysics Data System (ADS)

Nakano, C. Masato; Byun, Hye Suk; Ma, Heng; Wei, Tao; El-Naggar, Mohamed Y.

2015-08-01

Electron transfer (ET) dictates a wide variety of energy-conversion processes in biological systems. Visualizing ET dynamics could provide key insight into understanding and possibly controlling these processes. We present a computational framework named VizBET to visualize biological ET dynamics, using an outer-membrane Mtr-Omc cytochrome complex in Shewanella oneidensis MR-1 as an example. Starting from X-ray crystal structures of the constituent cytochromes, molecular dynamics simulations are combined with homology modeling, protein docking, and binding free energy computations to sample the configuration of the complex as well as the change of the free energy associated with ET. This information, along with quantum-mechanical calculations of the electronic coupling, provides inputs to kinetic Monte Carlo (KMC) simulations of ET dynamics in a network of heme groups within the complex. Visualization of the KMC simulation results has been implemented as a plugin to the Visual Molecular Dynamics (VMD) software. VizBET has been used to reveal the nature of ET dynamics associated with novel nonequilibrium phase transitions in a candidate configuration of the Mtr-Omc complex due to electron-electron interactions.

A cluster expansion model for predicting activation barrier of atomic processes

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

Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit, E-mail: achatter@iitk.ac.in

2013-06-15

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEBmore » results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.« less

State of the art and recommendations. Kangaroo mother care: application in a high-tech environment.

PubMed

Nyqvist, K H; Anderson, G C; Bergman, N; Cattaneo, A; Charpak, N; Davanzo, R; Ewald, U; Ludington-Hoe, S; Mendoza, S; Pallás-Allonso, C; Peláez, J G; Sizun, J; Wiström, A M

2010-11-01

Since Kangaroo Mother Care (KMC) was developed in Colombia in the 1970s, two trends in clinical application emerged. In low-income settings, the original KMC modelis implemented. This consists of continuous (24 h/day; 7 days/week) and prolonged mother/parent-infant skin-to-skin contact; early discharge with the infant in the kangaroo position; (ideally) exclusive breastfeeding and, adequate follow up. In affluent settings, intermittent KMC with sessions of one or a few hours skin-to-skin contact for a limited period is common. As a result of the increasing evidence of the benefits of KMC for both infants and families in all intensive care settings, KMC in a high-tech environment was chosen as the topic for the first European Conference on KMC, and the clinical implementation of the KMC modelin all types of settings was discussed at the 7th International Workshop on KMC Kangaroo Mother Care protocols in high-tech Neonatal Intensive Care Units (NICU) should specify criteria for initiation, kangaroo position, transfer to/from KMC, transport in kangaroo position, kangaroo nutrition, parents'role, modification of the NICU environment, performance of care in KMC, and KMCin case of infant instability. Implementation of the original KMC method, with continuous skin-to-skin contact whenever possible, is recommended for application in high-tech environments, although scientific evaluation should continue.

Consensus–based approach to develop a measurement framework and identify a core set of indicators to track implementation and progress towards effective coverage of facility–based Kangaroo Mother Care

PubMed Central

Guenther, Tanya; Moxon, Sarah; Valsangkar, Bina; Wetzel, Greta; Ruiz, Juan; Kerber, Kate; Blencowe, Hannah; Dube, Queen; Vani, Shashi N; Vivio, Donna; Magge, Hema; De Leon–Mendoza, Socorro; Patterson, Janna; Mazia, Goldy

2017-01-01

Background As efforts to scale up the delivery of Kangaroo Mother Care (KMC) in facilities are increasing, a standardized approach to measure implementation and progress towards effective coverage is needed. Here, we describe a consensus–based approach to develop a measurement framework and identify a core set of indicators for monitoring facility–based KMC that would be feasible to measure within existing systems. Methods The KMC measurement framework and core list of indicators were developed through: 1) scoping exercise to identify potential indicators through literature review and requests from researchers and program implementers; and 2) face–to–face consultations with KMC and measurement experts working at country and global levels to review candidate indicators and finalize selection and definitions. Results The KMC measurement framework includes two main components: 1) service readiness, based on the WHO building blocks framework; and 2) service delivery action sequence covering identification, service initiation, continuation to discharge, and follow–up to graduation. Consensus was reached on 10 core indicators for KMC, which were organized according to the measurement framework. We identified 4 service readiness indicators, capturing national level policy for KMC, availability of KMC indicators in HMIS, costed operational plans for KMC and availability of KMC services at health facilities with inpatient maternity services. Six indicators were defined for service delivery, including weighing of babies at birth, identification of those ≤2000 g, initiation of facility–based KMC, monitoring the quality of KMC, status of babies at discharge from the facility and levels of follow–up (according to country–specific protocol). Conclusions These core KMC indicators, identified with input from a wide range of global and country–level KMC and measurement experts, can aid efforts to strengthen monitoring systems and facilitate global tracking of KMC implementation. As data collection systems advance, we encourage program managers and evaluators to document their experiences using this framework to measure progress and allow indicator refinement, with the overall aim of working towards sustainable, country–led data systems. PMID:29057074

Consensus-based approach to develop a measurement framework and identify a core set of indicators to track implementation and progress towards effective coverage of facility-based Kangaroo Mother Care.

PubMed

Guenther, Tanya; Moxon, Sarah; Valsangkar, Bina; Wetzel, Greta; Ruiz, Juan; Kerber, Kate; Blencowe, Hannah; Dube, Queen; Vani, Shashi N; Vivio, Donna; Magge, Hema; De Leon-Mendoza, Socorro; Patterson, Janna; Mazia, Goldy

2017-12-01

As efforts to scale up the delivery of Kangaroo Mother Care (KMC) in facilities are increasing, a standardized approach to measure implementation and progress towards effective coverage is needed. Here, we describe a consensus-based approach to develop a measurement framework and identify a core set of indicators for monitoring facility-based KMC that would be feasible to measure within existing systems. The KMC measurement framework and core list of indicators were developed through: 1) scoping exercise to identify potential indicators through literature review and requests from researchers and program implementers; and 2) face-to-face consultations with KMC and measurement experts working at country and global levels to review candidate indicators and finalize selection and definitions. The KMC measurement framework includes two main components: 1) service readiness, based on the WHO building blocks framework; and 2) service delivery action sequence covering identification, service initiation, continuation to discharge, and follow-up to graduation. Consensus was reached on 10 core indicators for KMC, which were organized according to the measurement framework. We identified 4 service readiness indicators, capturing national level policy for KMC, availability of KMC indicators in HMIS, costed operational plans for KMC and availability of KMC services at health facilities with inpatient maternity services. Six indicators were defined for service delivery, including weighing of babies at birth, identification of those ≤2000 g, initiation of facility-based KMC, monitoring the quality of KMC, status of babies at discharge from the facility and levels of follow-up (according to country-specific protocol). These core KMC indicators, identified with input from a wide range of global and country-level KMC and measurement experts, can aid efforts to strengthen monitoring systems and facilitate global tracking of KMC implementation. As data collection systems advance, we encourage program managers and evaluators to document their experiences using this framework to measure progress and allow indicator refinement, with the overall aim of working towards sustainable, country-led data systems.

To study the effect of Kangaroo Mother Care on pain response in preterm neonates and to determine the behavioral and physiological responses to painful stimuli in preterm neonates: a study from western Rajasthan.

PubMed

Choudhary, Mukesh; Dogiyal, Hemaram; Sharma, Deepak; Datt Gupta, Brahma; Madabhavi, Irappa; Choudhary, Jagveer Singh; Choudhary, Sushil Kumar

2016-03-01

To study the effect of Kangaroo Mother Care (KMC) on pain response in preterm neonates and to determine the behavioral and physiological responses to painful stimuli in preterm neonates. This was a single-blind cross over study in which total 140 neonates were enrolled. Pain stimulus was given in the form of heel-lance before and after giving KMC and data were recorded. The effect of KMC on heart rate variability was statistically significant in preterm (30-34 wks) and very low birth weight (1.0-1.5 kg) neonates. The mean fall in SpO2 from base line was less in KMC group as compared to without KMC group at 60 s (1.63% versus 2.22%) and 120 s (0.45% versus 2.22%). The mean duration of cry was less in the KMC group (15.05 s) as compared to without KMC group (24.82 s) and the difference was statistically significant (p < 0.05). The mean duration of cry was reduced by 36% in KMC group as compared to the without KMC group. The effect of KMC on pain scores (premature infant pain profile (PIPP)) were significantly lower after heel-lance in KMC at 60 s (p < 0.01). KMC is a most physiological, non-pharmacological and easy intervention that involves parents: to manage procedural pain that can be implemented for physiological or behavioral stability in their premature infants.

Effect of Kangaroo Mother Care on physical growth, breastfeeding and its acceptability.

PubMed

Gathwala, Geeta; Singh, Bir; Singh, Jagjit

2010-10-01

The aim of this study was to determine whether the implementation of Kangaroo Mother Care (KMC) to low birth weight infants would improve physical growth, breastfeeding and its acceptability. A randomized controlled trial was performed over 16 months in which 110 neonates were randomized into a KMC group and a control group using a random number table. The KMC group was subjected to KMC for at least 6 h per day. The babies also received KMC after moving from the neonatal intensive care unit and at home. The control group received standard care (incubator or open care system). Weight, length and occipitofrontal circumference (OFC) were measured weekly for three months. The acceptability of KMC by mothers and nursing staff was assessed on day 7 after the start of KMC using a questionnaire incorporating the Likert scale. Breastfeeding rates were calculated based on history at end of three months. The mean gestational age was 35.48 ± 1.20 weeks in the KMC group and 35.04 ± 1.09 weeks in the control group (P > 0.05). KMC was initiated at a mean age of 1.72 ± 0.45 days and the duration of KMC was 9.74 ± 1.48 h/day. The mean birth weight was 1.69 ± 0.11 kg in the KMC group compared to 1.69 ± 0.12 kg in the control group (P > 0.05). The mean weight gain in gm/day in the KMC group was 21.92 ± 1.44 compared to 18.61 ± 1.28 in the control group (P < 0.05). The mean length gain in cm/week was 1.03 ± 0.5 in the KMC group compared to 0.74 ± 0.05 in the control group (P < 0.05). The mean OFC gain in cm/week was 0.59 ± 0.04 in the KMC group compared to 0.47 ± 0.03 in the control group (P < 0.05). The exclusive breast-feeding rate at end of three months was 88% in the KMC group compared to 72% in the control group (P < 0.05). KMC improved physical growth, breastfeeding rates and was well accepted by both mothers and nursing staff.

Kangaroo mother care to reduce morbidity and mortality in low birthweight infants.

PubMed

Conde-Agudelo, Agustin; Belizán, José M; Diaz-Rossello, Jose

2011-03-16

Kangaroo mother care (KMC), originally defined as skin-to-skin contact between a mother and her newborn, frequent and exclusive or nearly exclusive breastfeeding, and early discharge from hospital, has been proposed as an alternative to conventional neonatal care for low birthweight (LBW) infants. To determine whether there is evidence to support the use of KMC in LBW infants as an alternative to conventional neonatal care. The standard search strategy of the Cochrane Neonatal Group was used. This included searches of MEDLINE, EMBASE, LILACS, POPLINE, CINAHL databases (from inception to January 31, 2011), and the Cochrane Central Register of Controlled Trials (The Cochrane Library, Issue 1, 2011). In addition, we searched the web page of the Kangaroo Foundation, conference and symposia proceedings on KMC, and Google scholar. Randomized controlled trials comparing KMC versus conventional neonatal care, or early onset KMC (starting within 24 hours after birth) versus late onset KMC (starting after 24 hours after birth) in LBW infants. Data collection and analysis were performed according to the methods of the Cochrane Neonatal Review Group. Sixteen studies, including 2518 infants, fulfilled inclusion criteria. Fourteen studies evaluated KMC in LBW infants after stabilization, one evaluated KMC in LBW infants before stabilization, and one compared early onset KMC with late onset KMC in relatively stable LBW infants. Eleven studies evaluated intermittent KMC and five evaluated continuous KMC. At discharge or 40 - 41 weeks' postmenstrual age, KMC was associated with a reduction in the risk of mortality (typical risk ratio (RR) 0.60, 95% confidence interval (CI) 0.39 to 0.93; seven trials, 1614 infants), nosocomial infection/sepsis (typical RR 0.42, 95% CI 0.24 to 0.73), hypothermia (typical RR 0.23, 95% CI 0.10 to 0.55), and length of hospital stay (typical mean difference 2.4 days, 95% CI 0.7 to 4.1). At latest follow up, KMC was associated with a decreased risk of mortality (typical RR 0.68, 95% CI 0.48 to 0.96; nine trials, 1952 infants) and severe infection/sepsis (typical RR 0.57, 95% CI 0.40 to 0.80). Moreover, KMC was found to increase some measures of infant growth, breastfeeding, and mother-infant attachment. The evidence from this updated review supports the use of KMC in LBW infants as an alternative to conventional neonatal care mainly in resource-limited settings. Further information is required concerning effectiveness and safety of early onset continuous KMC in unstabilized LBW infants, long term neurodevelopmental outcomes, and costs of care.

The implementation of kangaroo mother care and nurses' perspective of barriers in Iranian' NICUs.

PubMed

Namnabati, Mahboobeh; Talakoub, Sedigheh; Mohammadizadeh, Majid; Mousaviasl, Fatemesadat

2016-01-01

Kangaroo mother care (KMC) is the most implementation intervention in caring of the infants, as in this method, both the mothers and infants are cared. The World Health Organization recommends implementation of KMC for all infants. However, there are some barriers in the way of its application. The purpose of this study was evaluation of the practical application of KMC and nurses' perspective about its implantation barriers in the neonatal intensive care units (NICUs) in Iran. The descriptive study was conducted on 96 infants and 80 nurses working in the NICUs of two university hospitals in Isfahan, Iran. Data were collected by a two-section questionnaire and analyzed by t-test through SPSS 14. Study findings indicated that mean weight and age of the infants with KMC were 1510 g and 32 weeks, respectively. KMC was implantation for 32 min in a day. From nurses' perspective, mother-related barriers were the main barriers in the implantation of KMC as mothers were not present by their infants. Another barrier was the mothers' fear of touching their infants. In the domain of organizational barriers, physician's order was found to be the most important barrier in application of KMC. Identifying barriers in implantation of KMC is essential to support the mothers. Regarding mother-related barriers, organizational barriers, and the need for a physician's order for implementation of KMC, policy makers must provide facilities and equipment for applying KMC practice for mothers and improve the protocol of KMC in the NICU.

Barriers and Enablers of Kangaroo Mother Care Practice: A Systematic Review

PubMed Central

Seidman, Gabriel; Unnikrishnan, Shalini; Kenny, Emma; Myslinski, Scott; Cairns-Smith, Sarah; Mulligan, Brian; Engmann, Cyril

2015-01-01

Kangaroo mother care (KMC) is an evidence-based approach to reducing mortality and morbidity in preterm infants. Although KMC is a key intervention package in newborn health initiatives, there is limited systematic information available on the barriers to KMC practice that mothers and other stakeholders face while practicing KMC. This systematic review sought to identify the most frequently reported barriers to KMC practice for mothers, fathers, and health practitioners, as well as the most frequently reported enablers to practice for mothers. We searched nine electronic databases and relevant reference lists for publications reporting barriers or enablers to KMC practice. We identified 1,264 unique publications, of which 103 were included based on pre-specified criteria. Publications were scanned for all barriers / enablers. Each publication was also categorized based on its approach to identification of barriers / enablers, and more weight was assigned to publications which had systematically sought to understand factors influencing KMC practice. Four of the top five ranked barriers to KMC practice for mothers were resource-related: “Issues with the facility environment / resources,” “negative impressions of staff attitudes or interactions with staff,” “lack of help with KMC practice or other obligations,” and “low awareness of KMC / infant health.” Considering only publications from low- and middle-income countries, “pain / fatigue” was ranked higher than when considering all publications. Top enablers to practice were included “mother-infant attachment” and “support from family, friends, and other mentors.” Our findings suggest that mother can understand and enjoy KMC, and it has benefits for mothers, infants, and families. However, continuous KMC may be physically and emotionally difficult, and often requires support from family members, health practitioners, or other mothers. These findings can serve as a starting point for researchers and program implementers looking to improve KMC programs. PMID:25993306

Charge carrier concentration dependence of encounter-limited bimolecular recombination in phase-separated organic semiconductor blends

NASA Astrophysics Data System (ADS)

Heiber, Michael C.; Nguyen, Thuc-Quyen; Deibel, Carsten

2016-05-01

Understanding how the complex intermolecular configurations and nanostructure present in organic semiconductor donor-acceptor blends impacts charge carrier motion, interactions, and recombination behavior is a critical fundamental issue with a particularly major impact on organic photovoltaic applications. In this study, kinetic Monte Carlo (KMC) simulations are used to numerically quantify the complex bimolecular charge carrier recombination behavior in idealized phase-separated blends. Recent KMC simulations have identified how the encounter-limited bimolecular recombination rate in these blends deviates from the often used Langevin model and have been used to construct the new power mean mobility model. Here, we make a challenging but crucial expansion to this work by determining the charge carrier concentration dependence of the encounter-limited bimolecular recombination coefficient. In doing so, we find that an accurate treatment of the long-range electrostatic interactions between charge carriers is critical, and we further argue that many previous KMC simulation studies have used a Coulomb cutoff radius that is too small, which causes a significant overestimation of the recombination rate. To shed more light on this issue, we determine the minimum cutoff radius required to reach an accuracy of less than ±10 % as a function of the domain size and the charge carrier concentration and then use this knowledge to accurately quantify the charge carrier concentration dependence of the recombination rate. Using these rigorous methods, we finally show that the parameters of the power mean mobility model are determined by a newly identified dimensionless ratio of the domain size to the average charge carrier separation distance.

The three waves in implementation of facility-based kangaroo mother care: a multi-country case study from Asia.

PubMed

Bergh, Anne-Marie; de Graft-Johnson, Joseph; Khadka, Neena; Om'Iniabohs, Alyssa; Udani, Rekha; Pratomo, Hadi; De Leon-Mendoza, Socorro

2016-01-27

Kangaroo mother care has been highlighted as an effective intervention package to address high neonatal mortality pertaining to preterm births and low birth weight. However, KMC uptake and service coverage have not progressed well in many countries. The aim of this case study was to understand the institutionalisation processes of facility-based KMC services in three Asian countries (India, Indonesia and the Philippines) and the reasons for the slow uptake of KMC in these countries. Three main data sources were available: background documents providing insight in the state of implementation of KMC in the three countries; visits to a selection of health facilities to gauge their progress with KMC implementation; and data from interviews and meetings with key stakeholders. The establishment of KMC services at individual facilities began many years before official prioritisation for scale-up. Three major themes were identified: pioneers of facility-based KMC; patterns of KMC knowledge and skills dissemination; and uptake and expansion of KMC services in relation to global trends and national policies. Pioneers of facility-based KMC were introduced to the concept in the 1990s and established the practice in a few individual tertiary or teaching hospitals, without further spread. A training method beneficial to the initial establishment of KMC services in a country was to send institutional health-professional teams to learn abroad, notably in Colombia. Further in-country cascading took place afterwards and still later on KMC was integrated into newborn and obstetric care programs. The patchy uptake and expansion of KMC services took place in three phases aligned with global trends of the time: the pioneer phase with individual champions while the global focus was on child survival (1998-2006); the newborn-care phase (2007-2012); and lastly the current phase where small babies are also included in action plans. This paper illustrates the complexities of implementing a new healthcare intervention. Although preterm care is currently in the limelight, clear and concerted country-led KMC scale-up strategies with associated operational plans and budgets are essential for successful scale-up.

Kinetic Monte Carlo simulation of the efficiency roll-off, emission color, and degradation of organic light-emitting diodes (Presentation Recording)

NASA Astrophysics Data System (ADS)

Coehoorn, Reinder; van Eersel, Harm; Bobbert, Peter A.; Janssen, Rene A. J.

2015-10-01

The performance of Organic Light Emitting Diodes (OLEDs) is determined by a complex interplay of the charge transport and excitonic processes in the active layer stack. We have developed a three-dimensional kinetic Monte Carlo (kMC) OLED simulation method which includes all these processes in an integral manner. The method employs a physically transparent mechanistic approach, and is based on measurable parameters. All processes can be followed with molecular-scale spatial resolution and with sub-nanosecond time resolution, for any layer structure and any mixture of materials. In the talk, applications to the efficiency roll-off, emission color and lifetime of white and monochrome phosphorescent OLEDs [1,2] are demonstrated, and a comparison with experimental results is given. The simulations show to which extent the triplet-polaron quenching (TPQ) and triplet-triplet-annihilation (TTA) contribute to the roll-off, and how the microscopic parameters describing these processes can be deduced properly from dedicated experiments. Degradation is treated as a result of the (accelerated) conversion of emitter molecules to non-emissive sites upon a triplet-polaron quenching (TPQ) process. The degradation rate, and hence the device lifetime, is shown to depend on the emitter concentration and on the precise type of TPQ process. Results for both single-doped and co-doped OLEDs are presented, revealing that the kMC simulations enable efficient simulation-assisted layer stack development. [1] H. van Eersel et al., Appl. Phys. Lett. 105, 143303 (2014). [2] R. Coehoorn et al., Adv. Funct. Mater. (2015), publ. online (DOI: 10.1002/adfm.201402532)

Mechanism of CO 2 hydrogenation over Cu/ZrO 2(2̅12) interface from first-principles kinetics Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Hong, Qi-Jun; Liu, Zhi-Pan

2010-10-01

It has been a goal consistently pursued by chemists to understand and control the catalytic process over composite materials. In order to provide deeper insight on complex interfacial catalysis at the experimental conditions, we performed an extensive analysis on CO 2 hydrogenation over a Cu/ZrO 2 model catalyst by employing density functional theory (DFT) calculations and kinetic Monte Carlo (kMC) simulations based on the continuous stirred tank model. The free energy profiles are determined for the reaction at the oxygen-rich Cu/m-ZrO 2 (2̅12) interface, where all interfacial Zr are six-coordinated since the interface accumulates oxidative species at the reaction conditions. We show that not only methanol but also CO are produced through the formate pathway dominantly, whilst the reverse-water-gas-shift (RWGS) channel has only a minor contribution. H 2CO is a key intermediate species in the reaction pathway, the hydrogenation of which dictates the high temperature of CO 2 hydrogenation. The kinetics simulation shows that the CO 2 conversion is 1.20%, the selectivity towards methanol is 68% at 500 K and the activation energies for methanol and CO formation are 0.79 and 1.79 eV, respectively. The secondary reactions due to the product readsorption lower the overall turnover frequency (TOF) but increase the selectivity towards methanol by 16%. We also show that kMC is a more reliable tool for simulating heterogeneous catalytic processes compared to the microkinetics approach.

Kangaroo mother care to reduce morbidity and mortality in low birthweight infants.

PubMed

Conde-Agudelo, Agustin; Díaz-Rossello, José L

2014-04-22

Kangaroo mother care (KMC), originally defined as skin-to-skin contact between a mother and her newborn, frequent and exclusive or nearly exclusive breastfeeding, and early discharge from hospital, has been proposed as an alternative to conventional neonatal care for low birthweight (LBW) infants. To determine whether there is evidence to support the use of KMC in LBW infants as an alternative to conventional neonatal care. The standard search strategy of the Cochrane Neonatal Group was used. This included searches in MEDLINE, EMBASE, LILACS, POPLINE, CINAHL databases (all from inception to March 31, 2014) and the Cochrane Central Register of Controlled Trials (The Cochrane Library, Issue 3, 2014) In addition, we searched the web page of the Kangaroo Foundation, conference and symposia proceedings on KMC, and Google scholar. Randomized controlled trials comparing KMC versus conventional neonatal care, or early onset KMC (starting within 24 hours after birth) versus late onset KMC (starting after 24 hours after birth) in LBW infants. Data collection and analysis were performed according to the methods of the Cochrane Neonatal Review Group. Eighteen studies, including 2751 infants, fulfilled inclusion criteria. Sixteen studies evaluated KMC in LBW infants after stabilization, one evaluated KMC in LBW infants before stabilization, and one compared early onset KMC with late onset KMC in relatively stable LBW infants. Thirteen studies evaluated intermittent KMC and five evaluated continuous KMC. At discharge or 40-41 weeks' postmenstrual age, KMC was associated with a reduction in the risk of mortality (typical risk ratio (RR) 0.60, 95% confidence interval (CI) 0.39 to 0.92; eight trials, 1736 infants), nosocomial infection/sepsis (typical RR 0.45, 95% CI 0.27 to 0.76), hypothermia (typical RR 0.34, 95% CI 0.17 to 0.67), and length of hospital stay (typical mean difference 2.2 days, 95% CI 0.6 to 3.7). At latest follow up, KMC was associated with a decreased risk of mortality (typical RR 0.67, 95% CI 0.48 to 0.95; 11 trials, 2167 infants) and severe infection/sepsis (typical RR 0.56, 95% CI 0.40 to 0.78). Moreover, KMC was found to increase some measures of infant growth, breastfeeding, and mother-infant attachment. There were no significant differences between KMC infants and controls in neurodevelopmental and neurosensory impairment at one year of corrected age. Sensitivity analysis suggested that the inclusion of studies with high risk of bias did not affect the general direction of findings or the size of the treatment effect for the main outcomes. The evidence from this updated review supports the use of KMC in LBW infants as an alternative to conventional neonatal care mainly in resource-limited settings. Further information is required concerning effectiveness and safety of early onset continuous KMC in unstabilized or relatively stabilized LBW infants, long term neurodevelopmental outcomes, and costs of care.

The implementation of kangaroo mother care and nurses’ perspective of barriers in Iranian’ NICUs

PubMed Central

Namnabati, Mahboobeh; Talakoub, Sedigheh; Mohammadizadeh, Majid; Mousaviasl, Fatemesadat

2016-01-01

Background: Kangaroo mother care (KMC) is the most implementation intervention in caring of the infants, as in this method, both the mothers and infants are cared. The World Health Organization recommends implementation of KMC for all infants. However, there are some barriers in the way of its application. The purpose of this study was evaluation of the practical application of KMC and nurses’ perspective about its implantation barriers in the neonatal intensive care units (NICUs) in Iran. Materials and Methods: The descriptive study was conducted on 96 infants and 80 nurses working in the NICUs of two university hospitals in Isfahan, Iran. Data were collected by a two-section questionnaire and analyzed by t-test through SPSS 14. Results: Study findings indicated that mean weight and age of the infants with KMC were 1510 g and 32 weeks, respectively. KMC was implantation for 32 min in a day. From nurses’ perspective, mother-related barriers were the main barriers in the implantation of KMC as mothers were not present by their infants. Another barrier was the mothers’ fear of touching their infants. In the domain of organizational barriers, physician's order was found to be the most important barrier in application of KMC. Conclusions: Identifying barriers in implantation of KMC is essential to support the mothers. Regarding mother-related barriers, organizational barriers, and the need for a physician's order for implementation of KMC, policy makers must provide facilities and equipment for applying KMC practice for mothers and improve the protocol of KMC in the NICU. PMID:26985227

KMCLib: A general framework for lattice kinetic Monte Carlo (KMC) simulations

NASA Astrophysics Data System (ADS)

Leetmaa, Mikael; Skorodumova, Natalia V.

2014-09-01

KMCLib is a general framework for lattice kinetic Monte Carlo (KMC) simulations. The program can handle simulations of the diffusion and reaction of millions of particles in one, two, or three dimensions, and is designed to be easily extended and customized by the user to allow for the development of complex custom KMC models for specific systems without having to modify the core functionality of the program. Analysis modules and on-the-fly elementary step diffusion rate calculations can be implemented as plugins following a well-defined API. The plugin modules are loosely coupled to the core KMCLib program via the Python scripting language. KMCLib is written as a Python module with a backend C++ library. After initial compilation of the backend library KMCLib is used as a Python module; input to the program is given as a Python script executed using a standard Python interpreter. We give a detailed description of the features and implementation of the code and demonstrate its scaling behavior and parallel performance with a simple one-dimensional A-B-C lattice KMC model and a more complex three-dimensional lattice KMC model of oxygen-vacancy diffusion in a fluorite structured metal oxide. KMCLib can keep track of individual particle movements and includes tools for mean square displacement analysis, and is therefore particularly well suited for studying diffusion processes at surfaces and in solids. Catalogue identifier: AESZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AESZ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 49 064 No. of bytes in distributed program, including test data, etc.: 1 575 172 Distribution format: tar.gz Programming language: Python and C++. Computer: Any computer that can run a C++ compiler and a Python interpreter. Operating system: Tested on Ubuntu 12.4 LTS, CentOS release 5.9, Mac OSX 10.5.8 and Mac OSX 10.8.2, but should run on any system that can have a C++ compiler, MPI and a Python interpreter. Has the code been vectorized or parallelized?: Yes. From one to hundreds of processors depending on the type of input and simulation. RAM: From a few megabytes to several gigabytes depending on input parameters and the size of the system to simulate. Classification: 4.13, 16.13. External routines: KMCLib uses an external Mersenne Twister pseudo random number generator that is included in the code. A Python 2.7 interpreter and a standard C++ runtime library are needed to run the serial version of the code. For running the parallel version an MPI implementation is needed, such as e.g. MPICH from http://www.mpich.org or Open-MPI from http://www.open-mpi.org. SWIG (obtainable from http://www.swig.org/) and CMake (obtainable from http://www.cmake.org/) are needed for building the backend module, Sphinx (obtainable from http://sphinx-doc.org) for building the documentation and CPPUNIT (obtainable from http://sourceforge.net/projects/cppunit/) for building the C++ unit tests. Nature of problem: Atomic scale simulation of slowly evolving dynamics is a great challenge in many areas of computational materials science and catalysis. When the rare-events dynamics of interest is orders of magnitude slower than the typical atomic vibrational frequencies a straight-forward propagation of the equations of motions for the particles in the simulation cannot reach time scales of relevance for modeling the slow dynamics. Solution method: KMCLib provides an implementation of the kinetic Monte Carlo (KMC) method that solves the slow dynamics problem by utilizing the separation of time scales between fast vibrational motion and the slowly evolving rare-events dynamics. Only the latter is treated explicitly and the system is simulated as jumping between fully equilibrated local energy minima on the slow-dynamics potential energy surface. Restrictions: KMCLib implements the lattice KMC method and is as such restricted to geometries that can be expressed on a grid in space. Unusual features: KMCLib has been designed to be easily customized, to allow for user-defined functionality and integration with other codes. The user can define her own on-the-fly rate calculator via a Python API, so that site-specific elementary process rates, or rates depending on long-range interactions or complex geometrical features can easily be included. KMCLib also allows for on-the-fly analysis with user-defined analysis modules. KMCLib can keep track of individual particle movements and includes tools for mean square displacement analysis, and is therefore particularly well suited for studying diffusion processes at surfaces and in solids. Additional comments: The full documentation of the program is distributed with the code and can also be found at http://www.github.com/leetmaa/KMCLib/manual Running time: rom a few seconds to several days depending on the type of simulation and input parameters.

Maternal perceptions and factors affecting Kangaroo mother care continuum at home: a descriptive study.

PubMed

Raajashri, R; Adhisivam, B; Vishnu Bhat, B; Palanivel, C

2018-03-01

To estimate the proportion of mothers who continued to practice Kangaroo mother care (KMC) at home and evaluate potential factors influencing this practice. This descriptive study was conducted in a tertiary care teaching hospital in south India. Mothers of preterm and low birth weight infants were trained in KMC during hospital stay. During follow up after 45 days, data regarding their perceptions and the practice of KMC at home and the factors influencing them were collected using questionnaires. Among 200 mothers interviewed, 82.5% continued to practice KMC at home after discharge. The mean total duration of KMC was 30.2 days and average duration per day was 1.3 h. Support of family members was facilitatory in 70% and lack of privacy at home was hindering in 25%. After KMC training in hospital, majority of the post natal mothers were able to continue the practice satisfactorily at home despite hindering factors including lack of privacy. KMC training modules should emphasize continuing the practice at home after discharge and address the potential barriers for KMC continuum in the community.

KMC 2: fast and resource-frugal k-mer counting.

PubMed

Deorowicz, Sebastian; Kokot, Marek; Grabowski, Szymon; Debudaj-Grabysz, Agnieszka

2015-05-15

Building the histogram of occurrences of every k-symbol long substring of nucleotide data is a standard step in many bioinformatics applications, known under the name of k-mer counting. Its applications include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. The tremendous amounts of NGS data require fast algorithms for k-mer counting, preferably using moderate amounts of memory. We present a novel method for k-mer counting, on large datasets about twice faster than the strongest competitors (Jellyfish 2, KMC 1), using about 12 GB (or less) of RAM. Our disk-based method bears some resemblance to MSPKmerCounter, yet replacing the original minimizers with signatures (a carefully selected subset of all minimizers) and using (k, x)-mers allows to significantly reduce the I/O and a highly parallel overall architecture allows to achieve unprecedented processing speeds. For example, KMC 2 counts the 28-mers of a human reads collection with 44-fold coverage (106 GB of compressed size) in about 20 min, on a 6-core Intel i7 PC with an solid-state disk. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Rolling out of kangaroo mother care in secondary level facilities in Bihar-Some experiences.

PubMed

Neogi, Sutapa B; Chauhan, Monika; Sharma, Jyoti; Negandhi, Preeti; Sethy, Ghanshyam

2016-01-01

Preterm birth is one of the leading causes of under-five child deaths worldwide and in India. Kangaroo mother care (KMC) is a powerful and easy-to-use method to promote health and well-being and reduce morbidity and mortality in preterm/low birth weight (LBW) babies. As the part of the roll-out of India Newborn Action Plan interventions, we implemented KMC in select facilities with an objective to assess the responsiveness of public health system to roll out KMC. KMC intervention was implemented in two select high priority districts, Gaya and Purnea in Bihar over the duration of 8 months from August 2015 to March 2016. The implementation of intervention was phased out into; situation analysis, implementation of intervention, and interim assessment. KMC model, as envisaged keeping in mind the building blocks of health system, was established in 6 identified health-care facilities. A pretested simple checklist was used to assess the awareness, knowledge, skills, and practice of KMC during baseline situational analysis and interim assessment phases for comparison. The intervention clearly seemed to improve the awareness among auxiliary nurse midwives/nurses about KMC. Improvements were also observed in the availability of infrastructure required for KMC and support logistics like facility for manual expression of breast milk, cups/suitable devices such as paladi cups for feeding small babies and digital weighing scale. Although the recording of information regarding LBW babies and KMC practice improved, still there is scope for much improvement. There is a commitment at the national level to promote KMC in every facility. The present experience shows the possibility of rolling out KMC in secondary level facilities with support from government functionaries.

Real-time ab initio KMC simulation of the self-assembly and sintering of bimetallic epitaxial nanoclusters: Au + Ag on Ag(100).

PubMed

Han, Yong; Liu, Da-Jiang; Evans, James W

2014-08-13

Far-from-equilibrium shape and structure evolution during formation and post-assembly sintering of bimetallic nanoclusters is extremely sensitive to the periphery diffusion and intermixing kinetics. Precise characterization of the many distinct local-environment-dependent diffusion barriers is achieved for epitaxial nanoclusters using density functional theory to assess interaction energies both with atoms at adsorption sites and at transition states. Kinetic Monte Carlo simulation incorporating these barriers then captures structure evolution on the appropriate time scale for two-dimensional core-ring and intermixed Au-Ag nanoclusters on Ag(100).

Real-Time Ab Initio KMC Simulation of the Self-Assembly and Sintering of Bimetallic Epitaxial Nanoclusters: Au + Ag on Ag(100)

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

Han, Yong; Liu, Da-Jiang; Evans, James W

2014-08-13

Far-from-equilibrium shape and structure evolution during formation and post-assembly sintering of bimetallic nanoclusters is extremely sensitive to the periphery diffusion and intermixing kinetics. Precise characterization of the many distinct local-environment-dependent diffusion barriers is achieved for epitaxial nanoclusters using density functional theory to assess interaction energies both with atoms at adsorption sites and at transition states. Kinetic Monte Carlo simulation incorporating these barriers then captures structure evolution on the appropriate time scale for two-dimensional core-ring and intermixed Au-Ag nanoclusters on Ag(100).

The role of the electrolyte in the selective dissolution of metal alloys

NASA Astrophysics Data System (ADS)

Policastro, Steven A.

Dealloying plays an important role in several corrosion processes, including pitting corrosion through the formation of local cathodes from the selective dissolution of intermetallic particles and stress-corrosion cracking in which it is responsible for injecting cracks from the surface into the undealloyed bulk material. Additionally, directed dealloying in the laboratory to form nanoporous structures has been the subject of much recent study because of the unique structural properties that the porous layer provides. In order to better understand the physical reasons for dealloying as well as understand the parameters that influence the evolution of the microstructure, several models have been proposed. Current theoretical descriptions of dealloying have been very successful in explaining some features of selective dissolution but additional behaviors can be included into the model to improve understanding of the dealloying process. In the present work, the effects of electrolyte component interactions, temperature, alloy cohesive energies, and applied potential on the development of nanoporosity via the selective dissolution of the less-noble component from binary and ternary alloys are considered. Both a kinetic Monte-Carlo (KMC) model of the behavior of the metal atoms and the electrolyte ions at the metal-solution interface and a phase-yield model of ligament coarsening are developed. By adding these additional parameters into the KMC model, a rich set of behaviors is observed in the simulation results. From the simulation results, it is suggested that selectively dissolving a binary alloy in a very aggressive electrolyte that targeted the LN atoms could provide a porous microstructure that retained a higher concentration of the LN atoms in its ligaments and thus retain more of the mechanical properties of the bulk alloy. In addition, by adding even a small fraction of a third, noble component to form a ternary alloy the dissolution kinetics of the least noble component can be dramatically altered, providing a means of controlling dealloying depth. Some molecular dynamics calculations are used to justify the assumptions of metal atom motion in the KMC model. A recently developed parameter-space exploration technique, COERCE, is employed to optimize the process of obtaining meaningful parameter values from the KMC simulation.

Earlier versus later continuous Kangaroo Mother Care (KMC) for stable low-birth-weight infants: a randomized controlled trial.

PubMed

Nagai, S; Andrianarimanana, D; Rabesandratana, N; Yonemoto, N; Nakayama, T; Mori, R

2010-06-01

The aim of this study was to examine the effectiveness of earlier continuous Kangaroo Mother Care (KMC) for relatively stable low-birth-weight (LBW) infants in a resource-limited country. A randomized controlled trial was performed in LBW infants at a referral hospital in Madagascar. Earlier continuous KMC (intervention) was begun as soon as possible, within 24 h postbirth, and later continuous KMC (control: conventional care) was begun after complete stabilization (generally after 24 h postbirth). Main outcome measure was mortality during the first 28 days postbirth. This trial was registered with ClinicalTrials.gov, NCT00531492. A total of 73 infants (intervention 37, control 36) were included. Earlier continuous KMC had higher but no statistically different mortality in the first 28 days postbirth (1 vs. 2; risk ratio, 1.95; 95% CIs, 0.18-20.53; p = 1.00). There were no differences in incidence of morbidities. Body weight loss from birth to 24 h postbirth was significantly less in earlier KMC infants compared with later KMC infants. (-34.81 g vs. -73.97 g; mean difference, 39.16 g; 95% CIs, 10.30-68.03; p = 0.01; adjusted p = 0.02). Adverse events and duration of hospitalization were not different between the two groups. Further evaluations of earlier continuous KMC including measurement of KMC dose, are needed in resource-limited countries.

Maternal and neonatal nurse perceived value of kangaroo mother care and maternal care partnership in the neonatal intensive care unit.

PubMed

Hendricks-Muñoz, Karen D; Li, Yihong; Kim, Yang S; Prendergast, Carol C; Mayers, Roslyn; Louie, Moi

2013-11-01

Kangaroo Mother Care (KMC) enhances infant and maternal well-being and requires maternal-care partnerships (MCP) for implementation. To examine maternal and neonatal nurse provider perspectives on the value of KMC and MCP. Prospective cohort design of neonatal nurses and mothers of preterm infants self-report anonymous questionnaire. Analyses of categorical independent variables and continuous variables were calculated. In all, 82.3% of nurses (42) and 100% (143) of mothers participated in the survey. compared with 18% of nurses, 63% of mothers believed "KMC should be provided daily" and 90% of mothers compared with 40% of nurses strongly believed "mothers should be partners in care." In addition, 61% of nonwhite mothers identified that "KMC was not something they were told they could do for their infant" compared with 39% of white mothers. Nonwhite and foreign-born nurses were 2.8 and 3.1 times more likely to encourage MCP and KMC. Mothers held strong positive perceptions of KMC and MCP value compared with nurses. Nonwhite mothers perceived they received less education and access to KMC. Barriers to KMC and MCP exist among nurses, though less in nonwhite, foreign-born, and/or nurses with their own children, identifying important provider educational opportunities to improve maternal KMC access in the NICU. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Kangaroo mother care for low birth weight infants: a randomized controlled trial.

PubMed

Suman, Rao P N; Udani, Rekha; Nanavati, Ruchi

2008-01-01

To compare the effect of Kangaroo mother care (KMC) and conventional methods of care (CMC) on growth in LBW babies (> 2000 g). Randomized controlled trial. Level III NICU of a teaching institution in western India. 206 neonates with birth weight < 2000 g. The subjects were randomized into two groups: the intervention group (KMC-103) received Kangaroo mother care. The control group (CMC: 103) received conventional care. Growth, as measured by average daily weight gain and by other anthropometrical parameters at 40 weeks postmenstrual age in preterm babies and at 2500 g in term SGA infants was assessed. The KMC babies had better average weight gain per day (KMC: 23.99 g vs CMC: 15.58 g, P< 0.0001). The weekly increments in head circumference (KMC: 0.75 cm vs CMC: 0.49 cm, P = 0.02) and length (KMC: 0.99 cm vs CMC: 0.7 cm, P = 0.008) were higher in the KMC group. A significantly higher number of babies in the CMC group suffered from hypothermia, hypoglycemia, and sepsis. There was no effect on time to discharge. More KMC babies were exclusively breastfed at the end of the study (98% vs 76%). KMC was acceptable to most mothers and families at home. Kangaroo mother care improves growth and reduces morbidities in low birth weight infants. It is simple, acceptable to mothers and can be continued at home.

Maternal and Neonatal Nurse Perceived Value of Kangaroo Mother Care and Maternal Care Partnership in the Neonatal Intensive Care Unit

PubMed Central

Hendricks-Muñoz, Karen D.; Li, Yihong; Kim, Yang S.; Prendergast, Carol C.; Mayers, Roslyn; Louie, Moi

2015-01-01

Background Kangaroo Mother Care (KMC) enhances infant and maternal well-being and requires maternal-care partnerships (MCP) for implementation. Objective To examine maternal and neonatal nurse provider perspectives on the value of KMC and MCP. Study Design Prospective cohort design of neonatal nurses and mothers of preterm infants self-report anonymous questionnaire. Analyses of categorical independent variables and continuous variables were calculated. Results In all, 82.3% of nurses (42) and 100% (143) of mothers participated in the survey. compared with 18% of nurses, 63% of mothers believed “KMC should be provided daily” and 90% of mothers compared with 40% of nurses strongly believed “mothers should be partners in care.” In addition, 61% of nonwhite mothers identified that “KMC was not something they were told they could do for their infant” compared with 39% of white mothers. Nonwhite and foreign-born nurses were 2.8 and 3.1 times more likely to encourage MCP and KMC. Conclusion Mothers held strong positive perceptions of KMC and MCP value compared with nurses. Nonwhite mothers perceived they received less education and access to KMC. Barriers to KMC and MCP exist among nurses, though less in nonwhite, foreign-born, and/or nurses with their own children, identifying important provider educational opportunities to improve maternal KMC access in the NICU. PMID:23359231

Progress with the implementation of kangaroo mother care in four regions in Ghana.

PubMed

Bergh, A-M; Manu, R; Davy, K; Van Rooyen, E; Quansah Asare, G; Awoonor-Williams, Jk; Dedzo, M; Twumasi, A; Nang-Beifubah, A

2013-06-01

To measure progress with the implementation of kangaroo mother care (KMC) for low birth-weight (LBW) infants at a health systems level. Action research design, with district and regional hospitals as the unit of analysis. Four regions in Ghana, identified by the Ghana Health Service and UNICEF. Health workers and officials, health care facilities and districts in the four regions. A one-year implementation programme with three phases: (1) introduction to KMC, skills development in KMC practice and the management of implementation; (2) advanced skills development for regional steering committee members; and (3) an assessment of progress at the end of the intervention. Description of practices, services and facilities for KMC and the identification of strengths and challenges. Twenty-six of 38 hospitals (68%) demonstrated sufficient progress with KMC implementation. Half of the hospitals had designated a special ward for KMC. 66% of hospitals used a special record for infants receiving KMC. Two of the main challenges were lack of support for mothers who had to remain with their LBW infants in hospital and no follow-up review services for LBW infants in 39% of hospitals. It was possible to roll out KMC in Ghana, but further support for the regions is needed to maintain the momentum. Lessons learned from this project could inform further scale-up of KMC and other projects in Ghana.

Role of Sink Density in Nonequilibrium Chemical Redistribution in Alloys

DOE PAGES

Martinez, Enrique Saez; Senninger, Oriane; Caro, Alfredo; ...

2018-03-08

Nonequilibrium chemical redistribution in open systems submitted to external forces, such as particle irradiation, leads to changes in the structural properties of the material, potentially driving the system to failure. Such redistribution is controlled by the complex interplay between the production of point defects, atomic transport rates, and the sink character of the microstructure. In this work, we analyze this interplay by means of a kinetic Monte Carlo (KMC) framework with an underlying atomistic model for the Fe-Cr model alloy to study the effect of ideal defect sinks on Cr concentration profiles, with a particular focus on the role ofmore » interface density. We observe that the amount of segregation decreases linearly with decreasing interface spacing. Within the framework of the thermodynamics of irreversible processes, a general analytical model is derived and assessed against the KMC simulations to elucidate the structure-property relationship of this system. Interestingly, in the kinetic regime where elimination of point defects at sinks is dominant over bulk recombination, the solute segregation does not directly depend on the dose rate but only on the density of sinks. Furthermore, this model provides new insight into the design of microstructures that mitigate chemical redistribution and improve radiation tolerance.« less

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos

2013-09-05

The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomassmore » transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.« less

Refined BCF-type boundary conditions for mesoscale surface step dynamics

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

Zhao, Renjie; Ackerman, David M.; Evans, James W.

Deposition on a vicinal surface with alternating rough and smooth steps is described by a solid-on-solid model with anisotropic interactions. Kinetic Monte Carlo (KMC) simulations of the model reveal step pairing in the absence of any additional step attachment barriers. We explore the description of this behavior within an analytic Burton-Cabrera-Frank (BCF)-type step dynamics treatment. Without attachment barriers, conventional kinetic coefficients for the rough and smooth steps are identical, as are the predicted step velocities for a vicinal surface with equal terrace widths. However, we determine refined kinetic coefficients from a two-dimensional discrete deposition-diffusion equation formalism which accounts for stepmore » structure. These coefficients are generally higher for rough steps than for smooth steps, reflecting a higher propensity for capture of diffusing terrace adatoms due to a higher kink density. Such refined coefficients also depend on the local environment of the step and can even become negative (corresponding to net detachment despite an excess adatom density) for a smooth step in close proximity to a rough step. Incorporation of these refined kinetic coefficients into a BCF-type step dynamics treatment recovers quantitatively the mesoscale step-pairing behavior observed in the KMC simulations.« less

Role of Sink Density in Nonequilibrium Chemical Redistribution in Alloys

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

Martinez, Enrique Saez; Senninger, Oriane; Caro, Alfredo

Nonequilibrium chemical redistribution in open systems submitted to external forces, such as particle irradiation, leads to changes in the structural properties of the material, potentially driving the system to failure. Such redistribution is controlled by the complex interplay between the production of point defects, atomic transport rates, and the sink character of the microstructure. In this work, we analyze this interplay by means of a kinetic Monte Carlo (KMC) framework with an underlying atomistic model for the Fe-Cr model alloy to study the effect of ideal defect sinks on Cr concentration profiles, with a particular focus on the role ofmore » interface density. We observe that the amount of segregation decreases linearly with decreasing interface spacing. Within the framework of the thermodynamics of irreversible processes, a general analytical model is derived and assessed against the KMC simulations to elucidate the structure-property relationship of this system. Interestingly, in the kinetic regime where elimination of point defects at sinks is dominant over bulk recombination, the solute segregation does not directly depend on the dose rate but only on the density of sinks. Furthermore, this model provides new insight into the design of microstructures that mitigate chemical redistribution and improve radiation tolerance.« less

Refined BCF-type boundary conditions for mesoscale surface step dynamics

DOE PAGES

Zhao, Renjie; Ackerman, David M.; Evans, James W.

2015-06-24

Deposition on a vicinal surface with alternating rough and smooth steps is described by a solid-on-solid model with anisotropic interactions. Kinetic Monte Carlo (KMC) simulations of the model reveal step pairing in the absence of any additional step attachment barriers. We explore the description of this behavior within an analytic Burton-Cabrera-Frank (BCF)-type step dynamics treatment. Without attachment barriers, conventional kinetic coefficients for the rough and smooth steps are identical, as are the predicted step velocities for a vicinal surface with equal terrace widths. However, we determine refined kinetic coefficients from a two-dimensional discrete deposition-diffusion equation formalism which accounts for stepmore » structure. These coefficients are generally higher for rough steps than for smooth steps, reflecting a higher propensity for capture of diffusing terrace adatoms due to a higher kink density. Such refined coefficients also depend on the local environment of the step and can even become negative (corresponding to net detachment despite an excess adatom density) for a smooth step in close proximity to a rough step. Incorporation of these refined kinetic coefficients into a BCF-type step dynamics treatment recovers quantitatively the mesoscale step-pairing behavior observed in the KMC simulations.« less

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.

Mesoscale Thermodynamically motivated Statistical Mechanics based Kinetic Model for Sintering monoliths

NASA Astrophysics Data System (ADS)

Mohan, Nisha

Modeling the evolution of microstructure during sintering is a persistent challenge in ceramics science, although needed as the microstructure impacts properties of an engineered material. Bridging the gap between microscopic and continuum models, kinetic Monte Carlo (kMC) methods provide a stochastic approach towards sintering and microstructure evolution. These kMC models work at the mesoscale, with length and time-scales between those of atomistic and continuum approaches. We develop a sintering/compacting model for the two-phase sintering of boron nitride ceramics and allotropes alike. Our formulation includes mechanisms for phase transformation between h-BN and c-BN and takes into account thermodynamics of pressure and temperature on interaction energies and mechanism rates. In addition to replicating the micro-structure evolution observed in experiments, it also captures the phase diagram of Boron Nitride materials. Results have been analyzed in terms of phase diagrams and crystal growth. It also serves with insights to guide the choice of additives and conditions for the sintering process.While detailed time and spatial resolutions are lost in any MC, the progression of stochastic events still captures plausible local energy minima and long-time temporal developments. DARPA.

Role of Sink Density in Nonequilibrium Chemical Redistribution in Alloys

NASA Astrophysics Data System (ADS)

Martínez, Enrique; Senninger, Oriane; Caro, Alfredo; Soisson, Frédéric; Nastar, Maylise; Uberuaga, Blas P.

2018-03-01

Nonequilibrium chemical redistribution in open systems submitted to external forces, such as particle irradiation, leads to changes in the structural properties of the material, potentially driving the system to failure. Such redistribution is controlled by the complex interplay between the production of point defects, atomic transport rates, and the sink character of the microstructure. In this work, we analyze this interplay by means of a kinetic Monte Carlo (KMC) framework with an underlying atomistic model for the Fe-Cr model alloy to study the effect of ideal defect sinks on Cr concentration profiles, with a particular focus on the role of interface density. We observe that the amount of segregation decreases linearly with decreasing interface spacing. Within the framework of the thermodynamics of irreversible processes, a general analytical model is derived and assessed against the KMC simulations to elucidate the structure-property relationship of this system. Interestingly, in the kinetic regime where elimination of point defects at sinks is dominant over bulk recombination, the solute segregation does not directly depend on the dose rate but only on the density of sinks. This model provides new insight into the design of microstructures that mitigate chemical redistribution and improve radiation tolerance.

Shape transitions in strained Cu islands on Ni(100): kinetics versus energetics

NASA Astrophysics Data System (ADS)

Shim, Yunsic; Amar, Jacques

2012-02-01

We examine the shape transition from compact to ramified islands observed in submonolayer Cu/Ni(100) growth. Recently, it has been argued that this transition is not due to a growth instability but can be understood in terms of energetic arguments. In order to determine the responsible mechanisms we have carried out energetics calculations as well as temperature-accelerated dynamics (TAD) and kinetic Monte Carlo (KMC) simulations. Our results indicate that the shape transition cannot be explained by equilibrium arguments, but is instead due to kinetic effects which are mediated by strain. In particular, by calculating the relevant line-tension and strain energies, we find that the equilibrium critical island-width is at least four orders of magnitude larger than the experimentally observed arm-width. In contrast, our TAD simulations indicate that unexpected concerted motions occurring at step edges are responsible. The energy barriers for these concerted motions decrease with increasing island size and appear to saturate for islands larger than 300 - 400 atoms. By including these strain-induced kinetic processes in our KMC simulations of island-growth, we have been able to explain both the temperature- and coverage-dependence of the island morphology.

Dendritic growth shapes in kinetic Monte Carlo models

NASA Astrophysics Data System (ADS)

Krumwiede, Tim R.; Schulze, Tim P.

2017-02-01

For the most part, the study of dendritic crystal growth has focused on continuum models featuring surface energies that yield six pointed dendrites. In such models, the growth shape is a function of the surface energy anisotropy, and recent work has shown that considering a broader class of anisotropies yields a correspondingly richer set of growth morphologies. Motivated by this work, we generalize nanoscale models of dendritic growth based on kinetic Monte Carlo simulation. In particular, we examine the effects of extending the truncation radius for atomic interactions in a bond-counting model. This is done by calculating the model’s corresponding surface energy and equilibrium shape, as well as by running KMC simulations to obtain nanodendritic growth shapes. Additionally, we compare the effects of extending the interaction radius in bond-counting models to that of extending the number of terms retained in the cubic harmonic expansion of surface energy anisotropy in the context of continuum models.

Charge Transport Properties in Disordered Organic Semiconductor as a Function of Charge Density: Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Shukri, Seyfan Kelil

2017-01-01

We have done Kinetic Monte Carlo (KMC) simulations to investigate the effect of charge carrier density on the electrical conductivity and carrier mobility in disordered organic semiconductors using a lattice model. The density of state (DOS) of the system are considered to be Gaussian and exponential. Our simulations reveal that the mobility of the charge carrier increases with charge carrier density for both DOSs. In contrast, the mobility of charge carriers decreases as the disorder increases. In addition the shape of the DOS has a significance effect on the charge transport properties as a function of density which are clearly seen. On the other hand, for the same distribution width and at low carrier density, the change occurred on the conductivity and mobility for a Gaussian DOS is more pronounced than that for the exponential DOS.

Perception and practice of Kangaroo Mother Care after discharge from hospital in Kumasi, Ghana: A longitudinal study

PubMed Central

2011-01-01

Background The practice of Kangaroo Mother Care (KMC) is life saving in babies weighing less than 2000 g. Little is known about mothers' continued unsupervised practice after discharge from hospitals. This study aimed to evaluate its in-hospital and continued practice in the community among mothers of low birth weight (LBW) infants discharged from two hospitals in Kumasi, Ghana. Methods A longitudinal study of 202 mothers and their inpatient LBW neonates was conducted from November 2009 to May 2010. Mothers were interviewed at recruitment to ascertain their knowledge of KMC, and then oriented on its practice. After discharge, the mothers reported at weekly intervals for four follow up visits where data about their perceptions, attitudes and practices of KMC were recorded. A repeated measure logistic regression analysis was done to assess variability in the binary responses at the various reviews visits. Results At recruitment 23 (11.4%, 95%CI: 7.4 to 16.6%) mothers knew about KMC. At discharge 95.5% were willing to continue KMC at home with 93.1% willing to practice at night. 95.5% thought KMC was beneficial to them and 96.0% beneficial to their babies. 98.0% would recommend KMC to other mothers with 71.8% willing to practice KMC outdoors. At first follow up visit 99.5% (181) were still practicing either intermittent or continuous KMC. This proportion did not change significantly over the four weeks (OR: 1.4, 95%CI: 0.6 to 3.3, p-value: 0.333). Over the four weeks, increasingly more mothers practiced KMC at night (OR: 1.7, 95%CI: 1.2 to 2.6, p = 0.005), outside their homes (OR: 2.4, 95%CI: 1.7 to 3.3, p < 0.001) and received spousal help (OR: 1.6, 95%CI: 1.1 to 2.4, p = 0.007). Household chores and potentially negative community perceptions of KMC did not affect its practice with odds of 0.8 (95%CI: 0.5 to 1.2, p = 0.282) and 1.0 (95%CI: 0.6 to 1.7, p = 0.934) respectively. During the follow-up period the neonates gained 23.7 sg (95%CI: 22.6 g to 24.7 g) per day. Conclusion Maternal knowledge of KMC was low at outset. Once initiated mothers continued practicing KMC in hospital and at home with their infants gaining optimal weight. Continued KMC practice was not affected by perceived community attitudes. PMID:22133462

Perception and practice of Kangaroo Mother Care after discharge from hospital in Kumasi, Ghana: a longitudinal study.

PubMed

Nguah, Samuel B; Wobil, Priscilla N L; Obeng, Regina; Yakubu, Ayi; Kerber, Kate J; Lawn, Joy E; Plange-Rhule, Gyikua

2011-12-01

The practice of Kangaroo Mother Care (KMC) is life saving in babies weighing less than 2000 g. Little is known about mothers' continued unsupervised practice after discharge from hospitals. This study aimed to evaluate its in-hospital and continued practice in the community among mothers of low birth weight (LBW) infants discharged from two hospitals in Kumasi, Ghana. A longitudinal study of 202 mothers and their inpatient LBW neonates was conducted from November 2009 to May 2010. Mothers were interviewed at recruitment to ascertain their knowledge of KMC, and then oriented on its practice. After discharge, the mothers reported at weekly intervals for four follow up visits where data about their perceptions, attitudes and practices of KMC were recorded. A repeated measure logistic regression analysis was done to assess variability in the binary responses at the various reviews visits. At recruitment 23 (11.4%, 95%CI: 7.4 to 16.6%) mothers knew about KMC. At discharge 95.5% were willing to continue KMC at home with 93.1% willing to practice at night. 95.5% thought KMC was beneficial to them and 96.0% beneficial to their babies. 98.0% would recommend KMC to other mothers with 71.8% willing to practice KMC outdoors.At first follow up visit 99.5% (181) were still practicing either intermittent or continuous KMC. This proportion did not change significantly over the four weeks (OR: 1.4, 95%CI: 0.6 to 3.3, p-value: 0.333). Over the four weeks, increasingly more mothers practiced KMC at night (OR: 1.7, 95%CI: 1.2 to 2.6, p = 0.005), outside their homes (OR: 2.4, 95%CI: 1.7 to 3.3, p < 0.001) and received spousal help (OR: 1.6, 95%CI: 1.1 to 2.4, p = 0.007). Household chores and potentially negative community perceptions of KMC did not affect its practice with odds of 0.8 (95%CI: 0.5 to 1.2, p = 0.282) and 1.0 (95%CI: 0.6 to 1.7, p = 0.934) respectively. During the follow-up period the neonates gained 23.7 sg (95%CI: 22.6 g to 24.7 g) per day. Maternal knowledge of KMC was low at outset. Once initiated mothers continued practicing KMC in hospital and at home with their infants gaining optimal weight. Continued KMC practice was not affected by perceived community attitudes.

Long-term stability of Cu surface nanotips

NASA Astrophysics Data System (ADS)

Jansson, V.; Baibuz, E.; Djurabekova, F.

2016-07-01

Sharp nanoscale tips on the metal surfaces of electrodes enhance locally applied electric fields. Strongly enhanced electric fields trigger electron field emission and atom evaporation from the apexes of nanotips. Together, these processes may explain electric discharges in the form of small local arcs observed near metal surfaces in the presence of electric fields, even in ultra-high vacuum conditions. In the present work, we investigate the stability of nanoscale tips by means of computer simulations of surface diffusion processes on copper, the main material used in high-voltage electronics. We study the stability and lifetime of thin copper (Cu) surface nanotips at different temperatures in terms of diffusion processes. For this purpose we have developed a surface kinetic Monte Carlo (KMC) model where the jump processes are described by tabulated precalculated energy barriers. We show that tall surface features with high aspect ratios can be fairly stable at room temperature. However, the stability was found to depend strongly on the temperature: 13 nm nanotips with the major axes in the < 110> crystallographic directions were found to flatten down to half of the original height in less than 100 ns at temperatures close to the melting point, whereas no significant change in the height of these nanotips was observed after 10 {{μ }}{{s}} at room temperature. Moreover, the nanotips built up along the < 110> crystallographic directions were found to be significantly more stable than those oriented in the < 100> or < 111> crystallographic directions. The proposed KMC model has been found to be well-suited for simulating atomic surface processes and was validated against molecular dynamics simulation results via the comparison of the flattening times obtained by both methods. We also note that the KMC simulations were two orders of magnitude computationally faster than the corresponding molecular dynamics calculations.

Translating research findings into practice – the implementation of kangaroo mother care in Ghana

PubMed Central

2012-01-01

Background Kangaroo mother care (KMC) is a safe and effective method of caring for low birth weight infants and is promoted for its potential to improve newborn survival. Many countries find it difficult to take KMC to scale in healthcare facilities providing newborn care. KMC Ghana was an initiative to scale up KMC in four regions in Ghana. Research findings from two outreach trials in South Africa informed the design of the initiative. Two key points of departure were to equip healthcare facilities that conduct deliveries with the necessary skills for KMC practice and to single out KMC for special attention instead of embedding it in other newborn care initiatives. This paper describes the contextualisation and practical application of previous research findings and the results of monitoring the progress of the implementation of KMC in Ghana. Methods A three-phase outreach intervention was adapted from previous research findings to suit the local setting. A more structured system of KMC regional steering committees was introduced to drive the process and take the initiative forward. During Phase I, health workers in regions and districts were oriented in KMC and received basic support for the management of the outreach. Phase II entailed the strengthening of the regional steering committees. Phase III comprised a more formal assessment, utilising a previously validated KMC progress-monitoring instrument. Results Twenty-six out of 38 hospitals (68 %) scored over 10 out of 30 and had reached the level of ‘evidence of practice’ by the end of Phase III. Seven hospitals exceeded expected performance by scoring at the level of ‘evidence of routine and institutionalised practice.’ The collective mean score for all participating hospitals was 12.07. Hospitals that had attained baby-friendly status or had been re-accredited in the five years before the intervention scored significantly better than the rest, with a mean score of 14.64. Conclusion The KMC Ghana initiative demonstrated how research findings regarding successful outreach for the implementation of KMC could be transferred to a different context by making context-appropriate adaptations to the model. PMID:22889113

Translating research findings into practice--the implementation of kangaroo mother care in Ghana.

PubMed

Bergh, Anne-Marie; Manu, Rhoda; Davy, Karen; van Rooyen, Elise; Asare, Gloria Quansah; Williams, J Koku Awoonor; Dedzo, McDamien; Twumasi, Akwasi; Nang-Beifubah, Alexis

2012-08-13

Kangaroo mother care (KMC) is a safe and effective method of caring for low birth weight infants and is promoted for its potential to improve newborn survival. Many countries find it difficult to take KMC to scale in healthcare facilities providing newborn care. KMC Ghana was an initiative to scale up KMC in four regions in Ghana. Research findings from two outreach trials in South Africa informed the design of the initiative. Two key points of departure were to equip healthcare facilities that conduct deliveries with the necessary skills for KMC practice and to single out KMC for special attention instead of embedding it in other newborn care initiatives. This paper describes the contextualisation and practical application of previous research findings and the results of monitoring the progress of the implementation of KMC in Ghana. A three-phase outreach intervention was adapted from previous research findings to suit the local setting. A more structured system of KMC regional steering committees was introduced to drive the process and take the initiative forward. During Phase I, health workers in regions and districts were oriented in KMC and received basic support for the management of the outreach. Phase II entailed the strengthening of the regional steering committees. Phase III comprised a more formal assessment, utilising a previously validated KMC progress-monitoring instrument. Twenty-six out of 38 hospitals (68 %) scored over 10 out of 30 and had reached the level of 'evidence of practice' by the end of Phase III. Seven hospitals exceeded expected performance by scoring at the level of 'evidence of routine and institutionalised practice.' The collective mean score for all participating hospitals was 12.07. Hospitals that had attained baby-friendly status or had been re-accredited in the five years before the intervention scored significantly better than the rest, with a mean score of 14.64. The KMC Ghana initiative demonstrated how research findings regarding successful outreach for the implementation of KMC could be transferred to a different context by making context-appropriate adaptations to the model.

Kangaroo mother care for low birthweight infants: a randomized controlled trial in different settings.

PubMed

Cattaneo, A; Davanzo, R; Worku, B; Surjono, A; Echeverria, M; Bedri, A; Haksari, E; Osorno, L; Gudetta, B; Setyowireni, D; Quintero, S; Tamburlini, G

1998-09-01

A randomized controlled trial was carried out for 1 y in three tertiary and teaching hospitals, in Addis Ababa (Ethiopia), Yogyakarta (Indonesia) and Merida (Mexico), to study the effectiveness, feasibility, acceptability and cost of kangaroo mother care (KMC) when compared to conventional methods of care (CMC). About 29% of 649 low birthweight infants (LBWI; 1000-1999 g) died before eligibility. Of the survivors, 38% were excluded for various reasons, 149 were randomly assigned to KMC (almost exclusive skin-to-skin care after stabilization), and 136 to CMC (warm room or incubator care). There were three deaths in each group and no difference in the incidence of severe disease. Hypothermia was significantly less common in KMC infants in Merida (13.5 vs 31.5 episodes/100 infants/d) and overall (10.8 vs 14.6). Exclusive breastfeeding at discharge was more common in KMC infants in Merida (80% vs 16%) and overall (88% vs 70%). KMC infants had a higher mean daily weight gain (21.3 g vs 17.7 g) and were discharged earlier (13.4 vs 16.3 d after enrolment). KMC was considered feasible and presented advantages over CMC in terms of maintenance of equipment. Mothers expressed a clear preference for KMC and health workers found it safe and convenient. KMC was cheaper than CMC in terms of salaries (US$ 11,788 vs US$ 29,888) and other running costs (US$ 7501 vs US$ 9876). This study confirms that hospital KMC for stabilized LBWI 1000-1999 g is at least as effective and safe as CMC, and shows that it is feasible in different settings, acceptable to mothers of different cultures, and less expensive. Where exclusive breastfeeding is uncommon among LBWI, KMC may bring about an increase in its prevalence and duration, with consequent benefits for health and growth. For hospitals in low-income countries KMC may represent an appropriate use of scarce resources.

Mesoscopic kinetic Monte Carlo modeling of organic photovoltaic device characteristics

NASA Astrophysics Data System (ADS)

Kimber, Robin G. E.; Wright, Edward N.; O'Kane, Simon E. J.; Walker, Alison B.; Blakesley, James C.

2012-12-01

Measured mobility and current-voltage characteristics of single layer and photovoltaic (PV) devices composed of poly{9,9-dioctylfluorene-co-bis[N,N'-(4-butylphenyl)]bis(N,N'-phenyl-1,4-phenylene)diamine} (PFB) and poly(9,9-dioctylfluorene-co-benzothiadiazole) (F8BT) have been reproduced by a mesoscopic model employing the kinetic Monte Carlo (KMC) approach. Our aim is to show how to avoid the uncertainties common in electrical transport models arising from the need to fit a large number of parameters when little information is available, for example, a single current-voltage curve. Here, simulation parameters are derived from a series of measurements using a self-consistent “building-blocks” approach, starting from data on the simplest systems. We found that site energies show disorder and that correlations in the site energies and a distribution of deep traps must be included in order to reproduce measured charge mobility-field curves at low charge densities in bulk PFB and F8BT. The parameter set from the mobility-field curves reproduces the unipolar current in single layers of PFB and F8BT and allows us to deduce charge injection barriers. Finally, by combining these disorder descriptions and injection barriers with an optical model, the external quantum efficiency and current densities of blend and bilayer organic PV devices can be successfully reproduced across a voltage range encompassing reverse and forward bias, with the recombination rate the only parameter to be fitted, found to be 1×107 s-1. These findings demonstrate an approach that removes some of the arbitrariness present in transport models of organic devices, which validates the KMC as an accurate description of organic optoelectronic systems, and provides information on the microscopic origins of the device behavior.

Kangaroo Mother Care and Neonatal Outcomes: A Meta-analysis

PubMed Central

Dastjerdi, Roya; Spiegelman, Donna; Fawzi, Wafaie W.; Missmer, Stacey A.; Lieberman, Ellice; Kajeepeta, Sandhya; Wall, Stephen; Chan, Grace J.

2016-01-01

CONTEXT: Kangaroo mother care (KMC) is an intervention aimed at improving outcomes among preterm and low birth weight newborns. OBJECTIVE: Conduct a systematic review and meta-analysis estimating the association between KMC and neonatal outcomes. DATA SOURCES: PubMed, Embase, Web of Science, Scopus, African Index Medicus (AIM), Latin American and Caribbean Health Sciences Information System (LILACS), Index Medicus for the Eastern Mediterranean Region (IMEMR), Index Medicus for the South-East Asian Region (IMSEAR), and Western Pacific Region Index Medicus (WPRIM). STUDY SELECTION: We included randomized trials and observational studies through April 2014 examining the relationship between KMC and neonatal outcomes among infants of any birth weight or gestational age. Studies with <10 participants, lack of a comparison group without KMC, and those not reporting a quantitative association were excluded. DATA EXTRACTION: Two reviewers extracted data on study design, risk of bias, KMC intervention, neonatal outcomes, relative risk (RR) or mean difference measures. RESULTS: 1035 studies were screened; 124 met inclusion criteria. Among LBW newborns, KMC compared to conventional care was associated with 36% lower mortality(RR 0.64; 95% [CI] 0.46, 0.89). KMC decreased risk of neonatal sepsis (RR 0.53, 95% CI 0.34, 0.83), hypothermia (RR 0.22; 95% CI 0.12, 0.41), hypoglycemia (RR 0.12; 95% CI 0.05, 0.32), and hospital readmission (RR 0.42; 95% CI 0.23, 0.76) and increased exclusive breastfeeding (RR 1.50; 95% CI 1.26, 1.78). Newborns receiving KMC had lower mean respiratory rate and pain measures, and higher oxygen saturation, temperature, and head circumference growth. LIMITATIONS: Lack of data on KMC limited the ability to assess dose-response. CONCLUSIONS: Interventions to scale up KMC implementation are warranted. PMID:26702029

Provision of Kangaroo Mother Care: supportive factors and barriers perceived by parents.

PubMed

Blomqvist, Ylva Thernström; Frölund, Lovisa; Rubertsson, Christine; Nyqvist, Kerstin Hedberg

2013-06-01

Kangaroo Mother Care (KMC) supports parents' role at the neonatal intensive care unit (NICU). To enhance parents' provision of KMC, it is essential to obtain knowledge of what parents perceive as supportive factors and barriers regarding their opportunities to perform KMC. To identify factors that parents of preterm infants perceived as supportive factors or barriers for their performance of KMC and to explore the timing of and reasons for parents' discontinuation of KMC. A descriptive study performed at two NICUs in Sweden with 76 mothers and 74 fathers of preterm infants born at gestational ages ranging from 28 to 33 weeks. Data on infant characteristics were obtained from the infants' medical records. A questionnaire, based on scientific literature and the researchers' clinical experience, was completed by the mothers and the fathers separately, shortly after the infant's discharge from the hospital. The data were analyzed with qualitative content analysis and descriptive statistic. Four categories were identified in parents' responses regarding support and barriers for their performance of KMC: Parent related factors, Time, Infants related factors and The NICU and home environment. The hospital staff and environment were described by the parents as both supportive and barriers for their application of KMC. Some mothers described the infants' feeding process as an obstacle to KMC. Sleeping with the infant skin-to-skin in the same position throughout the night could be difficult, as an uncomfortable sleeping position caused insufficient sleep. A majority of both mothers and fathers continued providing their infant with KMC to some extent after discharge. Interventions for enhancing parents' opportunities for performing KMC should address both hospital staff attitudes and practices and the NICU environment. © 2012 Nordic College of Caring Science.

Kangaroo Mother Care and Neonatal Outcomes: A Meta-analysis.

PubMed

Boundy, Ellen O; Dastjerdi, Roya; Spiegelman, Donna; Fawzi, Wafaie W; Missmer, Stacey A; Lieberman, Ellice; Kajeepeta, Sandhya; Wall, Stephen; Chan, Grace J

2016-01-01

Kangaroo mother care (KMC) is an intervention aimed at improving outcomes among preterm and low birth weight newborns. Conduct a systematic review and meta-analysis estimating the association between KMC and neonatal outcomes. PubMed, Embase, Web of Science, Scopus, African Index Medicus (AIM), Latin American and Caribbean Health Sciences Information System (LILACS), Index Medicus for the Eastern Mediterranean Region (IMEMR), Index Medicus for the South-East Asian Region (IMSEAR), and Western Pacific Region Index Medicus (WPRIM). We included randomized trials and observational studies through April 2014 examining the relationship between KMC and neonatal outcomes among infants of any birth weight or gestational age. Studies with <10 participants, lack of a comparison group without KMC, and those not reporting a quantitative association were excluded. Two reviewers extracted data on study design, risk of bias, KMC intervention, neonatal outcomes, relative risk (RR) or mean difference measures. 1035 studies were screened; 124 met inclusion criteria. Among LBW newborns, KMC compared to conventional care was associated with 36% lower mortality(RR 0.64; 95% [CI] 0.46, 0.89). KMC decreased risk of neonatal sepsis (RR 0.53, 95% CI 0.34, 0.83), hypothermia (RR 0.22; 95% CI 0.12, 0.41), hypoglycemia (RR 0.12; 95% CI 0.05, 0.32), and hospital readmission (RR 0.42; 95% CI 0.23, 0.76) and increased exclusive breastfeeding (RR 1.50; 95% CI 1.26, 1.78). Newborns receiving KMC had lower mean respiratory rate and pain measures, and higher oxygen saturation, temperature, and head circumference growth. Lack of data on KMC limited the ability to assess dose-response. Interventions to scale up KMC implementation are warranted. Copyright © 2016 by the American Academy of Pediatrics.

Randomized Controlled Trial on Effect of Intermittent Early Versus Late Kangaroo Mother Care on Human Milk Feeding in Low-Birth-Weight Neonates.

PubMed

Jayaraman, Dhaarani; Mukhopadhyay, Kanya; Bhalla, Anil Kumar; Dhaliwal, Lakhbir Kaur

2017-08-01

Breastfeeding at discharge among sick low-birth-weight (LBW) infants is low despite counseling and intervention like kangaroo mother care (KMC). Research aim: The aim was to study the effects of early initiation of KMC on exclusive human milk feeding, growth, mortality, and morbidities in LBW neonates compared with late initiation of KMC during the hospital stay and postdischarge. A randomized controlled trial was conducted in level 2 and 3 areas of a tertiary care neonatal unit over 15 months. Inborn neonates weighing 1 to 1.8 kg and hemodynamically stable were randomized to receive either early KMC, initiated within the first 4 days of life, or late KMC (off respiratory support and intravenous fluids). Follow-up was until 1 month postdischarge. Outcomes were proportion of infants achieving exclusive human milk feeding and direct breastfeeding, growth, mortality and morbidities during hospital stay, and postdischarge feeding and KMC practices until 1 month. The early KMC group ( n = 80) achieved significantly higher exclusive human milk feeding (86% vs. 45%, p < .001) and direct breastfeeding (49% vs. 30%, p = .021) in hospital and almost exclusive human milk feeding (73% vs. 36%, p < .001) until 1 month postdischarge than the late KMC group ( n = 80). The incidence of apnea (11.9% vs. 20%, p = .027) and recurrent apnea requiring ventilation (8.8% vs. 15%, p = .02) were significantly reduced in the early KMC group. There was no significant difference in mortality, morbidities, and growth during the hospital stay and postdischarge. Early KMC significantly increased exclusive human milk feeding and direct breastfeeding in LBW infants.

Kangaroo mother care to reduce morbidity and mortality in low birthweight infants.

PubMed

Conde-Agudelo, Agustin; Díaz-Rossello, José L

2016-08-23

Kangaroo mother care (KMC), originally defined as skin-to-skin contact between a mother and her newborn, frequent and exclusive or nearly exclusive breastfeeding, and early discharge from hospital, has been proposed as an alternative to conventional neonatal care for low birthweight (LBW) infants. To determine whether evidence is available to support the use of KMC in LBW infants as an alternative to conventional neonatal care before or after the initial period of stabilization with conventional care, and to assess beneficial and adverse effects. We used the standard search strategy of the Cochrane Neonatal Review Group. This included searches in CENTRAL (Cochrane Central Register of Controlled Trials; 2016, Issue 6), MEDLINE, Embase, CINAHL (Cumulative Index to Nursing and Allied Health Literature), LILACS (Latin American and Caribbean Health Science Information database), and POPLINE (Population Information Online) databases (all from inception to June 30, 2016), as well as the WHO (World Health Organization) Trial Registration Data Set (up to June 30, 2016). In addition, we searched the web page of the Kangaroo Foundation, conference and symposia proceedings on KMC, and Google Scholar. Randomized controlled trials comparing KMC versus conventional neonatal care, or early-onset KMC versus late-onset KMC, in LBW infants. Data collection and analysis were performed according to the methods of the Cochrane Neonatal Review Group. Twenty-one studies, including 3042 infants, fulfilled inclusion criteria. Nineteen studies evaluated KMC in LBW infants after stabilization, one evaluated KMC in LBW infants before stabilization, and one compared early-onset KMC with late-onset KMC in relatively stable LBW infants. Sixteen studies evaluated intermittent KMC, and five evaluated continuous KMC. KMC versus conventional neonatal care: At discharge or 40 to 41 weeks' postmenstrual age, KMC was associated with a statistically significant reduction in the risk of mortality (risk ratio [RR] 0.60, 95% confidence interval [CI] 0.39 to 0.92; eight trials, 1736 infants), nosocomial infection/sepsis (RR 0.35, 95% CI 0.22 to 0.54; five trials, 1239 infants), and hypothermia (RR 0.28, 95% CI 0.16 to 0.49; nine trials, 989 infants; moderate-quality evidence). At latest follow-up, KMC was associated with a significantly decreased risk of mortality (RR 0.67, 95% CI 0.48 to 0.95; 12 trials, 2293 infants; moderate-quality evidence) and severe infection/sepsis (RR 0.50, 95% CI 0.36 to 0.69; eight trials, 1463 infants; moderate-quality evidence). Moreover, KMC was found to increase weight gain (mean difference [MD] 4.1 g/d, 95% CI 2.3 to 5.9; 11 trials, 1198 infants; moderate-quality evidence), length gain (MD 0.21 cm/week, 95% CI 0.03 to 0.38; three trials, 377 infants) and head circumference gain (MD 0.14 cm/week, 95% CI 0.06 to 0.22; four trials, 495 infants) at latest follow-up, exclusive breastfeeding at discharge or 40 to 41 weeks' postmenstrual age (RR 1.16, 95% CI 1.07 to 1.25; six studies, 1453 mothers) and at one to three months' follow-up (RR 1.20, 95% CI 1.01 to 1.43; five studies, 600 mothers), any (exclusive or partial) breastfeeding at discharge or at 40 to 41 weeks' postmenstrual age (RR 1.20, 95% CI 1.07 to 1.34; 10 studies, 1696 mothers; moderate-quality evidence) and at one to three months' follow-up (RR 1.17, 95% CI 1.05 to 1.31; nine studies, 1394 mothers; low-quality evidence), and some measures of mother-infant attachment and home environment. No statistically significant differences were found between KMC infants and controls in Griffith quotients for psychomotor development at 12 months' corrected age (low-quality evidence). Sensitivity analysis suggested that inclusion of studies with high risk of bias did not affect the general direction of findings nor the size of the treatment effect for main outcomes. Early-onset KMC versus late-onset KMC in relatively stable infants: One trial compared early-onset continuous KMC (within 24 hours post birth) versus late-onset continuous KMC (after 24 hours post birth) in 73 relatively stable LBW infants. Investigators reported no significant differences between the two study groups in mortality, morbidity, severe infection, hypothermia, breastfeeding, and nutritional indicators. Early-onset KMC was associated with a statistically significant reduction in length of hospital stay (MD 0.9 days, 95% CI 0.6 to 1.2). Evidence from this updated review supports the use of KMC in LBW infants as an alternative to conventional neonatal care, mainly in resource-limited settings. Further information is required concerning the effectiveness and safety of early-onset continuous KMC in unstabilized or relatively stabilized LBW infants, as well as long-term neurodevelopmental outcomes and costs of care.

Effect of Kangaroo mother care in reducing pain due to heel prick among preterm neonates: a crossover trial.

PubMed

Chidambaram, Ambika Gnanam; Manjula, S; Adhisivam, B; Bhat, B Vishnu

2014-03-01

Preterm neonates undergo several painful procedures in NICU including heel prick for blood sugar monitoring. Nonpharmacological interventions have been tried to decrease this procedural pain. There are only few studies on Kangaroo mother care (KMC) in reducing pain among preterm neonates. This crossover trial was conducted at a tertiary care teaching hospital in south India. Premature Infant Pain Profile (PIPP) related to heel prick was assessed in 50 preterm neonates undergoing KMC and compared with 50 preterm babies without KMC. PIPP scores at 15 minutes and 30 minutes after heel prick were significantly less in KMC group compared to control group. Mean PIPP difference between baseline and 30 minutes after heel prick was also significantly low in KMC group compared to control group. KMC is effective in reducing pain due to heel prick among preterm babies.

Kangaroo Mother Care (KMC) in LBW infants--a western Rajasthan experience.

PubMed

Gupta, Mukesh; Jora, Rakesh; Bhatia, Ravi

2007-08-01

This study was taken to study the various beneficial effects of KMC in LBW babies. 50 LBW babies (birth weight> 2 kg) two who delivered at Umaid Hospital, RIMCH Jodhpur included in this study and they have given KMC 4-6 hours/day in 3-4 settings. Maternal & Neonatal characteristics and complications prospectively recorded. Of 50 LBW babies enrolled, M:F ratio was 1.5:1 and mean birth weight was 1.487 +/- 0.175 kg. The mean age at which KMC started was 4+/-1.738 days. The mean weight gain was 29 +/- 3.52 g, mean age of discharge 23.6 +/- 3.52 days and mean duration of hospital stay was 15.5 +/- 11.3 days. KMC is effective and safe in stable preterm infants and as effective on traditional care with incubators. KMC because of its simplicity may have a place in home care of LBW babies.

Derivation of a Theory to Estimate the Kinetic Parameters for Systems with Multiple Substrates Competing for the Same Active Site on an Enzyme

DTIC Science & Technology

2006-12-01

where a = (k2+k3)/(k1A) = KmA/A; b = (k5+k6)/(k4B) = KmB/B; c = (k8+k9)/(k7C) = KmC /C; and d = (k11+k12)/(k10D) = KmD/D...in terms of the system parameters EA/E0 = (A/KmA) / (1 + A/KmA + B/KmB + C/ KmC + D/KmD) EB/E0 = (B/KmB) / (1 + A/KmA + B/KmB + C/ KmC + D/KmD...EC/E0 = (C/ KmC ) / (1 + A/KmA + B/KmB + C/ KmC + D/KmD) ED/E0 = (D/KmD) / (1 + A/KmA + B/KmB + C/ KmC + D/KmD) The fraction of free enzyme existing

Effect of kangaroo mother care on vital physiological parameters of the low birth weight newborn.

PubMed

Bera, Alpanamayi; Ghosh, Jagabandhu; Singh, Arun Kumarendu; Hazra, Avijit; Som, Tapas; Munian, Dinesh

2014-10-01

Low birth weight (LBW; <2500 g), which is often associated with preterm birth, is a common problem in India. Both are recognized risk factors for neonatal mortality. Kangaroo mother care (KMC) is a non-conventional, low-cost method for newborn care based upon intimate skin-to-skin contact between mother and baby. Our objective was to assess physiological state of LBW babies before and after KMC in a teaching hospital setting. Study cohort comprised in-born LBW babies and their mothers - 300 mother-baby pairs were selected through purposive sampling. Initially, KMC was started for 1 hour duration (at a stretch) on first day and then increased by 1 hour each day for next 2 days. Axillary temperature, respiration rate (RR/ min), heart rate (HR/ min), and oxygen saturation (SpO2) were assessed for 3 consecutive days, immediately before and after KMC. Data from 265 mother-baby pairs were analyzed. Improvements occurred in all 4 recorded physiological parameters during the KMC sessions. Mean temperature rose by about 0.4°C, RR by 3 per minute, HR by 5 bpm, and SpO2 by 5% following KMC sessions. Although modest, these changes were statistically significant on all 3 days. Individual abnormalities (e.g. hypothermia, bradycardia, tachycardia, low SpO2) were often corrected during the KMC sessions. Babies receiving KMC showed modest but statistically significant improvement in vital physiological parameters on all 3 days. Thus, without using special equipment, the KMC strategy can offer improved care to LBW babies. These findings support wider implementation of this strategy.

Kangaroo mother care: using formative research to design an acceptable community intervention.

PubMed

Mazumder, Sarmila; Upadhyay, Ravi Prakash; Hill, Zelee; Taneja, Sunita; Dube, Brinda; Kaur, Jasmine; Shekhar, Medha; Ghosh, Runa; Bisht, Shruti; Martines, Jose Carlos; Bahl, Rajiv; Sommerfelt, Halvor; Bhandari, Nita

2018-03-02

Low and middle income countries (LMICs), including India, contribute to a major proportion of low birth weight (LBW) infants globally. These infants require special care. Kangaroo Mother Care (KMC) in hospitals is a cost effective and efficacious intervention. In institutional deliveries, the duration of facility stay is often short. In LMICs, a substantial proportion of deliveries still occur at home and access to health care services is limited. In these circumstances, a pragmatic choice may be to initiate KMC at home for LBW babies. However, evidence is lacking on benefits of community-initiated KMC (cKMC). Promoting KMC at home without an understanding of its acceptability may lead to limited success. We conducted formative research to assess the feasibility, acceptability and adoption of cKMC with the aim of designing an intervention package for a randomised controlled trial in LBW infants in Haryana, India. Qualitative methods included 40 in-depth interviews with recently delivered women and 6 focus group discussions, two each with fathers and grandfathers, grandmothers, and community health workers. A prototype intervention package to promote cKMC was developed and tested in 28 mother-infant pairs (of them, one mother had twins), using Household (HH) trials. We found that most mothers in the community recognized that babies born small required special care. In spite of not being aware of the practice of KMC, respondents felt that creating awareness of KMC benefits will promote practice. They expressed concerns about doing KMC for long periods because mothers needed rest after delivery. However, the cultural practice of recently delivered women not expected to be doing household chores and availability of other family members were identified as enablers. HH trials provided an opportunity to test the intervention package and showed high acceptability for KMC. Most mothers perceived benefits such as weight gain and increased activity in the infant. Community-initiated KMC is acceptable by mothers and adoption rates are high. Formative research is essential for developing a strategy for delivery of an intervention. Trial registration number CTRI/2015/10/006267 . Name of Registry: Clinical Trials Registry - India. URL of Registry: http://ctri.nic.in/Clinicaltrials/login.php Date of Registration: 15/10/2015. Date of enrolment of the first participant to the trial: 18/04/2015.

Growth of nitrogen-doped graphene on copper: Multiscale simulations

NASA Astrophysics Data System (ADS)

Gaillard, P.; Schoenhalz, A. L.; Moskovkin, P.; Lucas, S.; Henrard, L.

2016-02-01

We used multiscale simulations to model the growth of nitrogen-doped graphene on a copper substrate by chemical vapour deposition (CVD). Our simulations are based on ab-initio calculations of energy barriers for surface diffusion, which are complemented by larger scale Kinetic Monte Carlo (KMC) simulations. Our results indicate that the shape of grown doped graphene flakes depends on the temperature and deposition flux they are submitted during the process, but we found no significant effect of nitrogen doping on this shape. However, we show that nitrogen atoms have a preference for pyridine-like sites compared to graphite-like sites, as observed experimentally.

Complete Genome Sequence of Moraxella osloensis Strain KMC41, a Producer of 4-Methyl-3-Hexenoic Acid, a Major Malodor Compound in Laundry

PubMed Central

Hirakawa, Hideki; Morita, Yuji; Tomida, Junko; Sato, Jun; Matsumura, Yuta; Mitani, Asako; Niwano, Yu; Takeuchi, Kohei; Kubota, Hiromi; Kawamura, Yoshiaki

2016-01-01

We report the complete genome sequence of Moraxella osloensis strain KMC41, isolated from laundry with malodor. The KMC41 genome comprises a 2,445,556-bp chromosome and three plasmids. A fatty acid desaturase and at least four β-oxidation-related genes putatively associated with 4-methyl-3-hexenoic acid generation were detected in the KMC41 chromosome. PMID:27445387

Feasibility of kangaroo mother care in Mumbai.

PubMed

Kadam, Sandeep; Binoy, S; Kanbur, Wasundhara; Mondkar, J A; Fernandez, Armida

2005-01-01

The purpose of this study was to determine the feasibility and acceptability of kangaroo care in a tertiary care hospital in India. A randomized controlled trial was performed over one year period in which 89 neonates were randomized into two groups kangaroo mother care (KMC) and conventional method of care (CMC). Forty-four babies were randomized into KMC group and 45 to CMC. There was significant reduction in KMC vs CMC group of hypothermia (10/44 vs 21/45, p-value < 0.01), higher oxygen saturations (95.7 vs 94.8%, p-value < 0.01) and decrease in respiratory rates (36.2 vs 40.7, p-value < 0.01). There were no statistically significant differences in the incidence of hyperthermia, sepsis, apnea, onset of breastfeeding and hospital stay in two groups. 79% of mothers felt comfortable during the KMC and 73% felt they would be able to give KMC at home. KMC is feasible, as mothers are already admitted in hospitals and are involved in the care of newborn. KMC is a simple and feasible intervention; acceptable to most mothers admitted in hospitals. There may be benefits in terms of reducing the incidence of hypothermia with no adverse effects of KMC demonstrated in the study. The present study has important implications in the care of LBW infants in the developing countries, where expensive facilities for conventional care may not be available at all place.

Trial of repeated analgesia with Kangaroo Mother Care (TRAKC Trial).

PubMed

Campbell-Yeo, Marsha; Johnston, Celeste; Benoit, Britney; Latimer, Margot; Vincer, Michael; Walker, Claire-Dominique; Streiner, David; Inglis, Darlene; Caddell, Kim

2013-11-09

Skin-to-skin contact (SSC) between mother and infant, commonly referred to as Kangaroo Mother Care (KMC), is recommended as an intervention for procedural pain. Evidence demonstrates its consistent efficacy in reducing pain for a single painful procedure. The purpose of this study is to examine the sustained efficacy of KMC, provided during all routine painful procedures for the duration of Neonatal Intensive Care Unit (NICU) hospitalization, in diminishing behavioral pain response in preterm neonates. The efficacy of KMC alone will be compared to standard care of 24% oral sucrose, as well as the combination of KMC and 24% oral sucrose. Infants admitted to the NICU who are less than 36 6/7 weeks gestational age (according to early ultrasound), that are stable enough to be held in KMC, will be considered eligible (N = 258). Using a single-blinded randomized parallel group design, participants will be assigned to one of three possible interventions: 1) KMC, 2) combined KMC and sucrose, and 3) sucrose alone, when they undergo any routine painful procedure (heel lance, venipuncture, intravenous, oro/nasogastric insertion). The primary outcome is infant's pain intensity, which will be assessed using the Premature Infant Pain Profile (PIPP). The secondary outcome will be maturity of neurobehavioral functioning, as measured by the Neurobehavioral Assessment of the Preterm Infant (NAPI). Gestational age, cumulative exposure to KMC provided during non-pain contexts, and maternal cortisol levels will be considered in the analysis. Clinical feasibility will be accounted for from nurse and maternal questionnaires. This will be the first study to examine the repeated use of KMC for managing procedural pain in preterm neonates. It is also the first to compare KMC to sucrose, or the interventions in combination, across time. Based on the theoretical framework of the brain opioid theory of attachment, it is expected that KMC will be a preferred standard of care. However, current pain management guidelines are based on minimal data on repeated use of either intervention. Therefore, regardless of the outcomes of this study, results will have important implications for guidelines and practices related to management of procedural pain in preterm infants. ClinicalTrials.gov Identifier: NCT01561547.

KMC facilitates mother baby attachment in low birth weight infants.

PubMed

Gathwala, Geeta; Singh, Bir; Balhara, Bharti

2008-01-01

To determine whether Kangaroo mother care (KMC) facilitates mother baby attachment in low birth weight infants. Over 16 month period 110 neonates were randomized into kangaroo mother care group and control group using a random number table. The kangaroo group was subjected to Kangaroo mother care for at least 6 hours per day. The babies also received kangaroo care after shifting out from NICU and at home. The control group received standard care (incubator or open care system). After 3 months followup, structured maternal interview was conducted to assess attachment between mothers and their babies. Mean birth weight was 1.69 +/- 0.11 Kg in KMC group compared to 1.690 +/- 0.12 Kg in control group (p>0.05). Mean gestational age was 35.48 +/- 1.20 week in KMC group and 35.04+/-1.09 week in the control group (p>0.05). KMC was initiated at a mean age of 1.72+/-0.45 days. The duration of KMC in first month was 10.21+/-1.50 hour, in the 2nd month was 10.03+/-1.57 hour and in the 3rd month was 8.97+/-1.37 hours. The duration of hospital stay was significantly shorter in the KMC group (3.56+/-0.57 days) compared to control group (6.80+/-1.30 days). The total attachment score (24.46+/-1.64) in the KMC group was significantly higher than that obtained in control group (18.22+/-1.79, p< 0.001). In KMC group, mother was more often the main caretaker of the baby. Mothers were significantly more involved in care taking activities like bathing, diapering, sleeping with their babies and spent more time beyond usual care taking. They went out without their babies less often and only for unavoidable reasons. They derived greater pleasure from their babies. KMC facilitates mother baby attachment in low birth weight infants.

Influence of maternal factors on the successful outcome of kangaroo mother care in low birth-weight infants: A randomized controlled trial.

PubMed

Lumbanraja, S N

2016-01-01

Kangaroo mother care (KMC) is associated with positive neonatal outcomes. Studies demonstrated significant influence of maternal factors on the success of applying KMC. To determine maternal factors that influence on anthropometric parameters in low birth weight babies that received kangaroo mother care. This is a randomized controlled study that involved low birth weight newborns. We randomly assigned newborns into two groups; a group who received KMC and a group who received conventional care. Maternal factors were recorded. We followed weight, length, and head circumferences of newborns for thirty days. A total of 40 newborns were included. Weight parameters were significantly higher in the KMC group than the conventional group. From maternal characteristics, only gestational age was found to influence increased head circumference in KMC group (p = 0.035); however, it did not affect the increase in weight or length. Maternal age, parity, education, mode of delivery, fetal sex, and initial Apgar score did not influence growth parameters in either groups. KMC was associated with increased weight gain in LBW infants. Gestational age influences head growth in infants who received KMC.

Complete Genome Sequence of Moraxella osloensis Strain KMC41, a Producer of 4-Methyl-3-Hexenoic Acid, a Major Malodor Compound in Laundry.

PubMed

Goto, Takatsugu; Hirakawa, Hideki; Morita, Yuji; Tomida, Junko; Sato, Jun; Matsumura, Yuta; Mitani, Asako; Niwano, Yu; Takeuchi, Kohei; Kubota, Hiromi; Kawamura, Yoshiaki

2016-07-21

We report the complete genome sequence of Moraxella osloensis strain KMC41, isolated from laundry with malodor. The KMC41 genome comprises a 2,445,556-bp chromosome and three plasmids. A fatty acid desaturase and at least four β-oxidation-related genes putatively associated with 4-methyl-3-hexenoic acid generation were detected in the KMC41 chromosome. Copyright © 2016 Goto et al.

Barriers and enablers of kangaroo mother care implementation from a health systems perspective: a systematic review

PubMed Central

Chan, Grace; Bergelson, Ilana; Smith, Emily R; Skotnes, Tobi; Wall, Stephen

2017-01-01

Abstract Kangaroo Mother Care (KMC) is an evidence-based intervention that reduces neonatal morbidity and mortality. However, adoption among health systems has varied. Understanding the interaction between health system functions—leadership, financing, healthcare workers (HCWs), technologies, information and research, and service delivery—and KMC is essential to understanding KMC adoption. We present a systematic review of the barriers and enablers of KMC implementation from the perspective of health systems, with a focus on HCWs and health facilities. Using the search terms ‘kangaroo mother care’, ‘skin to skin (STS) care’ and ‘kangaroo care’, we searched Embase, Scopus, Web of Science, Pubmed, and World Health Organization Regional Databases. Reports and hand searched references from publications were also included. Screening and data abstraction were conducted by two independent reviewers using standardized forms. A conceptual model to assess KMC adoption themes was developed using NVivo software. Our search strategy yielded 2875 studies. We included 86 studies with qualitative data on KMC implementation from the perspective of HCWs and/or facilities. Six themes emerged on barriers and enablers to KMC adoption: buy-in and bonding; social support; time; medical concerns; training; and cultural norms. Analysis of interactions between HCWs and facilities yielded further barriers and enablers in the areas of training, communication, and support. HCWs and health facilities serve as two important adopters of Kangaroo Mother Care within a health system. The complex components of KMC lead to multifaceted barriers and enablers to integration, which inform facility, regional, and country-level recommendations for increasing adoption. Further research of methods to promote context-specific adoption of KMC at the health systems level is needed. PMID:28973515

Kangaroo-mother care method and neurobehavior of preterm infants.

PubMed

Silva, Margareth Gurgel de Castro; Barros, Marina Carvalho de Moraes; Pessoa, Úrsula Maria Lima; Guinsburg, Ruth

2016-04-01

To evaluate the effect of kangaroo-mother care (KMC) in preterm (PT) neurobehavior between 36 and 41 weeks post-conceptual age (PCA). A prospective cohort of 61 preterm infants with gestational age (GA) of 28-32 w evaluated by the Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS), with 36-41 w PCA. Infants with clinical instability were excluded. They were analyzed in 2 groups: - Kangaroo (KAN): KMC for 7 or more days; Conventional (CON): did not receive KMC. Scores of the 13 NNNS variables were compared between groups and the effect of KMC in the scores of the variables of NNNS were evaluated by multiple linear regression, controlling for confounders. The KAN groups (n=24) and CON (n=37) were similar regarding main demographic and clinical maternal and neonatal characteristics. Mean GA was 30.3 w; and birth weight was 1170 g for both groups. PT of KAN group were admitted in KMC with PCA of 35.8 w (38.5 days of life) and remained with this care for 14.3 days. The NNNS was applied 13 days after the start of KMC. PT submitted to KMC showed higher quality of movements (KAN: 4.98 ± 0.53 vs CON: 4.53 ± 0.47; p=0.001) and lower scores on Signs of stress and abstinence (KAN: 0.03 ± 0.03 vs CON: 0.05 ± 0.03; p=0.001). Controlling for confounders, the KMC was associated with higher scores on the variables Attention, Quality of movements, and lower scores on Asymmetry and Signs of stress and abstinence. PT submitted to the KMC, compared to those non-submitted, have better neurobehavior performance between 36 and 41 weeks of post-conceptual age. Copyright © 2016. Published by Elsevier Ireland Ltd.

Increasing Confidence and Ability in Implementing Kangaroo Mother Care Method Among Young Mothers.

PubMed

Kenanga Purbasary, Eleni; Rustina, Yeni; Budiarti, Tri

Mothers giving birth to low birth weight babies (LBWBs) have low confidence in caring for their babies because they are often still young and may lack the knowledge, experience, and ability to care for the baby. This research aims to determine the effect of education about kangaroo mother care (KMC) on the confidence and ability of young mothers to implement KMC. The research methodology used was a controlled-random experimental approach with pre- and post-test equivalent groups of 13 mothers and their LBWBs in the intervention group and 13 mothers and their LBWBs in the control group. Data were collected via an instrument measuring young mothers' confidence, the validity and reliability of which have been tested with a resulting r value of .941, and an observation sheet on KMC implementation. After conducting the education, the confidence score of young mothers and their ability to perform KMC increased meaningfully. The score of confidence of young mothers before education was 37 (p = .1555: and the ability score for KMC Implementation before education was 9 (p = .1555). The median score of confidence of young mothers after education in the intervention group was 87 and in the control group was 50 (p = .001, 95% CI 60.36-75.56), and ability median score for KMC implementation after education in the intervention group was 16 and in the control group was 12 (p = .001, 95% CI 1.50-1.88). KMC education should be conducted gradually, and it is necessary to involve the family, in order for KMC implementation to continue at home. A family visit can be done for LBWBs to evaluate the ability of the young mothers to implement KMC.

Barriers and enablers of kangaroo mother care implementation from a health systems perspective: a systematic review.

PubMed

Chan, Grace; Bergelson, Ilana; Smith, Emily R; Skotnes, Tobi; Wall, Stephen

2017-12-01

Kangaroo Mother Care (KMC) is an evidence-based intervention that reduces neonatal morbidity and mortality. However, adoption among health systems has varied. Understanding the interaction between health system functions-leadership, financing, healthcare workers (HCWs), technologies, information and research, and service delivery-and KMC is essential to understanding KMC adoption. We present a systematic review of the barriers and enablers of KMC implementation from the perspective of health systems, with a focus on HCWs and health facilities. Using the search terms 'kangaroo mother care', 'skin to skin (STS) care' and 'kangaroo care', we searched Embase, Scopus, Web of Science, Pubmed, and World Health Organization Regional Databases. Reports and hand searched references from publications were also included. Screening and data abstraction were conducted by two independent reviewers using standardized forms. A conceptual model to assess KMC adoption themes was developed using NVivo software. Our search strategy yielded 2875 studies. We included 86 studies with qualitative data on KMC implementation from the perspective of HCWs and/or facilities. Six themes emerged on barriers and enablers to KMC adoption: buy-in and bonding; social support; time; medical concerns; training; and cultural norms. Analysis of interactions between HCWs and facilities yielded further barriers and enablers in the areas of training, communication, and support. HCWs and health facilities serve as two important adopters of Kangaroo Mother Care within a health system. The complex components of KMC lead to multifaceted barriers and enablers to integration, which inform facility, regional, and country-level recommendations for increasing adoption. Further research of methods to promote context-specific adoption of KMC at the health systems level is needed. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Effect of Kangaroo Mother Care on Vital Physiological Parameters of The Low Birth Weight Newborn

PubMed Central

Bera, Alpanamayi; Ghosh, Jagabandhu; Singh, Arun Kumarendu; Hazra, Avijit; Som, Tapas; Munian, Dinesh

2014-01-01

Objectives: Low birth weight (LBW; <2500 g), which is often associated with preterm birth, is a common problem in India. Both are recognized risk factors for neonatal mortality. Kangaroo mother care (KMC) is a non-conventional, low-cost method for newborn care based upon intimate skin-to-skin contact between mother and baby. Our objective was to assess physiological state of LBW babies before and after KMC in a teaching hospital setting. Materials and Methods: Study cohort comprised in-born LBW babies and their mothers - 300 mother-baby pairs were selected through purposive sampling. Initially, KMC was started for 1 hour duration (at a stretch) on first day and then increased by 1 hour each day for next 2 days. Axillary temperature, respiration rate (RR/ min), heart rate (HR/ min), and oxygen saturation (SpO2) were assessed for 3 consecutive days, immediately before and after KMC. Results: Data from 265 mother-baby pairs were analyzed. Improvements occurred in all 4 recorded physiological parameters during the KMC sessions. Mean temperature rose by about 0.4°C, RR by 3 per minute, HR by 5 bpm, and SpO2 by 5% following KMC sessions. Although modest, these changes were statistically significant on all 3 days. Individual abnormalities (e.g. hypothermia, bradycardia, tachycardia, low SpO2) were often corrected during the KMC sessions. Conclusions: Babies receiving KMC showed modest but statistically significant improvement in vital physiological parameters on all 3 days. Thus, without using special equipment, the KMC strategy can offer improved care to LBW babies. These findings support wider implementation of this strategy. PMID:25364150

A comparison of kangaroo mother care and conventional incubator care for thermal regulation of infants < 2000 g in Nigeria using continuous ambulatory temperature monitoring.

PubMed

Ibe, O E; Austin, T; Sullivan, K; Fabanwo, O; Disu, E; Costello, A M de L

2004-09-01

Although skin-to-skin contact (or kangaroo mother care, KMC) for preterm infants is a practical alternative to incubator care, no studies have compared these methods using continuous ambulatory temperature monitoring. To compare thermal regulation in low birthweight infants (< 2000 g) managed by KMC alternating with conventional care (CC) and to determine the acceptability to mothers of KMC, an experimental study with a crossover design with observational and qualitative data collected on temperature patterns and mothers attitudes to skin-to-skin care was conducted in the neonatal wards of three hospitals in Lagos, Nigeria. Thirteen eligible infants were nursed by their mothers or surrogates in 38 4-hour sessions of KMC and the results compared with 38 sessions of incubator care. The risk of hypothermia was reduced by > 90% when nursed by KMC rather than conventional care, relative risk (RR) 0.09 (0.03-0.25). More cases of hyperthermia (> 37.5 degrees C) occurred with KMC, and coreperiphery temperature differences were widened, but the risk of hyperthermia > 37.9 degrees C (RR 1.3, 0.9-1.7) was not significant. Micro-ambient temperatures were higher during KMC, although the average room temperatures during both procedures did not differ significantly. Mothers felt that KMC was safe, and preferred the method to CC because it did not separate them from their infants, although some had problems adjusting to this method of care. Where equipment for thermal regulation is lacking or unreliable, KMC is a preferable method for managing stable low birthweight infants. Copyright 2004 Liverpool School of Tropical Medicine

Direct Detection of Stereospecific Soman Hydrolysis by Wild-Type Human Serum Paraoxonase

DTIC Science & Technology

2007-01-01

was used as Tc = (Ao/VmaA)(1 - (C/Co)( Kmc /KwA)(VmaxA/Vmac)) the carrier gas at a linear velocity of 45 crns-1. The oven + (B0/VmaxB)(1 - (C/Co)( Kmc ...KmB)(VmaxB/Vm.c)) temperature was held initially at 80 ’C for 14 min, pro- + (Co/Vmac)(1 - (C/Co)( Kmc / Kmc )(Vm.c/Vmac)) grammed from 80 to 90 ’C at 5...oC’min-1, and held at + (DO/VmaD)(1 - (C/Co)(K.C/KmD)(Vm.D1/V.aC)) 90 ’C for 3 min. Split injections of 1 tiL volume were made ( Kmc /VmaxC) Log(C/Co

Impact of community-initiated Kangaroo Mother Care on survival of low birth weight infants: study protocol for a randomized controlled trial.

PubMed

Mazumder, Sarmila; Taneja, Sunita; Dalpath, Suresh Kumar; Gupta, Rakesh; Dube, Brinda; Sinha, Bireshwar; Bhatia, Kiran; Yoshida, Sachiyo; Norheim, Ole Frithjof; Bahl, Rajiv; Sommerfelt, Halvor; Bhandari, Nita; Martines, Jose

2017-06-07

Around 70% neonatal deaths occur in low birth weight (LBW) babies. Globally, 15% of babies are born with LBW. Kangaroo Mother Care (KMC) appears to be an effective way to reduce mortality and morbidity among LBW babies. KMC comprises of early and continuous skin-to-skin contact between mother and baby as well as exclusive breastfeeding. Evidence derived from hospital-based studies shows that KMC results in a 40% relative reduction in mortality, a 58% relative reduction in the risk of nosocomial infections or sepsis, shorter hospital stay, and a lower risk of lower respiratory tract infections in babies with birth weight <2000 g. There has been considerable interest in KMC initiated outside health facilities for LBW babies born at home or discharged early. Currently, there is insufficient evidence to support initiation of KMC in the community (cKMC). Formative research in our study setting, where 24% of babies are born with LBW, demonstrated that KMC is feasible and acceptable when initiated at home for LBW babies. The aim of this trial is to determine the impact of cKMC on the survival of these babies. This randomized controlled trial is being undertaken in the Palwal and Faridabad districts in the State of Haryana, India. Neonates weighing 1500-2250 g identified within 3 days of birth and their mothers are being enrolled. Other inclusion criteria are that the family is likely to be available in the study area over the next 6 months, that KMC was not initiated in the delivery facility, and that the infant does not have an illness requiring hospitalization. Eligible neonates are randomized into intervention and control groups. The intervention is delivered through home visits during the first month of life by study workers with a background and education similar to that of workers in the government health system. An independent study team collects mortality and morbidity data as well as anthropometric measurements during periodic home visits. The primary outcomes of the study are postenrollment neonatal mortality and mortality between enrollment and 6 months of age. The secondary outcomes are breastfeeding practices; prevalence of illnesses and care-seeking practices for the same; hospitalizations; weight and length gain; and, in a subsample, neurodevelopment. This efficacy trial will answer the question whether the benefits of KMC observed in hospital settings can also be observed when KMC is started in the community. The formative research used for intervention development suggests that the necessary high level of KMC adoption can be reached in the community, addressing a problem that seriously constrained conclusions in the only other trial in which researchers examined the benefits of cKMC. ClinicalTrials.gov identifier: NCT02653534 . Registered on 26 December 2015 (retrospectively registered).

Long-term effects of earlier initiated continuous Kangaroo Mother Care (KMC) for low-birth-weight (LBW) infants in Madagascar.

PubMed

Nagai, Shuko; Yonemoto, Naohiro; Rabesandratana, Norotiana; Andrianarimanana, Diavolana; Nakayama, Takeo; Mori, Rintaro

2011-12-01

To examine the long-term effects of earlier initiated continuous Kangaroo Mother Care (KMC) for relatively stable low-birth-weight (LBW) infants in a resource-limited country. A randomized controlled trial with long-term follow-up was performed in LBW infants in Madagascar. Earlier continuous KMC (intervention group) was initiated as soon as possible within 24 h postbirth, and later continuous KMC (control group: conventional care) was initiated after complete stabilization. Outcome measures were mortality or readmission, nutritional indicators at 6-12 months postbirth and feeding condition at 6 months postbirth (ClinicalTrials.gov, NCT00531492). A total of 72 infants were followed for mortality or readmission at 6-12 months postbirth. There was no difference between the two groups (7/36 vs. 7/36, Risk ratio (RR), 1.00; 95% CIs, 0.39-2.56; p = 1.00). The proportion of exclusive breast feeding (EBF) at 6 months postbirth was significantly higher with earlier KMC than later KMC (12/29 vs. 4/26; RR 2.69; 95% CIs, 1.00-7.31; p = 0.04). There were no differences in nutritional indicators between the two groups at 6-12 months postbirth. Earlier initiated continuous KMC results in a significantly higher proportion of EBF at 6 months postbirth. Further larger-scale long-term evaluations of earlier initiated continuous KMC for LBW infants are needed. © 2011 The Author(s)/Acta Paediatrica © 2011 Foundation Acta Paediatrica.

The Effect of Kangaroo Mother Care (KMC) on Breast Feeding at the Time of NICU Discharge.

PubMed

Heidarzadeh, Mohammad; Hosseini, Mohammad Bagher; Ershadmanesh, Mashallah; Gholamitabar Tabari, Maryam; Khazaee, Soheila

2013-04-01

Exclusive breastfeeding is one of the most important essential components of Kangaroo Mother Care. This study was performed to evaluate the effects of KMC on exclusive breastfeeding just at the time of discharge. In this cross sectional study, 251 consecutive premature newborns admitted to neonatal intensive care unit (NICU) between May 2008 and May 2009 in Alzahra University Hospital in Tabriz were evaluated. All of candidate mothers were educated for KMC method by scheduled program. Standard questionnaire was prepared by focus group discussion, and mothers filled it prior to infant hospital discharge. In this study 157(62.5%) mothers performed kangaroo mother care (KMC group) versus 94 (37.5%) in conventional method care (CMC group). In KMC group exclusive breast feeding was 98 (62.5%) vs. 34 (37.5%), and P =.00 in CMC group, at the time of hospital discharge. Receiving KMC, and gestational age were the only effective factors predicting exclusive breastfeeding. Our result indicated that there was a 4.1 time increase in exclusive breastfeeding by KMC, and also weekly increase in gestational age increased it 1.2 times, but maternal age, birth weight, mode of delivery, and 5 minute Apgar score had no influence on it. KMC is more effective, and increases exclusive breast feeding successfully. It can be a good substitution for CMC (conventional methods of care). It is a safe, effective, and feasible method of care for LBWI even in the NICU settings.

Carrier mobility in mesoscale heterogeneous organic materials: Effects of crystallinity and anisotropy on efficient charge transport

NASA Astrophysics Data System (ADS)

Kobayashi, Hajime; Shirasawa, Raku; Nakamoto, Mitsunori; Hattori, Shinnosuke; Tomiya, Shigetaka

2017-07-01

Charge transport in the mesoscale bulk heterojunctions (BHJs) of organic photovoltaic devices (OPVs) is studied using multiscale simulations in combination with molecular dynamics, the density functional theory, the molecular-level kinetic Monte Carlo (kMC) method, and the coarse-grained kMC method, which was developed to estimate mesoscale carrier mobility. The effects of the degree of crystallinity and the anisotropy of the conductivity of donors on hole mobility are studied for BHJ structures that consist of crystalline and amorphous pentacene grains that act as donors and amorphous C60 grains that act as acceptors. We find that the hole mobility varies dramatically with the degree of crystallinity of pentacene because it is largely restricted by a low-mobility amorphous region that occurs in the hole transport network. It was also found that the percolation threshold of crystalline pentacene is relatively high at approximately 0.6. This high percolation threshold is attributed to the 2D-like conductivity of crystalline pentacene, and the threshold is greatly improved to a value of approximately 0.3 using 3D-like conductive donors. We propose essential guidelines to show that it is critical to increase the degree of crystallinity and develop 3D conductive donors for efficient hole transport through percolative networks in the BHJs of OPVs.

Optimizing Binding Energies of Key Intermediates for CO 2 Hydrogenation to Methanol over Oxide-Supported Copper

DOE PAGES

None, None

2016-08-29

Rational optimization of catalytic performance has been one of the major challenges in catalysis. We report a bottom-up study on the ability of TiO 2 and ZrO 2 to optimize the CO 2 conversion to methanol on Cu, using combined density functional theory (DFT) calculations, kinetic Monte Carlo (KMC) simulations, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) measurements, and steady-state flow reactor tests. Furthermore, the theoretical results from DFT and KMC agree with in situ DRIFTS measurements, showing that both TiO 2 and ZrO 2 help to promote methanol synthesis on Cu via carboxyl intermediates and the reversemore » water–gas-shift (RWGS) pathway; the formate intermediates, on the other hand, likely act as a spectator eventually. The origin of the superior promoting effect of ZrO 2 is associated with the fine-tuning capability of reduced Zr 3+ at the interface, being able to bind the key reaction intermediates, e.g. *CO 2, *CO, *HCO, and *H 2CO, moderately to facilitate methanol formation. Our study demonstrates the importance of synergy between theory and experiments to elucidate the complex reaction mechanisms of CO 2 hydrogenation for the realization of a better catalyst by design.« less

Competing growth processes induced by next-nearest-neighbor interactions: Effects on meandering wavelength and stiffness

NASA Astrophysics Data System (ADS)

Blel, Sonia; Hamouda, Ajmi BH.; Mahjoub, B.; Einstein, T. L.

2017-02-01

In this paper we explore the meandering instability of vicinal steps with a kinetic Monte Carlo simulations (kMC) model including the attractive next-nearest-neighbor (NNN) interactions. kMC simulations show that increase of the NNN interaction strength leads to considerable reduction of the meandering wavelength and to weaker dependence of the wavelength on the deposition rate F. The dependences of the meandering wavelength on the temperature and the deposition rate obtained with simulations are in good quantitative agreement with the experimental result on the meandering instability of Cu(0 2 24) [T. Maroutian et al., Phys. Rev. B 64, 165401 (2001), 10.1103/PhysRevB.64.165401]. The effective step stiffness is found to depend not only on the strength of NNN interactions and the Ehrlich-Schwoebel barrier, but also on F. We argue that attractive NNN interactions intensify the incorporation of adatoms at step edges and enhance step roughening. Competition between NNN and nearest-neighbor interactions results in an alternative form of meandering instability which we call "roughening-limited" growth, rather than attachment-detachment-limited growth that governs the Bales-Zangwill instability. The computed effective wavelength and the effective stiffness behave as λeff˜F-q and β˜eff˜F-p , respectively, with q ≈p /2 .

Prediction of charge mobility in organic semiconductors with consideration of the grain-size effect

NASA Astrophysics Data System (ADS)

Park, Jin Woo; Lee, Kyu Il; Choi, Youn-Suk; Kim, Jung-Hwa; Jeong, Daun; Kwon, Young-Nam; Park, Jong-Bong; Ahn, Ho Young; Park, Jeong-Il; Lee, Hyo Sug; Shin, Jaikwang

2016-09-01

A new computational model to predict the hole mobility of poly-crystalline organic semiconductors in thin film was developed (refer to Phys. Chem. Chem. Phys., 2016, DOI: 10.1039/C6CP02993K). Site energy differences and transfer integrals in crystalline morphologies of organic molecules were obtained from quantum chemical calculation, in which the periodic boundary condition was efficiently applied to capture the interactions with the surrounding molecules in the crystalline organic layer. Then the parameters were employed in kinetic Monte Carlo (kMC) simulations to estimate the carrier mobility. Carrier transport in multiple directions has been considered in the kMC simulation to mimic polycrystalline characteristic in thin-film condition. Furthermore, the calculated mobility was corrected with a calibration equation based on the microscopic images of thin films to take the effect of grain boundary into account. As a result, good agreement was observed between the predicted and measured hole mobility values for 21 molecular species: the coefficient of determination (R2) was estimated to be 0.83 and the mean absolute error was 1.32 cm2 V-1 s-1. This numerical approach can be applied to any molecules for which crystal structures are available and will provide a rapid and precise way of predicting the device performance.

Solution processed deposition of electron transport layers on perovskite crystal surface-A modeling based study

NASA Astrophysics Data System (ADS)

Mortuza, S. M.; Taufique, M. F. N.; Banerjee, Soumik

2017-02-01

The power conversion efficiency (PCE) of planar perovskite solar cells (PSCs) has reached up to ∼20%. However, structural and chemicals defects that lead to hysteresis in the perovskite based thin film pose challenges. Recent work has shown that thin films of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) deposited on the photo absorption layer, using solution processing techniques, minimize surface pin holes and defects thereby increasing the PCE. We developed and employed a multiscale model based on molecular dynamics (MD) and kinetic Monte Carlo (kMC) to establish a relationship between deposition rate and surface coverage on perovskite surface. The MD simulations of PCBMs dispersed in chlorobenzene, sandwiched between (110) perovskite substrates, indicate that PCBMs are deposited through anchoring of the oxygen atom of carbonyl group to the exposed lead (Pb) atom of (110) perovskite surface. Based on rates of distinct deposition events calculated from MD, kMC simulations were run to determine surface coverage at much larger time and length scales than accessible by MD alone. Based on the model, a generic relationship is established between deposition rate of PCBMs and surface coverage on perovskite crystal. The study also provides detailed insights into the morphology of the deposited film.

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, KMC CONTROLS, INC. SLE-1001 SIGHT GLASS MONITOR

EPA Science Inventory

The Environmental Technology Verification report discusses the technology and performance of the KMC SLE-1001 Sight Glass Monitor manufactured by KMC Controls, Inc. The sight glass monitor (SGM) fits over the sight glass that may be installed in a refrigeration system for the pur...

Kangaroo mother care for clinically unstable neonates weighing ≤2000 g: Is it feasible at a hospital in Uganda?

PubMed

Morgan, Melissa C; Nambuya, Harriet; Waiswa, Peter; Tann, Cally; Elbourne, Diana; Seeley, Janet; Allen, Elizabeth; Lawn, Joy E

2018-06-01

Kangaroo mother care (KMC) for stable neonates ≤2000 g (g) is associated with decreased mortality, sepsis, hypothermia, and length of stay compared to conventional care. The World Health Organization states that KMC "should be initiated… as soon as newborns are clinically stable " [12]. However, the majority of deaths occur in unstable neonates. We aimed to determine the proportion of admitted neonates meeting proposed instability criteria, assess the feasibility of providing KMC to unstable neonates, and evaluate the acceptability of this intervention to parents and providers at Jinja Regional Referral Hospital in Uganda. This was a mixed-methods study. We recorded data including birthweight, chronological age, and treatments administered from medical charts, and calculated the percentage of clinically unstable neonates, defined as the need for ≥2 medical therapies in the first 48 hours of admission. We enrolled a sample of neonates meeting pre-defined instability criteria. Mothers were counselled to provide KMC as close to continuously as possible. We calculated the median duration of KMC per episode and per day. To explore acceptability, we conducted semi-structured interviews with parents and newborn unit care providers, and analysed data using the thematic content approach. We included 254 neonates in the audit, 10 neonates in the feasibility sub-study, and 20 participants in the acceptability sub-study. Instability criteria were easily implementable, identifying 89% of neonates as unstable in the audit. The median duration of individual KMC episodes ranged from 115 to 134 minutes. The median daily duration ranged from 4.5 to 9.7 hours. Seventy-five percent of interviewees felt KMC could be used in neonates concurrently receiving other medical therapies. Barriers included lack of resources (beds/space, monitoring devices), privacy issues, inadequate education, and difficulties motivating mothers to devote time to KMC. Recommendations included staff/peer counselling, resources, family support, and community outreach. There remains a need for an evidence-based approach to consistently define stability criteria for KMC to improve care. We found that KMC for unstable neonates weighing ≤2000g was feasible and acceptable at Jinja Hospital in Uganda. Randomised controlled trials are needed to demonstrate the effect of KMC on survival among unstable neonates in low-resource settings.

Kangaroo mother care for clinically unstable neonates weighing ≤2000 g: Is it feasible at a hospital in Uganda?

PubMed Central

Morgan, Melissa C; Nambuya, Harriet; Waiswa, Peter; Tann, Cally; Elbourne, Diana; Seeley, Janet; Allen, Elizabeth; Lawn, Joy E

2018-01-01

Background Kangaroo mother care (KMC) for stable neonates ≤2000 g (g) is associated with decreased mortality, sepsis, hypothermia, and length of stay compared to conventional care. The World Health Organization states that KMC “should be initiated… as soon as newborns are clinically stable” [12]. However, the majority of deaths occur in unstable neonates. We aimed to determine the proportion of admitted neonates meeting proposed instability criteria, assess the feasibility of providing KMC to unstable neonates, and evaluate the acceptability of this intervention to parents and providers at Jinja Regional Referral Hospital in Uganda. Methods This was a mixed-methods study. We recorded data including birthweight, chronological age, and treatments administered from medical charts, and calculated the percentage of clinically unstable neonates, defined as the need for ≥2 medical therapies in the first 48 hours of admission. We enrolled a sample of neonates meeting pre-defined instability criteria. Mothers were counselled to provide KMC as close to continuously as possible. We calculated the median duration of KMC per episode and per day. To explore acceptability, we conducted semi-structured interviews with parents and newborn unit care providers, and analysed data using the thematic content approach. Findings We included 254 neonates in the audit, 10 neonates in the feasibility sub-study, and 20 participants in the acceptability sub-study. Instability criteria were easily implementable, identifying 89% of neonates as unstable in the audit. The median duration of individual KMC episodes ranged from 115 to 134 minutes. The median daily duration ranged from 4.5 to 9.7 hours. Seventy-five percent of interviewees felt KMC could be used in neonates concurrently receiving other medical therapies. Barriers included lack of resources (beds/space, monitoring devices), privacy issues, inadequate education, and difficulties motivating mothers to devote time to KMC. Recommendations included staff/peer counselling, resources, family support, and community outreach. Conclusions There remains a need for an evidence-based approach to consistently define stability criteria for KMC to improve care. We found that KMC for unstable neonates weighing ≤2000g was feasible and acceptable at Jinja Hospital in Uganda. Randomised controlled trials are needed to demonstrate the effect of KMC on survival among unstable neonates in low-resource settings. PMID:29497509

Trial of Repeated Analgesia with Kangaroo Mother Care (TRAKC Trial)

PubMed Central

2013-01-01

Background Skin-to-skin contact (SSC) between mother and infant, commonly referred to as Kangaroo Mother Care (KMC), is recommended as an intervention for procedural pain. Evidence demonstrates its consistent efficacy in reducing pain for a single painful procedure. The purpose of this study is to examine the sustained efficacy of KMC, provided during all routine painful procedures for the duration of Neonatal Intensive Care Unit (NICU) hospitalization, in diminishing behavioral pain response in preterm neonates. The efficacy of KMC alone will be compared to standard care of 24% oral sucrose, as well as the combination of KMC and 24% oral sucrose. Methods/design Infants admitted to the NICU who are less than 36 6/7 weeks gestational age (according to early ultrasound), that are stable enough to be held in KMC, will be considered eligible (N = 258). Using a single-blinded randomized parallel group design, participants will be assigned to one of three possible interventions: 1) KMC, 2) combined KMC and sucrose, and 3) sucrose alone, when they undergo any routine painful procedure (heel lance, venipuncture, intravenous, oro/nasogastric insertion). The primary outcome is infant’s pain intensity, which will be assessed using the Premature Infant Pain Profile (PIPP). The secondary outcome will be maturity of neurobehavioral functioning, as measured by the Neurobehavioral Assessment of the Preterm Infant (NAPI). Gestational age, cumulative exposure to KMC provided during non-pain contexts, and maternal cortisol levels will be considered in the analysis. Clinical feasibility will be accounted for from nurse and maternal questionnaires. Discussion This will be the first study to examine the repeated use of KMC for managing procedural pain in preterm neonates. It is also the first to compare KMC to sucrose, or the interventions in combination, across time. Based on the theoretical framework of the brain opioid theory of attachment, it is expected that KMC will be a preferred standard of care. However, current pain management guidelines are based on minimal data on repeated use of either intervention. Therefore, regardless of the outcomes of this study, results will have important implications for guidelines and practices related to management of procedural pain in preterm infants. Trial registration ClinicalTrials.gov Identifier: NCT01561547. PMID:24284002

Report on an international workshop on kangaroo mother care: lessons learned and a vision for the future.

PubMed

Cattaneo, Adriano; Amani, Adidja; Charpak, Nathalie; De Leon-Mendoza, Socorro; Moxon, Sarah; Nimbalkar, Somashekhar; Tamburlini, Giorgio; Villegas, Julieta; Bergh, Anne-Marie

2018-05-16

Globally, complications of prematurity are the leading cause of death in children under five. Preterm infants who survive their first month of life are at greater risk for various diseases and impairments in infancy, childhood and later life, representing a heavy social and economic burden for families, communities and health and social systems. Kangaroo mother care (KMC) is recommended as a beneficial and effective intervention for improving short- and long-term preterm birth outcomes in low- and high-income settings. Nevertheless, KMC is not as widely used as it should be. The International Network on KMC runs biennial workshops and congresses to help improve the coverage and quality of KMC worldwide. This paper reports the results of the two-day workshop held in November 2016, where 92 participants from 33 countries shared experiences in a series of round tables, group work sessions and plenaries. Barriers to and enablers of KMC are discussed with regard to parents, health workers and the health system. Key factors for effective implementation and uptake relate to appropriate training for health staff, adherence to protocols and the creation of a welcoming environment for families. Recommendations for planning for national programmes are made according to a six-stage change model. Resources and the cost of making progress are discussed in terms of investment, maintenance, and acceleration and scaling-up costs. KMC training requirements are presented according to three levels of care. To ensure quality KMC, key requisites are proposed for the different KMC components and for sensitive communication with caregivers. The group attending to the monitoring and evaluation of KMC at a national and subnational level highlight the lack of standard indicator definitions. Key priorities for investment include health services research, harmonisation of indicators, development of a costing tool, programming and scaling up, and the follow-up of preterm infants. It is hoped that this report will help to further scale-up and sustain KMC through a systematic approach that includes raising commitment, identifying key strategies to address the main barriers and using existing facilitators, ensuring training and quality, agreeing on indicators for monitoring and evaluation, and advancing implementation research.

Oxygen Reduction Reaction on Ag(111) in Alkaline Solution: A Combined Density Functional Theory and Kinetic Monte Carlo Study

DOE PAGES

Liu, Shizhong; White, Michael G.; Liu, Ping

2018-01-25

We reported a detailed mechanistic study of the oxygen reduction reaction (ORR) on the model Ag(111) surface in alkaline solution by using density functional theory (DFT) and Kinetic Monte Carlo (KMC) simulations, in which multiple pathways involving either 2 e - or 4 e - mechanisms were included. The theoretical modelling presented here is able to reproduce the experimentally measured polarization curves in both low and high potential regions. An electrochemical 4 e - network including both a chemisorbed water (*H 2O)-mediated 4 e - associative pathway and the conventional associative pathway was identified to dominate the ORR mechanism. Onmore » the basis of the mechanistic understanding derived from these calculations, the ways to promote the ORR on Ag(111) were provided, including facilitating *OH removal, **O 2 reduction by *H 2O, and suppressing **O 2 desorption. Finally, the origin of the different ORR behaviors of Ag(111) and Pt(111) was also discussed in detail.« less

Surface vacancies concentration of CeO2(1 1 1) using kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Mattiello, S.; Kolling, S.; Heiliger, C.

2016-01-01

Kinetic Monte Carlo simulations (kMC) are useful tools for the investigation of the dynamics of surface properties. Within this method we investigate the oxygen vacancy concentration of \\text{Ce}{{\\text{O}}2}(1 1 1) at ultra high vacuum conditions (UHV). In order to achieve first principles calculations the input for the simulations, i.e. energy barriers for the microscopic processes, we use density functional theory (DFT) results from literature. We investigate the possibility of ad- and desorption of oxygen on ceria as well as the diffusion of oxygen vacancies to and from the subsurface. In particular, we focus on the vacancy surface concentration as well as on the ratio of the number of subsurface vacancies to the number of vacancies at the surface. The comparison of our dynamically obtained results to the experimental findings leads to several issues. In conclusion, we can claim a substantial incompatibility of the experimental results and the dynamical calculation using DFT inputs.

Reliability investigation of high-k/metal gate in nMOSFETs by three-dimensional kinetic Monte-Carlo simulation with multiple trap interactions

NASA Astrophysics Data System (ADS)

Li, Yun; Jiang, Hai; Lun, Zhiyuan; Wang, Yijiao; Huang, Peng; Hao, Hao; Du, Gang; Zhang, Xing; Liu, Xiaoyan

2016-04-01

Degradation behaviors in the high-k/metal gate stacks of nMOSFETs are investigated by three-dimensional (3D) kinetic Monte-Carlo (KMC) simulation with multiple trap coupling. Novel microscopic mechanisms are simultaneously considered in a compound system: (1) trapping/detrapping from/to substrate/gate; (2) trapping/detrapping to other traps; (3) trap generation and recombination. Interacting traps can contribute to random telegraph noise (RTN), bias temperature instability (BTI), and trap-assisted tunneling (TAT). Simulation results show that trap interaction induces higher probability and greater complexity in trapping/detrapping processes and greatly affects the characteristics of RTN and BTI. Different types of trap distribution cause largely different behaviors of RTN, BTI, and TAT. TAT currents caused by multiple trap coupling are sensitive to the gate voltage. Moreover, trap generation and recombination have great effects on the degradation of HfO2-based nMOSFETs under a large stress.

Oxygen Reduction Reaction on Ag(111) in Alkaline Solution: A Combined Density Functional Theory and Kinetic Monte Carlo Study

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

Liu, Shizhong; White, Michael G.; Liu, Ping

We reported a detailed mechanistic study of the oxygen reduction reaction (ORR) on the model Ag(111) surface in alkaline solution by using density functional theory (DFT) and Kinetic Monte Carlo (KMC) simulations, in which multiple pathways involving either 2 e - or 4 e - mechanisms were included. The theoretical modelling presented here is able to reproduce the experimentally measured polarization curves in both low and high potential regions. An electrochemical 4 e - network including both a chemisorbed water (*H 2O)-mediated 4 e - associative pathway and the conventional associative pathway was identified to dominate the ORR mechanism. Onmore » the basis of the mechanistic understanding derived from these calculations, the ways to promote the ORR on Ag(111) were provided, including facilitating *OH removal, **O 2 reduction by *H 2O, and suppressing **O 2 desorption. Finally, the origin of the different ORR behaviors of Ag(111) and Pt(111) was also discussed in detail.« less

Experience with Kangaroo mother care in a neonatal intensive care unit (NICU) in Chandigarh, India.

PubMed

Parmar, Veena Rani; Kumar, Ajay; Kaur, Rupinder; Parmar, Siddharth; Kaur, D; Basu, Srikant; Jain, Suksham; Narula, Sunny

2009-01-01

To study the feasibility and acceptability of Kangaroo mother care (KMC) on the low birth weight infants (LBWI) in the neonatal intensive care unit (NICU) by the mothers, family members and health care workers (HCW) and to observe its effect on the vital parameters of the babies. A observation in the NICU. A total of 135 babies (74 boys and 61 girls) who completed minimum of 4 hrs of KMC/day, were included. The mean birth weight and gestation were 1460 gm and 30 week respectively. 47% babies started KMC within first week of age. Mean duration of KMC was 7 days (3-48) days. The O(2) saturation improved by 2-3%, temperature ( degrees C) rose from 36.75 +/- 0.19 to 37.23 +/- 0.25, respiration stabilized (p<0.05 for all) and heart rate dropped by 3-5 beats. No episodes of hypothermia or apnea were observed during KMC. KMC was accepted by 96 % mothers, 82% fathers and 84% other family members. 94% HCW considered it to be safe and conservative method of care of LBWI. Benefits of KMC on the babies' behavior and on maternal confidence and lactation were reported by 57%, 94% and 80% respectively. A decline in use of heating devices in the NICU was reported by 85% and 79% said it did not increase their work load. KMC was found to be safe, effective and feasible method of care of LBWI even in the NICU settings. Positive attitudes were observed in mothers, families and HCW.

The Effect of Kangaroo Mother Care (KMC) on Breast Feeding at the Time of NICU Discharge

PubMed Central

Heidarzadeh, Mohammad; Hosseini, Mohammad Bagher; Ershadmanesh, Mashallah; Gholamitabar Tabari, Maryam; Khazaee, Soheila

2013-01-01

Background Exclusive breastfeeding is one of the most important essential components of Kangaroo Mother Care. Objective This study was performed to evaluate the effects of KMC on exclusive breastfeeding just at the time of discharge. Patients and Methods In this cross sectional study, 251 consecutive premature newborns admitted to neonatal intensive care unit (NICU) between May 2008 and May 2009 in Alzahra University Hospital in Tabriz were evaluated. All of candidate mothers were educated for KMC method by scheduled program. Standard questionnaire was prepared by focus group discussion, and mothers filled it prior to infant hospital discharge. Results In this study 157(62.5%) mothers performed kangaroo mother care (KMC group) versus 94 (37.5%) in conventional method care (CMC group). In KMC group exclusive breast feeding was 98 (62.5%) vs. 34 (37.5%), and P =.00 in CMC group, at the time of hospital discharge. Receiving KMC, and gestational age were the only effective factors predicting exclusive breastfeeding. Our result indicated that there was a 4.1 time increase in exclusive breastfeeding by KMC, and also weekly increase in gestational age increased it 1.2 times, but maternal age, birth weight, mode of delivery, and 5 minute Apgar score had no influence on it. Conclusions KMC is more effective, and increases exclusive breast feeding successfully. It can be a good substitution for CMC (conventional methods of care). It is a safe, effective, and feasible method of care for LBWI even in the NICU settings. PMID:24083002

Towards universal Kangaroo Mother Care: recommendations and report from the First European conference and Seventh International Workshop on Kangaroo Mother Care.

PubMed

Nyqvist, K H; Anderson, G C; Bergman, N; Cattaneo, A; Charpak, N; Davanzo, R; Ewald, U; Ibe, O; Ludington-Hoe, S; Mendoza, S; Pallás-Allonso, C; Ruiz Peláez, J G; Sizun, J; Widström, A-M

2010-06-01

The hallmark of Kangaroo Mother Care (KMC) is the kangaroo position: the infant is cared for skin-to-skin vertically between the mother's breasts and below her clothes, 24 h/day, with father/substitute(s) participating as KMC providers. Intermittent KMC (for short periods once or a few times per day, for a variable number of days) is commonly employed in high-tech neonatal intensive care units. These two modalities should be regarded as a progressive adaptation of the mother-infant dyad, ideally towards continuous KMC, starting gradually and progressively with intermittent KMC. The other components in KMC are exclusive breastfeeding (ideally) and early discharge in kangaroo position with strict follow-up. Current evidence allows the following general statements about KMC in affluent and low-income settings: KMC enhances bonding and attachment; reduces maternal postpartum depression symptoms; enhances infant physiologic stability and reduces pain, increases parental sensitivity to infant cues; contributes to the establishment and longer duration of breastfeeding and has positive effects on infant development and infant/parent interaction. Therefore, intrapartum and postnatal care in all types of settings should adhere to a paradigm of nonseparation of infants and their mothers/families. Preterm/low-birth-weight infants should be regarded as extero-gestational foetuses needing skin-to-skin contact to promote maturation. Kangaroo Mother Care should begin as soon as possible after birth, be applied as continuous skin-to-skin contact to the extent that this is possible and appropriate and continue for as long as appropriate.

Identification of large-scale meteorological patterns associated with extreme precipitation in the US northeast

NASA Astrophysics Data System (ADS)

Agel, Laurie; Barlow, Mathew; Feldstein, Steven B.; Gutowski, William J.

2018-03-01

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.

Effect of kangaroo mother care on postpartum depression.

PubMed

de Alencar, Andréa Echeverria Martins Arraes; Arraes, Luis Cláudio; de Albuquerque, Emídio Cavalcanti; Alves, João Guilherme Bezerra

2009-02-01

Postpartum depression (PPD) is a serious public health issue. Kangaroo mother care (KMC) is widely considered to be the most feasible, readily available and preferred intervention for decreasing neonatal morbidity and mortality in developing countries. We conducted a prospective study to assess the effect of KMC on PPD. The study population included 177 low-income mothers with their preterm infants. We used the validated Portuguese version of the Postpartum Depression Screening Scale for the assessment of maternal depression. The mothers were evaluated twice, at Neonatal Intensive Care Unit admission and at KMC discharge. We found 66 mothers (37.3%) with depression and it decreased to 30 (16.9%) after KMC intervention; p < 0.0001. None developed PPD during the Kangaroo stay. We concluded that KMC may lessen maternal depression. Further studies, may be required to clarify these preliminary findings.

Kangaroo Mother Care: four years of experience in very low birth weight and preterm infants.

PubMed

Tuoni, C; Scaramuzzo, R T; Ghirri, P; Boldrini, A; Bartalena, L

2012-08-01

Kangaroo Mother Care (KMC) is a method of providing care for preterm infants through skin-to-skin contact with the mother and, preferably, exclusive breastfeeding. The growing interest in KMC at the Neonatology Unit of Pisa has provided the occasion for a retrospective analysis of the last four years, comparing the clinical effects of the kangaroo method vs. those obtained with conventional care (CNC) with respect to indicators of the general health of the infants (indices of growth, and duration of breastfeeding and hospitalization). A total of 213 infants, aged <37 gestational weeks and weighing ≤1500 g were enrolled for the study; these were divided into two groups for the purpose of comparison (91 in KMC vs. 71 in CNC). The indices of growth and the duration of the infants in hospital were not significantly different in the two groups. Nevertheless, it is worth noting how KMC is more efficacious in the very tiny VLBW infants, and that the means of the growth parameters in the KMC infants are greater than those referring to the CNC subjects, body temperatures taken at the beginning and end of a KMC session are higher, and that the mother-child relationship facilitates better sucking-feeding. While KMC is equivalent to CNC in terms of safety, thermal protection, morbidity and auxologic development, it appears to promote humanisation of infant care and mother-child bond more quickly.

The Effects of Kangaroo Mother Care and Swaddling on Venipuncture Pain in Premature Neonates: A Randomized Clinical Trial.

PubMed

Dezhdar, Shahin; Jahanpour, Faezeh; Firouz Bakht, Saeedeh; Ostovar, Afshin

2016-04-01

Hospitalized premature babies often undergo various painful procedures. Kangaroo mother care (KMC) and swaddling are two pain reduction methods. This study was undertaken to compare the effects of swaddling and KMC on pain during venous sampling in premature neonates. This study was performed as a randomized clinical trial on 90 premature neonates. The neonates were divided into three groups using a random allocation block. The three groups were group A (swaddling), group B (KMC), and group C (control). In all three groups, the heart rate and arterial oxygen saturation were measured and recorded in time intervals of 30 seconds before, during, and 30, 60, 90, and 120 seconds after blood sampling. The neonate's face was video recorded and assessed using the premature infant pain profile (PIPP) at time intervals of 30 seconds. The data was analyzed using the t-test, chi-square test, Repeated Measure analysis of variance (ANOVA), Kruskal-Wallis, Post-hoc, and Bonferroni test. The findings revealed that pain was reduced to a great extent in the swaddling and KMC methods compared to the control group. However, there was no significant difference between KMC and swaddling (P ≥ 0.05). The results of this study indicate that there is no meaningful difference between swaddling and KMC on physiological indexes and pain in neonates. Therefore, the swaddling method may be a good substitute for KMC.

Barriers and enablers of health system adoption of kangaroo mother care: a systematic review of caregiver perspectives.

PubMed

Smith, Emily R; Bergelson, Ilana; Constantian, Stacie; Valsangkar, Bina; Chan, Grace J

2017-01-25

Despite improvements in child survival in the past four decades, an estimated 6.3 million children under the age of five die each year, and more than 40% of these deaths occur in the neonatal period. Interventions to reduce neonatal mortality are needed. Kangaroo mother care (KMC) is one such life-saving intervention; however it has not yet been fully integrated into health systems around the world. Utilizing a conceptual framework for integration of targeted health interventions into health systems, we hypothesize that caregivers play a critical role in the adoption, diffusion, and assimilation of KMC. The objective of this research was to identify barriers and enablers of implementation and scale up of KMC from caregivers' perspective. We searched Pubmed, Embase, Web of Science, Scopus, and WHO regional databases using search terms 'kangaroo mother care' or 'kangaroo care' or 'skin to skin care'. Studies published between January 1, 1960 and August 19, 2015 were included. To be eligible, published work had to be based on primary data collection regarding barriers or enablers of KMC implementation from the family perspective. Abstracted data were linked to the conceptual framework using a deductive approach, and themes were identified within each of the five framework areas using Nvivo software. We identified a total of 2875 abstracts. After removing duplicates and ineligible studies, 98 were included in the analysis. The majority of publications were published within the past 5 years, had a sample size less than 50, and recruited participants from health facilities. Approximately one-third of the studies were conducted in the Americas, and 26.5% were conducted in Africa. We identified four themes surrounding the interaction between families and the KMC intervention: buy in and bonding (i.e. benefits of KMC to mothers and infants and perceptions of bonding between mother and infant), social support (i.e. assistance from other people to perform KMC), sufficient time to perform KMC, and medical concerns about mother or newborn health. Furthermore, we identified barriers and enablers of KMC adoption by caregivers within the context of the health system regarding financing and service delivery. Embedded within the broad social context, barriers to KMC adoption by caregivers included adherence to traditional newborn practices, stigma surrounding having a preterm infant, and gender roles regarding childcare. Efforts to scale up and integrate KMC into health systems must reduce barriers in order to promote the uptake of the intervention by caregivers.

Is a woolen cap effective in maintaining normothermia in low-birth-weight infants during kangaroo mother care? Study protocol for a randomized controlled trial.

PubMed

Trevisanuto, Daniele; Putoto, Giovanni; Pizzol, Damiano; Serena, Tiziana; Manenti, Fabio; Varano, Silvia; Urso, Eleonora; Massavon, William; Tsegaye, Ademe; Wingi, Oliver; Onapa, Emanuel; Segafredo, Giulia; Cavallin, Francesco

2016-05-26

Neonatal hypothermia is an important challenge associated with morbidity and mortality. Preventing neonatal hypothermia is important in high-resource countries, but is of fundamental importance in low-resource settings where supportive care is limited. Kangaroo mother care (KMC) is a low-cost intervention that, whenever possible, is strongly recommended for temperature maintenance. During KMC, the World Health Organization (WHO) guidelines recommend the use of a cap/hat, but its effect on temperature control during KMC remains to be established. In the hospitals participating in the projects of the non-governmental organization CUAMM, KMC represents a standard of care, but the heads of the babies often remain uncovered due to local habits or to the unavailability of a cap. The aim of the present study will be to assess the effectiveness and safety of using a woolen cap in maintaining normothermia in low-birth-weight infants (LBWI) during KMC. This is a multicenter (three hospitals), multicountry (three countries), prospective, unblinded, randomized controlled trial of KMC treatment with and without a woolen cap in LBWI. After obtaining parental consent, all infants with a birth weight below 2500 g and who are candidates for KMC, based on the clinical decision of the attending physician, will be assigned to the KMC with a woolen cap group or to the KMC without a woolen cap group in a 1:1 ratio according to a computer-generated, randomized sequence. The duration of the study will be until the patient's discharge, with a maximum treatment duration of 7 days. The primary outcome measure will be whether the infants' temperatures remain within the normal range (36.5-37.5 °C) in the course of KMC during the intervention. In all participants, axillary temperature will be measured with a digital thermometer four times per day. In addition, maternal and room temperature will be recorded. Secondary outcome measures will be: episodes of apnea; sepsis; mortality before hospital discharge; in-hospital growth; and age at discharge. The findings of this study will be important for other units/settings in high- as well low-resource countries where KMC is routinely performed. Based on the results of the present study, we could speculate whether the use of a woolen cap may help to maintain the neonate within the normal thermal range. Furthermore, potential complications such as hyperthermia will be strictly monitored and collected. ClinicalTrials.gov Identifier: NCT02645526 (registered on 31 December 2015).

Effect of kangaroo mother care on growth and development of low birthweight babies up to 12 months of age: a controlled clinical trial.

PubMed

Bera, Alpanamayi; Ghosh, Jagabandhu; Singh, Arun K; Hazra, Avijit; Mukherjee, Suchandra; Mukherjee, Ranajit

2014-06-01

Kangaroo mother care (KMC) is a nonconventional low-cost method of newborn care. Our aim was to assess the effect of sustained KMC on the growth and development of low birthweight Indian babies up to the age of 12 months. We enrolled 500 mother and baby pairs, in groups of five, in a parallel group controlled clinical trial. The three infants with the lowest birthweight in each group received KMC, while the other two received conventional care. All babies were exclusively breastfed for 6 months. Babies in the intervention group were provided KMC until the infant was 40 weeks of corrected gestation or weighed 2500 g. Weight, length and head, chest and arm circumferences were evaluated at birth and at the corrected ages of 0, 3, 6, 9 and 12 months. Development was assessed using the Developmental Assessment Scales for Indian Infants (DASII) at 12 months. The KMC babies rapidly achieved physical growth parameters similar to the control babies at 40 weeks of corrected age. But after that, they surpassed them, despite being smaller at birth. DASII motor and mental development quotients were also significantly better for KMC babies. The infants in the KMC group showed better physical growth and development than the conventional control group. ©2014 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

A consistent hierarchy of generalized kinetic equation approximations to the master equation applied to surface catalysis.

PubMed

Herschlag, Gregory J; Mitran, Sorin; Lin, Guang

2015-06-21

We develop a hierarchy of approximations to the master equation for systems that exhibit translational invariance and finite-range spatial correlation. Each approximation within the hierarchy is a set of ordinary differential equations that considers spatial correlations of varying lattice distance; the assumption is that the full system will have finite spatial correlations and thus the behavior of the models within the hierarchy will approach that of the full system. We provide evidence of this convergence in the context of one- and two-dimensional numerical examples. Lower levels within the hierarchy that consider shorter spatial correlations are shown to be up to three orders of magnitude faster than traditional kinetic Monte Carlo methods (KMC) for one-dimensional systems, while predicting similar system dynamics and steady states as KMC methods. We then test the hierarchy on a two-dimensional model for the oxidation of CO on RuO2(110), showing that low-order truncations of the hierarchy efficiently capture the essential system dynamics. By considering sequences of models in the hierarchy that account for longer spatial correlations, successive model predictions may be used to establish empirical approximation of error estimates. The hierarchy may be thought of as a class of generalized phenomenological kinetic models since each element of the hierarchy approximates the master equation and the lowest level in the hierarchy is identical to a simple existing phenomenological kinetic models.

On the mobility of carriers at semi-coherent oxide heterointerfaces

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

Dholabhai, Pratik P.; Martinez, Enrique Saez; Brown, Nicholas Taylor

In the quest to develop new materials with enhanced ionic conductivity for battery and fuel cell applications, nano-structured oxides have attracted attention. Experimental reports indicate that oxide heterointerfaces can lead to enhanced ionic conductivity, but these same reports cannot elucidate the origin of this enhancement, often vaguely referring to pipe diffusion at misfit dislocations as a potential explanation. However, this highlights the need to understand the role of misfit dislocation structure at semi-coherent oxide heterointerfaces in modifying carrier mobilities. Here, we use atomistic and kinetic Monte Carlo (KMC) simulations to develop a model of oxygen vacancy migration at SrTiO 3/MgOmore » interfaces, chosen because the misfit dislocation structure can be modified by changing the termination chemistry. We use atomistic simulations to determine the energetics of oxygen vacancies at both SrO and TiO 2 terminated interfaces, which are then used as the basis of the KMC simulations. While this model is approximate (as revealed by select nudged elastic band calculations), it highlights the role of the misfit dislocation structure in modifying the oxygen vacancy dynamics. We find that oxygen vacancy mobility is significantly reduced at either interface, with slight differences at each interface due to the differing misfit dislocation structure. Here, we conclude that if such semi-coherent oxide heterointerfaces induce enhanced ionic conductivity, it is not a consequence of higher carrier mobility.« less

Structure and specificity of the RNA-guided endonuclease Cas9 during DNA interrogation, target binding and cleavage

PubMed Central

Josephs, Eric A.; Kocak, D. Dewran; Fitzgibbon, Christopher J.; McMenemy, Joshua; Gersbach, Charles A.; Marszalek, Piotr E.

2015-01-01

CRISPR-associated endonuclease Cas9 cuts DNA at variable target sites designated by a Cas9-bound RNA molecule. Cas9's ability to be directed by single ‘guide RNA’ molecules to target nearly any sequence has been recently exploited for a number of emerging biological and medical applications. Therefore, understanding the nature of Cas9's off-target activity is of paramount importance for its practical use. Using atomic force microscopy (AFM), we directly resolve individual Cas9 and nuclease-inactive dCas9 proteins as they bind along engineered DNA substrates. High-resolution imaging allows us to determine their relative propensities to bind with different guide RNA variants to targeted or off-target sequences. Mapping the structural properties of Cas9 and dCas9 to their respective binding sites reveals a progressive conformational transformation at DNA sites with increasing sequence similarity to its target. With kinetic Monte Carlo (KMC) simulations, these results provide evidence of a ‘conformational gating’ mechanism driven by the interactions between the guide RNA and the 14th–17th nucleotide region of the targeted DNA, the stabilities of which we find correlate significantly with reported off-target cleavage rates. KMC simulations also reveal potential methodologies to engineer guide RNA sequences with improved specificity by considering the invasion of guide RNAs into targeted DNA duplex. PMID:26384421

On the mobility of carriers at semi-coherent oxide heterointerfaces

DOE PAGES

Dholabhai, Pratik P.; Martinez, Enrique Saez; Brown, Nicholas Taylor; ...

2017-08-17

In the quest to develop new materials with enhanced ionic conductivity for battery and fuel cell applications, nano-structured oxides have attracted attention. Experimental reports indicate that oxide heterointerfaces can lead to enhanced ionic conductivity, but these same reports cannot elucidate the origin of this enhancement, often vaguely referring to pipe diffusion at misfit dislocations as a potential explanation. However, this highlights the need to understand the role of misfit dislocation structure at semi-coherent oxide heterointerfaces in modifying carrier mobilities. Here, we use atomistic and kinetic Monte Carlo (KMC) simulations to develop a model of oxygen vacancy migration at SrTiO 3/MgOmore » interfaces, chosen because the misfit dislocation structure can be modified by changing the termination chemistry. We use atomistic simulations to determine the energetics of oxygen vacancies at both SrO and TiO 2 terminated interfaces, which are then used as the basis of the KMC simulations. While this model is approximate (as revealed by select nudged elastic band calculations), it highlights the role of the misfit dislocation structure in modifying the oxygen vacancy dynamics. We find that oxygen vacancy mobility is significantly reduced at either interface, with slight differences at each interface due to the differing misfit dislocation structure. Here, we conclude that if such semi-coherent oxide heterointerfaces induce enhanced ionic conductivity, it is not a consequence of higher carrier mobility.« less

Miscut dependent surface evolution in the process of N-polar GaN(000 1 bar) growth under N-rich condition

NASA Astrophysics Data System (ADS)

Krzyżewski, Filip; Załuska-Kotur, Magdalena A.; Turski, Henryk; Sawicka, Marta; Skierbiszewski, Czesław

2017-01-01

The evolution of surface morphology during the growth of N-polar (000 1 bar) GaN under N-rich conditions is studied by kinetic Monte Carlo (kMC) simulations for two substrates miscuts 2° and 4°. The results are compared with experimentally observed surface morphologies of (000 1 bar) GaN layers grown by plasma-assisted molecular beam epitaxy. The proposed kMC two-component model of GaN(000 1 bar) surface where both types of atoms, nitrogen and gallium, attach to the surface and diffuse independently shows that at relatively high rates of the step flow (miscut angle < 2 °) the low mobility of gallium adatoms causes surface instabilities and leads to experimentally observed roughening while for low rates of the step flow (miscut 4°), smooth surface can be obtained. In the presence of almost immobile nitrogen atoms under N-rich conditions crystal growth is realized by the process of two-dimensional island nucleation and coalescence. Larger crystal miscut, lower growth rate or higher temperature results in similar effect of the surface smoothening. We show that the surface also smoothens for the growth conditions with very high N-excess. In the presence of large number of nitrogen atoms the mobility of gallium atoms changes locally thus providing easier coalescence of separated island.

Study on influences of TiN capping layer on time-dependent dielectric breakdown characteristic of ultra-thin EOT high-k metal gate NMOSFET with kMC TDDB simulations

NASA Astrophysics Data System (ADS)

Xu, Hao; Yang, Hong; Luo, Wei-Chun; Xu, Ye-Feng; Wang, Yan-Rong; Tang, Bo; Wang, Wen-Wu; Qi, Lu-Wei; Li, Jun-Feng; Yan, Jiang; Zhu, Hui-Long; Zhao, Chao; Chen, Da-Peng; Ye, Tian-Chun

2016-08-01

The thickness effect of the TiN capping layer on the time dependent dielectric breakdown (TDDB) characteristic of ultra-thin EOT high-k metal gate NMOSFET is investigated in this paper. Based on experimental results, it is found that the device with a thicker TiN layer has a more promising reliability characteristic than that with a thinner TiN layer. From the charge pumping measurement and secondary ion mass spectroscopy (SIMS) analysis, it is indicated that the sample with the thicker TiN layer introduces more Cl passivation at the IL/Si interface and exhibits a lower interface trap density. In addition, the influences of interface and bulk trap density ratio N it/N ot are studied by TDDB simulations through combining percolation theory and the kinetic Monte Carlo (kMC) method. The lifetime reduction and Weibull slope lowering are explained by interface trap effects for TiN capping layers with different thicknesses. Project supported by the National High Technology Research and Development Program of China (Grant No. SS2015AA010601), the National Natural Science Foundation of China (Grant Nos. 61176091 and 61306129), and the Opening Project of Key Laboratory of Microelectronics Devices & Integrated Technology, Institute of MicroElectronics of Chinese Academy of Sciences.

Modeling the atomistic growth behavior of gold nanoparticles in solution

NASA Astrophysics Data System (ADS)

Turner, C. Heath; Lei, Yu; Bao, Yuping

2016-04-01

The properties of gold nanoparticles strongly depend on their three-dimensional atomic structure, leading to an increased emphasis on controlling and predicting nanoparticle structural evolution during the synthesis process. In order to provide this atomistic-level insight and establish a link to the experimentally-observed growth behavior, a kinetic Monte Carlo simulation (KMC) approach is developed for capturing Au nanoparticle growth characteristics. The advantage of this approach is that, compared to traditional molecular dynamics simulations, the atomistic nanoparticle structural evolution can be tracked on time scales that approach the actual experiments. This has enabled several different comparisons against experimental benchmarks, and it has helped transition the KMC simulations from a hypothetical toy model into a more experimentally-relevant test-bed. The model is initially parameterized by performing a series of automated comparisons of Au nanoparticle growth curves versus the experimental observations, and then the refined model allows for detailed structural analysis of the nanoparticle growth behavior. Although the Au nanoparticles are roughly spherical, the maximum/minimum dimensions deviate from the average by approximately 12.5%, which is consistent with the corresponding experiments. Also, a surface texture analysis highlights the changes in the surface structure as a function of time. While the nanoparticles show similar surface structures throughout the growth process, there can be some significant differences during the initial growth at different synthesis conditions.

Controlling Self-Assembly in Al(110) Homoepitaxy

NASA Astrophysics Data System (ADS)

Tiwary, Yogesh; Fichthorn, Kristen

2010-03-01

Homoepitaxial growth on Al(110) exhibits nanoscale self-assembly into huts with well-defined (100) and (111) facets [1]. Although some of the diffusion mechanisms underlying this kinetic self-assembly were identified and incorporated into a two-dimensional model [2], we used density-functional theory (DFT) to identify many other mechanisms that are needed to describe the three-dimensional assembly seen experimentally [3]. We developed a three-dimensional kinetic Monte Carlo (KMC) model of Al(110) homoepitaxy. The inputs to the model were obtained from DFT [3,4]. Our model is in agreement with experimentally observed trends for this system. We used KMC to predict self-assembly under various growth conditions. To achieve precise placement of Al nanohuts, we simulated thermal-field-directed assembly [5]. Our results indicate that this technique can be used to create uniform arrays of nanostructures. [1] F. Buatier de Mongeot, W. Zhu, A. Molle, R. Buzio, C. Boragno, U. Valbusa, E. Wang, and Z. Zhang, Phys. Rev. Lett. 91, 016102 (2003). [2] W. Zhu, F. Buatier de Mongeot, U. Valbusa, E. G. Wang, and Z. Y. Zhang, Phys. Rev. Lett. 92, 106102 (2004). [3] Y. Tiwary and K. A. Fichthorn, submitted to Phys. Rev. B. [4] Y. Tiwary and K. A. Fichthorn, Phys. Rev. B 78, 205418 (2008). [5] C. Zhang and R. Kalyanaraman, Appl. Phys. Lett. 83, 4827 (2003).

Dose calculation accuracy of the Monte Carlo algorithm for CyberKnife compared with other commercially available dose calculation algorithms.

PubMed

Sharma, Subhash; Ott, Joseph; Williams, Jamone; Dickow, Danny

2011-01-01

Monte Carlo dose calculation algorithms have the potential for greater accuracy than traditional model-based algorithms. This enhanced accuracy is particularly evident in regions of lateral scatter disequilibrium, which can develop during treatments incorporating small field sizes and low-density tissue. A heterogeneous slab phantom was used to evaluate the accuracy of several commercially available dose calculation algorithms, including Monte Carlo dose calculation for CyberKnife, Analytical Anisotropic Algorithm and Pencil Beam convolution for the Eclipse planning system, and convolution-superposition for the Xio planning system. The phantom accommodated slabs of varying density; comparisons between planned and measured dose distributions were accomplished with radiochromic film. The Monte Carlo algorithm provided the most accurate comparison between planned and measured dose distributions. In each phantom irradiation, the Monte Carlo predictions resulted in gamma analysis comparisons >97%, using acceptance criteria of 3% dose and 3-mm distance to agreement. In general, the gamma analysis comparisons for the other algorithms were <95%. The Monte Carlo dose calculation algorithm for CyberKnife provides more accurate dose distribution calculations in regions of lateral electron disequilibrium than commercially available model-based algorithms. This is primarily because of the ability of Monte Carlo algorithms to implicitly account for tissue heterogeneities, density scaling functions; and/or effective depth correction factors are not required. Copyright © 2011 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Effect of intermittent kangaroo mother care on weight gain of low birth weight neonates with delayed weight gain.

PubMed

Samra, Nashwa M; Taweel, Amal El; Cadwell, Karin

2013-01-01

To evaluate intermittent Kangaroo Mother Care (KMC) with additional opportunities to breastfeed on weight gain of low birth weight (LBW) neonates with delayed weight gain. 40 LBW neonates were followed to see whether KMC with additional opportunities to breastfeed improved weight gain. In the KMC group, the mean age of regaining birth weight was significantly less (15.68 vs. 24.56 days) and the average daily weight gain was significantly higher (22.09 vs. 10.39 g, p < .001) than controls. KMC with additional opportunities to breastfeed was found to be an effective intervention for LBWs with delayed weight gain and should be considered to be an effective strategy.

Physical time scale in kinetic Monte Carlo simulations of continuous-time Markov chains.

PubMed

Serebrinsky, Santiago A

2011-03-01

We rigorously establish a physical time scale for a general class of kinetic Monte Carlo algorithms for the simulation of continuous-time Markov chains. This class of algorithms encompasses rejection-free (or BKL) and rejection (or "standard") algorithms. For rejection algorithms, it was formerly considered that the availability of a physical time scale (instead of Monte Carlo steps) was empirical, at best. Use of Monte Carlo steps as a time unit now becomes completely unnecessary.

Kangaroo Mother Care: A review of mothers׳'experiences at Bwaila hospital and Zomba Central hospital (Malawi).

PubMed

Chisenga, Jayne Z; Chalanda, Marcia; Ngwale, Mathews

2015-02-01

Kangaroo Mother Care is an intervention that can help reduce neonatal mortality rate in Malawi but it has not been rolled out to all health facilities. Understanding the mothers׳ experience would help strategise when scaling-up this intervention. to review experiences of mothers Kangaroo Mother Care at two hospitals of Bwaila and Zomba. quantitative, descriptive using open interviews. two central hospitals in Malawi. 113 mothers that were in the Kangaroo Mother Care unit and those that had come for follow-up two weeks after discharge before the study took place. mothers had high level of knowledge about the significant benefits of Kangaroo Mother Care but 84% were not aware of the services prior to their hospitalisation. 18.6% (n=19) were not counselled prior to KMC practice. Mothers preferred KMC to incubator care. There were factors affecting compliance and continuation of KMC, which were lack of support, culture, lack of assistance with skin-to-skin contact, multiple roles of the mother and stigma. mothers had a positive attitude towards KMC once fully aware of its benefits. there is need for awareness campaigns on KMC services, provision of counselling, support and assistance which can help motivate mothers and their families to comply with the guidelines of KMC services. Copyright © 2014 Elsevier Ltd. All rights reserved.

Kangaroo mother care in the neonatal intensive care unit: staff attitudes and beliefs and opportunities for parents.

PubMed

Strand, H; Blomqvist, Y T; Gradin, M; Nyqvist, K H

2014-04-01

To compare attitudes towards Kangaroo mother care (KMC) among staff in two high-tech neonatal intensive care units, which provided parents with different opportunities to get involved in their infants' care. Questionnaires were completed by healthcare staff in Unit A, which provided parents with unrestricted access so that they could provide continuous KMC, and Unit B, where parents could only practice KMC intermittently. Unit A staff were more positive about the benefits and use of KMC, including its use in unstable infants, and rated their knowledge and practical skills more highly than staff in the other unit. Unit B staff also appreciated the method, but expressed more hesitation in using it with unstable infants. In particular, they stressed the need to adapt the physical environment of the NICU to enable parents to stay with their infants and practice the method. Staff working in the NICU that gave parents unrestricted access were more positive about KMC than staff in the NICU that offered limited opportunities for parents to stay with their children. This finding suggests that it is important to eliminate unjustifiable obstacles to the presence of parents in the NICU, so that they can provide KMC. ©2013 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

The effect of formal, neonatal communication-intervention training on mothers in kangaroo care.

PubMed

Kritzinger, Alta; van Rooyen, Elise

2014-11-06

Due to low-birth-weight, preterm birth, HIV and/or AIDS and poverty-related factors, South Africa presents with an increased prevalence of infants at risk of language delay. A Kangaroo Mother Care (KMC) unit offers unique opportunities for training. The aim of the present study was to determine if formal, neonatal communication-intervention training had an effect on mothers' knowledge and communication interaction with their high-risk infants. Three groups of mothers participated: Group 1 was trained whilst practicing KMC; Group 2 was not trained but practiced KMC; and Group 3 was also not trained but practiced sporadic KMC. Ten mothers per group were matched for age, education level and birth order of their infants. The individual training was based on graded sensory stimulation and responsive mother-infant communication interaction, which emphasised talking and singing by the mother. Significant differences were found in mother-infant communication interaction between all three groups, which indicated a positive effect on Group 1 with training. Group 2, KMC without training, also had a positive effect on interaction. However, Group 1 mothers with training demonstrated better knowledge of their infants and were more responsive during interaction than the other two groups. The present study suggests that neonatal communication-intervention training adds value to a KMC programme.

Positive effect of kangaroo mother care on long-term breastfeeding in very preterm infants.

PubMed

Flacking, Renée; Ewald, Uwe; Wallin, Lars

2011-01-01

To investigate the use of Kangaroo Mother Care (KMC) and its association with breastfeeding at 1 to 6 months of corrected age in mothers of very preterm (VPT) and preterm (PT) infants. Prospective longitudinal study. Neonatal Intensive Care Units in four counties in Sweden. The study included 103 VPT (< 32 gestational weeks) and 197 PT (32-36 gestational weeks) singleton infants and their mothers. Data on KMC, measured in duration of skin-to-skin contact/day during all days admitted to a neonatal unit, were collected using self-reports from the parents. Data on breastfeeding were obtained by telephone interviews. VPT dyads that breastfed at 1, 2, 5, and 6 months had spent more time in KMC per day than those not breastfeeding at these times. A trend toward significance was noted at 3 and 4 months. In the PT dyads no statistically significant differences were found in the amount of KMC per day between those dyads that breastfed and those that did not. This study shows the importance of KMC during hospital stay for breastfeeding duration in VPT dyads. Hence, KMC has empowering effects on the process of breastfeeding, especially in those dyads with the smallest and most vulnerable infants. © 2011 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses.

Evaluation of retinopathy of prematurity screening in reverse Kangaroo Mother Care: a pilot study.

PubMed

Padhi, T R; Sareen, D; Pradhan, L; Jalali, S; Sutar, S; Das, T; Modi, R R; Behera, U C

2015-04-01

To evaluate retinopathy of prematurity (ROP) screening practice in reverse Kangaroo Mother Care (R-KMC) with respect to stress and pain to the infant. In a pilot study we evaluated ROP screening practice in R-KMC in 20 babies at risk of ROP. The R-KMC differed from the conventional KMC with respect to the baby position where the baby lay supine on mother's chest. With the mother lying supine and the baby in R-KMC position, screening examinations were done with indirect ophthalmoscope. The outcome measures included stress (quantified by pulse, respiration, and oxygen saturation) and pain to the baby by observing facial expression (eye squeezing, crying, and brow bulge). The heart rate, respiratory rate, and SpO2 (%) were compared before and immediately after the procedure using paired t-test. Mean (±SD) gestational age and birth weight were 30.8±2.3 weeks and 1362.5±253.9 g, respectively. During examination in R- KMC position 8 babies (40%) were completely relaxed (no eye squeezing and crying), 10 (50%) were partially relaxed (no brow bulge) and 2 babies (10%) were not relaxed. A change in heart and respiration rate both by 10 per minute was recorded in 12 (60%) and 10 (50%) babies, respectively. Five babies (25%) had reduction in blood oxygen concentration below 92%. The majority of the mothers (19 of 20) were relaxed. ROP screening in R-KMC can be a baby friendly screening practice with respect to stress and pain to the infant and needs further evaluation in a larger cohort.

Twenty-year Follow-up of Kangaroo Mother Care Versus Traditional Care.

PubMed

Charpak, Nathalie; Tessier, Rejean; Ruiz, Juan G; Hernandez, Jose Tiberio; Uriza, Felipe; Villegas, Julieta; Nadeau, Line; Mercier, Catherine; Maheu, Francoise; Marin, Jorge; Cortes, Darwin; Gallego, Juan Miguel; Maldonado, Dario

2017-01-01

Kangaroo mother care (KMC) is a multifaceted intervention for preterm and low birth weight infants and their parents. Short- and mid-term benefits of KMC on survival, neurodevelopment, breastfeeding, and the quality of mother-infant bonding were documented in a randomized controlled trial (RCT) conducted in Colombia from 1993 to 1996. The aim of the present study was to evaluate the persistence of these results in young adulthood. From 2012 to 2014, a total of 494 (69%) of the 716 participants of the original RCT known to be alive were identified; 441 (62% of the participants in the original RCT) were re-enrolled, and results for the 264 participants weighing ≤1800 g at birth were analyzed. The KMC and control groups were compared for health status and neurologic, cognitive, and social functioning with the use of neuroimaging, neurophysiological, and behavioral tests. The effects of KMC at 1 year on IQ and home environment were still present 20 years later in the most fragile individuals, and KMC parents were more protective and nurturing, reflected by reduced school absenteeism and reduced hyperactivity, aggressiveness, externalization, and socio-deviant conduct of young adults. Neuroimaging showed larger volume of the left caudate nucleus in the KMC group. This study indicates that KMC had significant, long-lasting social and behavioral protective effects 20 years after the intervention. Coverage with this efficient and scientifically based health care intervention should be extended to the 18 million infants born each year who are candidates for the method. Copyright © 2017 by the American Academy of Pediatrics.

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

Du, Jincheng; Rimsza, Jessica

Computational simulations at the atomistic level play an increasing important role in understanding the structures, behaviors, and the structure-property relationships of glass and amorphous materials. In this paper, we reviewed atomistic simulation methods ranging from first principles calculations and ab initio molecular dynamics (AIMD), to classical molecular dynamics (MD) and meso-scale kinetic Monte Carlo (KMC) simulations and their applications to glass-water interactions and glass dissolutions. Particularly, the use of these simulation methods in understanding the reaction mechanisms of water with oxide glasses, water-glass interfaces, hydrated porous silica gels formation, the structure and properties of multicomponent glasses, and microstructure evolution aremore » reviewed. Here, the advantages and disadvantageous of these methods are discussed and the current challenges and future direction of atomistic simulations in glass dissolution are presented.« less

Effect of Intermittent Kangaroo Mother Care on Weight Gain of Low Birth Weight Neonates With Delayed Weight Gain

PubMed Central

Samra, Nashwa M.; Taweel, Amal El; Cadwell, Karin

2013-01-01

Objective: To evaluate intermittent Kangaroo Mother Care (KMC) with additional opportunities to breastfeed on weight gain of low birth weight (LBW) neonates with delayed weight gain. Methods: 40 LBW neonates were followed to see whether KMC with additional opportunities to breastfeed improved weight gain. Results: In the KMC group, the mean age of regaining birth weight was significantly less (15.68 vs. 24.56 days) and the average daily weight gain was significantly higher (22.09 vs. 10.39 g, p < .001) than controls. Conclusion: KMC with additional opportunities to breastfeed was found to be an effective intervention for LBWs with delayed weight gain and should be considered to be an effective strategy. PMID:24868132

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 .

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).

Kangaroo mother care: a multi-country analysis of health system bottlenecks and potential solutions.

PubMed

Vesel, Linda; Bergh, Anne-Marie; Kerber, Kate J; Valsangkar, Bina; Mazia, Goldy; Moxon, Sarah G; Blencowe, Hannah; Darmstadt, Gary L; de Graft Johnson, Joseph; Dickson, Kim E; Ruiz Peláez, Juan; von Xylander, Severin; Lawn, Joy E

2015-01-01

Preterm birth is now the leading cause of under-five child deaths worldwide with one million direct deaths plus approximately another million where preterm is a risk factor for neonatal deaths due to other causes. There is strong evidence that kangaroo mother care (KMC) reduces mortality among babies with birth weight <2000 g (mostly preterm). KMC involves continuous skin-to-skin contact, breastfeeding support, and promotion of early hospital discharge with follow-up. The World Health Organization has endorsed KMC for stabilised newborns in health facilities in both high-income and low-resource settings. The objectives of this paper are to: (1) use a 12-country analysis to explore health system bottlenecks affecting the scale-up of KMC; (2) propose solutions to the most significant bottlenecks; and (3) outline priority actions for scale-up. The bottleneck analysis tool was applied in 12 countries in Africa and Asia as part of the Every Newborn Action Plan process. Country workshops involved technical experts to complete the survey tool, which is designed to synthesise and grade health system "bottlenecks", factors that hinder the scale-up, of maternal-newborn intervention packages. We used quantitative and qualitative methods to analyse the bottleneck data, combined with literature review, to present priority bottlenecks and actions relevant to different health system building blocks for KMC. Marked differences were found in the perceived severity of health system bottlenecks between Asian and African countries, with the former reporting more significant or very major bottlenecks for KMC with respect to all the health system building blocks. Community ownership and health financing bottlenecks were significant or very major bottlenecks for KMC in both low and high mortality contexts, particularly in South Asia. Significant bottlenecks were also reported for leadership and governance and health workforce building blocks. There are at least a dozen countries worldwide with national KMC programmes, and we identify three pathways to scale: (1) champion-led; (2) project-initiated; and (3) health systems designed. The combination of all three pathways may lead to more rapid scale-up. KMC has the potential to save lives, and change the face of facility-based newborn care, whilst empowering women to care for their preterm newborns.

Kangaroo mother care: a multi-country analysis of health system bottlenecks and potential solutions

PubMed Central

2015-01-01

Background Preterm birth is now the leading cause of under-five child deaths worldwide with one million direct deaths plus approximately another million where preterm is a risk factor for neonatal deaths due to other causes. There is strong evidence that kangaroo mother care (KMC) reduces mortality among babies with birth weight <2000 g (mostly preterm). KMC involves continuous skin-to-skin contact, breastfeeding support, and promotion of early hospital discharge with follow-up. The World Health Organization has endorsed KMC for stabilised newborns in health facilities in both high-income and low-resource settings. The objectives of this paper are to: (1) use a 12-country analysis to explore health system bottlenecks affecting the scale-up of KMC; (2) propose solutions to the most significant bottlenecks; and (3) outline priority actions for scale-up. Methods The bottleneck analysis tool was applied in 12 countries in Africa and Asia as part of the Every Newborn Action Plan process. Country workshops involved technical experts to complete the survey tool, which is designed to synthesise and grade health system "bottlenecks", factors that hinder the scale-up, of maternal-newborn intervention packages. We used quantitative and qualitative methods to analyse the bottleneck data, combined with literature review, to present priority bottlenecks and actions relevant to different health system building blocks for KMC. Results Marked differences were found in the perceived severity of health system bottlenecks between Asian and African countries, with the former reporting more significant or very major bottlenecks for KMC with respect to all the health system building blocks. Community ownership and health financing bottlenecks were significant or very major bottlenecks for KMC in both low and high mortality contexts, particularly in South Asia. Significant bottlenecks were also reported for leadership and governance and health workforce building blocks. Conclusions There are at least a dozen countries worldwide with national KMC programmes, and we identify three pathways to scale: (1) champion-led; (2) project-initiated; and (3) health systems designed. The combination of all three pathways may lead to more rapid scale-up. KMC has the potential to save lives, and change the face of facility-based newborn care, whilst empowering women to care for their preterm newborns. PMID:26391115

Impact of kangaroo mother care on cerebral blood flow of preterm infants.

PubMed

Korraa, Afaf A; El Nagger, Alyaa A I; Mohamed, Ragaa Abd El-Salam; Helmy, Noha M

2014-11-13

Kangaroo mother care (KMC) has been widely used to improve the care of preterms and low birth weight infants. However, very little is known about cerebral hemodynamics responses in preterm infants during KMC intervention. The aim of this study is to evaluate the changes of cerebral blood flow (CBF) in middle cerebral artery, before and after a 30 minute application of KMC in stable preterm infants. It is a prospective, pre-post test without a control group study. CBF flow paremeters were measured with Doppler ultrasonography in one middle cerebral artery. Sixty preterm stable infants were assessed before and after 30 min KMC. CBF indices were assessed in different positions before KMC, forty neonates in supine position and 20 in vertical suspension (baby is held vertically away from the skin of his mother). Other dependent variables heart rate and mean arterial blood pressure and Spo2 were also studied before and after KMC. The mean gestational age of the infants was (32 ± 2 weeks), and mean birth weight was (2080 ± 270 gm). Comparing CBF indices (Pulsatility index and Resistive index) before and after KMC has shown a significant decrease in both Pulsatility index (PI) and Resistive index (RI) after 30 min. KMC, the mean values were (2.0 ± 0.43 vs 1.68 ± 0.33 & 0.81 ± 0.05 vs 0.76 ± 0.06 respectively P < 0.05*) with mean difference (0.32 & 95% CI 0.042-0.41 & 0.05 & 95% CI 0.04 to 0.06 respectively P < 0.05*) and increase in end diastolic velocity & mean velocity 30 min of KMC (10.97 ± 4.63 vs. 15.39 ± 5.66 P < 0.05*& 25.66 ± 10.74 vs. 32.86 ± 11.47 P < 0.05* ) with mean difference (- 4.42 & 95% CI -5.67 to -3.18 and -7.21 & 95% CI - 9.41 to 5.00 respectively). These changes indicate improvement in CBF. No correlation has been found between CBF parameters and studied vital signs or SpO2. Kangaroo mother care improves cerebral blood flow, thus it might influence the structure and promote development of the premature infant's brain.

Using Human Patient Simulation to Improve Emergency Airway Management Safety in Post Anesthesia Nursing: A Pilot Project

DTIC Science & Technology

2010-08-04

airway management practices in the PACU has been deemed successful by KMC anesthesia management 15. SUBJECT TERMS Human Patient Simulation; Emergency...of South Alabama and KMC Clinical Research Laboratory (CRL) were received. The training sessions were planned for two 4-hour sessions in the HPS...assistance ofthe KMC CRL research statistician. Findings Results of the NLN Simulation Design Scale surveys showed seven of eight nurses in the

The effect of formal, neonatal communication-intervention training on mothers in kangaroo care

PubMed Central

van Rooyen, Elise

2014-01-01

Abstract Background Due to low-birth-weight, preterm birth, HIV and/or AIDS and poverty-related factors, South Africa presents with an increased prevalence of infants at risk of language delay. A Kangaroo Mother Care (KMC) unit offers unique opportunities for training. Aim The aim of the present study was to determine if formal, neonatal communication-intervention training had an effect on mothers’ knowledge and communication interaction with their high-risk infants. Methods Three groups of mothers participated: Group 1 was trained whilst practicing KMC; Group 2 was not trained but practiced KMC; and Group 3 was also not trained but practiced sporadic KMC. Ten mothers per group were matched for age, education level and birth order of their infants. The individual training was based on graded sensory stimulation and responsive mother-infant communication interaction, which emphasised talking and singing by the mother. Results Significant differences were found in mother-infant communication interaction between all three groups, which indicated a positive effect on Group 1 with training. Group 2, KMC without training, also had a positive effect on interaction. However, Group 1 mothers with training demonstrated better knowledge of their infants and were more responsive during interaction than the other two groups. Conclusion The present study suggests that neonatal communication-intervention training adds value to a KMC programme. PMID:26245414

The effect of kangaroo mother care on mental health of mothers with low birth weight infants.

PubMed

Badiee, Zohreh; Faramarzi, Salar; MiriZadeh, Tahereh

2014-01-01

The mothers of premature infants are at risk of psychological stress because of separation from their infants. One of the methods influencing the maternal mental health in the postpartum period is kangaroo mother care (KMC). This study was conducted to evaluate the effect of KMC of low birth weight infants on their maternal mental health. The study was conducted in the Department of Pediatrics of Isfahan University of Medical Sciences, Isfahan, Iran. Premature infants were randomly allocated into two groups. The control group received standard caring in the incubator. In the experimental group, caring with three sessions of 60 min KMC daily for 1 week was practiced. Mental health scores of the mothers were evaluated by using the 28-item General Health Questionnaire. Statistical analysis was performed by the analysis of covariance using SPSS. The scores of 50 infant-mother pairs were analyzed totally (25 in KMC group and 25 in standard care group). Results of covariance analysis showed the positive effects of KMC on the rate of maternal mental health scores. There were statistically significant differences between the mean scores of the experimental group and control subjects in the posttest period (P < 0.001). KMC for low birth weight infants is a safe way to improve maternal mental health. Therefore, it is suggested as a useful method that can be recommended for improving the mental health of mothers.

Cerebral motor function in very premature-at-birth adolescents: a brain stimulation exploration of kangaroo mother care effects.

PubMed

Schneider, Cyril; Charpak, Nathalie; Ruiz-Peláez, Juan G; Tessier, Réjean

2012-10-01

  Given that prematurity has deleterious effects on brain networking development beyond childhood, the study explored whether an early intervention such as Kangaroo Mother Care (KMC) in very preterm preemies could have influenced brain motor function up to adolescence.   Transcranial magnetic stimulation (TMS) was applied over the primary motor cortex (M1) of 39 adolescents born very prematurely (<33 weeks' gestational age, 21 having received KMC after birth, 18 Controls with no KMC) and nine adolescents born at term (>37 weeks' gestational age, >2500 g) to assess the functional integrity of motor circuits in each hemisphere (motor planning) and between hemispheres (callosal function).   All TMS outcomes were similar between KMC and term adolescents, with typical values as in healthy adults, and better than in Controls. KMC adolescents presented faster conduction times revealing more efficient M1 cell synchronization (p < 0.05) and interhemispheric transfer time (p < 0.0001), more frequent inhibitory processes with a better control between hemispheres (p < 0.0001).   The enhanced synchronization, conduction times and connectivity of cerebral motor pathways in the KMC group suggests that the Kangaroo Mother Care positively influenced the premature brain networks and synaptic efficacy up to adolescence. © 2012 The Author(s)/Acta Paediatrica © 2012 Foundation Acta Paediatrica.

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.

Individual Decision-Making in Uncertain and Large-Scale Multi-Agent Environments

DTIC Science & Technology

2009-02-18

first method, labeled as MC, limits and holds constant the number of models, 0 < KMC < M, where M is the possibly large number of candidate models of...equivalent and hence may be replaced by a subset of representative models without a significant loss in the optimality of the decision maker. KMC ...for different horizons. KMC and M are equal to 50 and 100 respectively for both approximate and exact approaches (Pentium 4, 3.0GHz, 1GB RAM, WinXP

Quantum speedup of Monte Carlo methods.

PubMed

Montanaro, Ashley

2015-09-08

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.

Quantum speedup of Monte Carlo methods

PubMed Central

Montanaro, Ashley

2015-01-01

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079

The effect of kangaroo mother care on mental health of mothers with low birth weight infants

PubMed Central

Badiee, Zohreh; Faramarzi, Salar; MiriZadeh, Tahereh

2014-01-01

Background: The mothers of premature infants are at risk of psychological stress because of separation from their infants. One of the methods influencing the maternal mental health in the postpartum period is kangaroo mother care (KMC). This study was conducted to evaluate the effect of KMC of low birth weight infants on their maternal mental health. Materials and Methods: The study was conducted in the Department of Pediatrics of Isfahan University of Medical Sciences, Isfahan, Iran. Premature infants were randomly allocated into two groups. The control group received standard caring in the incubator. In the experimental group, caring with three sessions of 60 min KMC daily for 1 week was practiced. Mental health scores of the mothers were evaluated by using the 28-item General Health Questionnaire. Statistical analysis was performed by the analysis of covariance using SPSS. Results: The scores of 50 infant-mother pairs were analyzed totally (25 in KMC group and 25 in standard care group). Results of covariance analysis showed the positive effects of KMC on the rate of maternal mental health scores. There were statistically significant differences between the mean scores of the experimental group and control subjects in the posttest period (P < 0.001). Conclusion: KMC for low birth weight infants is a safe way to improve maternal mental health. Therefore, it is suggested as a useful method that can be recommended for improving the mental health of mothers. PMID:25371871

Diffusion of interacting particles in discrete geometries: Equilibrium and dynamical properties

NASA Astrophysics Data System (ADS)

Becker, T.; Nelissen, K.; Cleuren, B.; Partoens, B.; Van den Broeck, C.

2014-11-01

We expand on a recent study of a lattice model of interacting particles [Phys. Rev. Lett. 111, 110601 (2013), 10.1103/PhysRevLett.111.110601]. The adsorption isotherm and equilibrium fluctuations in particle number are discussed as a function of the interaction. Their behavior is similar to that of interacting particles in porous materials. Different expressions for the particle jump rates are derived from transition-state theory. Which expression should be used depends on the strength of the interparticle interactions. Analytical expressions for the self- and transport diffusion are derived when correlations, caused by memory effects in the environment, are neglected. The diffusive behavior is studied numerically with kinetic Monte Carlo (kMC) simulations, which reproduces the diffusion including correlations. The effect of correlations is studied by comparing the analytical expressions with the kMC simulations. It is found that the Maxwell-Stefan diffusion can exceed the self-diffusion. To our knowledge, this is the first time this is observed. The diffusive behavior in one-dimensional and higher-dimensional systems is qualitatively the same, with the effect of correlations decreasing for increasing dimension. The length dependence of both the self- and transport diffusion is studied for one-dimensional systems. For long lengths the self-diffusion shows a 1 /L dependence. Finally, we discuss when agreement with experiments and simulations can be expected. The assumption that particles in different cavities do not interact is expected to hold quantitatively at low and medium particle concentrations if the particles are not strongly interacting.

Temporal Evolution of Nanostructures in a Model Nickel-Base Superalloy: Experiments and Simulations

NASA Technical Reports Server (NTRS)

Sudbrack, Chantal K.; Yoon, Kevin E.; Mao, Zugang; Noebe, Ronald D.; Isheim, Dieter; Seidman, David N.

2003-01-01

The temporal evolution of the nanostructure of a model Ni-base superalloy (Ni-5.2 at.% Al-14.2 at.% Cr) is studied experimentally employing three-dimensional atom-probe (3DAP) microscopy in conjunction with kinetic Monte Carlo (KMC) simulations at 600 C. It is demonstrated that not only can the mean compositions of individual gamma' (Ni3Al with the Li2 structure) precipitates be measured but the Ni, Al, and Cr concentration profiles within the precipitates can also be determined for precipitates with a mean radius () as small as 0.85 nm. The three asymptotic tinie dependencies of the Lifshitz-Slyzov-Wagner (LSW) theory of coarsening (Ostwald ripening) are measured and found to deviate from its theoretical predictions: possible explanations for these discrepancies are discussed. At 0.25 hr. there is 3DAP microscope evidence for the presence of precipitates of another nickel-rich phase. ="Ni3Cr" (Ni3Cr(1-x)Al(x)), which exhibits short-range order (SRO) and that is metastable with respect to Ni3Al. This metastable phase is also found by KMC simulations and has the composition Ni3Cr(1-x)Al(x), which is Ni-2.91 at.% Al-21.98 at.% Cr at 16 hours. Our results demonstrate that the decomposition of gamma the primary gamma (FCC) phase results in the concurrent formation of an ordered phase and a disordered phase by 0.25 hours.

Stability diagrams for the surface patterns of GaN(0001bar) as a function of Schwoebel barrier height

NASA Astrophysics Data System (ADS)

Krzyżewski, Filip; Załuska-Kotur, Magdalena A.

2017-01-01

Height and type of Schwoebel barriers (direct or inverse) decides about the character of the surface instability. Different surface morphologies are presented. Step bunches, double steps, meanders, mounds and irregular patterns emerge at the surface as a result of step (Schwoebel) barriers at some temperature or miscut values. The study was carried out on the two-component kinetic Monte Carlo (kMC) model of GaN(0001bar) surface grown in nitrogen rich conditions. Diffusion of gallium adatoms over N-polar surface is slow and nitrogen adatoms are almost immobile. We show that in such conditions surfaces remain smooth when gallium adatoms diffuse in the presence of low inverse Schwoebel barrier. It is illustrated by adequate stability diagrams for surface morphologies.

Kangaroo mother care: a randomized controlled trial on effectiveness of early kangaroo mother care for the low birthweight infants in Addis Ababa, Ethiopia.

PubMed

Worku, Bogale; Kassie, Assaye

2005-04-01

A randomized controlled trial was conducted over a 1-year period (November 2001-November 2002) in Addis Ababa to study the effectiveness of early Kangaroo mother care before stabilization of low birthweight infants as compared with the conventional method of care. There were 259 babies weighing less than 2000 g during the study period and a total of 123 (47.5 per cent) low birthweight infants were included in to the study. Sixty-two infants were enrolled as Kangaroo Mother Care (KMC) and the remaining 61 were Conventional Method of Care (CMC) cases. The demographic and socioeconomic characteristics for both groups were comparable. The mean age at the time of enrollment was 10 and 9.8 h for KMC and CMC, respectively (p>0.05 with 95 per cent confidence interval). The mean birthweight was 1514.8 g (range 1000-1900 g) for KMC and 1471.8 g (range 930-1900 g) for CMC (p>0.05 with 95 per cent CI) and the mean gestational age was 32.42 and 31.59 weeks for KMC and CMC cases, respectively. Fifty-eight per cent of KMC and 52 per cent of CMC cases were on i.v. fluid. Twenty-one of 62 (34 per cent) of KMC and 23/61 (37 per cent) of CMC babies were on oxygen through nasopharyngeal catheter. The mean age at exit from the study was 4.6 days for KMC and 5.4 days for CMC. Ninety-one per cent and 88 per cent of babies in KMC and CMC were discharged from the study in the first 7 days of life, respectively. The study showed that 14/62 (22.5 per cent) of KMC vs. 24/63 (38 per cent) CMC babies died during the study (p<0.05 and CI of 95 per cent.) The majority of deaths occurred during the first 12 h of life. Survival for the preterm low birthweight infants was remarkably better for the early kangaroo mother care group than the babies in the conventional method of care in the first 12 h and there after. More than 95 per cent of mothers reported that they were happy to care for their low birthweight babies using the early Kangaroo mother method. It was recommended to study the feasibility and effectiveness of Kangaroo mother care at the community level.

Short spell kangaroo mother care and its differential physiological influence in subgroups of preterm babies.

PubMed

Boju, Sangeetha Lakshmi; Gopi Krishna, Muddu; Uppala, Rajani; Chodavarapu, Praneeta; Chodavarapu, Ravikumar

2012-06-01

In routine practice, 4-6 h of kangaroo mother care (KMC) is adopted. Many mothers feel the duration impracticable. In 86 preterm babies, pre and post 1 h KMC changes in heart rate (HR), respiratory rate (RR), axillary temperature and SpO(2) are measured, in each baby. Postnatal age at the time of the study is 7.7 ± 5.2 days. Significant changes observed are decrease in mean HR by 3 bpm, RR by 3 min(-1) and increase in mean axillary temperature by 0.4 F and SpO(2) by 1.1%. In SGA babies, post KMC decrease in mean HR by 5 bpm, increase in mean axillary temperature by 0.6 F and SpO(2) by 2.1% are significant. In female babies, post KMC decrease in mean RR by 6 min(-1) and increase mean axillary temperature by 0.3 F and SpO(2) by 1.5% are significant. We conclude that preterm babies are benefited by 1 h KMC. SGA and female preterm babies showed different and greater response.

Kangaroo mother care for the prevention of neonatal hypothermia: a randomised controlled trial in term neonates.

PubMed

Ramani, Manimaran; Choe, Eunjoo A; Major, Meggin; Newton, Rebecca; Mwenechanya, Musaku; Travers, Colm P; Chomba, Elwyn; Ambalavanan, Namasivayam; Carlo, Waldemar A

2018-05-01

To test the hypothesis that kangaroo mother care (KMC) initiated either at birth or at 1 hour after birth reduces moderate or severe hypothermia in term neonates at (A) 1 hour after birth and (B) at discharge when compared with standard thermoregulation care. Term neonates born at a tertiary delivery centre in Zambia were randomised in two phases (phase 1: birth to 1 hour, phase 2: 1 hour to discharge) to either as much KMC as possible in combination with standard thermoregulation care (KMC group) or to standard thermoregulation care (control group). The primary outcomes were moderate or severe hypothermia (axillary temperature <36.0°C) at (A) 1 hour after birth and (B) at discharge. The proportion of neonates with moderate or severe hypothermia did not differ between the KMC and control groups at 1 hour after birth (25% vs 27%, relative risk (RR)=0.93, 95% CI 0.59 to 1.4, P=0.78) or at discharge (7% vs 2%, RR=2.8, 95% CI 0.6 to 13.9, P=0.16). Hypothermia was not found among the infants who had KMC for at least 9 hours or 80% of the hospital stay. KMC practised as much as possible in combination with standard thermoregulation care initiated either at birth or at 1 hour after birth did not reduce moderate or severe hypothermia in term infants compared with standard thermoregulation care. The current study also shows that duration of KMC either for at least 80% of the time or at least 9 hours during the day of birth was effective in preventing hypothermia in term infants. NCT02189759. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Progress in the implementation of kangaroo mother care in 10 hospitals in Indonesia.

PubMed

Bergh, Anne-Marie; Rogers-Bloch, Quail; Pratomo, Hadi; Uhudiyah, Uut; Sidi, Ieda Poernomo Sigit; Rustina, Yeni; Suradi, Rulina; Gipson, Reginald

2012-10-01

Kangaroo mother care (KMC) is an effective and safe method of caring for low-birthweight infants. This article describes the results of a health systems strengthening intervention in KMC involving 10 hospitals in Java, Indonesia. Implementation progress was measured with an instrument scoring hospitals out of 100. Hospital scores ranged from 28 to 85, with a mean score of 62.1. One hospital had not reached the level of 'evidence of practice'; five hospitals had reached the expected level of 'evidence of practice' and two hospitals already scored on the level of 'evidence of routine and integration'. The two training hospitals were on the border of 'evidence of sustainable practice'. The implementation of KMC is a long-term process that requires dedication and support for a number of years. Some items in the progress-monitoring tool could be used to set standards for KMC that hospitals must meet for accreditation purposes.

The Rational Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Clark, Michael

2006-12-01

The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.

Metabarcoding of the kombucha microbial community grown in different microenvironments.

PubMed

Reva, Oleg N; Zaets, Iryna E; Ovcharenko, Leonid P; Kukharenko, Olga E; Shpylova, Switlana P; Podolich, Olga V; de Vera, Jean-Pierre; Kozyrovska, Natalia O

2015-12-01

Introducing of the DNA metabarcoding analysis of probiotic microbial communities allowed getting insight into their functioning and establishing a better control on safety and efficacy of the probiotic communities. In this work the kombucha poly-microbial probiotic community was analysed to study its flexibility under different growth conditions. Environmental DNA sequencing revealed a complex and flexible composition of the kombucha microbial culture (KMC) constituting more bacterial and fungal organisms in addition to those found by cultural method. The community comprised bacterial and yeast components including cultured and uncultivable microorganisms. Culturing the KMC under different conditions revealed the core part of the community which included acetobacteria of two genera Komagataeibacter (former Gluconacetobacter) and Gluconobacter, and representatives of several yeast genera among which Brettanomyces/Dekkera and Pichia (including former Issatchenkia) were dominant. Herbaspirillum spp. and Halomonas spp., which previously had not been described in KMC, were found to be minor but permanent members of the community. The community composition was dependent on the growth conditions. The bacterial component of KMC was relatively stable, but may include additional member-lactobacilli. The yeast species composition was significantly variable. High-throughput sequencing showed complexity and variability of KMC that may affect the quality of the probiotic drink. It was hypothesized that the kombucha core community might recruit some environmental bacteria, particularly lactobacilli, which potentially may contribute to the fermentative capacity of the probiotic drink. As many KMC-associated microorganisms cannot be cultured out of the community, a robust control for community composition should be provided by using DNA metabarcoding.

The cost-savings of implementing kangaroo mother care in Nicaragua.

PubMed

Broughton, Edward I; Gomez, Ivonne; Sanchez, Nieves; Vindell, Concepción

2013-09-01

To examine the costs of implementing kangaroo mother care (KMC) in a referral hospital in Nicaragua, including training, implementation, and ongoing operating costs, and to estimate the economic impact on the Nicaraguan health system if KMC were implemented in other maternity hospitals in the country. After receiving clinical training in KMC, the implementation team trained their colleagues, wrote guidelines for clinicians and education material for parents, and ensured adherence to the new guidelines. The intervention began September 2010 The study compared data on infant weight, medication use, formula consumption, incubator use, and hospitalization for six months before and after implementation. Cost data were collected from accounting records of the implementers and health ministry formularies. A total of 46 randomly selected infants before implementation were compared to 52 after implementation. Controlling for confounders, neonates after implementation had lower lengths of hospitalization by 4.64 days (P = 0.017) and 71% were exclusively breastfed (P < 0.001). The intervention cost US$ 23 113 but the money saved with shorter hospitalization, elimination of incubator use, and lower antibiotic and infant formula costs made up for this expense in 1 - 2 months. Extending KMC to 12 other facilities in Nicaragua is projected to save approximately US$ 166 000 (based on the referral hospital incubator use estimate) or US$ 233 000 after one year (based on the more conservative incubator use estimate). Treating premature and low-birth-weight infants in Nicaragua with KMC implemented as a quality improvement program saves money within a short period even without considering the beneficial health effects of KMC. Implementation in more facilities is strongly recommended.

Full System Model of Magnetron Sputter Chamber - Proof-of-Principle Study

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

Walton, C; Gilmer, G; Zepeda-Ruiz, L

2007-05-04

The lack of detailed knowledge of internal process conditions remains a key challenge in magnetron sputtering, both for chamber design and for process development. Fundamental information such as the pressure and temperature distribution of the sputter gas, and the energies and arrival angles of the sputtered atoms and other energetic species is often missing, or is only estimated from general formulas. However, open-source or low-cost tools are available for modeling most steps of the sputter process, which can give more accurate and complete data than textbook estimates, using only desktop computations. To get a better understanding of magnetron sputtering, wemore » have collected existing models for the 5 major process steps: the input and distribution of the neutral background gas using Direct Simulation Monte Carlo (DSMC), dynamics of the plasma using Particle In Cell-Monte Carlo Collision (PIC-MCC), impact of ions on the target using molecular dynamics (MD), transport of sputtered atoms to the substrate using DSMC, and growth of the film using hybrid Kinetic Monte Carlo (KMC) and MD methods. Models have been tested against experimental measurements. For example, gas rarefaction as observed by Rossnagel and others has been reproduced, and it is associated with a local pressure increase of {approx}50% which may strongly influence film properties such as stress. Results on energies and arrival angles of sputtered atoms and reflected gas neutrals are applied to the Kinetic Monte Carlo simulation of film growth. Model results and applications to growth of dense Cu and Be films are presented.« less

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.

Three-dimensional kinetic Monte Carlo simulations of cubic transition metal nitride thin film growth

NASA Astrophysics Data System (ADS)

Nita, F.; Mastail, C.; Abadias, G.

2016-02-01

A three-dimensional kinetic Monte Carlo (KMC) model has been developed and used to simulate the microstructure and growth morphology of cubic transition metal nitride (TMN) thin films deposited by reactive magnetron sputtering. Results are presented for the case of stoichiometric TiN, chosen as a representative TMN prototype. The model is based on a NaCl-type rigid lattice and includes deposition and diffusion events for both N and Ti species. It is capable of reproducing voids and overhangs, as well as surface faceting. Simulations were carried out assuming a uniform flux of incoming particles approaching the surface at normal incidence. The ballistic deposition model is parametrized with an interaction parameter r0 that mimics the capture distance at which incoming particles may stick on the surface, equivalently to a surface trapping mechanism. Two diffusion models are implemented, based on the different ways to compute the site-dependent activation energy for hopping atoms. The influence of temperature (300-500 K), deposition flux (0.1-100 monolayers/s), and interaction parameter r0 (1.5-6.0 Å) on the obtained growth morphology are presented. Microstructures ranging from highly porous, [001]-oriented straight columns with smooth top surface to rough columns emerging with different crystallographic facets are reproduced, depending on kinetic restrictions, deposited energy (seemingly captured by r0), and shadowing effect. The development of facets is a direct consequence of the diffusion model which includes an intrinsic (minimum energy-based) diffusion anisotropy, although no crystallographic diffusion anisotropy was explicitly taken into account at this stage. The time-dependent morphological evolution is analyzed quantitatively to extract the growth exponent β and roughness exponent α , as indicators of kinetic roughening behavior. For dense TiN films, values of α ≈0.7 and β =0.24 are obtained in good agreement with existing experimental data. At this stage a single lattice is considered but the KMC model will be extended further to address more complex mechanisms, such as anisotropic surface diffusion and grain boundary migration at the origin of the competitive columnar growth observed in polycrystalline TiN-based films.

SU-F-T-619: Dose Evaluation of Specific Patient Plans Based On Monte Carlo Algorithm for a CyberKnife Stereotactic Radiosurgery System

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

Piao, J; PLA 302 Hospital, Beijing; Xu, S

2016-06-15

Purpose: This study will use Monte Carlo to simulate the Cyberknife system, and intend to develop the third-party tool to evaluate the dose verification of specific patient plans in TPS. Methods: By simulating the treatment head using the BEAMnrc and DOSXYZnrc software, the comparison between the calculated and measured data will be done to determine the beam parameters. The dose distribution calculated in the Raytracing, Monte Carlo algorithms of TPS (Multiplan Ver4.0.2) and in-house Monte Carlo simulation method for 30 patient plans, which included 10 head, lung and liver cases in each, were analyzed. The γ analysis with the combinedmore » 3mm/3% criteria would be introduced to quantitatively evaluate the difference of the accuracy between three algorithms. Results: More than 90% of the global error points were less than 2% for the comparison of the PDD and OAR curves after determining the mean energy and FWHM.The relative ideal Monte Carlo beam model had been established. Based on the quantitative evaluation of dose accuracy for three algorithms, the results of γ analysis shows that the passing rates (84.88±9.67% for head,98.83±1.05% for liver,98.26±1.87% for lung) of PTV in 30 plans between Monte Carlo simulation and TPS Monte Carlo algorithms were good. And the passing rates (95.93±3.12%,99.84±0.33% in each) of PTV in head and liver plans between Monte Carlo simulation and TPS Ray-tracing algorithms were also good. But the difference of DVHs in lung plans between Monte Carlo simulation and Ray-tracing algorithms was obvious, and the passing rate (51.263±38.964%) of γ criteria was not good. It is feasible that Monte Carlo simulation was used for verifying the dose distribution of patient plans. Conclusion: Monte Carlo simulation algorithm developed in the CyberKnife system of this study can be used as a reference tool for the third-party tool, which plays an important role in dose verification of patient plans. This work was supported in part by the grant from Chinese Natural Science Foundation (Grant No. 11275105). Thanks for the support from Accuray Corp.« less

The long-term effects of the Kangaroo Mother Care intervention on cognitive functioning: Results from a longitudinal study.

PubMed

Ropars, Stéphanie; Tessier, Réjean; Charpak, Nathalie; Uriza, Luis Felipe

2018-01-01

This study aimed to evaluate the long-term effects of the Kangaroo Mother Care (KMC) intervention on the intellectual and attentional functioning of young adults born with low birth weight. Three hundred infants were randomly assigned at birth in one of two interventions, KMC or traditional care (TC), and completed cognitive tests at adulthood (19-21 years after recruitment). The main results show that participants with a neurological vulnerability at 6 months had higher IQ and sustained attention scores at adulthood if they had received KMC than if they had received TC.

The presence of physician champions improved Kangaroo Mother Care in rural western India.

PubMed

Soni, Apurv; Amin, Amee; Patel, Dipen V; Fahey, Nisha; Shah, Nikhil; Phatak, Ajay G; Allison, Jeroan; Nimbalkar, Somashekhar M

2016-09-01

This study determined the effect of physician champions on the two main components of Kangaroo Mother Care (KMC): skin-to-skin care and breastfeeding. KMC practices among a retrospective cohort of 648 infants admitted to a rural Indian neonatal intensive care unit (NICU) between January 5, 2011 and October 7, 2014 were studied. KMC champions were identified based on their performance evaluation. We examined the effect of withdrawing physician champions on overall use, time to initiation and intensity of skin-to-skin care and breastfeeding, using separate models. In comparison with when KMC champions were present, their absence was associated with a 45% decrease in the odds of receiving skin-to-skin care, with a 95% confidence interval (CI) of 64% to 17%, a 38% decrease in the rate of initiation skin-to-skin care (95% CI 53-82%) and an average of 1.47 less hours of skin-to-skin care (95% CI -2.07 to -0.86). Breastfeeding practices were similar across the different champion environments. Withdrawing physician champions from the NICU setting was associated with a decline in skin-to-skin care, but not breastfeeding. Training health care workers and community stakeholders to become champions could help to scale up and maintain KMC practices. ©2016 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

The presence of physician champions improved Kangaroo mother care in rural western India

PubMed Central

Soni, Apurv; Amin, Amee; Patel, Dipen V; Fahey, Nisha; Shah, Nikhil; Phatak, Ajay G; Allison, Jeroan; Nimbalkar, Somashekhar M

2016-01-01

Aim This study determined the effect of physician champions on the two main components of Kangaroo mother care (KMC): skin-to-skin care and breastfeeding. Methods KMC practices among a retrospective cohort of 648 infants admitted to a rural Indian neonatal intensive care unit (NICU) between 5 January 2011 and 7 October 2014 were studied. KMC champions were identified based on their performance evaluation. We examined the effect of withdrawing physician champions on overall use, time to initiation and intensity of skin-to-skin care and breastfeeding, using separate models. Results In comparison to when KMC champions were present, their absence was associated with a 45% decrease in the odds of receiving skin-to-skin care, with a 95% Confidence Interval (CI) of 64% to 17%, a 38% decrease in the rate of initiation skin-to-skin care (95% CI 53% to 82%) and an average of 1.47 less hours of skin-to-skin care (95% CI −2.07 to −0.86). Breastfeeding practices were similar across the different champion environments. Conclusion Withdrawing physician champions from the NICU setting was associated with a decline in skin-to-skin care, but not breastfeeding. Training healthcare workers and community stakeholders to become champions could help to scale up and maintain KMC practices. PMID:27111097

Practical application of kangaroo mother care in preterm infants: clinical characteristics and safety of kangaroo mother care.

PubMed

Park, Hyun-kyung; Choi, Byeong Seon; Lee, Seung Jin; Son, In-A; Seol, In-Joon; Lee, Hyun Ju

2014-03-01

To determine the clinical characteristics and safety of kangaroo mother care (KMC) according to the gestational age (GA) or postmenstrual age (PMA). We conducted a prospective clinical study in 31 infants between 25 and 32 weeks' GA. The subjects were categorized into two groups (25-28 weeks' and 29-32 weeks' GA groups) to compare the clinical characteristics associated with KMC. Heart rate, respiratory rate, oxygen saturation, blood pressure and body temperature (BT) were longitudinally assessed for 60 min with respect to the PMA group (29-32 weeks' and 33-36 weeks' PMA groups). The authors analyzed 70 sessions with 31 infants (25-32 weeks' GA, birth weight 760-1740 g, 29-36 weeks' PMA). All infants had statistically significant higher temperatures during KMC than before KMC within clinically acceptable limits (P<0.001). We found a significantly lower variation of BT in the 25-28 weeks' GA group compared with the 29-32 weeks' GA group at 33-36 weeks' PMA, suggesting accelerated skin maturation in more premature infants (P<0.001). Our intermittent KMC was a safe and feasible method for preterm infants. Notably, at the same PMA, preterm infants in the lower at-birth GA group showed an advanced maturation of thermoregulation compared with those in the higher GA group.

Studies of concentration and temperature dependences of precipitation kinetics in iron-copper alloys using kinetic Monte Carlo and stochastic statistical simulations

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

Khromov, K. Yu.; Vaks, V. G., E-mail: vaks@mbslab.kiae.ru; Zhuravlev, I. A.

2013-02-15

The previously developed ab initio model and the kinetic Monte Carlo method (KMCM) are used to simulate precipitation in a number of iron-copper alloys with different copper concentrations x and temperatures T. The same simulations are also made using an improved version of the previously suggested stochastic statistical method (SSM). The results obtained enable us to make a number of general conclusions about the dependences of the decomposition kinetics in Fe-Cu alloys on x and T. We also show that the SSM usually describes the precipitation kinetics in good agreement with the KMCM, and using the SSM in conjunction withmore » the KMCM allows extending the KMC simulations to the longer evolution times. The results of simulations seem to agree with available experimental data for Fe-Cu alloys within statistical errors of simulations and the scatter of experimental results. Comparison of simulation results with experiments for some multicomponent Fe-Cu-based alloys allows making certain conclusions about the influence of alloying elements in these alloys on the precipitation kinetics at different stages of evolution.« less

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

Kinetic Monte Carlo simulation on influence of vacancy on hydrogen diffusivity in tungsten

NASA Astrophysics Data System (ADS)

Oda, Takuji; Zhu, Deqiong; Watanabe, Yoshiyuki

2015-12-01

Kinetic Mote Carlo (KMC) simulations are performed to quantify the influence of trap in hydrogen diffusivity in tungsten. As a typical trap, mono-vacancy is considered in the simulation. Experimental results reported by Frauenfelder are nicely reproduced when hydrogen concentration and trap concentration expected in the experiment are employed in the simulation. The effective diffusivity of hydrogen is evidently decreased by traps even at high temperatures like 1300 K. These results suggest that only high-temperature experimental data, which are not significantly affected by traps, should be fitted to, in order to derive the true hydrogen diffusivity from experiments. Therefore, we recommend D = 1.58 ×10-7exp(- 0.25 eV / kT) m2 s-1 as the equation for hydrogen diffusion coefficient in tungsten, which was obtained by fitting only to experimental data at 1500-2400 K by Heinola and Ahlgren, rather than the most cited equation D = 4.1 ×10-7exp(- 0.39 eV / kT) m2 s-1, which was obtained by fitting to all experimental data at 1100-2400 K including some data that should be affected by traps.

Arsenic in groundwater of the Kolkata Municipal Corporation (KMC), India: Critical review and modes of mitigation.

PubMed

Chakraborti, Dipankar; Das, Bhaskar; Rahman, Mohammad Mahmudur; Nayak, Bishwajit; Pal, Arup; Sengupta, Mrinal K; Ahamed, Sad; Hossain, Md Amir; Chowdhury, Uttam K; Biswas, Bhajan Kumar; Saha, Khitish Chandra; Dutta, R N

2017-08-01

This study represents the first comprehensive report of groundwater arsenic contamination status in the Kolkata Municipal Corporation (KMC). During the past 23 years, 4210 groundwater samples were analysed from all 141 wards in the KMC: 14.2% and 5.2% samples had arsenic >10 μg/l and >50 μg/l, respectively, representing 77 and 37 wards. The study shows that the number of arsenic contaminated samples (and wards) in the southern part of the KMC exceeds that of other parts of the city. The daily intake of arsenic from drinking water was estimated as 0.95 μg per kg bw and the cancer risk was estimated as 1425/10 6 . Analyses of biological samples (hair, nail and urine) showed elevated concentrations of arsenic indicating the presence of subclinical arsenic poisoning, predicting an enhanced lifetime cancer risk for the population in southern part of the KMC. In the KMC, groundwater is not a sustainable source of freshwater due to arsenic, high iron, hardness and total dissolved solids. Its continued use is impelled by the lack of an adequate infrastructure to treat and supply surface water and in some wards the unaccounted for water (UFW) is even >45% incurred during distribution. The rare imposition of a water tax makes the water supply systems unsustainable and fosters indifference to water conservation. To mitigate the arsenic problem, continuous groundwater monitoring for pollutants, a treated surface water supply with strict policy implications, rainwater harvesting in the urban areas and introduction of water taxes seem to be long-term visible solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of conventional phototherapy and phototherapy along with Kangaroo mother care on cutaneous bilirubin of neonates with physiological jaundice.

PubMed

Goudarzvand, Laleh; Dabirian, Akram; Nourian, Manijeh; Jafarimanesh, Hadi; Ranjbaran, Mehdi

2017-11-27

One of the adjuvant and desirable therapies is skin contact between mother and baby or Kangaroo mother care (KMC) that is a cheap, accessible, relaxing, noninvasive and easy method. This study aimed to compare the effect of conventional phototherapy method and phototherapy along with KMC on cutaneous bilirubin in neonates with physiological jaundice. In this randomized clinical trial, all infants with physiological jaundice who referred for phototherapy to Mofid Hospital of Shahid Beheshti University of Medical Sciences, Tehran, Iran were selected by convenience sampling based on inclusion criteria and were randomly assigned into two groups of conventional phototherapy (n = 35) and phototherapy along with KMC (n = 35). The results showed that there was a significant difference in the average volume of skin bilirubin before treatment with cutaneous bilirubin every 24 h after treatment (p < .001). This significant difference was present in both intervention and control groups. Although the average volume of skin bilirubin every 24 h after treatment was lower in the intervention group than the control group, this difference was not statistically significant (p = .236). Mean duration of hospitalization of infants in the intervention group was significantly lower than the control group (2.09 versus 3.03 d, p < .001). Although KMC along with phototherapy has a favorable effect on the reduction of cutaneous bilirubin in neonates with physiological jaundice, there are not significant differences in routine care. This may need to do KMC for a longer time (more than 1 h) which must be surveyed in the future studies. KMC was effective in reduction of the duration of hospitalization in jaundiced infants.

Multiscale atomistic simulation of metal-oxygen surface interactions: Methodological development, theoretical investigation, and correlation with experiment

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

Yang, Judith C.

The purpose of this grant is to develop the multi-scale theoretical methods to describe the nanoscale oxidation of metal thin films, as the PI (Yang) extensive previous experience in the experimental elucidation of the initial stages of Cu oxidation by primarily in situ transmission electron microscopy methods. Through the use and development of computational tools at varying length (and time) scales, from atomistic quantum mechanical calculation, force field mesoscale simulations, to large scale Kinetic Monte Carlo (KMC) modeling, the fundamental underpinings of the initial stages of Cu oxidation have been elucidated. The development of computational modeling tools allows for acceleratedmore » materials discovery. The theoretical tools developed from this program impact a wide range of technologies that depend on surface reactions, including corrosion, catalysis, and nanomaterials fabrication.« less

Atomistic Computer Simulations of Water Interactions and Dissolution of Inorganic Glasses

DOE PAGES

Du, Jincheng; Rimsza, Jessica

2017-09-01

Computational simulations at the atomistic level play an increasing important role in understanding the structures, behaviors, and the structure-property relationships of glass and amorphous materials. In this paper, we reviewed atomistic simulation methods ranging from first principles calculations and ab initio molecular dynamics (AIMD), to classical molecular dynamics (MD) and meso-scale kinetic Monte Carlo (KMC) simulations and their applications to glass-water interactions and glass dissolutions. Particularly, the use of these simulation methods in understanding the reaction mechanisms of water with oxide glasses, water-glass interfaces, hydrated porous silica gels formation, the structure and properties of multicomponent glasses, and microstructure evolution aremore » reviewed. Here, the advantages and disadvantageous of these methods are discussed and the current challenges and future direction of atomistic simulations in glass dissolution are presented.« less

Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not?

PubMed

Kim, Jihan; Rodgers, Jocelyn M; Athènes, Manuel; Smit, Berend

2011-10-11

In the waste recycling Monte Carlo (WRMC) algorithm, (1) multiple trial states may be simultaneously generated and utilized during Monte Carlo moves to improve the statistical accuracy of the simulations, suggesting that such an algorithm may be well posed for implementation in parallel on graphics processing units (GPUs). In this paper, we implement two waste recycling Monte Carlo algorithms in CUDA (Compute Unified Device Architecture) using uniformly distributed random trial states and trial states based on displacement random-walk steps, and we test the methods on a methane-zeolite MFI framework system to evaluate their utility. We discuss the specific implementation details of the waste recycling GPU algorithm and compare the methods to other parallel algorithms optimized for the framework system. We analyze the relationship between the statistical accuracy of our simulations and the CUDA block size to determine the efficient allocation of the GPU hardware resources. We make comparisons between the GPU and the serial CPU Monte Carlo implementations to assess speedup over conventional microprocessors. Finally, we apply our optimized GPU algorithms to the important problem of determining free energy landscapes, in this case for molecular motion through the zeolite LTA.

Taking kangaroo mother care forward in South Africa: The role of district clinical specialist teams.

PubMed

Feucht, Ute Dagmar; van Rooyen, Elise; Skhosana, Rinah; Bergh, Anne-Marie

2015-11-20

The global agenda for improved neonatal care includes the scale-up of kangaroo mother care (KMC) services. The establishment of district clinical specialist teams (DCSTs) in South Africa (SA) provides an excellent opportunity to enhance neonatal care at district level and ensure translation of policies, including the requirement for KMC implementation, into everyday clinical practice. Tshwane District in Gauteng Province, SA, has been experiencing an increasing strain on obstetric and neonatal services at central, tertiary and regional hospitals in recent years as a result of growing population numbers and rapid up-referral of patients, with limited down-referral of low-risk patients to district-level services. We describe a successful multidisciplinary quality improvement initiative under the leadership of the Tshwane DCST, in conjunction with experienced local KMC implementers, aimed at expanding the district's KMC services. The project subsequently served as a platform for improvement of other areas of neonatal care by means of a systematic approach.

Off-diagonal expansion quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Off-diagonal expansion quantum Monte Carlo.

PubMed

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Kangaroo mother care diminishes pain from heel lance in very preterm neonates: a crossover trial.

PubMed

Johnston, C Celeste; Filion, Francoise; Campbell-Yeo, Marsha; Goulet, Celine; Bell, Linda; McNaughton, Kathryn; Byron, Jasmine; Aita, Marilyn; Finley, G Allen; Walker, Claire-Dominique

2008-04-24

Skin-to-skin contact, or kangaroo mother care (KMC) has been shown to be efficacious in diminishing pain response to heel lance in full term and moderately preterm neonates. The purpose of this study was to determine if KMC would also be efficacious in very preterm neonates. Preterm neonates (n = 61) between 28 0/7 and 31 6/7 weeks gestational age in three Level III NICU's in Canada comprised the sample. A single-blind randomized crossover design was employed. In the experimental condition, the infant was held in KMC for 15 minutes prior to and throughout heel lance procedure. In the control condition, the infant was in prone position swaddled in a blanket in the incubator. The primary outcome was the Premature Infant Pain Profile (PIPP), which is comprised of three facial actions, maximum heart rate, minimum oxygen saturation levels from baseline in 30-second blocks from heel lance. The secondary outcome was time to recover, defined as heart rate return to baseline. Continuous video, heart rate and oxygen saturation monitoring were recorded with event markers during the procedure and were subsequently analyzed. Repeated measures analysis-of-variance was employed to generate results. PIPP scores at 90 seconds post lance were significantly lower in the KMC condition (8.871 (95%CI 7.852-9.889) versus 10.677 (95%CI 9.563-11.792) p < .001) and non-significant mean differences ranging from 1.2 to1.8. favoring KMC condition at 30, 60 and 120 seconds. Time to recovery was significantly shorter, by a minute(123 seconds (95%CI 103-142) versus 193 seconds (95%CI 158-227). Facial actions were highly significantly lower across all points in time reaching a two-fold difference by 120 seconds post-lance and heart rate was significantly lower across the first 90 seconds in the KMC condition. Very preterm neonates appear to have endogenous mechanisms elicited through skin-to-skin maternal contact that decrease pain response, but not as powerfully as in older preterm neonates. The shorter recovery time in KMC is clinically important in helping maintain homeostasis. (Current Controlled Trials) ISRCTN63551708.

Molecular dynamics simulations of the diffusion and coalescence of helium in tungsten

NASA Astrophysics Data System (ADS)

Zhou, Y. L.; Wang, J.; Hou, Q.; Deng, A. H.

2014-03-01

Molecular dynamics (MD) simulations are performed on the diffusion and coalescence of helium in tungsten. A new method for determining the effective capture radii (ECRs) and the dissociation energies of helium-related defects is proposed in this work. It is observed that the ECR of an interstitial helium atom trapping helium interstitials (denoted as He-Hen, n = 1-3) decreases with increasing temperature, except for He-He2 at T < 400 K. The traditional view that the ECR is approximately equal to the lattice constant, which has been widely used in kinetic Monte Carlo (KMC) and rate theory (RT) models, is only valid in some cases. However, the ECR between an interstitial helium atom and a substitutional helium atom (denoted as He-HeV) always approximates the third nearest-neighbor tetrahedral positions of the HeV. The diffusion coefficients Dn for helium clusters are also investigated. He2 migrates more quickly than a single He atom does at T < 400 K, whereas the diffusion path of He2 changes at higher temperatures. Another counterintuitive observation is that D5 > D3 > D4 at T < 500 K, which can be attributed to the disordered structure of He5. The Arrhenius relation describes the diffusion of Hen well in the temperature range from 300 K to 550 K, whereas the diffusion is not a standard thermally activated process at higher temperatures. Taken together, these results help elucidate the initial stage of helium bubble formation in tungsten as well as the requirements of long-term evolution methods such as KMC or RT models.

Effect of Förster-mediated triplet-polaron quenching and triplet-triplet annihilation on the efficiency roll-off of organic light-emitting diodes

NASA Astrophysics Data System (ADS)

van Eersel, H.; Bobbert, P. A.; Janssen, R. A. J.; Coehoorn, R.

2016-04-01

We report the results of a systematic study of the interplay of triplet-polaron quenching (TPQ) and triplet-triplet annihilation (TTA) on the efficiency roll-off of organic light-emitting diodes (OLEDs) with increasing current density. First, we focus on OLEDs based on the green phosphorescent emitter tris[2-phenylpyridine]iridium(III) (Ir(ppy)3) and the red phosphorescent dye platinum octaethylporphyrin. It is found that the experimental data can be reproduced using kinetic Monte Carlo (kMC) simulations within which TPQ and TTA are due to a nearest-neighbor (NN) interaction, or due to a more long-range Förster-type process. Furthermore, we find a subtle interplay between TPQ and TTA: decreasing the contribution of one process can increase the contribution of the other process, so that the roll-off is not significantly reduced. Furthermore, we find that just analyzing the shape of the roll-off is insufficient for determining the relative role of TPQ and TTA. Subsequently, we investigate the wider validity of this picture using kMC simulations for idealized but realistic symmetric OLEDs, with an emissive layer containing a small concentration of phosphorescent dye molecules in a matrix material. Whereas for NN-interactions the roll-off can be reduced when the dye molecules act as shallow hole and electron traps, we find that such an approach becomes counterproductive for long-range TTA and TPQ. Developing well-founded OLED design rules will thus require that more quantitative information is available on the rate and detailed mechanism of the TPQ and TTA processes.

Utilizing Energy Transfer in Binary and Ternary Bulk Heterojunction Organic Solar Cells.

PubMed

Feron, Krishna; Cave, James M; Thameel, Mahir N; O'Sullivan, Connor; Kroon, Renee; Andersson, Mats R; Zhou, Xiaojing; Fell, Christopher J; Belcher, Warwick J; Walker, Alison B; Dastoor, Paul C

2016-08-17

Energy transfer has been identified as an important process in ternary organic solar cells. Here, we develop kinetic Monte Carlo (KMC) models to assess the impact of energy transfer in ternary and binary bulk heterojunction systems. We used fluorescence and absorption spectroscopy to determine the energy disorder and Förster radii for poly(3-hexylthiophene-2,5-diyl), [6,6]-phenyl-C61-butyric acid methyl ester, 4-bis[4-(N,N-diisobutylamino)-2,6-dihydroxyphenyl]squaraine (DIBSq), and poly(2,5-thiophene-alt-4,9-bis(2-hexyldecyl)-4,9-dihydrodithieno[3,2-c:3',2'-h][1,5]naphthyridine-5,10-dione). Heterogeneous energy transfer is found to be crucial in the exciton dissociation process of both binary and ternary organic semiconductor systems. Circumstances favoring energy transfer across interfaces allow relaxation of the electronic energy level requirements, meaning that a cascade structure is not required for efficient ternary organic solar cells. We explain how energy transfer can be exploited to eliminate additional energy losses in ternary bulk heterojunction solar cells, thus increasing their open-circuit voltage without loss in short-circuit current. In particular, we show that it is important that the DIBSq is located at the electron donor-acceptor interface; otherwise charge carriers will be trapped in the DIBSq domain or excitons in the DIBSq domains will not be able to dissociate efficiently at an interface. KMC modeling shows that only small amounts of DIBSq (<5% by weight) are needed to achieve substantial performance improvements due to long-range energy transfer.

Review of admission of MBBS students at KMC.

PubMed

Dixit, H; Maharjan, S

2003-01-01

This is an account regarding the intake of the 7th batch of MBBS students at Kathmandu Medical College (KMC) for the academic session 2003-2004. A total of 257 admission forms had been issued to Nepali students. Of these, 252 admission forms were filled up and were submitted to KMC together with the completed questionnaire by the Nepali students. Seven students (approximately 2.7%) did not attend interview. After the interview, out of the 245 interviewed students, the names of only 50 were brought out in the 1st list for admission. The paper presents the system for admission of MBBS students and has made recommendations for future action.

Design of a breathing mattress based on the respiratory movement of kangaroo mother care for the development of neonates.

PubMed

Schets, M W M; Chen, W; Bambang Oetomo, S

2015-01-01

Kangaroo mother care (KMC) benefits the development of neonates. This paper focuses on the design and implementing the extension of KMC for infants at Neonatal Intensive Care Units (NICU). A breathing mattress is proposed to comfort infants and stimulate them to breathe regularly by mimicking the movement of the parent's chest during KMC. The incubator mattress simulates the breathing of the parent's chest with embedded electronics and pneumatic technology for mattress motion actuating systems. The stakeholders, including the child, parents and NICU staff, were directly involved during the concept development, prototyping and evaluation.

Final Report: Technical Assistance for the Kearsarge Metallurgical Corporation Superfund Site, Conway, New Hampshire, EPA Region 1

EPA Pesticide Factsheets

This report reviews and provides recommendations for a long-term groundwater monitoring network for the Kearsarge Metallurgical Corporation Superfund site (KMC site). The KMC site is a former foundry and metal fabrication facility in Conway, New Hampshire.

When alternative female Kangaroo care is provided by other immediate postpartum mothers, it reduces postprocedural pain in preterm babies more than swaddling.

PubMed

Murmu, Jitendranath; Venkatnarayan, Kannan; Thapar, Rajeev Kumar; Shaw, Subhash Chandra; Dalal, Shamsher Singh

2017-03-01

Research on alternative female Kangaroo care (KC) has been hampered by high maternal refusal rates. We assessed the efficacy of Kangaroo mother care (KMC), alternative KC provided by other postpartum mothers and swaddling for postprocedural pain relief in preterm babies. The study was carried out in a tertiary armed forces hospital, where mothers did not have support from other female relatives and other postpartum mothers agreed to act as alternative female KC providers. We exposed 51 stable preterm neonates, with a gestational age of 30-36 weeks, to KMC, alternative female KC and swaddling for 30 minutes before heel lancing. The outcome measures included the Preterm Infant Pain Profile (PIPP) scores at 30 seconds and the time taken for the heart rate to return to baseline. The mean PIPP scores were lower with KMC (10.59) and alternative female KC (11.24) than swaddling (12.96) and heart rate normalisation took 111, 117 and 149 seconds respectively. The p values were <0.001 for individual groups and outcomes. KMC fared better than alternative female KC for both pain (p = 0.045) and heart rate (p = 0.013). Providing KMC and alternative female KC before heel lancing resulted in better pain relief than swaddling. ©2016 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Multiscale Monte Carlo equilibration: Pure Yang-Mills theory

DOE PAGES

Endres, Michael G.; Brower, Richard C.; Orginos, Kostas; ...

2015-12-29

In this study, we present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.

Modeling hexavalent chromium removal in a Bacillus sp. fixed-film bioreactor.

PubMed

Nkhalambayausi-Chirwa, Evans M; Wang, Yi-Tin

2004-09-30

A one-dimensional diffusion-reaction model was developed to simulate Cr(VI) reduction in a Bacillus sp. pure culture biofilm reactor with glucose as a sole supplied carbon and energy source. Substrate utilization and Cr(VI) reduction in the biofilm was best represented by a system of (second-order) partial differential equations (PDEs). The PDE system was solved by the (fourth-order) Runge-Kutta method adjusted for mass transport resistance using the (second-order) Crank-Nicholson and Backward Euler finite difference methods. A heuristic procedure (genetic search algorithm) was used to find global optimum values of Cr(VI) reduction and substrate utilization rate kinetic parameters. The fixed-film bioreactor system yielded higher values of the maximum specific Cr(VI) reduction rate coefficient and Cr(VI) reduction capacity (kmc = 0.062 1/h, and Rc = 0.13 mg/mg, respectively) than previously determined in batch reactors (kmc = 0.022 1/h and Rc = 0.012 mg/mg). The model predicted effluent Cr(VI) concentration well with 98.9% confidence (sigmay2 = 2.37 mg2/L2, N = 119) and effluent glucose with 96.4 % confidence (sigmay(w)2 = 5402 mg2/L2, N = 121, w = 100) over a wide range of Cr(VI) loadings (10-498 mg Cr(VI)/L/d). Copyright 2004 Wiley Periodicals, Inc.

Contractor Incentives for Success in Implementing Performance-Based Logistics: A Progress Report

DTIC Science & Technology

2010-04-30

amount of risk; this, however, gives the contractor more latitude in determining and applying its methods ( KMC /OPI, 2010). The general consensus...Klevan, P. (2008, October 27). Navy success with PBL. Presentation at the DoD Maintenance Symposium. KMC /OPI. (2010, January 19). Acquisition

Collision of Physics and Software in the Monte Carlo Application Toolkit (MCATK)

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

Sweezy, Jeremy Ed

2016-01-21

The topic is presented in a series of slides organized as follows: MCATK overview, development strategy, available algorithms, problem modeling (sources, geometry, data, tallies), parallelism, miscellaneous tools/features, example MCATK application, recent areas of research, and summary and future work. MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library with continuous energy neutron and photon transport. Designed to build specialized applications and to provide new functionality in existing general-purpose Monte Carlo codes like MCNP, it reads ACE formatted nuclear data generated by NJOY. The motivation behind MCATK was to reduce costs. MCATK physics involves continuous energy neutron & gammamore » transport with multi-temperature treatment, static eigenvalue (k eff and α) algorithms, time-dependent algorithm, and fission chain algorithms. MCATK geometry includes mesh geometries and solid body geometries. MCATK provides verified, unit-test Monte Carlo components, flexibility in Monte Carlo application development, and numerous tools such as geometry and cross section plotters.« less

Evaluation of an analytic linear Boltzmann transport equation solver for high-density inhomogeneities

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

Lloyd, S. A. M.; Ansbacher, W.; Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia V8W 3P6

2013-01-15

Purpose: Acuros external beam (Acuros XB) is a novel dose calculation algorithm implemented through the ECLIPSE treatment planning system. The algorithm finds a deterministic solution to the linear Boltzmann transport equation, the same equation commonly solved stochastically by Monte Carlo methods. This work is an evaluation of Acuros XB, by comparison with Monte Carlo, for dose calculation applications involving high-density materials. Existing non-Monte Carlo clinical dose calculation algorithms, such as the analytic anisotropic algorithm (AAA), do not accurately model dose perturbations due to increased electron scatter within high-density volumes. Methods: Acuros XB, AAA, and EGSnrc based Monte Carlo are usedmore » to calculate dose distributions from 18 MV and 6 MV photon beams delivered to a cubic water phantom containing a rectangular high density (4.0-8.0 g/cm{sup 3}) volume at its center. The algorithms are also used to recalculate a clinical prostate treatment plan involving a unilateral hip prosthesis, originally evaluated using AAA. These results are compared graphically and numerically using gamma-index analysis. Radio-chromic film measurements are presented to augment Monte Carlo and Acuros XB dose perturbation data. Results: Using a 2% and 1 mm gamma-analysis, between 91.3% and 96.8% of Acuros XB dose voxels containing greater than 50% the normalized dose were in agreement with Monte Carlo data for virtual phantoms involving 18 MV and 6 MV photons, stainless steel and titanium alloy implants and for on-axis and oblique field delivery. A similar gamma-analysis of AAA against Monte Carlo data showed between 80.8% and 87.3% agreement. Comparing Acuros XB and AAA evaluations of a clinical prostate patient plan involving a unilateral hip prosthesis, Acuros XB showed good overall agreement with Monte Carlo while AAA underestimated dose on the upstream medial surface of the prosthesis due to electron scatter from the high-density material. Film measurements support the dose perturbations demonstrated by Monte Carlo and Acuros XB data. Conclusions: Acuros XB is shown to perform as well as Monte Carlo methods and better than existing clinical algorithms for dose calculations involving high-density volumes.« less

SU-E-T-188: Film Dosimetry Verification of Monte Carlo Generated Electron Treatment Plans

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

Enright, S; Asprinio, A; Lu, L

2014-06-01

Purpose: The purpose of this study was to compare dose distributions from film measurements to Monte Carlo generated electron treatment plans. Irradiation with electrons offers the advantages of dose uniformity in the target volume and of minimizing the dose to deeper healthy tissue. Using the Monte Carlo algorithm will improve dose accuracy in regions with heterogeneities and irregular surfaces. Methods: Dose distributions from GafChromic{sup ™} EBT3 films were compared to dose distributions from the Electron Monte Carlo algorithm in the Eclipse{sup ™} radiotherapy treatment planning system. These measurements were obtained for 6MeV, 9MeV and 12MeV electrons at two depths. Allmore » phantoms studied were imported into Eclipse by CT scan. A 1 cm thick solid water template with holes for bonelike and lung-like plugs was used. Different configurations were used with the different plugs inserted into the holes. Configurations with solid-water plugs stacked on top of one another were also used to create an irregular surface. Results: The dose distributions measured from the film agreed with those from the Electron Monte Carlo treatment plan. Accuracy of Electron Monte Carlo algorithm was also compared to that of Pencil Beam. Dose distributions from Monte Carlo had much higher pass rates than distributions from Pencil Beam when compared to the film. The pass rate for Monte Carlo was in the 80%–99% range, where the pass rate for Pencil Beam was as low as 10.76%. Conclusion: The dose distribution from Monte Carlo agreed with the measured dose from the film. When compared to the Pencil Beam algorithm, pass rates for Monte Carlo were much higher. Monte Carlo should be used over Pencil Beam for regions with heterogeneities and irregular surfaces.« less

Morphological evolution of nanocrystal metal-on-insulator films grown by pulsed laser deposition

NASA Astrophysics Data System (ADS)

Warrender, Jeffrey Michael

Pulsed laser deposition (PLD) film growth differs from conventional thermal deposition in two essential ways: the depositing species arrive in short bursts of 10--100mus, and with 10--100 eV of kinetic energy. This thesis presents a comprehensive study of the influence of these separate characteristics of the PLD flux on film growth, with the goal of understanding what mechanisms and processes govern PLD morphology evolution. A theoretical description of the early stages of pulsed, non-energetic growth is presented, with the principal results being a discussion of the dimensionless parameters that must be controlled to achieve data collapse for a variety of conditions; the identification of at least four different island size distribution shapes, which characterize the growth mode being observed; and a rate equation formalism for pulsed deposition that gives excellent agreement with results from kinetic Monte Carlo (KMC) simulations. The model system of metal-on-insulator film growth has been studied extensively for thermal deposition, and is known to exhibit a characteristic morphological progression beginning with isolated three-dimensional islands and ending with a percolating, continuous film that conducts electrically. Two separate experimental investigations are reported for PLD growth of this system. In the fast, the details of the PLD pulse are held constant and the pulse frequency is varied; this amounts to varying the time-averaged deposition flux. Non-energetic KMC simulations, which take into account only the pulsed nature of the flux, predicted that, for the case where surface diffusion is very fast compared to the pulse frequency and the deposition rate, percolation thickness would scale with pulse frequency with an exponent of -0.34. Experiments performed at 93°C and 135°C gave scaling exponents of -0.31 and -0.34 respectively, in good agreement with the KMC prediction. The experiments also showed good data collapse when maintaining a constant value B/f, where B is the coalescence "efficiency" and f is the pulse frequency. A separate experimental investigation was performed to compare PLD with thermal deposition under otherwise identical background and substrate conditions; this amounts to studying the effect of varying the average deposition flux. For this case, non-energetic simulations predict that PLD deposits, by virtue of having smaller and more densely spaced islands, would reach percolation with relatively less deposition. (Abstract shortened by UMI.)

Renyi entanglement entropy of interacting fermions calculated using the continuous-time quantum Monte Carlo method.

PubMed

Wang, Lei; Troyer, Matthias

2014-09-12

We present a new algorithm for calculating the Renyi entanglement entropy of interacting fermions using the continuous-time quantum Monte Carlo method. The algorithm only samples the interaction correction of the entanglement entropy, which by design ensures the efficient calculation of weakly interacting systems. Combined with Monte Carlo reweighting, the algorithm also performs well for systems with strong interactions. We demonstrate the potential of this method by studying the quantum entanglement signatures of the charge-density-wave transition of interacting fermions on a square lattice.

Latin American Clinical Epidemiology Network Series - Paper 4: Economic evaluation of Kangaroo Mother Care: cost utility analysis of results from a randomized controlled trial conducted in Bogotá.

PubMed

Ruiz, Juan Gabriel; Charpak, Nathalie; Castillo, Mario; Bernal, Astrid; Ríos, John; Trujillo, Tammy; Córdoba, María Adelaida

2017-06-01

Although kangaroo mother care (KMC) has been shown to be safe and effective in randomized controlled trials (RCTs), there are no published complete economic evaluations including the three components of the full intervention. A cost utility analysis performed on the results of an RCT conducted in Bogotá, Colombia between 1993 and 1996. Hospital and ambulatory costs were estimated by microcosting in a sample of preterm infants from a University Hospital in Bogotá in 2011 and at a KMC clinic in the same period. Utility scores were assigned by experts by means of (1) direct ordering and scoring discrete health states and (2) constructing a multi-attribute utility function. Ninety-five percent confidence intervals (CIs) for the incremental cost-utility ratios (ICURs) were computed by the Fiellers theorem method. One-way sensitivity analysis on price estimates for valuing costs was performed. ICUR at 1 year of corrected age was $ -1,546 per extra quality-adjusted life year gained using the KMC method (95% CI $ -7,963 to $ 4,910). In Bogotá, the use of KMC is dominant: more effective and cost-saving. Although results from an economic analysis should not be extrapolated to different systems and communities, this dominant result suggests that KMC could be cost-effective in similar low and middle income countries settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparative Effect of Massage Therapy versus Kangaroo Mother Care on Body Weight and Length of Hospital Stay in Low Birth Weight Preterm Infants.

PubMed

Rangey, Priya Singh; Sheth, Megha

2014-01-01

Background. Massage therapy (MT) and kangaroo mother care (KMC) are both effective in increasing the weight and reducing length of hospital stay in low birth weight preterm infants but they have not been compared. Aim. Comparison of effectiveness of MT and KMC on body weight and length of hospital stay in low birth weight preterm (LBWPT) infants. Method. 30 LBWPT infants using convenience sampling from Neonatal Intensive Care Unit, V.S. hospital, were randomly divided into 2 equal groups. Group 1 received MT and Group 2 received KMC for 15 minutes, thrice daily for 5 days. Medically stable babies with gestational age < 37 weeks and birth weight < 2500 g were included. Those on ventilators and with congenital, orthopedic, or genetic abnormality were excluded. Outcome measures, body weight and length of hospital stay, were taken before intervention day 1 and after intervention day 5. Level of significance was 5%. Result. Data was analyzed using SPSS16. Both MT and KMC were found to be effective in improving body weight (P = 0.001, P = 0.001). Both were found to be equally effective for improving body weight (P = 0.328) and reducing length of hospital stay (P = 0.868). Conclusion. MT and KMC were found to be equally effective in improving body weight and reducing length of hospital stay. Limitation. Long term follow-up was not taken.

Multi-scale modeling of irradiation effects in spallation neutron source materials

NASA Astrophysics Data System (ADS)

Yoshiie, T.; Ito, T.; Iwase, H.; Kaneko, Y.; Kawai, M.; Kishida, I.; Kunieda, S.; Sato, K.; Shimakawa, S.; Shimizu, F.; Hashimoto, S.; Hashimoto, N.; Fukahori, T.; Watanabe, Y.; Xu, Q.; Ishino, S.

2011-07-01

Changes in mechanical property of Ni under irradiation by 3 GeV protons were estimated by multi-scale modeling. The code consisted of four parts. The first part was based on the Particle and Heavy-Ion Transport code System (PHITS) code for nuclear reactions, and modeled the interactions between high energy protons and nuclei in the target. The second part covered atomic collisions by particles without nuclear reactions. Because the energy of the particles was high, subcascade analysis was employed. The direct formation of clusters and the number of mobile defects were estimated using molecular dynamics (MD) and kinetic Monte-Carlo (kMC) methods in each subcascade. The third part considered damage structural evolutions estimated by reaction kinetic analysis. The fourth part involved the estimation of mechanical property change using three-dimensional discrete dislocation dynamics (DDD). Using the above four part code, stress-strain curves for high energy proton irradiated Ni were obtained.

Effect of deposition rate and NNN interactions on adatoms mobility in epitaxial growth

NASA Astrophysics Data System (ADS)

Hamouda, Ajmi B. H.; Mahjoub, B.; Blel, S.

2017-07-01

This paper provides a detailed analysis of the surface diffusion problem during epitaxial step-flow growth using a simple theoretical model for the diffusion equation of adatoms concentration. Within this framework, an analytical expression for the adatom mobility as a function of the deposition rate and the Next-Nearest-Neighbor (NNN) interactions is derived and compared with the effective mobility computed from kinetic Monte Carlo (kMC) simulations. As far as the 'small' step velocity or relatively weak deposition rate commonly used for copper growth is concerned, an excellent quantitative agreement with the theoretical prediction is found. The effective adatoms mobility is shown to exhibit an exponential decrease with NNN interactions strength and increases in roughly linear behavior versus deposition rate F. The effective step stiffness and the adatoms mobility are also shown to be closely related to the concentration of kinks.

Carbon diffusion in bulk hcp zirconium: A multi-scale approach

NASA Astrophysics Data System (ADS)

Xu, Y.; Roques, J.; Domain, C.; Simoni, E.

2016-05-01

In the framework of the geological repository of the used fuel claddings of pressurized water reactor, carbon behavior in bulk zirconium is studied by periodic Density Functional Theory calculations. The C interstitial sites were investigated and it was found that there are two possible carbon interstitial sites: a distorted basal tetragonal site and an octahedral site. There are four types of possible atomic jumps between them. After calculating the migration energies, the attempt frequencies and the jump probabilities for each possible migration path, kinetic Monte Carlo (KMC) simulations were performed to simulate carbon diffusion at the macroscopic scale. The results show that carbon diffusion in pure Zr bulk is extremely limited at the storage temperature (50 °C). Since there are defects in Zr bulk, in a second step, the effect of atomic vacancy was studied and it was proved that vacancies cannot increase carbon diffusion.

Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

NASA Astrophysics Data System (ADS)

Warrier, M.; Bhardwaj, U.; Bukkuru, S.

2016-10-01

Modification of materials in nuclear reactors due to neutron irradiation is a multiscale problem. These neutrons pass through materials creating several energetic primary knock-on atoms (PKA) which cause localized collision cascades creating damage tracks, defects (interstitials and vacancies) and defect clusters depending on the energy of the PKA. These defects diffuse and recombine throughout the whole duration of operation of the reactor, thereby changing the micro-structure of the material and its properties. It is therefore desirable to develop predictive computational tools to simulate the micro-structural changes of irradiated materials. In this paper we describe how statistical averages of the collision cascades from thousands of MD simulations are used to provide inputs to Kinetic Monte Carlo (KMC) simulations which can handle larger sizes, more defects and longer time durations. Use of unsupervised learning and graph optimization in handling and analyzing large scale MD data will be highlighted.

RECKONER: read error corrector based on KMC.

PubMed

Dlugosz, Maciej; Deorowicz, Sebastian

2017-04-01

Presence of sequencing errors in data produced by next-generation sequencers affects quality of downstream analyzes. Accuracy of them can be improved by performing error correction of sequencing reads. We introduce a new correction algorithm capable of processing eukaryotic close to 500 Mbp-genome-size, high error-rated data using less than 4 GB of RAM in about 35 min on 16-core computer. Program is freely available at http://sun.aei.polsl.pl/REFRESH/reckoner . sebastian.deorowicz@polsl.pl. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

IMPACT OF PARTIAL KANGAROO MOTHER CARE ON GROWTH RATES AND DURATION OF HOSPITAL STAY OF LOW BIRTH WEIGHT INFANTS AT THE KENYATTA NATIONAL HOSPITAL, NAIROBI.

PubMed

Mwendwa, A C; Musoke, R N; Wamalwa, D C

2012-02-01

To determine the effect of partial Kangaroo Mother Care (KMC) on growth rates and duration of hospital stay of Low Birth Weight (LBW) infants. Unblinded, randomised clinical controlled trial. Kenyatta National Hospital, Nairobi, Kenya. Over a nine month period, consecutive recruitment of eligible LBW infants weighing 1000 g to 1750 g was done until a sample of 166 infants was reached. Kangaroo mother care was practised over an eight hour period per day for the intervention group while the controls remained in incubators or cots. Weight, head circumference, and mid upper arm circumference were monitored for all infants till discharge at 1800 g. Of the 166 infants recruited 157 were followed up to discharge. Baseline characteristics were similar for the two groups except for mother's age, with the KMC group mothers having a mean age of 26.5 years while the control group mothers had a mean age of 24 years, (p = 0.04). The KMC group had significantly higher growth rates as shown by the higher mean weight gain of 22.5 g/kg/day compared with 16.7g/kg/day for the control group, (p < 0.001); higher mean head circumference gain of 0.91 cm/week compared with 0.54 cm/week for the control group, (p < 0.001) and higher mean mid upper arm circumference gain of 0.76 cm/week compared with 0.48 cm/week for the control group, (p = 0.002). Although overall duration of stay was similar between study arms, when infants were stratified into those above or below 1500 g KMC infants' duration of stay was significantly shorter than those in regular care. Using logistic regression, KMCwas the strongest predictor formeanweight, meanhead circumference and mean MUAC gain while mother's age (older) was the strongest predictor for mean duration of stay with KMC being an independent predictor of duration of stay. Low birth weight infants in this cohort achieved rates of growth within the recommended intrauterine growth but babies managed using partial KMC grew faster and were thus discharged earlier than those on standard of care. Since partial KMC was beneficial, it should be fully implemented for all eligible infants.

Event-chain Monte Carlo algorithms for three- and many-particle interactions

NASA Astrophysics Data System (ADS)

Harland, J.; Michel, M.; Kampmann, T. A.; Kierfeld, J.

2017-02-01

We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. The examples demonstrate that the generalization to many-particle interactions broadens the applicability of event-chain algorithms considerably.

A study on the coagulation of polycyclic aromatic hydrocarbon clusters to determine their collision efficiency

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

Raj, Abhijeet; Sander, Markus; Janardhanan, Vinod

2010-03-15

This paper presents a theoretical study on the physical interaction between polycyclic aromatic hydrocarbons (PAHs) and their clusters of different sizes in laminar premixed flames. Two models are employed for this study: a detailed PAH growth model, referred to as the kinetic Monte Carlo - aromatic site (KMC-ARS) model [Raj et al., Combust. Flame 156 (2009) 896-913]; and a multivariate PAH population balance model, referred to as the PAH - primary particle (PAH-PP) model. Both the models are solved by kinetic Monte Carlo methods. PAH mass spectra are generated using the PAH-PP model, and compared to the experimentally observed spectramore » for a laminar premixed ethylene flame. The position of the maxima of PAH dimers in the spectra and their concentrations are found to depend strongly on the collision efficiency of PAH coagulation. The variation in the collision efficiency with various flame and PAH parameters is studied to determine the factors on which it may depend. A correlation for the collision efficiency is proposed by comparing the computed and the observed spectra for an ethylene flame. With this correlation, a good agreement between the computed and the observed spectra for a number of laminar premixed ethylene flames is found. (author)« less

Effect of Förster-mediated triplet-polaron quenching and triplet-triplet annihilation on the efficiency roll-off of organic light-emitting diodes

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

Eersel, H. van; Bobbert, P. A.; Janssen, R. A. J.

2016-04-28

We report the results of a systematic study of the interplay of triplet-polaron quenching (TPQ) and triplet-triplet annihilation (TTA) on the efficiency roll-off of organic light-emitting diodes (OLEDs) with increasing current density. First, we focus on OLEDs based on the green phosphorescent emitter tris[2-phenylpyridine]iridium(III) (Ir(ppy){sub 3}) and the red phosphorescent dye platinum octaethylporphyrin. It is found that the experimental data can be reproduced using kinetic Monte Carlo (kMC) simulations within which TPQ and TTA are due to a nearest-neighbor (NN) interaction, or due to a more long-range Förster-type process. Furthermore, we find a subtle interplay between TPQ and TTA: decreasingmore » the contribution of one process can increase the contribution of the other process, so that the roll-off is not significantly reduced. Furthermore, we find that just analyzing the shape of the roll-off is insufficient for determining the relative role of TPQ and TTA. Subsequently, we investigate the wider validity of this picture using kMC simulations for idealized but realistic symmetric OLEDs, with an emissive layer containing a small concentration of phosphorescent dye molecules in a matrix material. Whereas for NN-interactions the roll-off can be reduced when the dye molecules act as shallow hole and electron traps, we find that such an approach becomes counterproductive for long-range TTA and TPQ. Developing well-founded OLED design rules will thus require that more quantitative information is available on the rate and detailed mechanism of the TPQ and TTA processes.« less

Effect of the size of nanoparticles on their dissolution within metal-glass nanocomposites under sustained irradiation

NASA Astrophysics Data System (ADS)

Vu, T. H. Y.; Ramjauny, Y.; Rizza, G.; Hayoun, M.

2016-01-01

We investigate the dissolution law of metallic nanoparticles (NPs) under sustained irradiation. The system is composed of isolated spherical gold NPs (4-100 nm) embedded in an amorphous silica host matrix. Samples are irradiated at room temperature in the nuclear stopping power regime with 4 MeV Au ions for fluences up to 8 × 1016 cm-2. Experimentally, the dependence of the dissolution kinetics on the irradiation fluence is linear for large NPs (45-100 nm) and exponential for small NPs (4-25 nm). A lattice-based kinetic Monte Carlo (KMC) code, which includes atomic diffusion and ballistic displacement events, is used to simulate the dynamical competition between irradiation effects and thermal healing. The KMC simulations allow for a qualitative description of the NP dissolution in two main stages, in good agreement with the experiment. Moreover, the perfect correlation obtained between the evolution of the simulated flux of ejected atoms and the dissolution rate in two stages implies that there exists an effect of the size of NPs on their dissolution and a critical size for the transition between the two stages. The Frost-Russell model providing an analytical solution for the dissolution rate, accounts well for the first dissolution stage but fails in reproducing the data for the second stage. An improved model obtained by including a size-dependent recoil generation rate permits fully describing the dissolution for any NP size. This proves, in particular, that the size effect on the generation rate is the principal reason for the existence of two regimes. Finally, our results also demonstrate that it is justified to use a unidirectional approximation to describe the dissolution of the NP under irradiation, because the solute concentration is particularly low in metal-glass nanocomposites.

Study of Ag induced bimetallic (Au-Ag) nanowires on silicon (5 5 12) surfaces: Experiment and theoretical aspects

NASA Astrophysics Data System (ADS)

Bhukta, Anjan; Bagarti, Trilochan; Guha, Puspendu; Ravulapalli, Sathyavathi; Satpati, Biswarup; Rakshit, Bipul; Maiti, Paramita; Parlapalli, Venkata Satyam

2017-10-01

The reconstructed vicinal (high index) silicon surfaces, such as, Si (5 5 12) composes row-like structures that can be used as templates for growing aligned nanowires. By using a sub-monolayers of Ag, prior to Au deposition on reconstructed Si (5 512) surface, intermixing of Au and Ag, enhancement of aspect ratio of bimetallic Au-Ag nanowires with tunable morphology is reported. This is attributed to a combined effect of pre-grown Ag strips as nucleation centers for incoming Au ad-atoms and anisotropic Au-Ag intermixing. To achieve optimum conditions for the growth of larger aspect ratio Au-Ag nanostructures, the growth kinetics have been studied by varying growth and annealing temperatures. At ≈400 °C, the Ag diffused into silicon substrate and the inter-diffusion found to inhibit the formation of Au-Ag bimetallic nanostructures. Controlled experiments under ultra-high vacuum condition in a molecular beam epitaxy system and in-situ scanning tunneling microscopy measurements along with ex-situ scanning transmission and secondary electron microscopy measurements have been carried out to understand the bimetallic nanostructure growth. Kinetic Monte Carlo (KMC) simulations based on kinematics of ad-atoms on an anisotropic template with a solid on solid model in which the relative ratios of binding energies (that are obtained from the Density Functional Theory) have been used and the KMC simulations results agree with the experimental observations. Advantage of having bimetallic structures as effective substrates for Surface enhanced Raman spectroscopy application is demonstrated by detecting Rhodamine 6 G (R6G) molecule at the concentration of 10-7M.

Scalable Domain Decomposed Monte Carlo Particle Transport

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

O'Brien, Matthew Joseph

2013-12-05

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.

Kangaroo care by fathers and mothers: comparison of physiological and stress responses in preterm infants.

PubMed

Srinath, B K; Shah, J; Kumar, P; Shah, P S

2016-05-01

To compare physiological and biochemical responses in stable preterm neonates and their parents following kangaroo mother care (KMC) and kangaroo father care (KFC). We conducted a prospective cross-over design study of stable preterm neonates of <35 weeks gestation in a tertiary Neonatal Unit in Toronto. All neonates received KMC and KFC for 1 h on consecutive days in a random order. Heart rate, temperature, blood pressure, oxygen saturation and salivary cortisol in infants before and after kangaroo care and heart rate, temperature and salivary cortisol in parents before and after kangaroo care were measured. Pairwise comparisons of changes in these measures were analyzed. Twenty-six sets of neonates and their parents were studied for physiological parameters, of which 19 had adequate samples for salivary cortisol assessment. The infants had a mean birth weight of 1096 g (s.d.=217) and a mean postmenstrual age at study of 32 weeks (s.d.=2). There were no significant differences in the changes in mean heart rate (P=0.51), temperature (P=0.37), oxygen saturation (P=0.50), systolic blood pressure (P=0.32), mean blood pressure (0.10) and salivary cortisol (P=0.50) before and after KMC or KFC in the neonates. The changes in mean heart rate (P=0.62), temperature (P=0.28) and salivary cortisol (P=0.59) before and after kangaroo care were similar between mothers and fathers. No significant differences in physiological and stress responses were identified following KMC or KFC in preterm neonates. KFC may be as safe and as effective as KMC.

Implementation of Monte Carlo Dose calculation for CyberKnife treatment planning

NASA Astrophysics Data System (ADS)

Ma, C.-M.; Li, J. S.; Deng, J.; Fan, J.

2008-02-01

Accurate dose calculation is essential to advanced stereotactic radiosurgery (SRS) and stereotactic radiotherapy (SRT) especially for treatment planning involving heterogeneous patient anatomy. This paper describes the implementation of a fast Monte Carlo dose calculation algorithm in SRS/SRT treatment planning for the CyberKnife® SRS/SRT system. A superposition Monte Carlo algorithm is developed for this application. Photon mean free paths and interaction types for different materials and energies as well as the tracks of secondary electrons are pre-simulated using the MCSIM system. Photon interaction forcing and splitting are applied to the source photons in the patient calculation and the pre-simulated electron tracks are repeated with proper corrections based on the tissue density and electron stopping powers. Electron energy is deposited along the tracks and accumulated in the simulation geometry. Scattered and bremsstrahlung photons are transported, after applying the Russian roulette technique, in the same way as the primary photons. Dose calculations are compared with full Monte Carlo simulations performed using EGS4/MCSIM and the CyberKnife treatment planning system (TPS) for lung, head & neck and liver treatments. Comparisons with full Monte Carlo simulations show excellent agreement (within 0.5%). More than 10% differences in the target dose are found between Monte Carlo simulations and the CyberKnife TPS for SRS/SRT lung treatment while negligible differences are shown in head and neck and liver for the cases investigated. The calculation time using our superposition Monte Carlo algorithm is reduced up to 62 times (46 times on average for 10 typical clinical cases) compared to full Monte Carlo simulations. SRS/SRT dose distributions calculated by simple dose algorithms may be significantly overestimated for small lung target volumes, which can be improved by accurate Monte Carlo dose calculations.

Hybrid dose calculation: a dose calculation algorithm for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Donzelli, Mattia; Bräuer-Krisch, Elke; Oelfke, Uwe; Wilkens, Jan J.; Bartzsch, Stefan

2018-02-01

Microbeam radiation therapy (MRT) is still a preclinical approach in radiation oncology that uses planar micrometre wide beamlets with extremely high peak doses, separated by a few hundred micrometre wide low dose regions. Abundant preclinical evidence demonstrates that MRT spares normal tissue more effectively than conventional radiation therapy, at equivalent tumour control. In order to launch first clinical trials, accurate and efficient dose calculation methods are an inevitable prerequisite. In this work a hybrid dose calculation approach is presented that is based on a combination of Monte Carlo and kernel based dose calculation. In various examples the performance of the algorithm is compared to purely Monte Carlo and purely kernel based dose calculations. The accuracy of the developed algorithm is comparable to conventional pure Monte Carlo calculations. In particular for inhomogeneous materials the hybrid dose calculation algorithm out-performs purely convolution based dose calculation approaches. It is demonstrated that the hybrid algorithm can efficiently calculate even complicated pencil beam and cross firing beam geometries. The required calculation times are substantially lower than for pure Monte Carlo calculations.

Event-chain algorithm for the Heisenberg model: Evidence for z≃1 dynamic scaling.

PubMed

Nishikawa, Yoshihiko; Michel, Manon; Krauth, Werner; Hukushima, Koji

2015-12-01

We apply the event-chain Monte Carlo algorithm to the three-dimensional ferromagnetic Heisenberg model. The algorithm is rejection-free and also realizes an irreversible Markov chain that satisfies global balance. The autocorrelation functions of the magnetic susceptibility and the energy indicate a dynamical critical exponent z≈1 at the critical temperature, while that of the magnetization does not measure the performance of the algorithm. We show that the event-chain Monte Carlo algorithm substantially reduces the dynamical critical exponent from the conventional value of z≃2.

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

A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation spectroscopy.

PubMed

Guan, Fada; Johns, Jesse M; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W; Braby, Leslie A

2015-06-01

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

Mosaicing of airborne LiDAR bathymetry strips based on Monte Carlo matching

NASA Astrophysics Data System (ADS)

Yang, Fanlin; Su, Dianpeng; Zhang, Kai; Ma, Yue; Wang, Mingwei; Yang, Anxiu

2017-09-01

This study proposes a new methodology for mosaicing airborne light detection and ranging (LiDAR) bathymetry (ALB) data based on Monte Carlo matching. Various errors occur in ALB data due to imperfect system integration and other interference factors. To account for these errors, a Monte Carlo matching algorithm based on a nonlinear least-squares adjustment model is proposed. First, the raw data of strip overlap areas were filtered according to their relative drift of depths. Second, a Monte Carlo model and nonlinear least-squares adjustment model were combined to obtain seven transformation parameters. Then, the multibeam bathymetric data were used to correct the initial strip during strip mosaicing. Finally, to evaluate the proposed method, the experimental results were compared with the results of the Iterative Closest Points (ICP) and three-dimensional Normal Distributions Transform (3D-NDT) algorithms. The results demonstrate that the algorithm proposed in this study is more robust and effective. When the quality of the raw data is poor, the Monte Carlo matching algorithm can still achieve centimeter-level accuracy for overlapping areas, which meets the accuracy of bathymetry required by IHO Standards for Hydrographic Surveys Special Publication No.44.

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.

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.

The Impact of Monte Carlo Dose Calculations on Intensity-Modulated Radiation Therapy

NASA Astrophysics Data System (ADS)

Siebers, J. V.; Keall, P. J.; Mohan, R.

The effect of dose calculation accuracy for IMRT was studied by comparing different dose calculation algorithms. A head and neck IMRT plan was optimized using a superposition dose calculation algorithm. Dose was re-computed for the optimized plan using both Monte Carlo and pencil beam dose calculation algorithms to generate patient and phantom dose distributions. Tumor control probabilities (TCP) and normal tissue complication probabilities (NTCP) were computed to estimate the plan outcome. For the treatment plan studied, Monte Carlo best reproduces phantom dose measurements, the TCP was slightly lower than the superposition and pencil beam results, and the NTCP values differed little.

Arecoline decreases interleukin-6 production and induces apoptosis and cell cycle arrest in human basal cell carcinoma cells

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

Huang, Li-Wen; Hsieh, Bau-Shan; Cheng, Hsiao-Ling

2012-01-15

Arecoline, the most abundant areca alkaloid, has been reported to decrease interleukin-6 (IL-6) levels in epithelial cancer cells. Since IL-6 overexpression contributes to the tumorigenic potency of basal cell carcinoma (BCC), this study was designed to investigate whether arecoline altered IL-6 expression and its downstream regulation of apoptosis and the cell cycle in cultured BCC-1/KMC cells. BCC-1/KMC cells and a human keratinocyte cell line, HaCaT, were treated with arecoline at concentrations ranging from 10 to 100 μg/ml, then IL-6 production and expression of apoptosis- and cell cycle progress-related factors were examined. After 24 h exposure, arecoline inhibited BCC-1/KMC cell growthmore » and decreased IL-6 production in terms of mRNA expression and protein secretion, but had no effect on HaCaT cells. Analysis of DNA fragmentation and chromatin condensation showed that arecoline induced apoptosis of BCC-1/KMC cells in a dose-dependent manner, activated caspase-3, and decreased expression of the anti-apoptotic protein Bcl-2. In addition, arecoline induced progressive and sustained accumulation of BCC-1/KMC cells in G2/M phase as a result of reducing checkpoint Cdc2 activity by decreasing Cdc25C phosphatase levels and increasing p53 levels. Furthermore, subcutaneous injection of arecoline led to decreased BCC-1/KMC tumor growth in BALB/c mice by inducing apoptosis. This study demonstrates that arecoline has potential for preventing BCC tumorigenesis by reducing levels of the tumor cell survival factor IL-6, increasing levels of the tumor suppressor factor p53, and eliciting cell cycle arrest, followed by apoptosis. Highlights: ► Arecoline has potential to prevent against basal cell carcinoma tumorigenesis. ► It has more effectiveness on BCC as compared with a human keratinocyte cell line. ► Mechanisms involved including reducing tumor cells’ survival factor IL-6, ► Decreasing Cdc25C phosphatase, enhancing tumor suppressor factor p53, ► Eliciting G2/M phase arrest, followed by apoptosis.« less

Promoter Methylation of PTEN Is a Significant Prognostic Factor in Melanoma Survival.

PubMed

Roh, Mi Ryung; Gupta, Sameer; Park, Kyu-Hyun; Chung, Kee Yang; Lauss, Martin; Flaherty, Keith T; Jönsson, Göran; Rha, Sun Young; Tsao, Hensin

2016-05-01

Structural compromise of the tumor suppressor gene, phosphatase and tensin homolog (PTEN), occurs in 10% of melanoma specimens, and loss of PTEN expression through DNA methylation of the PTEN promoter region has also been reported in a number of other malignancies. However, the role of PTEN promoter methylation in melanoma is not well understood. We thus sought to elucidate the prevalence of PTEN promoter methylation in melanoma specimens, its relationship to clinical features, and its impact on the outcome of patients with melanoma. PTEN promoter methylation data were acquired from an archived primary Korean melanoma cohort (KMC) of 158 patients and, for validation, 234 patients from The Cancer Genome Atlas melanoma (TCGA-MEL) cohort. Hierarchical clustering was performed to identify PTEN "high methylated" and "low methylated" samples. Subsequently, differences in clinical features and outcomes based on PTEN promoter methylation status were then analyzed using SPSS and R. In the KMC, all tumors were acquired from primary tumors and 65.7% (n = 105) were acral or mucosal by site, whereas in the TCGA-MEL cohort, 90.5% of the tumors were from regional lymph node and distant metastatic lesions. Overall, 17.7% and 45.7% of the specimens harbored BRAF mutations in the KMC and TCGA-MEL cohort, respectively. Neuroblastoma RAS viral oncogene homolog was mutated in 12.2% and 26.9% of the tumors in the KMC and TCGA-MEL cohort, respectively. In the KMC, 31 cases (19.6%) were included in the high methylated group versus 142 cases (60.7%) in the TCGA-MEL cohort (P < 0.001). Multivariate Cox-regression analysis revealed promoter methylation of PTEN to be an independent negative prognostic factor for survival in both the KMC (hazard ratio 3.76, 95% confidence interval = 1.24-11.12, P = 0.017) and TCGA-MEL cohort (HR 1.88, 95% confidence interval = 1.13-3.12, P = 0.015). Our results indicate that PTEN promoter methylation is an independent predictor for impaired survival in patients with melanoma. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A Christoffel function weighted least squares algorithm for collocation approximations

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

Narayan, Akil; Jakeman, John D.; Zhou, Tao

Here, we propose, theoretically investigate, and numerically validate an algorithm for the Monte Carlo solution of least-squares polynomial approximation problems in a collocation framework. Our investigation is motivated by applications in the collocation approximation of parametric functions, which frequently entails construction of surrogates via orthogonal polynomials. A standard Monte Carlo approach would draw samples according to the density defining the orthogonal polynomial family. Our proposed algorithm instead samples with respect to the (weighted) pluripotential equilibrium measure of the domain, and subsequently solves a weighted least-squares problem, with weights given by evaluations of the Christoffel function. We present theoretical analysis tomore » motivate the algorithm, and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest.« less

A Christoffel function weighted least squares algorithm for collocation approximations

DOE PAGES

Narayan, Akil; Jakeman, John D.; Zhou, Tao

2016-11-28

Here, we propose, theoretically investigate, and numerically validate an algorithm for the Monte Carlo solution of least-squares polynomial approximation problems in a collocation framework. Our investigation is motivated by applications in the collocation approximation of parametric functions, which frequently entails construction of surrogates via orthogonal polynomials. A standard Monte Carlo approach would draw samples according to the density defining the orthogonal polynomial family. Our proposed algorithm instead samples with respect to the (weighted) pluripotential equilibrium measure of the domain, and subsequently solves a weighted least-squares problem, with weights given by evaluations of the Christoffel function. We present theoretical analysis tomore » motivate the algorithm, and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest.« less

The First Space-Related Study of a Kombucha Multimicrobial Cellulose-Forming Community: Preparatory Laboratory Experiments.

PubMed

Podolich, O; Zaets, I; Kukharenko, O; Orlovska, I; Reva, O; Khirunenko, L; Sosnin, M; Haidak, A; Shpylova, S; Rohutskyy, I; Kharina, A; Skoryk, М; Kremenskoy, M; Klymchuk, D; Demets, R; de Vera, J-P; Kozyrovska, N

2017-06-01

Biofilm-forming microbial communities are known as the most robust assemblages that can survive in harsh environments. Biofilm-associated microorganisms display greatly increased resistance to physical and chemical adverse conditions, and they are expected to be the first form of life on Earth or anywhere else. Biological molecules synthesized by biofilm -protected microbiomes may serve as markers of the nucleoprotein life. We offer a new experimental model, a kombucha multimicrobial culture (KMC), to assess a structural integrity of a widespread microbial polymer - cellulose - as a biosignature of bacteria-producers for the multipurpose international project "BIOlogical and Mars Experiment (BIOMEX)", which aims to study the vitality of pro- and eukaryotic organisms and the stability of organic biomolecules in contact with minerals to analyze the detectability of life markers in the context of a planetary background. In this study, we aimed to substantiate the detectability of mineralized cellulose with spectroscopy and to study the KMC macrocolony phenotype stability under adverse conditions (UV, excess of inorganics etc.). Cellulose matrix of the KMC macrocolony has been mineralized in the mineral-water interface under assistance of KMC-members. Effect of bioleached ions on the cellulose matrix has been visible, and the FT-IR spectrum proved changes in cellulose structure. However, the specific cellulose band vibration, confirming the presence of β(1,4)-linkages between monomers, has not been quenched by secondary minerals formed on the surface of pellicle. The cellulose-based KMC macrocolony phenotype was in a dependence on extracellular matrix components (ionome, viriome, extracellular membrane vesicles), which provided its integrity and rigidness in a certain extent under impact of stressful factors.

The First Space-Related Study of a Kombucha Multimicrobial Cellulose-Forming Community: Preparatory Laboratory Experiments

NASA Astrophysics Data System (ADS)

Podolich, O.; Zaets, I.; Kukharenko, O.; Orlovska, I.; Reva, O.; Khirunenko, L.; Sosnin, M.; Haidak, A.; Shpylova, S.; Rohutskyy, I.; Kharina, A.; Skoryk, M.; Kremenskoy, M.; Klymchuk, D.; Demets, R.; de Vera, J.-P.; Kozyrovska, N.

2017-06-01

Biofilm-forming microbial communities are known as the most robust assemblages that can survive in harsh environments. Biofilm-associated microorganisms display greatly increased resistance to physical and chemical adverse conditions, and they are expected to be the first form of life on Earth or anywhere else. Biological molecules synthesized by biofilm -protected microbiomes may serve as markers of the nucleoprotein life. We offer a new experimental model, a kombucha multimicrobial culture (KMC), to assess a structural integrity of a widespread microbial polymer - cellulose - as a biosignature of bacteria-producers for the multipurpose international project "BIOlogical and Mars Experiment (BIOMEX)", which aims to study the vitality of pro- and eukaryotic organisms and the stability of organic biomolecules in contact with minerals to analyze the detectability of life markers in the context of a planetary background. In this study, we aimed to substantiate the detectability of mineralized cellulose with spectroscopy and to study the KMC macrocolony phenotype stability under adverse conditions (UV, excess of inorganics etc.). Cellulose matrix of the KMC macrocolony has been mineralized in the mineral-water interface under assistance of KMC-members. Effect of bioleached ions on the cellulose matrix has been visible, and the FT-IR spectrum proved changes in cellulose structure. However, the specific cellulose band vibration, confirming the presence of β(1,4)-linkages between monomers, has not been quenched by secondary minerals formed on the surface of pellicle. The cellulose-based KMC macrocolony phenotype was in a dependence on extracellular matrix components (ionome, viriome, extracellular membrane vesicles), which provided its integrity and rigidness in a certain extent under impact of stressful factors.

Volume of milk obtained in relation to location and circumstances of expression in mothers of very low birth weight infants.

PubMed

Acuña-Muga, Juliana; Ureta-Velasco, Noelia; de la Cruz-Bértolo, Javier; Ballesteros-López, Rosa; Sánchez-Martínez, Rocío; Miranda-Casabona, Eugenia; Miguel-Trigoso, Almudena; García-San José, Lidia; Pallás-Alonso, Carmen

2014-02-01

Given the importance of mother's milk for very low birth weight (VLBW) infants, it would be helpful to know which circumstances are most favorable for milk expression. This study aimed to estimate the volume of milk obtained by mothers of VLBW infants as a function of proximity to the infant and use of the kangaroo position during the actual expression. In this prospective cohort study, when the infant was stable and the mother had established a breastfeeding routine, she was given a notebook in which to record the location of expression and the amount of milk expressed for 10 consecutive days. Breast milk expression volumes were recorded and analyzed. Data were collected on 26 mother-VLBW infant dyads and 1642 milk expressions. The first early morning expressions (n = 276, 17%) were conducted at home. Thereafter, 743 (45%) expressions were conducted far from the infant, either in a different room within the hospital or at home, and 623 (38%) were performed in proximity to the infant (beside the incubator, during kangaroo mother care [KMC], after KMC, or during kangaroo father care). The mean milk volume was significantly higher when expression was conducted in proximity to the infant. When only milk expressions conducted in proximity to the infant were considered, volumes obtained during KMC (107.7 mL, 91.8-123.5) and after KMC (117.7 mL, 99.0-136.5) were significantly higher than those obtained beside the incubator (96.9 mL, 79.9-113.9), respectively, P = .0030 and P = .0024. Milk expression conducted in proximity to the infant, particularly during and immediately after KMC, is associated with higher milk volume.

Intermittent kangaroo mother care: a NICU protocol.

PubMed

Davanzo, Riccardo; Brovedani, Pierpaolo; Travan, Laura; Kennedy, Jacqueline; Crocetta, Anna; Sanesi, Cecilia; Strajn, Tamara; De Cunto, Angela

2013-08-01

The practice of kangaroo mother care (KMC) is steadily increasing in high-tech settings due to its proven benefits for both infants and parents. In spite of that, clear guidelines about how to implement this method of care are lacking, and as a consequence, some restrictions are applied in many neonatal intensive care units (NICUs), preventing its practice. Based on recommendations from the Expert Group of the International Network on Kangaroo Mother Care, we developed a hospital protocol in the neonatal unit of the Institute for Maternal and Child Health in Trieste, Italy, a level 3 unit, aimed to facilitate and promote KMC implementation in high-tech settings. Our guideline is therefore proposed, based both on current scientific literature and on practical considerations and experience. Future adjustments and improvements would be considered based on increasing clinical KMC use and further knowledge.

Monte Carlo evaluation of Acuros XB dose calculation Algorithm for intensity modulated radiation therapy of nasopharyngeal carcinoma

NASA Astrophysics Data System (ADS)

Yeh, Peter C. Y.; Lee, C. C.; Chao, T. C.; Tung, C. J.

2017-11-01

Intensity-modulated radiation therapy is an effective treatment modality for the nasopharyngeal carcinoma. One important aspect of this cancer treatment is the need to have an accurate dose algorithm dealing with the complex air/bone/tissue interface in the head-neck region to achieve the cure without radiation-induced toxicities. The Acuros XB algorithm explicitly solves the linear Boltzmann transport equation in voxelized volumes to account for the tissue heterogeneities such as lungs, bone, air, and soft tissues in the treatment field receiving radiotherapy. With the single beam setup in phantoms, this algorithm has already been demonstrated to achieve the comparable accuracy with Monte Carlo simulations. In the present study, five nasopharyngeal carcinoma patients treated with the intensity-modulated radiation therapy were examined for their dose distributions calculated using the Acuros XB in the planning target volume and the organ-at-risk. Corresponding results of Monte Carlo simulations were computed from the electronic portal image data and the BEAMnrc/DOSXYZnrc code. Analysis of dose distributions in terms of the clinical indices indicated that the Acuros XB was in comparable accuracy with Monte Carlo simulations and better than the anisotropic analytical algorithm for dose calculations in real patients.

Automatic mesh adaptivity for hybrid Monte Carlo/deterministic neutronics modeling of difficult shielding problems

DOE PAGES

Ibrahim, Ahmad M.; Wilson, Paul P.H.; Sawan, Mohamed E.; ...

2015-06-30

The CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques dramatically increase the efficiency of neutronics modeling, but their use in the accurate design analysis of very large and geometrically complex nuclear systems has been limited by the large number of processors and memory requirements for their preliminary deterministic calculations and final Monte Carlo calculation. Three mesh adaptivity algorithms were developed to reduce the memory requirements of CADIS and FW-CADIS without sacrificing their efficiency improvement. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as muchmore » geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility. Using these algorithms resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation and, additionally, increased the efficiency of the Monte Carlo simulation by a factor of at least 3.4. The three algorithms enabled this difficult calculation to be accurately solved using an FW-CADIS simulation on a regular computer cluster, eliminating the need for a world-class super computer.« less

Carbon diffusion paths and segregation at high-angle tilt grain boundaries in α-Fe studied by using a kinetic activation-relation technique

NASA Astrophysics Data System (ADS)

Restrepo, Oscar A.; Mousseau, Normand; Trochet, Mickaël; El-Mellouhi, Fedwa; Bouhali, Othmane; Becquart, Charlotte S.

2018-02-01

Carbon diffusion and segregation in iron is fundamental to steel production but is also associated with corrosion. Using the kinetic activation-relaxation technique (k-ART), a kinetic Monte Carlo (KMC) algorithm with an on-the-fly catalog that allows to obtain diffusion properties over large time scales taking into account long-range elastic effects coupled with an EAM force field, we study the motion of a carbon impurity in four Fe systems with high-angle grain boundaries (GB), focusing on the impact of these extended defects on the long-time diffusion of C. Short and long-time stability of the various GBs is first analyzed, which allows us to conclude that the Σ 3 (1 1 1 ) θ =109 .53∘<110 > GB is unstable, with Fe migration barriers of ˜0.1 eV or less, and C acts as a pinning center. Focusing on three stable GBs, in all cases, these extended defects trap C in energy states lower than found in the crystal. Yet, contrary to general understanding, we show, through simulations extending to 0.1 s, that even tough C diffusion takes place predominantly in the GB, it is not necessarily faster than in the bulk and can even be slower by one to two orders of magnitude depending on the GB type. Analysis of the energy landscape provided by k-ART also shows that the free cavity volume around the impurity is not a strong predictor of diffusion barrier height. Overall, results show rather complex diffusion kinetics intimately dependent on the local environment.

Monte Carlo tests of the ELIPGRID-PC algorithm

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

Davidson, J.R.

1995-04-01

The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID computer code of Singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM{reg_sign} PC. However, no known independent validation of the ELIPGRID algorithm exists. This document describes a Monte Carlo simulation-based validation of a modified version of the ELIPGRID-PC code. The modified ELIPGRID-PC code is shown to match Monte Carlo-calculated hot-spot detection probabilities to within {plus_minus}0.5% for 319 out of 320 test cases. The one exception, a very thin elliptical hot spot located within a rectangularmore » sampling grid, differed from the Monte Carlo-calculated probability by about 1%. These results provide confidence in the ability of the modified ELIPGRID-PC code to accurately predict hot-spot detection probabilities within an acceptable range of error.« less

A Monte Carlo Approach for Adaptive Testing with Content Constraints

ERIC Educational Resources Information Center

Belov, Dmitry I.; Armstrong, Ronald D.; Weissman, Alexander

2008-01-01

This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the…

Teaching Markov Chain Monte Carlo: Revealing the Basic Ideas behind the Algorithm

ERIC Educational Resources Information Center

Stewart, Wayne; Stewart, Sepideh

2014-01-01

For many scientists, researchers and students Markov chain Monte Carlo (MCMC) simulation is an important and necessary tool to perform Bayesian analyses. The simulation is often presented as a mathematical algorithm and then translated into an appropriate computer program. However, this can result in overlooking the fundamental and deeper…

Finite element model updating using the shadow hybrid Monte Carlo technique

NASA Astrophysics Data System (ADS)

Boulkaibet, I.; Mthembu, L.; Marwala, T.; Friswell, M. I.; Adhikari, S.

2015-02-01

Recent research in the field of finite element model updating (FEM) advocates the adoption of Bayesian analysis techniques to dealing with the uncertainties associated with these models. However, Bayesian formulations require the evaluation of the Posterior Distribution Function which may not be available in analytical form. This is the case in FEM updating. In such cases sampling methods can provide good approximations of the Posterior distribution when implemented in the Bayesian context. Markov Chain Monte Carlo (MCMC) algorithms are the most popular sampling tools used to sample probability distributions. However, the efficiency of these algorithms is affected by the complexity of the systems (the size of the parameter space). The Hybrid Monte Carlo (HMC) offers a very important MCMC approach to dealing with higher-dimensional complex problems. The HMC uses the molecular dynamics (MD) steps as the global Monte Carlo (MC) moves to reach areas of high probability where the gradient of the log-density of the Posterior acts as a guide during the search process. However, the acceptance rate of HMC is sensitive to the system size as well as the time step used to evaluate the MD trajectory. To overcome this limitation we propose the use of the Shadow Hybrid Monte Carlo (SHMC) algorithm. The SHMC algorithm is a modified version of the Hybrid Monte Carlo (HMC) and designed to improve sampling for large-system sizes and time steps. This is done by sampling from a modified Hamiltonian function instead of the normal Hamiltonian function. In this paper, the efficiency and accuracy of the SHMC method is tested on the updating of two real structures; an unsymmetrical H-shaped beam structure and a GARTEUR SM-AG19 structure and is compared to the application of the HMC algorithm on the same structures.

Optimization of the Monte Carlo code for modeling of photon migration in tissue.

PubMed

Zołek, Norbert S; Liebert, Adam; Maniewski, Roman

2006-10-01

The Monte Carlo method is frequently used to simulate light transport in turbid media because of its simplicity and flexibility, allowing to analyze complicated geometrical structures. Monte Carlo simulations are, however, time consuming because of the necessity to track the paths of individual photons. The time consuming computation is mainly associated with the calculation of the logarithmic and trigonometric functions as well as the generation of pseudo-random numbers. In this paper, the Monte Carlo algorithm was developed and optimized, by approximation of the logarithmic and trigonometric functions. The approximations were based on polynomial and rational functions, and the errors of these approximations are less than 1% of the values of the original functions. The proposed algorithm was verified by simulations of the time-resolved reflectance at several source-detector separations. The results of the calculation using the approximated algorithm were compared with those of the Monte Carlo simulations obtained with an exact computation of the logarithm and trigonometric functions as well as with the solution of the diffusion equation. The errors of the moments of the simulated distributions of times of flight of photons (total number of photons, mean time of flight and variance) are less than 2% for a range of optical properties, typical of living tissues. The proposed approximated algorithm allows to speed up the Monte Carlo simulations by a factor of 4. The developed code can be used on parallel machines, allowing for further acceleration.

Effects of kangaroo mother care on maternal mood and interaction patterns between parents and their preterm, low birth weight infants: a systematic review.

PubMed

Athanasopoulou, Eirini; Fox, John R E

2014-01-01

The birth of a premature infant can have adverse effects on the mood of mothers and on the interaction patterns between parents and their preterm babies. The aim of the present systematic review was to examine whether the Kangaroo Mother Care (KMC) intervention can attenuate these adverse psychological effects of a premature birth by ameliorating negative maternal mood and/or promoting more positive interactions between preterm infants and their parents. The results showed that although findings of studies were inconclusive, there is some evidence to suggest that KMC can make a positive difference on these areas. Specifically, it was found that KMC can improve negative maternal mood (e.g., anxiety or depression) and promote more positive parent-child interactions. Limitations and directions for future research are discussed. © 2014 Michigan Association for Infant Mental Health.

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

Percentage depth dose evaluation in heterogeneous media using thermoluminescent dosimetry

PubMed Central

da Rosa, L.A.R.; Campos, L.T.; Alves, V.G.L.; Batista, D.V.S.; Facure, A.

2010-01-01

The purpose of this study is to investigate the influence of lung heterogeneity inside a soft tissue phantom on percentage depth dose (PDD). PDD curves were obtained experimentally using LiF:Mg,Ti (TLD‐100) thermoluminescent detectors and applying Eclipse treatment planning system algorithms Batho, modified Batho (M‐Batho or BMod), equivalent TAR (E‐TAR or EQTAR), and anisotropic analytical algorithm (AAA) for a 15 MV photon beam and field sizes of 1×1,2×2,5×5, and 10×10cm2. Monte Carlo simulations were performed using the DOSRZnrc user code of EGSnrc. The experimental results agree with Monte Carlo simulations for all irradiation field sizes. Comparisons with Monte Carlo calculations show that the AAA algorithm provides the best simulations of PDD curves for all field sizes investigated. However, even this algorithm cannot accurately predict PDD values in the lung for field sizes of 1×1 and 2×2cm2. An overdosage in the lung of about 40% and 20% is calculated by the AAA algorithm close to the interface soft tissue/lung for 1×1 and 2×2cm2 field sizes, respectively. It was demonstrated that differences of 100% between Monte Carlo results and the algorithms Batho, modified Batho, and equivalent TAR responses may exist inside the lung region for the 1×1cm2 field. PACS number: 87.55.kd

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

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

Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less

Origin of Multiple Peaks in the Potentiodynamic Oxidation of CO Adlayers on Pt and Ru-Modified Pt Electrodes

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

Wang, Hongsen; Abruña, Héctor D.

2015-05-21

The study of the electrooxidation mechanism of COad on Pt based catalysts is very important for designing more effective CO-tolerant electrocatalysts for fuel cells. We have studied the origin of multiple peaks in the cyclic voltammograms of CO stripping from polycrystalline Pt and Ru modified polycrystalline Pt (Pt/Ru) surfaces in both acidic and alkaline media by differential electrochemical mass spectrometry (DEMS), DFT calculations, and kinetic Monte Carlo (KMC) simulations. A new COad electrooxidation kinetic model on heterogeneous Pt and Pt/Ru catalysts is proposed to account for the multiple peaks experimentally observed. In this model, OH species prefer to adsorb atmore » low-coordination sites or Ru sites and, thus, suppress CO repopulation from high-coordination sites onto these sites. Therefore, COad oxidation occurs on different facets or regions, leading to multiplicity of CO stripping peaks. This work provides a new insight into the CO electrooxidation mechanism and kinetics on heterogeneous catalysts.« less

Microscopic modeling of confined crystal growth and dissolution.

PubMed

Høgberget, Jørgen; Røyne, Anja; Dysthe, Dag K; Jettestuen, Espen

2016-08-01

We extend the (1+1)-dimensional fluid solid-on-solid (SOS) model to include a confining flat surface opposite to the SOS surface subject to a constant load. This load is balanced by a repulsive surface-surface interaction given by an ansatz which agrees with known analytical solutions in the limit of two separated flat surfaces. Mechanical equilibrium is imposed at all times by repositioning the confining surface. By the use of kinetic Monte Carlo (KMC) we calculate how the equilibrium concentration (deposition rate) depends on the applied load, and find it to reproduce analytical thermodynamics independent of the parameters of the interaction ansatz. We also study the dependency between the surface roughness and the saturation level as we vary the surface tension, and expand on previous analyses of the asymmetry between growth and dissolution by parametrizing the linear growth rate constant for growth and dissolution separately. We find the presence of a confining surface to affect the speed of growth and dissolution equally.

Generalized adsorption isotherms for molecular and dissociative adsorption of a polar molecular species on two polar surface geometries: Perovskite (100) (Pm-3m) and fluorite (111) (Fm-3m)

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

Danielson, Thomas; Hin, Celine; Savara, Aditya

Lattice based kinetic Monte Carlo (KMC) simulations have been used to determine a functional form for the second order adsorption isotherms on two commonly investigated crystal surfaces: the (111) fluorite surface and the (100) perovskite surface which has the same geometric symmetry as the NaCl (100) surface. The functional form is generalized to be applicable to all values of the equilibrium constant by a shift along the pressure axis. Functions have been determined for estimating the pressure at which a desired coverage would be achieved and for estimating the coverage at a certain pressure. The generalized form has been calculatedmore » by investigating the surface adsorbate coverage across a range of thermodynamic equilibrium constants that span the range 10-26 to 1013. Finally, the equations have been shown to be general for any value of the adsorption equilibrium constant.« less

Simulation study of temperature-dependent diffusion behaviors of Ag/Ag(001) at low substrate temperature

NASA Astrophysics Data System (ADS)

Cai, Danyun; Mo, Yunjie; Feng, Xiaofang; He, Yingyou; Jiang, Shaoji

2017-06-01

In this study, a model based on the First Principles calculations and Kinetic Monte Carlo simulation were established to study the growth characteristic of Ag thin film at low substrate temperature. On the basis of the interaction between the adatom and nearest-neighbor atoms, some simplifications and assumptions were made to categorize the diffusion behaviors of Ag adatoms on Ag(001). Then the barriers of all possible diffusion behaviors were calculated using the Climbing Image Nudged Elastic Band method (CI-NEB). Based on the Arrhenius formula, the morphology variation, which is attributed to the surface diffusion behaviors during the growth, was simulated with a temperature-dependent KMC model. With this model, a non-monotonic relation between the surface roughness and the substrate temperature (decreasing from 300 K to 100 K) were discovered. The analysis of the temperature dependence on diffusion behaviors presents a theoretical explanation of diffusion mechanism for the non-monotonic variation of roughness at low substrate temperature.

Microscopic modeling of confined crystal growth and dissolution

NASA Astrophysics Data System (ADS)

Høgberget, Jørgen; Røyne, Anja; Dysthe, Dag K.; Jettestuen, Espen

2016-08-01

We extend the (1+1)-dimensional fluid solid-on-solid (SOS) model to include a confining flat surface opposite to the SOS surface subject to a constant load. This load is balanced by a repulsive surface-surface interaction given by an ansatz which agrees with known analytical solutions in the limit of two separated flat surfaces. Mechanical equilibrium is imposed at all times by repositioning the confining surface. By the use of kinetic Monte Carlo (KMC) we calculate how the equilibrium concentration (deposition rate) depends on the applied load, and find it to reproduce analytical thermodynamics independent of the parameters of the interaction ansatz. We also study the dependency between the surface roughness and the saturation level as we vary the surface tension, and expand on previous analyses of the asymmetry between growth and dissolution by parametrizing the linear growth rate constant for growth and dissolution separately. We find the presence of a confining surface to affect the speed of growth and dissolution equally.

BCA-kMC Hybrid Simulation for Hydrogen and Helium Implantation in Material under Plasma Irradiation

NASA Astrophysics Data System (ADS)

Kato, Shuichi; Ito, Atsushi; Sasao, Mamiko; Nakamura, Hiroaki; Wada, Motoi

2015-09-01

Ion implantation by plasma irradiation into materials achieves the very high concentration of impurity. The high concentration of impurity causes the deformation and the destruction of the material. This is the peculiar phenomena in the plasma-material interaction (PMI). The injection process of plasma particles are generally simulated by using the binary collision approximation (BCA) and the molecular dynamics (MD), while the diffusion of implanted atoms have been traditionally solved by the diffusion equation, in which the implanted atoms is replaced by the continuous concentration field. However, the diffusion equation has insufficient accuracy in the case of low concentration, and in the case of local high concentration such as the hydrogen blistering and the helium bubble. The above problem is overcome by kinetic Monte Carlo (kMC) which represents the diffusion of the implanted atoms as jumps on interstitial sites in a material. In this paper, we propose the new approach ``BCA-kMC hybrid simulation'' for the hydrogen and helium implantation under the plasma irradiation.

Slow relaxation of cascade-induced defects in Fe

DOE PAGES

Béland, Laurent Karim; Osetsky, Yuri N.; Stoller, Roger E.; ...

2015-02-17

On-the-fly kinetic Monte Carlo (KMC) simulations are performed to investigate slow relaxation of non-equilibrium systems. Point defects induced by 25 keV cascades in α -Fe are shown to lead to a characteristic time-evolution, described by the replenish and relax mechanism. Then, we produce an atomistically-based assessment of models proposed to explain the slow structural relaxation by focusing on the aggregation of 50 vacancies and 25 self-interstital atoms (SIA) in 10-lattice-parameter α-Fe boxes, two processes that are closely related to cascade annealing and exhibit similar time signature. Four atomistic effects explain the timescales involved in the evolution: defect concentration heterogeneities, concentration-enhancedmore » mobility, cluster-size dependent bond energies and defect-induced pressure. In conclusion, these findings suggest that the two main classes of models to explain slow structural relaxation, the Eyring model and the Gibbs model, both play a role to limit the rate of relaxation of these simple point-defect systems.« less

Generalized adsorption isotherms for molecular and dissociative adsorption of a polar molecular species on two polar surface geometries: Perovskite (100) (Pm-3m) and fluorite (111) (Fm-3m)

DOE PAGES

Danielson, Thomas; Hin, Celine; Savara, Aditya

2016-08-10

Lattice based kinetic Monte Carlo (KMC) simulations have been used to determine a functional form for the second order adsorption isotherms on two commonly investigated crystal surfaces: the (111) fluorite surface and the (100) perovskite surface which has the same geometric symmetry as the NaCl (100) surface. The functional form is generalized to be applicable to all values of the equilibrium constant by a shift along the pressure axis. Functions have been determined for estimating the pressure at which a desired coverage would be achieved and for estimating the coverage at a certain pressure. The generalized form has been calculatedmore » by investigating the surface adsorbate coverage across a range of thermodynamic equilibrium constants that span the range 10-26 to 1013. Finally, the equations have been shown to be general for any value of the adsorption equilibrium constant.« less

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

DOE PAGES

Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi; ...

2017-03-13

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less

Self-learning Monte Carlo method

DOE PAGES

Liu, Junwei; Qi, Yang; Meng, Zi Yang; ...

2017-01-04

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of a general and efficient update algorithm for large size systems close to the phase transition, for which local updates perform badly. In this Rapid Communication, we propose a general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. Lastly, we demonstrate the efficiency of SLMC in a spin model at the phasemore » transition point, achieving a 10–20 times speedup.« less

Random Numbers and Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Scherer, Philipp O. J.

Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.

Monte Carlo uncertainty analysis of dose estimates in radiochromic film dosimetry with single-channel and multichannel algorithms.

PubMed

Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen; González-López, Antonio

2018-03-01

To provide a multi-stage model to calculate uncertainty in radiochromic film dosimetry with Monte-Carlo techniques. This new approach is applied to single-channel and multichannel algorithms. Two lots of Gafchromic EBT3 are exposed in two different Varian linacs. They are read with an EPSON V800 flatbed scanner. The Monte-Carlo techniques in uncertainty analysis provide a numerical representation of the probability density functions of the output magnitudes. From this numerical representation, traditional parameters of uncertainty analysis as the standard deviations and bias are calculated. Moreover, these numerical representations are used to investigate the shape of the probability density functions of the output magnitudes. Also, another calibration film is read in four EPSON scanners (two V800 and two 10000XL) and the uncertainty analysis is carried out with the four images. The dose estimates of single-channel and multichannel algorithms show a Gaussian behavior and low bias. The multichannel algorithms lead to less uncertainty in the final dose estimates when the EPSON V800 is employed as reading device. In the case of the EPSON 10000XL, the single-channel algorithms provide less uncertainty in the dose estimates for doses higher than four Gy. A multi-stage model has been presented. With the aid of this model and the use of the Monte-Carlo techniques, the uncertainty of dose estimates for single-channel and multichannel algorithms are estimated. The application of the model together with Monte-Carlo techniques leads to a complete characterization of the uncertainties in radiochromic film dosimetry. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Experiences with Markov Chain Monte Carlo Convergence Assessment in Two Psychometric Examples

ERIC Educational Resources Information Center

Sinharay, Sandip

2004-01-01

There is an increasing use of Markov chain Monte Carlo (MCMC) algorithms for fitting statistical models in psychometrics, especially in situations where the traditional estimation techniques are very difficult to apply. One of the disadvantages of using an MCMC algorithm is that it is not straightforward to determine the convergence of the…

Large-Scale Meteorological Patterns Associated with Extreme Precipitation in the US Northeast

NASA Astrophysics Data System (ADS)

Agel, L. A.; Barlow, M. A.

2016-12-01

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. Tropopause height provides a compact representation of large-scale circulation patterns, as it is linked to mid-level circulation, low-level thermal contrasts and low-level diabatic heating. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into a larger context. Six tropopause patterns are identified on extreme days: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong upward motion during, and moisture transport preceding, extreme precipitation events.

Metis: A Pure Metropolis Markov Chain Monte Carlo Bayesian Inference Library

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

Bates, Cameron Russell; Mckigney, Edward Allen

The use of Bayesian inference in data analysis has become the standard for large scienti c experiments [1, 2]. The Monte Carlo Codes Group(XCP-3) at Los Alamos has developed a simple set of algorithms currently implemented in C++ and Python to easily perform at-prior Markov Chain Monte Carlo Bayesian inference with pure Metropolis sampling. These implementations are designed to be user friendly and extensible for customization based on speci c application requirements. This document describes the algorithmic choices made and presents two use cases.

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

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

Eisenbach, Markus; Li, Ying Wai

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage ofmore » avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.« less

Role of kangaroo mother care in growth and breast feeding rates in very low birth weight (VLBW) neonates: a systematic review.

PubMed

Sharma, Deepak; Farahbakhsh, Nazanin; Sharma, Sweta; Sharma, Pradeep; Sharma, Akash

2017-03-27

To evaluate the role of kangaroo mother care (KMC) on growth and breast feeding rates in very low birth weight (VLBW) neonates. A literature search was done to identify eligible studies using various electronic database searches including PubMed and EMBASE, various Web of Science including Scopus, Index Copernicus, African Index Medicus (AIM), Thomson Reuters (ESCI), Chemical Abstracts Service (CAS), SCIWIN (Scientific World Index), Google Scholar, Latin American and Caribbean Health Sciences Information System (LILACS), Index Medicus for the Eastern Mediterranean Region (IMEMR), Index Medicus for the South-East Asian Region (IMSEAR), and Western Pacific Region Index Medicus (WPRIM) and various clinical trial registries. Thirteen studies that evaluated the role of KMC in VLBW infants in improvement of growth outcome (weight/length/head circumference) or breast feeding rates as their primary or secondary outcome, were included in this systematic review. Seven studies evaluated both growth and breast feeding rates, four studies evaluated breast feeding rates and two studies evaluated growth outcome. All included studies except one either showed positive effect or no effect on growth and breast feeding rates. KMC has a positive effect on growth of the VLBW infants and also leads to increase in the breast-feeding rates. KMC should be an integral part of neonatal care and should be promoted as an essential newborn care component.

Effect of kangaroo mother care vs expressed breast milk administration on pain associated with removal of adhesive tape in very low birth weight neonates: a randomized controlled trial.

PubMed

Nanavati, Ruchi N; Balan, Rajiv; Kabra, Nandkishor S

2013-11-08

To compare the pain relief effect of Kangaroo Mother Care (KMC) and Expressed Breast Milk (EBM) on the pain associated with adhesive tape removal in very low birth weight (VLBW) neonates. Randomized Controlled Trial. Neonatal intensive care unit of a tertiary care teaching hospital. 15 VLBW neonates who needed adhesive tape removal for the first part and 50 VLBW neonates needing adhesive tape removal for the second part. In first stage of the study, we studied whether adhesive tape removal in VLBW neonates was painful. In the second stage, eligible VLBW neonates were randomised to compare the efficacy of KMC and EBM in reducing the pain during the procedure of adhesive tape removal. Premature Infant Pain Profile (PIPP) Score, heart rate, oxygen saturation. There was significant increase in pain associated with the removal of adhesive tape (Mean pre-procedure PIPP score 3.47 ± 0.74; post-procedure mean PIPP score 12.13 ± 2.59; P<0.0001). The post intervention mean PIPP pain score was not significantly different between the KMC and EBM groups (P= 0.62). Removal of adhesive tape is a painful procedure for VLBW neonates. There was no difference between KMC and EBM in relieving pain associated with adhesive tape removal.

‘Kangaroo mother care’ to prevent neonatal deaths due to preterm birth complications

PubMed Central

Lawn, Joy E; Mwansa-Kambafwile, Judith; Horta, Bernardo L; Barros, Fernando C; Cousens, Simon

2010-01-01

Background ‘Kangaroo mother care’ (KMC) includes thermal care through continuous skin-to-skin contact, support for exclusive breastfeeding or other appropriate feeding, and early recognition/response to illness. Whilst increasingly accepted in both high- and low-income countries, a Cochrane review (2003) did not find evidence of KMC’s mortality benefit, and did not report neonatal-specific data. Objectives The objectives of this study were to review the evidence, and estimate the effect of KMC on neonatal mortality due to complications of preterm birth. Methods We conducted systematic reviews. Standardized abstraction tables were used and study quality assessed by adapted GRADE methodology. Meta-analyses were undertaken. Results We identified 15 studies reporting mortality and/or morbidity outcomes including nine randomized controlled trials (RCTs) and six observational studies all from low- or middle-income settings. Except one, all were hospital-based and included only babies of birth-weight <2000 g (assumed preterm). The one community-based trial had missing birthweight data, as well as other limitations and was excluded. Neonatal-specific data were supplied by two authors. Meta-analysis of three RCTs commencing KMC in the first week of life showed a significant reduction in neonatal mortality [relative risk (RR) 0.49, 95% confidence interval (CI) 0.29–0.82] compared with standard care. A meta-analysis of three observational studies also suggested significant mortality benefit (RR 0.68, 95% CI 0.58–0.79). Five RCTs suggested significant reductions in serious morbidity for babies <2000 g (RR 0.34, 95% CI 0.17–0.65). Conclusion This is the first published meta-analysis showing that KMC substantially reduces neonatal mortality amongst preterm babies (birth weight <2000 g) in hospital, and is highly effective in reducing severe morbidity, particularly from infection. However, KMC remains unavailable at-scale in most low-income countries. PMID:20348117

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

DOE PAGES

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

2016-01-01

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

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

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

Exact and Monte carlo resampling procedures for the Wilcoxon-Mann-Whitney and Kruskal-Wallis tests.

PubMed

Berry, K J; Mielke, P W

2000-12-01

Exact and Monte Carlo resampling FORTRAN programs are described for the Wilcoxon-Mann-Whitney rank sum test and the Kruskal-Wallis one-way analysis of variance for ranks test. The program algorithms compensate for tied values and do not depend on asymptotic approximations for probability values, unlike most algorithms contained in PC-based statistical software packages.

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; Hurtado, John E.

2011-01-01

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Simulations of chemical vapor deposition diamond film growth using a kinetic Monte Carlo model and two-dimensional models of microwave plasma and hot filament chemical vapor deposition reactors

NASA Astrophysics Data System (ADS)

May, P. W.; Harvey, J. N.; Allan, N. L.; Richley, J. C.; Mankelevich, Yu. A.

2010-12-01

A one-dimensional kinetic Monte Carlo (KMC) model has been developed to simulate the chemical vapor deposition of a diamond (100) surface under conditions used to grow single-crystal diamond (SCD), microcrystalline diamond (MCD), nanocrystalline diamond (NCD), and ultrananocrystalline diamond (UNCD) films. The model considers adsorption, etching/desorption, lattice incorporation and surface migration but not defect formation or renucleation processes. Two methods have been devised for estimation of the gas phase concentrations of species at the growing diamond surface, and are used to determine adsorption rates for C1Hx hydrocarbons for the different conditions. The rate of migration of adsorbed carbon species is governed by the availability of neighboring radical sites, which, in turn, depend upon the rates of H abstraction and of surface-radical migration. The KMC model predicts growth rates and surface roughness for each of diamond types consistent with experiment. In the absence of defect formation and renucleation the average surface diffusion length, ℓ, is a key parameter controlling surface morphology. When ℓ <2, surface migration is limited by the lack of availability of surface radical sites, and the migrating surface species simply hop back and forth between two adjacent sites but do not travel far beyond their initial adsorption site. Thus, Eley-Rideal processes dominate the growth, leading to the rough surfaces seen in NCD and UNCD. The maximum or "intrinsic" surface roughness occurs for nominally zero-migration conditions (ℓ =0) with an rms value of approximately five carbon atoms. Conversely, when migration occurs over greater distances (ℓ >2), Langmuir-Hinshelwood processes dominate the growth producing the smoother surfaces of MCD and SCD. By extrapolation, we predict that atomically smooth surfaces over large areas should occur once migrating species can travel approximately five sites (ℓ ˜5). β-scission processes are found to be unimportant for MCD and SCD growth conditions, but can remove up to 5% of the adsorbing carbon for NCD and UNCD growth. C1Hx insertion reactions also contribute <1% to the growth for nearly all conditions, while C2Hx (x <2) insertion reactions are negligible due their very low concentrations at the surface. Finally, the predictions for growth rate and morphology for UNCD deposition in a microwave system were found to be anomalous compared to those for all the other growth conditions, suggesting that carbonaceous particulates created in these plasmas may significantly affect the gas chemistry.

High order methods for the integration of the Bateman equations and other problems of the form of y‧ = F(y,t)y

NASA Astrophysics Data System (ADS)

Josey, C.; Forget, B.; Smith, K.

2017-12-01

This paper introduces two families of A-stable algorithms for the integration of y‧ = F (y , t) y: the extended predictor-corrector (EPC) and the exponential-linear (EL) methods. The structure of the algorithm families are described, and the method of derivation of the coefficients presented. The new algorithms are then tested on a simple deterministic problem and a Monte Carlo isotopic evolution problem. The EPC family is shown to be only second order for systems of ODEs. However, the EPC-RK45 algorithm had the highest accuracy on the Monte Carlo test, requiring at least a factor of 2 fewer function evaluations to achieve a given accuracy than a second order predictor-corrector method (center extrapolation / center midpoint method) with regards to Gd-157 concentration. Members of the EL family can be derived to at least fourth order. The EL3 and the EL4 algorithms presented are shown to be third and fourth order respectively on the systems of ODE test. In the Monte Carlo test, these methods did not overtake the accuracy of EPC methods before statistical uncertainty dominated the error. The statistical properties of the algorithms were also analyzed during the Monte Carlo problem. The new methods are shown to yield smaller standard deviations on final quantities as compared to the reference predictor-corrector method, by up to a factor of 1.4.

GPU-powered Shotgun Stochastic Search for Dirichlet process mixtures of Gaussian Graphical Models

PubMed Central

Mukherjee, Chiranjit; Rodriguez, Abel

2016-01-01

Gaussian graphical models are popular for modeling high-dimensional multivariate data with sparse conditional dependencies. A mixture of Gaussian graphical models extends this model to the more realistic scenario where observations come from a heterogenous population composed of a small number of homogeneous sub-groups. In this paper we present a novel stochastic search algorithm for finding the posterior mode of high-dimensional Dirichlet process mixtures of decomposable Gaussian graphical models. Further, we investigate how to harness the massive thread-parallelization capabilities of graphical processing units to accelerate computation. The computational advantages of our algorithms are demonstrated with various simulated data examples in which we compare our stochastic search with a Markov chain Monte Carlo algorithm in moderate dimensional data examples. These experiments show that our stochastic search largely outperforms the Markov chain Monte Carlo algorithm in terms of computing-times and in terms of the quality of the posterior mode discovered. Finally, we analyze a gene expression dataset in which Markov chain Monte Carlo algorithms are too slow to be practically useful. PMID:28626348

GPU-powered Shotgun Stochastic Search for Dirichlet process mixtures of Gaussian Graphical Models.

PubMed

Mukherjee, Chiranjit; Rodriguez, Abel

2016-01-01

Gaussian graphical models are popular for modeling high-dimensional multivariate data with sparse conditional dependencies. A mixture of Gaussian graphical models extends this model to the more realistic scenario where observations come from a heterogenous population composed of a small number of homogeneous sub-groups. In this paper we present a novel stochastic search algorithm for finding the posterior mode of high-dimensional Dirichlet process mixtures of decomposable Gaussian graphical models. Further, we investigate how to harness the massive thread-parallelization capabilities of graphical processing units to accelerate computation. The computational advantages of our algorithms are demonstrated with various simulated data examples in which we compare our stochastic search with a Markov chain Monte Carlo algorithm in moderate dimensional data examples. These experiments show that our stochastic search largely outperforms the Markov chain Monte Carlo algorithm in terms of computing-times and in terms of the quality of the posterior mode discovered. Finally, we analyze a gene expression dataset in which Markov chain Monte Carlo algorithms are too slow to be practically useful.

Kangaroo Mother Care in Colombia: A Subaltern Health Innovation against For-profit Biomedicine.

PubMed

Abadía-Barrero, César Ernesto

2018-01-24

This ethnographic study presents the origins, growth, and collapse of the first Kangaroo Mother Care (KMC) program, a well-established practice for neonatal care created in 1978 in Colombia. The WHO and UNICEF praised this zero-cost revolutionary technique for its promotion of skin-to-skin contact between premature and low-birth-weight newborns and family members. KMC facilitates early hospital discharge, brings many clinical and psychological benefits, and constitutes an excellent alternative to placing babies in incubators. However, these benefits and political potential against biomedical interventions were undermined after being relabeled as a "reverse innovation," a business concept that encourages corporate investments in low-income countries to develop technologies that can both solve global health problems and boost multinational corporations profits. In response, I propose "subaltern health innovations" as a label for KMC that accounts for the power dynamics in global health between health care initiatives that originate in the Global South and neoliberal configurations of for-profit biomedicine. © 2018 by the American Anthropological Association.

Effect of the size of nanoparticles on their dissolution within metal-glass nanocomposites under sustained irradiation

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

Vu, T. H. Y., E-mail: thi-hai-yen.vu@polytechnique.edu; Ramjauny, Y.; Rizza, G.

2016-01-21

We investigate the dissolution law of metallic nanoparticles (NPs) under sustained irradiation. The system is composed of isolated spherical gold NPs (4–100 nm) embedded in an amorphous silica host matrix. Samples are irradiated at room temperature in the nuclear stopping power regime with 4 MeV Au ions for fluences up to 8 × 10{sup 16 }cm{sup −2}. Experimentally, the dependence of the dissolution kinetics on the irradiation fluence is linear for large NPs (45–100 nm) and exponential for small NPs (4–25 nm). A lattice-based kinetic Monte Carlo (KMC) code, which includes atomic diffusion and ballistic displacement events, is used to simulate the dynamical competition between irradiation effectsmore » and thermal healing. The KMC simulations allow for a qualitative description of the NP dissolution in two main stages, in good agreement with the experiment. Moreover, the perfect correlation obtained between the evolution of the simulated flux of ejected atoms and the dissolution rate in two stages implies that there exists an effect of the size of NPs on their dissolution and a critical size for the transition between the two stages. The Frost-Russell model providing an analytical solution for the dissolution rate, accounts well for the first dissolution stage but fails in reproducing the data for the second stage. An improved model obtained by including a size-dependent recoil generation rate permits fully describing the dissolution for any NP size. This proves, in particular, that the size effect on the generation rate is the principal reason for the existence of two regimes. Finally, our results also demonstrate that it is justified to use a unidirectional approximation to describe the dissolution of the NP under irradiation, because the solute concentration is particularly low in metal-glass nanocomposites.« less

Self-Learning Monte Carlo Method

NASA Astrophysics Data System (ADS)

Liu, Junwei; Qi, Yang; Meng, Zi Yang; Fu, Liang

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of general and efficient update algorithm for large size systems close to phase transition or with strong frustrations, for which local updates perform badly. In this work, we propose a new general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup. This work is supported by the DOE Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award DE-SC0010526.

Visual improvement for bad handwriting based on Monte-Carlo method

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

2014-03-01

A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Loading relativistic Maxwell distributions in particle simulations

NASA Astrophysics Data System (ADS)

Zenitani, S.

2015-12-01

In order to study energetic plasma phenomena by using particle-in-cell (PIC) and Monte-Carlo simulations, we need to deal with relativistic velocity distributions in these simulations. However, numerical algorithms to deal with relativistic distributions are not well known. In this contribution, we overview basic algorithms to load relativistic Maxwell distributions in PIC and Monte-Carlo simulations. For stationary relativistic Maxwellian, the inverse transform method and the Sobol algorithm are reviewed. To boost particles to obtain relativistic shifted-Maxwellian, two rejection methods are newly proposed in a physically transparent manner. Their acceptance efficiencies are 􏰅50% for generic cases and 100% for symmetric distributions. They can be combined with arbitrary base algorithms.

An unbiased Hessian representation for Monte Carlo PDFs.

PubMed

Carrazza, Stefano; Forte, Stefano; Kassabov, Zahari; Latorre, José Ignacio; Rojo, Juan

We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (MC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available together with (through LHAPDF6) a Hessian representations of the NNPDF3.0 set, and the MC-H PDF set.

SU-F-T-444: Quality Improvement Review of Radiation Therapy Treatment Planning in the Presence of Dental Implants

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

Parenica, H; Ford, J; Mavroidis, P

Purpose: To quantify and compare the effect of metallic dental implants (MDI) on dose distributions calculated using Collapsed Cone Convolution Superposition (CCCS) algorithm or a Monte Carlo algorithm (with and without correcting for the density of the MDI). Methods: Seven previously treated patients to the head and neck region were included in this study. The MDI and the streaking artifacts on the CT images were carefully contoured. For each patient a plan was optimized and calculated using the Pinnacle3 treatment planning system (TPS). For each patient two dose calculations were performed, a) with the densities of the MDI and CTmore » artifacts overridden (12 g/cc and 1 g/cc respectively) and b) without density overrides. The plans were then exported to the Monaco TPS and recalculated using Monte Carlo dose calculation algorithm. The changes in dose to PTVs and surrounding Regions of Interest (ROIs) were examined between all plans. Results: The Monte Carlo dose calculation indicated that PTVs received 6% lower dose than the CCCS algorithm predicted. In some cases, the Monte Carlo algorithm indicated that surrounding ROIs received higher dose (up to a factor of 2). Conclusion: Not properly accounting for dental implants can impact both the high dose regions (PTV) and the low dose regions (OAR). This study implies that if MDI and the artifacts are not appropriately contoured and given the correct density, there is potential significant impact on PTV coverage and OAR maximum doses.« less

Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2014-03-01

The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient algorithm for parameter estimations of the RSV model.

Exploring cluster Monte Carlo updates with Boltzmann machines

NASA Astrophysics Data System (ADS)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

Late Carboniferous high-pressure metamorphism of the Kassan Metamorphic Complex (Kyrgyz Tianshan) and assembly of the SW Central Asian Orogenic Belt

NASA Astrophysics Data System (ADS)

Mühlberg, M.; Hegner, E.; Klemd, R.; Pfänder, J. A.; Kaliwoda, M.; Biske, Y. S.

2016-11-01

High-pressure (HP) metamorphism of the Kassan Metamorphic Complex (KMC) in the western Kyrgyz Tianshan has been related to either late Ordovician or late Carboniferous-Permian subduction processes. We report Sm-Nd ages for retrogressed eclogite samples and 40Ar/39Ar cooling ages for enclosing garnet-muscovite samples from the KMC as new age constraints on HP metamorphism and rock exhumation. These data will be used for an upgraded paleogeographic model for late Paleozoic crustal consolidation in the southwestern Central Asian Orogenic Belt. The retrogressed eclogite samples have transitional alkaline to tholeiitic affinity and trace-element patterns consistent with protoliths derived from garnet-bearing mantle sources at rifting plate margins. Geothermobarometric data for a retrogressed eclogite sample indicate peak-metamorphic conditions of 540 ± 30 °C at 1.6 ± 0.1 GPa. Samples from different lithotectonic units of the KMC provide coherent Sm-Nd garnet-whole rock ages of 317 ± 4 Ma and 316 ± 3 Ma (2σ). The prograde major-element zoning in the mm-sized garnets in combination with the moderate peak-metamorphic temperature, support our interpretation of the Sm-Nd garnet ages as unambiguous evidence for late Carboniferous HP metamorphism. The Sm-Nd garnet growth ages overlap within-error with the 40Ar/39Ar mica cooling ages of 314 ± 2 Ma and 313 ± 2 Ma (2σ) indicating rapid uplift of the subduction complex after peak metamorphism. The ca. 317-313 Ma HP-exhumation event of the KMC is contemporaneous with those of the Atbashi and Akeyazi (ca. 500 km east in NW China) HP complexes and implies similar collision histories at the South Tianshan Suture to the east and west of the Talas-Fergana Fault (TFF). The exhumation of the KMC and Atbashi HP complexes overlaps with the initiation of the TFF (Rolland et al., 2013) suggesting incipient separation of the Chatkal and Atbashi complexes during rock exhumation and early plate collision.

Testing trivializing maps in the Hybrid Monte Carlo algorithm

PubMed Central

Engel, Georg P.; Schaefer, Stefan

2011-01-01

We test a recent proposal to use approximate trivializing maps in a field theory to speed up Hybrid Monte Carlo simulations. Simulating the CPN−1 model, we find a small improvement with the leading order transformation, which is however compensated by the additional computational overhead. The scaling of the algorithm towards the continuum is not changed. In particular, the effect of the topological modes on the autocorrelation times is studied. PMID:21969733

Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method

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

Sudheer, C. D.; Krishnan, S.; Srinivasan, A.

Diffusion Monte Carlo is the most accurate widely used Quantum Monte Carlo method for the electronic structure of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency and avoid accumulation of systematic errors on parallel machines. The load balancing step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receivingmore » at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL showing up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that requires load balancing.« less

Stochastic evaluation of second-order many-body perturbation energies.

PubMed

Willow, Soohaeng Yoo; Kim, Kwang S; Hirata, So

2012-11-28

With the aid of the Laplace transform, the canonical expression of the second-order many-body perturbation correction to an electronic energy is converted into the sum of two 13-dimensional integrals, the 12-dimensional parts of which are evaluated by Monte Carlo integration. Weight functions are identified that are analytically normalizable, are finite and non-negative everywhere, and share the same singularities as the integrands. They thus generate appropriate distributions of four-electron walkers via the Metropolis algorithm, yielding correlation energies of small molecules within a few mE(h) of the correct values after 10(8) Monte Carlo steps. This algorithm does away with the integral transformation as the hotspot of the usual algorithms, has a far superior size dependence of cost, does not suffer from the sign problem of some quantum Monte Carlo methods, and potentially easily parallelizable and extensible to other more complex electron-correlation theories.

The mood variation in mothers of preterm infants in Kangaroo mother care and conventional incubator care.

PubMed

de Macedo, Elizeu Coutinho; Cruvinel, Fernando; Lukasova, Katerina; D'Antino, Maria Eloisa Famá

2007-10-01

Preterm babies are more prone to develop disorders and so require immediate intensive care. In the conventional neonatal intensive care, the baby is kept in the incubator, separated from the mother. Some actions have been taken in order to make this mother-child separation less traumatic. One of these actions is the Kangaroo mother care (KMC) characterized by skin-to-skin contact between a mother and her newborn. The objective of this study was to compare the mood variation of mothers enrolled in the KMC program to those in the conventional incubator care. In one general hospital in Sao Paulo, Brazil, 90 mothers were evaluated before and after contact with the baby in the Neonatal Intensive Care Unit. The participants were divided into three groups: 30 mothers of term newborns (TG), 30 mothers of preterm infants included in KMC program (PGK) and 30 preterms with incubator placement (PGI). The Brazilian version of the Visual Analogue Mood Scale (VAMS) was used for the assessment before and after the infant's visit. Results showed that TG mothers reported fewer occurrences of depressive states than PGK and PGI mothers. A significant mood variation was observed for PGK and PGI after the infant's visit. PGK mothers reported feeling calmer, stronger, well-coordinated, energetic, contented, tranquil, quick-witted, relaxed, proficient, happy, friendly and clear-headed. The only variation showed by PGI mothers was an increase in feeling clumsy. This study shows a positive effect of the KMC on the mood variation of preterm mothers and points to the need of a more humane experience during the incubator care.

Annealed Importance Sampling Reversible Jump MCMC algorithms

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

Karagiannis, Georgios; Andrieu, Christophe

2013-03-20

It will soon be 20 years since reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithms have been proposed. They have significantly extended the scope of Markov chain Monte Carlo simulation methods, offering the promise to be able to routinely tackle transdimensional sampling problems, as encountered in Bayesian model selection problems for example, in a principled and flexible fashion. Their practical efficient implementation, however, still remains a challenge. A particular difficulty encountered in practice is in the choice of the dimension matching variables (both their nature and their distribution) and the reversible transformations which allow one to define the one-to-one mappingsmore » underpinning the design of these algorithms. Indeed, even seemingly sensible choices can lead to algorithms with very poor performance. The focus of this paper is the development and performance evaluation of a method, annealed importance sampling RJ-MCMC (aisRJ), which addresses this problem by mitigating the sensitivity of RJ-MCMC algorithms to the aforementioned poor design. As we shall see the algorithm can be understood as being an “exact approximation” of an idealized MCMC algorithm that would sample from the model probabilities directly in a model selection set-up. Such an idealized algorithm may have good theoretical convergence properties, but typically cannot be implemented, and our algorithms can approximate the performance of such idealized algorithms to an arbitrary degree while not introducing any bias for any degree of approximation. Our approach combines the dimension matching ideas of RJ-MCMC with annealed importance sampling and its Markov chain Monte Carlo implementation. We illustrate the performance of the algorithm with numerical simulations which indicate that, although the approach may at first appear computationally involved, it is in fact competitive.« less

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

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

Wang, Yuhe; Mazur, Thomas R.; Green, Olga

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: PENELOPE was first translated from FORTRAN to C++ and the result was confirmed to produce equivalent results to the original code. The C++ code was then adapted to CUDA in a workflow optimized for GPU architecture. The original code was expandedmore » to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gPENELOPE as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gPENELOPE. Ultimately, gPENELOPE was applied toward independent validation of patient doses calculated by MRIdian’s KMC. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread FORTRAN implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of PENELOPE. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.« less

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

PubMed Central

Wang, Yuhe; Mazur, Thomas R.; Green, Olga; Hu, Yanle; Li, Hua; Rodriguez, Vivian; Wooten, H. Omar; Yang, Deshan; Zhao, Tianyu; Mutic, Sasa; Li, H. Harold

2016-01-01

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on penelope and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: penelope was first translated from fortran to c++ and the result was confirmed to produce equivalent results to the original code. The c++ code was then adapted to cuda in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gpenelope highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gpenelope as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gpenelope. Ultimately, gpenelope was applied toward independent validation of patient doses calculated by MRIdian’s kmc. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread fortran implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gpenelope with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of penelope. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems. PMID:27370123

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model.

PubMed

Wang, Yuhe; Mazur, Thomas R; Green, Olga; Hu, Yanle; Li, Hua; Rodriguez, Vivian; Wooten, H Omar; Yang, Deshan; Zhao, Tianyu; Mutic, Sasa; Li, H Harold

2016-07-01

The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on penelope and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. penelope was first translated from fortran to c++ and the result was confirmed to produce equivalent results to the original code. The c++ code was then adapted to cuda in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gpenelope highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gpenelope as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gpenelope. Ultimately, gpenelope was applied toward independent validation of patient doses calculated by MRIdian's kmc. An acceleration factor of 152 was achieved in comparison to the original single-thread fortran implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gpenelope with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). A Monte Carlo simulation platform was developed based on a GPU- accelerated version of penelope. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.

A Mechanistic-Based Healing Model for Self-Healing Glass Seals Used in Solid Oxide Fuel Cells

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

Xu, Wei; Sun, Xin; Stephens, Elizabeth V.

The usage of self-healing glass as hermetic seals is a recent advancement in sealing technology development for the planar solid oxide fuel cells (SOFCs). Because of its capability of restoring the mechanical properties at elevated temperatures, the self-healing glass seal is expected to provide high reliability in maintaining the long-term structural integrity and functionality of SOFCs. In order to accommodate the design and to evaluate the effectiveness of such engineering seals under various thermo-mechanical operating conditions, computational modeling framework needs to be developed to accurately capture and predict the healing behavior of the glass material. In the present work, amore » mechanistic-based two-stage model was developed to study the stress and temperature-dependent crack healing of the self-healing glass materials. The model was first calibrated by experimental measurements combined with the kinetic Monte Carlo (kMC) simulation results and then implemented into the finite element analysis (FEA). The effects of various factors, i.e. stress, temperature, crack morphology, on the healing behavior of the glass were investigated and discussed.« less

A computation study on the interplay between surface morphology and electrochemical performance of patterned thin film electrodes for Li-ion batteries

NASA Astrophysics Data System (ADS)

Gur, Sourav; Frantziskonis, George N.; Aifantis, Katerina E.

2017-08-01

Recent experiments illustrate that the morphology of the electrode surface impacts the voltage - capacity curves and long term cycling performance of Li-ion batteries. The present study systematically explores the role of the electrode surface morphology and uncertainties in the reactions that occur during electrochemical cycling, by performing kinetic Monte Carlo (kMC) simulations using the lattice Boltzmann method (LBM). This allows encoding of the inherent stochasticity at discrete microscale reaction events over the deterministic mean field reaction dynamics that occur in Li-ion cells. The electrodes are taken to be dense thin films whose surfaces are patterned with conical, trapezoidal, dome-shaped, or pillar-shaped structures. It is shown that the inherent perturbations in the reactions together with the characteristics of the electrode surface configuration can significantly improve battery performance, mainly because patterned surfaces, as opposed to flat surfaces, result in a smaller voltage drop. The most efficient pattern was the trapezoidal, which is consistent with experimental evidence on Si patterned electrodes.

Multi-scale modeling to relate Be surface temperatures, concentrations and molecular sputtering yields

NASA Astrophysics Data System (ADS)

Lasa, Ane; Safi, Elnaz; Nordlund, Kai

2015-11-01

Recent experiments and Molecular Dynamics (MD) simulations show erosion rates of Be exposed to deuterium (D) plasma varying with surface temperature and the correlated D concentration. Little is understood how these three parameters relate for Be surfaces, despite being essential for reliable prediction of impurity transport and plasma facing material lifetime in current (JET) and future (ITER) devices. A multi-scale exercise is presented here to relate Be surface temperatures, concentrations and sputtering yields. Kinetic Monte Carlo (MC) code MMonCa is used to estimate equilibrium D concentrations in Be at different temperatures. Then, mixed Be-D surfaces - that correspond to the KMC profiles - are generated in MD, to calculate Be-D molecular erosion yields due to D irradiation. With this new database implemented in the 3D MC impurity transport code ERO, modeling scenarios studying wall erosion, such as RF-induced enhanced limiter erosion or main wall surface temperature scans run at JET, can be revisited with higher confidence. Work supported by U.S. DOE under Contract DE-AC05-00OR22725.

An improved target velocity sampling algorithm for free gas elastic scattering

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

Romano, Paul K.; Walsh, Jonathan A.

We present an improved algorithm for sampling the target velocity when simulating elastic scattering in a Monte Carlo neutron transport code that correctly accounts for the energy dependence of the scattering cross section. The algorithm samples the relative velocity directly, thereby avoiding a potentially inefficient rejection step based on the ratio of cross sections. Here, we have shown that this algorithm requires only one rejection step, whereas other methods of similar accuracy require two rejection steps. The method was verified against stochastic and deterministic reference results for upscattering percentages in 238U. Simulations of a light water reactor pin cell problemmore » demonstrate that using this algorithm results in a 3% or less penalty in performance when compared with an approximate method that is used in most production Monte Carlo codes« less

An improved target velocity sampling algorithm for free gas elastic scattering

DOE PAGES

Romano, Paul K.; Walsh, Jonathan A.

2018-02-03

We present an improved algorithm for sampling the target velocity when simulating elastic scattering in a Monte Carlo neutron transport code that correctly accounts for the energy dependence of the scattering cross section. The algorithm samples the relative velocity directly, thereby avoiding a potentially inefficient rejection step based on the ratio of cross sections. Here, we have shown that this algorithm requires only one rejection step, whereas other methods of similar accuracy require two rejection steps. The method was verified against stochastic and deterministic reference results for upscattering percentages in 238U. Simulations of a light water reactor pin cell problemmore » demonstrate that using this algorithm results in a 3% or less penalty in performance when compared with an approximate method that is used in most production Monte Carlo codes« less

Simulation of Nuclear Reactor Kinetics by the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Gomin, E. A.; Davidenko, V. D.; Zinchenko, A. S.; Kharchenko, I. K.

2017-12-01

The KIR computer code intended for calculations of nuclear reactor kinetics using the Monte Carlo method is described. The algorithm implemented in the code is described in detail. Some results of test calculations are given.

Markov chain Monte Carlo techniques applied to parton distribution functions determination: Proof of concept

NASA Astrophysics Data System (ADS)

Gbedo, Yémalin Gabin; Mangin-Brinet, Mariane

2017-07-01

We present a new procedure to determine parton distribution functions (PDFs), based on Markov chain Monte Carlo (MCMC) methods. The aim of this paper is to show that we can replace the standard χ2 minimization by procedures grounded on statistical methods, and on Bayesian inference in particular, thus offering additional insight into the rich field of PDFs determination. After a basic introduction to these techniques, we introduce the algorithm we have chosen to implement—namely Hybrid (or Hamiltonian) Monte Carlo. This algorithm, initially developed for Lattice QCD, turns out to be very interesting when applied to PDFs determination by global analyses; we show that it allows us to circumvent the difficulties due to the high dimensionality of the problem, in particular concerning the acceptance. A first feasibility study is performed and presented, which indicates that Markov chain Monte Carlo can successfully be applied to the extraction of PDFs and of their uncertainties.

Dose specification for radiation therapy: dose to water or dose to medium?

NASA Astrophysics Data System (ADS)

Ma, C.-M.; Li, Jinsheng

2011-05-01

The Monte Carlo method enables accurate dose calculation for radiation therapy treatment planning and has been implemented in some commercial treatment planning systems. Unlike conventional dose calculation algorithms that provide patient dose information in terms of dose to water with variable electron density, the Monte Carlo method calculates the energy deposition in different media and expresses dose to a medium. This paper discusses the differences in dose calculated using water with different electron densities and that calculated for different biological media and the clinical issues on dose specification including dose prescription and plan evaluation using dose to water and dose to medium. We will demonstrate that conventional photon dose calculation algorithms compute doses similar to those simulated by Monte Carlo using water with different electron densities, which are close (<4% differences) to doses to media but significantly different (up to 11%) from doses to water converted from doses to media following American Association of Physicists in Medicine (AAPM) Task Group 105 recommendations. Our results suggest that for consistency with previous radiation therapy experience Monte Carlo photon algorithms report dose to medium for radiotherapy dose prescription, treatment plan evaluation and treatment outcome analysis.

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.

Quantifying the effect of air gap, depth, and range shifter thickness on TPS dosimetric accuracy in superficial PBS proton therapy.

PubMed

Shirey, Robert J; Wu, Hsinshun Terry

2018-01-01

This study quantifies the dosimetric accuracy of a commercial treatment planning system as functions of treatment depth, air gap, and range shifter thickness for superficial pencil beam scanning proton therapy treatments. The RayStation 6 pencil beam and Monte Carlo dose engines were each used to calculate the dose distributions for a single treatment plan with varying range shifter air gaps. Central axis dose values extracted from each of the calculated plans were compared to dose values measured with a calibrated PTW Markus chamber at various depths in RW3 solid water. Dose was measured at 12 depths, ranging from the surface to 5 cm, for each of the 18 different air gaps, which ranged from 0.5 to 28 cm. TPS dosimetric accuracy, defined as the ratio of calculated dose relative to the measured dose, was plotted as functions of depth and air gap for the pencil beam and Monte Carlo dose algorithms. The accuracy of the TPS pencil beam dose algorithm was found to be clinically unacceptable at depths shallower than 3 cm with air gaps wider than 10 cm, and increased range shifter thickness only added to the dosimetric inaccuracy of the pencil beam algorithm. Each configuration calculated with Monte Carlo was determined to be clinically acceptable. Further comparisons of the Monte Carlo dose algorithm to the measured spread-out Bragg Peaks of multiple fields used during machine commissioning verified the dosimetric accuracy of Monte Carlo in a variety of beam energies and field sizes. Discrepancies between measured and TPS calculated dose values can mainly be attributed to the ability (or lack thereof) of the TPS pencil beam dose algorithm to properly model secondary proton scatter generated in the range shifter. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Hybrid Microgrid Configuration Optimization with Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Lopez, Nicolas

This dissertation explores the Renewable Energy Integration Problem, and proposes a Genetic Algorithm embedded with a Monte Carlo simulation to solve large instances of the problem that are impractical to solve via full enumeration. The Renewable Energy Integration Problem is defined as finding the optimum set of components to supply the electric demand to a hybrid microgrid. The components considered are solar panels, wind turbines, diesel generators, electric batteries, connections to the power grid and converters, which can be inverters and/or rectifiers. The methodology developed is explained as well as the combinatorial formulation. In addition, 2 case studies of a single objective optimization version of the problem are presented, in order to minimize cost and to minimize global warming potential (GWP) followed by a multi-objective implementation of the offered methodology, by utilizing a non-sorting Genetic Algorithm embedded with a monte Carlo Simulation. The method is validated by solving a small instance of the problem with known solution via a full enumeration algorithm developed by NREL in their software HOMER. The dissertation concludes that the evolutionary algorithms embedded with Monte Carlo simulation namely modified Genetic Algorithms are an efficient form of solving the problem, by finding approximate solutions in the case of single objective optimization, and by approximating the true Pareto front in the case of multiple objective optimization of the Renewable Energy Integration Problem.

SU-F-T-148: Are the Approximations in Analytic Semi-Empirical Dose Calculation Algorithms for Intensity Modulated Proton Therapy for Complex Heterogeneities of Head and Neck Clinically Significant?

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

Yepes, P; UT MD Anderson Cancer Center, Houston, TX; Titt, U

2016-06-15

Purpose: Evaluate the differences in dose distributions between the proton analytic semi-empirical dose calculation algorithm used in the clinic and Monte Carlo calculations for a sample of 50 head-and-neck (H&N) patients and estimate the potential clinical significance of the differences. Methods: A cohort of 50 H&N patients, treated at the University of Texas Cancer Center with Intensity Modulated Proton Therapy (IMPT), were selected for evaluation of clinical significance of approximations in computed dose distributions. H&N site was selected because of the highly inhomogeneous nature of the anatomy. The Fast Dose Calculator (FDC), a fast track-repeating accelerated Monte Carlo algorithm formore » proton therapy, was utilized for the calculation of dose distributions delivered during treatment plans. Because of its short processing time, FDC allows for the processing of large cohorts of patients. FDC has been validated versus GEANT4, a full Monte Carlo system and measurements in water and for inhomogeneous phantoms. A gamma-index analysis, DVHs, EUDs, and TCP and NTCPs computed using published models were utilized to evaluate the differences between the Treatment Plan System (TPS) and FDC. Results: The Monte Carlo results systematically predict lower dose delivered in the target. The observed differences can be as large as 8 Gy, and should have a clinical impact. Gamma analysis also showed significant differences between both approaches, especially for the target volumes. Conclusion: Monte Carlo calculations with fast algorithms is practical and should be considered for the clinic, at least as a treatment plan verification tool.« less

The Metropolis Monte Carlo method with CUDA enabled Graphic Processing Units

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

Hall, Clifford; School of Physics, Astronomy, and Computational Sciences, George Mason University, 4400 University Dr., Fairfax, VA 22030; Ji, Weixiao

2014-02-01

We present a CPU–GPU system for runtime acceleration of large molecular simulations using GPU computation and memory swaps. The memory architecture of the GPU can be used both as container for simulation data stored on the graphics card and as floating-point code target, providing an effective means for the manipulation of atomistic or molecular data on the GPU. To fully take advantage of this mechanism, efficient GPU realizations of algorithms used to perform atomistic and molecular simulations are essential. Our system implements a versatile molecular engine, including inter-molecule interactions and orientational variables for performing the Metropolis Monte Carlo (MMC) algorithm,more » which is one type of Markov chain Monte Carlo. By combining memory objects with floating-point code fragments we have implemented an MMC parallel engine that entirely avoids the communication time of molecular data at runtime. Our runtime acceleration system is a forerunner of a new class of CPU–GPU algorithms exploiting memory concepts combined with threading for avoiding bus bandwidth and communication. The testbed molecular system used here is a condensed phase system of oligopyrrole chains. A benchmark shows a size scaling speedup of 60 for systems with 210,000 pyrrole monomers. Our implementation can easily be combined with MPI to connect in parallel several CPU–GPU duets. -- Highlights: •We parallelize the Metropolis Monte Carlo (MMC) algorithm on one CPU—GPU duet. •The Adaptive Tempering Monte Carlo employs MMC and profits from this CPU—GPU implementation. •Our benchmark shows a size scaling-up speedup of 62 for systems with 225,000 particles. •The testbed involves a polymeric system of oligopyrroles in the condensed phase. •The CPU—GPU parallelization includes dipole—dipole and Mie—Jones classic potentials.« less

A point kernel algorithm for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Debus, Charlotte; Oelfke, Uwe; Bartzsch, Stefan

2017-11-01

Microbeam radiation therapy (MRT) is a treatment approach in radiation therapy where the treatment field is spatially fractionated into arrays of a few tens of micrometre wide planar beams of unusually high peak doses separated by low dose regions of several hundred micrometre width. In preclinical studies, this treatment approach has proven to spare normal tissue more effectively than conventional radiation therapy, while being equally efficient in tumour control. So far dose calculations in MRT, a prerequisite for future clinical applications are based on Monte Carlo simulations. However, they are computationally expensive, since scoring volumes have to be small. In this article a kernel based dose calculation algorithm is presented that splits the calculation into photon and electron mediated energy transport, and performs the calculation of peak and valley doses in typical MRT treatment fields within a few minutes. Kernels are analytically calculated depending on the energy spectrum and material composition. In various homogeneous materials peak, valley doses and microbeam profiles are calculated and compared to Monte Carlo simulations. For a microbeam exposure of an anthropomorphic head phantom calculated dose values are compared to measurements and Monte Carlo calculations. Except for regions close to material interfaces calculated peak dose values match Monte Carlo results within 4% and valley dose values within 8% deviation. No significant differences are observed between profiles calculated by the kernel algorithm and Monte Carlo simulations. Measurements in the head phantom agree within 4% in the peak and within 10% in the valley region. The presented algorithm is attached to the treatment planning platform VIRTUOS. It was and is used for dose calculations in preclinical and pet-clinical trials at the biomedical beamline ID17 of the European synchrotron radiation facility in Grenoble, France.

Monte Carlo Simulations of Radiative and Neutrino Transport under Astrophysical Conditions

NASA Astrophysics Data System (ADS)

Krivosheyev, Yu. M.; Bisnovatyi-Kogan, G. S.

2018-05-01

Monte Carlo simulations are utilized to model radiative and neutrino transfer in astrophysics. An algorithm that can be used to study radiative transport in astrophysical plasma based on simulations of photon trajectories in a medium is described. Formation of the hard X-ray spectrum of the Galactic microquasar SS 433 is considered in detail as an example. Specific requirements for applying such simulations to neutrino transport in a densemedium and algorithmic differences compared to its application to photon transport are discussed.

Monte Carlo sampling of Wigner functions and surface hopping quantum dynamics

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

Kube, Susanna; Lasser, Caroline; Weber, Marcus

2009-04-01

The article addresses the achievable accuracy for a Monte Carlo sampling of Wigner functions in combination with a surface hopping algorithm for non-adiabatic quantum dynamics. The approximation of Wigner functions is realized by an adaption of the Metropolis algorithm for real-valued functions with disconnected support. The integration, which is necessary for computing values of the Wigner function, uses importance sampling with a Gaussian weight function. The numerical experiments agree with theoretical considerations and show an error of 2-3%.

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.

Constant-pressure nested sampling with atomistic dynamics

NASA Astrophysics Data System (ADS)

Baldock, Robert J. N.; Bernstein, Noam; Salerno, K. Michael; Pártay, Lívia B.; Csányi, Gábor

2017-10-01

The nested sampling algorithm has been shown to be a general method for calculating the pressure-temperature-composition phase diagrams of materials. While the previous implementation used single-particle Monte Carlo moves, these are inefficient for condensed systems with general interactions where single-particle moves cannot be evaluated faster than the energy of the whole system. Here we enhance the method by using all-particle moves: either Galilean Monte Carlo or the total enthalpy Hamiltonian Monte Carlo algorithm, introduced in this paper. We show that these algorithms enable the determination of phase transition temperatures with equivalent accuracy to the previous method at 1 /N of the cost for an N -particle system with general interactions, or at equal cost when single-particle moves can be done in 1 /N of the cost of a full N -particle energy evaluation. We demonstrate this speed-up for the freezing and condensation transitions of the Lennard-Jones system and show the utility of the algorithms by calculating the order-disorder phase transition of a binary Lennard-Jones model alloy, the eutectic of copper-gold, the density anomaly of water, and the condensation and solidification of bead-spring polymers. The nested sampling method with all three algorithms is implemented in the pymatnest software.

A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters

NASA Astrophysics Data System (ADS)

Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli

2018-04-01

Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.

TH-AB-BRA-07: PENELOPE-Based GPU-Accelerated Dose Calculation System Applied to MRI-Guided Radiation Therapy

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

Wang, Y; Mazur, T; Green, O

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: We first translated PENELOPE from FORTRAN to C++ and validated that the translation produced equivalent results. Then we adapted the C++ code to CUDA in a workflow optimized for GPU architecture. We expanded upon the original code to include voxelized transportmore » boosted by Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, we incorporated the vendor-provided MRIdian head model into the code. We performed a set of experimental measurements on MRIdian to examine the accuracy of both the head model and gPENELOPE, and then applied gPENELOPE toward independent validation of patient doses calculated by MRIdian’s KMC. Results: We achieve an average acceleration factor of 152 compared to the original single-thread FORTRAN implementation with the original accuracy preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen (1), mediastinum (1) and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: We developed a Monte Carlo simulation platform based on a GPU-accelerated version of PENELOPE. We validated that both the vendor provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.« less

Hypothesis testing of scientific Monte Carlo calculations.

PubMed

Wallerberger, Markus; Gull, Emanuel

2017-11-01

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

Hypothesis testing of scientific Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Wallerberger, Markus; Gull, Emanuel

2017-11-01

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

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.

A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification

NASA Astrophysics Data System (ADS)

Wu, Keyi; Li, Jinglai

2016-09-01

In this work we consider a class of uncertainty quantification problems where the system performance or reliability is characterized by a scalar parameter y. The performance parameter y is random due to the presence of various sources of uncertainty in the system, and our goal is to estimate the probability density function (PDF) of y. We propose to use the multicanonical Monte Carlo (MMC) method, a special type of adaptive importance sampling algorithms, to compute the PDF of interest. Moreover, we develop an adaptive algorithm to construct local Gaussian process surrogates to further accelerate the MMC iterations. With numerical examples we demonstrate that the proposed method can achieve several orders of magnitudes of speedup over the standard Monte Carlo methods.

Path integral Monte Carlo ground state approach: formalism, implementation, and applications

NASA Astrophysics Data System (ADS)

Yan, Yangqian; Blume, D.

2017-11-01

Monte Carlo techniques have played an important role in understanding strongly correlated systems across many areas of physics, covering a wide range of energy and length scales. Among the many Monte Carlo methods applicable to quantum mechanical systems, the path integral Monte Carlo approach with its variants has been employed widely. Since semi-classical or classical approaches will not be discussed in this review, path integral based approaches can for our purposes be divided into two categories: approaches applicable to quantum mechanical systems at zero temperature and approaches applicable to quantum mechanical systems at finite temperature. While these two approaches are related to each other, the underlying formulation and aspects of the algorithm differ. This paper reviews the path integral Monte Carlo ground state (PIGS) approach, which solves the time-independent Schrödinger equation. Specifically, the PIGS approach allows for the determination of expectation values with respect to eigen states of the few- or many-body Schrödinger equation provided the system Hamiltonian is known. The theoretical framework behind the PIGS algorithm, implementation details, and sample applications for fermionic systems are presented.

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

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

Comments on "Including the effects of temperature-dependent opacities in the implicit Monte Carlo algorithm" by N.A. Gentile [J. Comput. Phys. 230 (2011) 5100-5114

NASA Astrophysics Data System (ADS)

Ghosh, Karabi

2017-02-01

We briefly comment on a paper by N.A. Gentile [J. Comput. Phys. 230 (2011) 5100-5114] in which the Fleck factor has been modified to include the effects of temperature-dependent opacities in the implicit Monte Carlo algorithm developed by Fleck and Cummings [1,2]. Instead of the Fleck factor, f = 1 / (1 + βcΔtσP), the author derived the modified Fleck factor g = 1 / (1 + βcΔtσP - min [σP‧ (aTr4 - aT4)cΔt/ρCV, 0 ]) to be used in the Implicit Monte Carlo (IMC) algorithm in order to obtain more accurate solutions with much larger time steps. Here β = 4 aT3 / ρCV, σP is the Planck opacity and the derivative of Planck opacity w.r.t. the material temperature is σP‧ = dσP / dT.

Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures

NASA Astrophysics Data System (ADS)

Romano, Paul Kollath

Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallel efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O( N ) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes---in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Kangaroo mother care may help oral growth and development in premature infants.

PubMed

Zhang, Feng; Liu, Shoutao

2012-08-01

Premature infants have a shorter prenatal development period and are prone to many serious medical problems during neonatal period. This may impact the development of oral tissues, as manifested by enamel hypoplasia, palatal distortion, malocclusion, or delay in tooth eruption and maturation. Kangaroo mother care (KMC) is a standardized and protocol-based care system for premature infants, based on skin-to-skin contact between the infant and their mother. Kangaroo mother care has been demonstrated to greatly improve the nurturing of premature infants and comparatively reduce the risk factors of oral defects. We hypothesize that KMC also facilitates oral growth and development in premature infants.

Comparison of effect of kangaroo mother care, breastfeeding and swaddling on Bacillus Calmette-Guerin vaccination pain score in healthy term neonates by a clinical trial.

PubMed

Fallah, Razieh; Naserzadeh, Naeimah; Ferdosian, Farzad; Binesh, Fariba

2017-05-01

The purpose of this research was to compare the analgesic effect of kangaroo mother care (KMC), breastfeeding and swaddling in Bacillus Calmette-Guerin (BCG) vaccination in term neonates. In a randomized 120 healthy term neonates who received routine BCG vaccination in the first day of their life are distributed into three groups. In group 1, neonates breastfed two minutes before, during and one minute after BCG vaccination. In group 2, neonates received KMC 10 minutes before, during and one minute after vaccination and in group 3, they were swaddled 10 minutes before, during and one minute after vaccination. Primary outcomes included pain score during, one minute and two minutes after BCG vaccination and obtaining pain score of less than three during vaccination . Pain scores during, one minute and two minutes after vaccination in group 1 were lower than in groups 2 and 3. Group 1 had higher success rate in painless vaccination and had lower crying duration in comparison to another groups (p < 0.05) Conclusion: Breastfeeding was more effective than KMC and swaddling in reduction of BCG vaccination pain in healthy term neonates.

Long Term Outcomes of Kangaroo Mother Care in Very Low Birth Weight Infants.

PubMed

Gavhane, Sunil; Eklare, Deepak; Mohammad, Haseeb

2016-12-01

Kangaroo Mother Care (KMC) has been gaining acceptance as an effective alternative to incubator based Conventional Medical Care (CMC) in preterm or Low Birth Weight (LBW) infants especially in resource scarce developing countries. To report and analyse the long-term effects of KMC for relatively stable Very Low Birth Weight (VLBW) infants on nutritional indicators and feeding conditions at 6-12 months of corrected age. This randomized controlled trial was done at a Level III Neonatal Intensive Care Unit (NICU) of a teaching institution in southern India. One hundred and forty neonates with birth weight <1500gm were enrolled. Inborn singleton, VLBW (birth weight <1500gm) infants, tolerating spoon feeds of 150mL/kg/day and haemodynamically stable (not on oxygen or respiratory support, no apnea for 72 hours, not on any intravenous fluids) were eligible. Infants with major malformation were excluded. Babies were randomized to KMC group or CMC group. At 6 to 12 months corrected age, the assessment included the measurement of growth parameters in terms of malnutrition, wasting, stunting and having small head. Feeding information was collected in relation to duration of exclusive or partial breastfeeding (months of chronological age and of corrected age), the age (chronological age and corrected age) at which weaning diet was started and the type of weaning diet. Comparisons between study groups for primary outcomes and secondary outcomes were performed with Odds Ratio (OR) calculator using Medcalc online statistical software. A total of 91 infants were followed at 6-12 months of corrected age. There was no difference between two groups in the incidence of malnutrition, wasting, stunting and having small head (47.7% vs 31.9%, p-0.13), (34.1% vs. 31.9%, p-0.83), (22.7% vs 12.8%, p-0.22) and (18.2% vs.31.9%, p-0.14). Although KMC group babies had better head growth and lesser weight and length compared to the CMC group, it was not statistically significant. The breast feeding and weaning rates at 6 months post birth were similar in both the groups. KMC group does not differ significantly with CMC group in terms of long-term growth and feeding pattern at 6 to 12 months of corrected age.

MDTS: automatic complex materials design using Monte Carlo tree search.

PubMed

M Dieb, Thaer; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-01-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

MDTS: automatic complex materials design using Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-12-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

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.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis.

PubMed

Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M

2016-07-14

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x'; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis

NASA Astrophysics Data System (ADS)

Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M.

2016-07-01

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x'; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

Event-driven Monte Carlo: Exact dynamics at all time scales for discrete-variable models

NASA Astrophysics Data System (ADS)

Mendoza-Coto, Alejandro; Díaz-Méndez, Rogelio; Pupillo, Guido

2016-06-01

We present an algorithm for the simulation of the exact real-time dynamics of classical many-body systems with discrete energy levels. In the same spirit of kinetic Monte Carlo methods, a stochastic solution of the master equation is found, with no need to define any other phase-space construction. However, unlike existing methods, the present algorithm does not assume any particular statistical distribution to perform moves or to advance the time, and thus is a unique tool for the numerical exploration of fast and ultra-fast dynamical regimes. By decomposing the problem in a set of two-level subsystems, we find a natural variable step size, that is well defined from the normalization condition of the transition probabilities between the levels. We successfully test the algorithm with known exact solutions for non-equilibrium dynamics and equilibrium thermodynamical properties of Ising-spin models in one and two dimensions, and compare to standard implementations of kinetic Monte Carlo methods. The present algorithm is directly applicable to the study of the real-time dynamics of a large class of classical Markovian chains, and particularly to short-time situations where the exact evolution is relevant.

Geometrically Constructed Markov Chain Monte Carlo Study of Quantum Spin-phonon Complex Systems

NASA Astrophysics Data System (ADS)

Suwa, Hidemaro

2013-03-01

We have developed novel Monte Carlo methods for precisely calculating quantum spin-boson models and investigated the critical phenomena of the spin-Peierls systems. Three significant methods are presented. The first is a new optimization algorithm of the Markov chain transition kernel based on the geometric weight allocation. This algorithm, for the first time, satisfies the total balance generally without imposing the detailed balance and always minimizes the average rejection rate, being better than the Metropolis algorithm. The second is the extension of the worm (directed-loop) algorithm to non-conserved particles, which cannot be treated efficiently by the conventional methods. The third is the combination with the level spectroscopy. Proposing a new gap estimator, we are successful in eliminating the systematic error of the conventional moment method. Then we have elucidated the phase diagram and the universality class of the one-dimensional XXZ spin-Peierls system. The criticality is totally consistent with the J1 -J2 model, an effective model in the antiadiabatic limit. Through this research, we have succeeded in investigating the critical phenomena of the effectively frustrated quantum spin system by the quantum Monte Carlo method without the negative sign. JSPS Postdoctoral Fellow for Research Abroad

Technical Note: A direct ray-tracing method to compute integral depth dose in pencil beam proton radiography with a multilayer ionization chamber.

PubMed

Farace, Paolo; Righetto, Roberto; Deffet, Sylvain; Meijers, Arturs; Vander Stappen, Francois

2016-12-01

To introduce a fast ray-tracing algorithm in pencil proton radiography (PR) with a multilayer ionization chamber (MLIC) for in vivo range error mapping. Pencil beam PR was obtained by delivering spots uniformly positioned in a square (45 × 45 mm 2 field-of-view) of 9 × 9 spots capable of crossing the phantoms (210 MeV). The exit beam was collected by a MLIC to sample the integral depth dose (IDD MLIC ). PRs of an electron-density and of a head phantom were acquired by moving the couch to obtain multiple 45 × 45 mm 2 frames. To map the corresponding range errors, the two-dimensional set of IDD MLIC was compared with (i) the integral depth dose computed by the treatment planning system (TPS) by both analytic (IDD TPS ) and Monte Carlo (IDD MC ) algorithms in a volume of water simulating the MLIC at the CT, and (ii) the integral depth dose directly computed by a simple ray-tracing algorithm (IDD direct ) through the same CT data. The exact spatial position of the spot pattern was numerically adjusted testing different in-plane positions and selecting the one that minimized the range differences between IDD direct and IDD MLIC . Range error mapping was feasible by both the TPS and the ray-tracing methods, but very sensitive to even small misalignments. In homogeneous regions, the range errors computed by the direct ray-tracing algorithm matched the results obtained by both the analytic and the Monte Carlo algorithms. In both phantoms, lateral heterogeneities were better modeled by the ray-tracing and the Monte Carlo algorithms than by the analytic TPS computation. Accordingly, when the pencil beam crossed lateral heterogeneities, the range errors mapped by the direct algorithm matched better the Monte Carlo maps than those obtained by the analytic algorithm. Finally, the simplicity of the ray-tracing algorithm allowed to implement a prototype procedure for automated spatial alignment. The ray-tracing algorithm can reliably replace the TPS method in MLIC PR for in vivo range verification and it can be a key component to develop software tools for spatial alignment and correction of CT calibration.

A robust algorithm for automated target recognition using precomputed radar cross sections

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2004-09-01

Passive radar is an emerging technology that offers a number of unique benefits, including covert operation. Many such systems are already capable of detecting and tracking aircraft. The goal of this work is to develop a robust algorithm for adding automated target recognition (ATR) capabilities to existing passive radar systems. In previous papers, we proposed conducting ATR by comparing the precomputed RCS of known targets to that of detected targets. To make the precomputed RCS as accurate as possible, a coordinated flight model is used to estimate aircraft orientation. Once the aircraft's position and orientation are known, it is possible to determine the incident and observed angles on the aircraft, relative to the transmitter and receiver. This makes it possible to extract the appropriate radar cross section (RCS) from our simulated database. This RCS is then scaled to account for propagation losses and the receiver's antenna gain. A Rician likelihood model compares these expected signals from different targets to the received target profile. We have previously employed Monte Carlo runs to gauge the probability of error in the ATR algorithm; however, generation of a statistically significant set of Monte Carlo runs is computationally intensive. As an alternative to Monte Carlo runs, we derive the relative entropy (also known as Kullback-Liebler distance) between two Rician distributions. Since the probability of Type II error in our hypothesis testing problem can be expressed as a function of the relative entropy via Stein's Lemma, this provides us with a computationally efficient method for determining an upper bound on our algorithm's performance. It also provides great insight into the types of classification errors we can expect from our algorithm. This paper compares the numerically approximated probability of Type II error with the results obtained from a set of Monte Carlo runs.

Bayesian Estimation of Multidimensional Item Response Models. A Comparison of Analytic and Simulation Algorithms

ERIC Educational Resources Information Center

Martin-Fernandez, Manuel; Revuelta, Javier

2017-01-01

This study compares the performance of two estimation algorithms of new usage, the Metropolis-Hastings Robins-Monro (MHRM) and the Hamiltonian MCMC (HMC), with two consolidated algorithms in the psychometric literature, the marginal likelihood via EM algorithm (MML-EM) and the Markov chain Monte Carlo (MCMC), in the estimation of multidimensional…

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.

Using Stan for Item Response Theory Models

ERIC Educational Resources Information Center

Ames, Allison J.; Au, Chi Hang

2018-01-01

Stan is a flexible probabilistic programming language providing full Bayesian inference through Hamiltonian Monte Carlo algorithms. The benefits of Hamiltonian Monte Carlo include improved efficiency and faster inference, when compared to other MCMC software implementations. Users can interface with Stan through a variety of computing…

Quantum Monte Carlo Simulation of Frustrated Kondo Lattice Models

NASA Astrophysics Data System (ADS)

Sato, Toshihiro; Assaad, Fakher F.; Grover, Tarun

2018-03-01

The absence of the negative sign problem in quantum Monte Carlo simulations of spin and fermion systems has different origins. World-line based algorithms for spins require positivity of matrix elements whereas auxiliary field approaches for fermions depend on symmetries such as particle-hole symmetry. For negative-sign-free spin and fermionic systems, we show that one can formulate a negative-sign-free auxiliary field quantum Monte Carlo algorithm that allows Kondo coupling of fermions with the spins. Using this general approach, we study a half-filled Kondo lattice model on the honeycomb lattice with geometric frustration. In addition to the conventional Kondo insulator and antiferromagnetically ordered phases, we find a partial Kondo screened state where spins are selectively screened so as to alleviate frustration, and the lattice rotation symmetry is broken nematically.

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).

Direct simulation Monte Carlo method for the Uehling-Uhlenbeck-Boltzmann equation.

PubMed

Garcia, Alejandro L; Wagner, Wolfgang

2003-11-01

In this paper we describe a direct simulation Monte Carlo algorithm for the Uehling-Uhlenbeck-Boltzmann equation in terms of Markov processes. This provides a unifying framework for both the classical Boltzmann case as well as the Fermi-Dirac and Bose-Einstein cases. We establish the foundation of the algorithm by demonstrating its link to the kinetic equation. By numerical experiments we study its sensitivity to the number of simulation particles and to the discretization of the velocity space, when approximating the steady-state distribution.

A highly optimized vectorized code for Monte Carlo simulations of SU(3) lattice gauge theories

NASA Technical Reports Server (NTRS)

Barkai, D.; Moriarty, K. J. M.; Rebbi, C.

1984-01-01

New methods are introduced for improving the performance of the vectorized Monte Carlo SU(3) lattice gauge theory algorithm using the CDC CYBER 205. Structure, algorithm and programming considerations are discussed. The performance achieved for a 16(4) lattice on a 2-pipe system may be phrased in terms of the link update time or overall MFLOPS rates. For 32-bit arithmetic, it is 36.3 microsecond/link for 8 hits per iteration (40.9 microsecond for 10 hits) or 101.5 MFLOPS.

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

DOE PAGES

McDaniel, Tyler; D’Azevedo, Ed F.; Li, Ying Wai; ...

2017-11-07

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is therefore formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with applicationmore » of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. Here this procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi- core CPUs and GPUs.« less

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

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

McDaniel, Tyler; D’Azevedo, Ed F.; Li, Ying Wai

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is therefore formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with applicationmore » of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. Here this procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi- core CPUs and GPUs.« less

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo.

PubMed

McDaniel, T; D'Azevedo, E F; Li, Y W; Wong, K; Kent, P R C

2017-11-07

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is, therefore, formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with an application of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. This procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo, where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi-core central processing units and graphical processing units.

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

NASA Astrophysics Data System (ADS)

McDaniel, T.; D'Azevedo, E. F.; Li, Y. W.; Wong, K.; Kent, P. R. C.

2017-11-01

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is, therefore, formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with an application of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. This procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo, where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi-core central processing units and graphical processing units.

Distance between configurations in Markov chain Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Fukuma, Masafumi; Matsumoto, Nobuyuki; Umeda, Naoya

2017-12-01

For a given Markov chain Monte Carlo algorithm we introduce a distance between two configurations that quantifies the difficulty of transition from one configuration to the other configuration. We argue that the distance takes a universal form for the class of algorithms which generate local moves in the configuration space. We explicitly calculate the distance for the Langevin algorithm, and show that it certainly has desired and expected properties as distance. We further show that the distance for a multimodal distribution gets dramatically reduced from a large value by the introduction of a tempering method. We also argue that, when the original distribution is highly multimodal with large number of degenerate vacua, an anti-de Sitter-like geometry naturally emerges in the extended configuration space.

The impact of low-Z and high-Z metal implants in IMRT: A Monte Carlo study of dose inaccuracies in commercial dose algorithms

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

Spadea, Maria Francesca, E-mail: mfspadea@unicz.it; Verburg, Joost Mathias; Seco, Joao

2014-01-15

Purpose: The aim of the study was to evaluate the dosimetric impact of low-Z and high-Z metallic implants on IMRT plans. Methods: Computed tomography (CT) scans of three patients were analyzed to study effects due to the presence of Titanium (low-Z), Platinum and Gold (high-Z) inserts. To eliminate artifacts in CT images, a sinogram-based metal artifact reduction algorithm was applied. IMRT dose calculations were performed on both the uncorrected and corrected images using a commercial planning system (convolution/superposition algorithm) and an in-house Monte Carlo platform. Dose differences between uncorrected and corrected datasets were computed and analyzed using gamma index (Pγ{submore » <1}) and setting 2 mm and 2% as distance to agreement and dose difference criteria, respectively. Beam specific depth dose profiles across the metal were also examined. Results: Dose discrepancies between corrected and uncorrected datasets were not significant for low-Z material. High-Z materials caused under-dosage of 20%–25% in the region surrounding the metal and over dosage of 10%–15% downstream of the hardware. Gamma index test yielded Pγ{sub <1}>99% for all low-Z cases; while for high-Z cases it returned 91% < Pγ{sub <1}< 99%. Analysis of the depth dose curve of a single beam for low-Z cases revealed that, although the dose attenuation is altered inside the metal, it does not differ downstream of the insert. However, for high-Z metal implants the dose is increased up to 10%–12% around the insert. In addition, Monte Carlo method was more sensitive to the presence of metal inserts than superposition/convolution algorithm. Conclusions: The reduction in terms of dose of metal artifacts in CT images is relevant for high-Z implants. In this case, dose distribution should be calculated using Monte Carlo algorithms, given their superior accuracy in dose modeling in and around the metal. In addition, the knowledge of the composition of metal inserts improves the accuracy of the Monte Carlo dose calculation significantly.« less

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

Jakeman, John D.; Narayan, Akil; Zhou, Tao

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions

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

Jakeman, John D.; Narayan, Akil; Zhou, Tao

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions

DOE PAGES

Jakeman, John D.; Narayan, Akil; Zhou, Tao

2017-06-22

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

An Ensemble-Based Smoother with Retrospectively Updated Weights for Highly Nonlinear Systems

NASA Technical Reports Server (NTRS)

Chin, T. M.; Turmon, M. J.; Jewell, J. B.; Ghil, M.

2006-01-01

Monte Carlo computational methods have been introduced into data assimilation for nonlinear systems in order to alleviate the computational burden of updating and propagating the full probability distribution. By propagating an ensemble of representative states, algorithms like the ensemble Kalman filter (EnKF) and the resampled particle filter (RPF) rely on the existing modeling infrastructure to approximate the distribution based on the evolution of this ensemble. This work presents an ensemble-based smoother that is applicable to the Monte Carlo filtering schemes like EnKF and RPF. At the minor cost of retrospectively updating a set of weights for ensemble members, this smoother has demonstrated superior capabilities in state tracking for two highly nonlinear problems: the double-well potential and trivariate Lorenz systems. The algorithm does not require retrospective adaptation of the ensemble members themselves, and it is thus suited to a streaming operational mode. The accuracy of the proposed backward-update scheme in estimating non-Gaussian distributions is evaluated by comparison to the more accurate estimates provided by a Markov chain Monte Carlo algorithm.

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

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

O'Brien, M. J.; Brantley, P. S.

2015-01-20

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2 21 = 2,097,152 MPI processes on the IBMmore » BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.« less

Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces

NASA Astrophysics Data System (ADS)

Neukart, Florian; Von Dollen, David; Seidel, Christian; Compostella, Gabriele

2017-12-01

Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems, have been subject to multiple analyses in research, with the aim of characterizing the technology's usefulness for optimization and sampling tasks. Here, we present a way to partially embed both Monte Carlo policy iteration for finding an optimal policy on random observations, as well as how to embed n sub-optimal state-value functions for approximating an improved state-value function given a policy for finite horizon games with discrete state spaces on a D-Wave 2000Q quantum processing unit (QPU). We explain how both problems can be expressed as a quadratic unconstrained binary optimization (QUBO) problem, and show that quantum-enhanced Monte Carlo policy evaluation allows for finding equivalent or better state-value functions for a given policy with the same number episodes compared to a purely classical Monte Carlo algorithm. Additionally, we describe a quantum-classical policy learning algorithm. Our first and foremost aim is to explain how to represent and solve parts of these problems with the help of the QPU, and not to prove supremacy over every existing classical policy evaluation algorithm.

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

NASA Astrophysics Data System (ADS)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

Modelling maximum river flow by using Bayesian Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Cheong, R. Y.; Gabda, D.

2017-09-01

Analysis of flood trends is vital since flooding threatens human living in terms of financial, environment and security. The data of annual maximum river flows in Sabah were fitted into generalized extreme value (GEV) distribution. Maximum likelihood estimator (MLE) raised naturally when working with GEV distribution. However, previous researches showed that MLE provide unstable results especially in small sample size. In this study, we used different Bayesian Markov Chain Monte Carlo (MCMC) based on Metropolis-Hastings algorithm to estimate GEV parameters. Bayesian MCMC method is a statistical inference which studies the parameter estimation by using posterior distribution based on Bayes’ theorem. Metropolis-Hastings algorithm is used to overcome the high dimensional state space faced in Monte Carlo method. This approach also considers more uncertainty in parameter estimation which then presents a better prediction on maximum river flow in Sabah.

Simulated Stochastic Approximation Annealing for Global Optimization with a Square-Root Cooling Schedule

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

Liang, Faming; Cheng, Yichen; Lin, Guang

2014-06-13

Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to have such a long CPU time. This paper proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation Markov chain Monte Carlo, it is shown that themore » new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, e.g., a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors.« less

Pharos: Collating protein information to shed light on the druggable genome.

PubMed

Nguyen, Dac-Trung; Mathias, Stephen; Bologa, Cristian; Brunak, Soren; Fernandez, Nicolas; Gaulton, Anna; Hersey, Anne; Holmes, Jayme; Jensen, Lars Juhl; Karlsson, Anneli; Liu, Guixia; Ma'ayan, Avi; Mandava, Geetha; Mani, Subramani; Mehta, Saurabh; Overington, John; Patel, Juhee; Rouillard, Andrew D; Schürer, Stephan; Sheils, Timothy; Simeonov, Anton; Sklar, Larry A; Southall, Noel; Ursu, Oleg; Vidovic, Dusica; Waller, Anna; Yang, Jeremy; Jadhav, Ajit; Oprea, Tudor I; Guha, Rajarshi

2017-01-04

The 'druggable genome' encompasses several protein families, but only a subset of targets within them have attracted significant research attention and thus have information about them publicly available. The Illuminating the Druggable Genome (IDG) program was initiated in 2014, has the goal of developing experimental techniques and a Knowledge Management Center (KMC) that would collect and organize information about protein targets from four families, representing the most common druggable targets with an emphasis on understudied proteins. Here, we describe two resources developed by the KMC: the Target Central Resource Database (TCRD) which collates many heterogeneous gene/protein datasets and Pharos (https://pharos.nih.gov), a multimodal web interface that presents the data from TCRD. We briefly describe the types and sources of data considered by the KMC and then highlight features of the Pharos interface designed to enable intuitive access to the IDG knowledgebase. The aim of Pharos is to encourage 'serendipitous browsing', whereby related, relevant information is made easily discoverable. We conclude by describing two use cases that highlight the utility of Pharos and TCRD. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Helping small babies survive: an evaluation of facility-based Kangaroo Mother Care implementation progress in Uganda

PubMed Central

Aliganyira, Patrick; Kerber, Kate; Davy, Karen; Gamache, Nathalie; Sengendo, Namaala Hanifah; Bergh, Anne-Marie

2014-01-01

Introduction Prematurity is the leading cause of newborn death in Uganda, accounting for 38% of the nation's 39,000 annual newborn deaths. Kangaroo mother care is a high-impact; cost-effective intervention that has been prioritized in policy in Uganda but implementation has been limited. Methods A standardised, cross-sectional, mixed-method evaluation design was used, employing semi-structured key-informant interviews and observations in 11 health care facilities implementing kangaroo mother care in Uganda. Results The facilities visited scored between 8.28 and 21.72 out of the possible 30 points with a median score of 14.71. Two of the 3 highest scoring hospitals were private, not-for-profit hospitals whereas the second highest scoring hospital was a central teaching hospital. Facilities with KMC services are not equally distributed throughout the country. Only 4 regions (Central 1, Central 2, East-Central and Southwest) plus the City of Kampala were identified as having facilities providing KMC services. Conclusion KMC services are not instituted with consistent levels of quality and are often dependent on private partner support. With increasing attention globally and in country, Uganda is in a unique position to accelerate access to and quality of health services for small babies across the country. PMID:25667699

Helping small babies survive: an evaluation of facility-based Kangaroo Mother Care implementation progress in Uganda.

PubMed

Aliganyira, Patrick; Kerber, Kate; Davy, Karen; Gamache, Nathalie; Sengendo, Namaala Hanifah; Bergh, Anne-Marie

2014-01-01

Prematurity is the leading cause of newborn death in Uganda, accounting for 38% of the nation's 39,000 annual newborn deaths. Kangaroo mother care is a high-impact; cost-effective intervention that has been prioritized in policy in Uganda but implementation has been limited. A standardised, cross-sectional, mixed-method evaluation design was used, employing semi-structured key-informant interviews and observations in 11 health care facilities implementing kangaroo mother care in Uganda. The facilities visited scored between 8.28 and 21.72 out of the possible 30 points with a median score of 14.71. Two of the 3 highest scoring hospitals were private, not-for-profit hospitals whereas the second highest scoring hospital was a central teaching hospital. Facilities with KMC services are not equally distributed throughout the country. Only 4 regions (Central 1, Central 2, East-Central and Southwest) plus the City of Kampala were identified as having facilities providing KMC services. KMC services are not instituted with consistent levels of quality and are often dependent on private partner support. With increasing attention globally and in country, Uganda is in a unique position to accelerate access to and quality of health services for small babies across the country.

Simulation of Nanowires on Metal Vicinal Surfaces: Effect of Growth Parameters and Energetic Barriers

NASA Astrophysics Data System (ADS)

Hamouda, Ajmi B. H.; Blel, Sonia; Einstein, T. L.

2012-02-01

Growing one-dimensional metal structures is an important task in the investigation of the electronic and magnetic properties of new devices. We used kinetic Monte-Carlo (kMC) method to simulate the formation of nanowires of several metallic and non-metallic adatoms on Cu and Pt vicinal surfaces. We found that mono-atomic chains form on step-edges due to energetic barriers (the so-called Ehrlich-shwoebel and exchange barriers) on step-edge. Creation of perfect wires is found to depend on growth parameters and binding energies. We measure the filling ratio of nanowires for different chemical species in a wide range of temperature and flux. Perfect wires were obtained at lower deposition rate for all tested adatoms, however we notice different temperature ranges. Our results were compared with experimental ones [Gambardella et al., Surf. Sci.449, 93-103 (2000), PRB 61, 2254-2262, (2000)]. We review the role of impurities in nanostructuring of surfaces [Hamouda et al., Phys. Rev. B 83, 035423, (2011)] and discuss the effect of their energetic barriers on the obtained quality of nanowires. Our work provides experimentalists with optimum growth parameters for the creation of a uniform distribution of wires on surfaces.

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.

Monte Carlo treatment planning with modulated electron radiotherapy: framework development and application

NASA Astrophysics Data System (ADS)

Alexander, Andrew William

Within the field of medical physics, Monte Carlo radiation transport simulations are considered to be the most accurate method for the determination of dose distributions in patients. The McGill Monte Carlo treatment planning system (MMCTP), provides a flexible software environment to integrate Monte Carlo simulations with current and new treatment modalities. A developing treatment modality called energy and intensity modulated electron radiotherapy (MERT) is a promising modality, which has the fundamental capabilities to enhance the dosimetry of superficial targets. An objective of this work is to advance the research and development of MERT with the end goal of clinical use. To this end, we present the MMCTP system with an integrated toolkit for MERT planning and delivery of MERT fields. Delivery is achieved using an automated "few leaf electron collimator" (FLEC) and a controller. Aside from the MERT planning toolkit, the MMCTP system required numerous add-ons to perform the complex task of large-scale autonomous Monte Carlo simulations. The first was a DICOM import filter, followed by the implementation of DOSXYZnrc as a dose calculation engine and by logic methods for submitting and updating the status of Monte Carlo simulations. Within this work we validated the MMCTP system with a head and neck Monte Carlo recalculation study performed by a medical dosimetrist. The impact of MMCTP lies in the fact that it allows for systematic and platform independent large-scale Monte Carlo dose calculations for different treatment sites and treatment modalities. In addition to the MERT planning tools, various optimization algorithms were created external to MMCTP. The algorithms produced MERT treatment plans based on dose volume constraints that employ Monte Carlo pre-generated patient-specific kernels. The Monte Carlo kernels are generated from patient-specific Monte Carlo dose distributions within MMCTP. The structure of the MERT planning toolkit software and optimization algorithms are demonstrated. We investigated the clinical significance of MERT on spinal irradiation, breast boost irradiation, and a head and neck sarcoma cancer site using several parameters to analyze the treatment plans. Finally, we investigated the idea of mixed beam photon and electron treatment planning. Photon optimization treatment planning tools were included within the MERT planning toolkit for the purpose of mixed beam optimization. In conclusion, this thesis work has resulted in the development of an advanced framework for photon and electron Monte Carlo treatment planning studies and the development of an inverse planning system for photon, electron or mixed beam radiotherapy (MBRT). The justification and validation of this work is found within the results of the planning studies, which have demonstrated dosimetric advantages to using MERT or MBRT in comparison to clinical treatment alternatives.

Simulation-Based Model Checking for Nondeterministic Systems and Rare Events

DTIC Science & Technology

2016-03-24

year, we have investigated AO* search and Monte Carlo Tree Search algorithms to complement and enhance CMU’s SMCMDP. 1 Final Report, March 14... tree , so we can use it to find the probability of reachability for a property in PRISM’s Probabilistic LTL. By finding the maximum probability of...savings, particularly when handling very large models. 2.3 Monte Carlo Tree Search The Monte Carlo sampling process in SMCMDP can take a long time to

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

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.

Interannual variability of summertime outgoing longwave radiation over the Maritime Continent in relation to East Asian summer monsoon anomalies

NASA Astrophysics Data System (ADS)

Xu, Qi; Guan, Zhaoyong

2017-08-01

The Maritime Continent (MC) is under influences of both the tropical Pacific and the Indian Ocean. Anomalous convective activities over the MC have significant impacts on the East Asian summer monsoon (EASM) and climate in China. In the present study, the variation in convective activity over the MC in boreal summer and its relationship to EASM anomalies are investigated based on regression analysis of NCEP-NCAR reanalysis and CMAP [Climate Prediction Center (CPC) Merged Analysis of Precipitation] data, with a focus on the impacts of ENSO and the Indian Ocean Dipole (IOD). The most significant interannual variability of convective activity is found over 10°S-10°N, 95°-145°E, which can be roughly defined as the key area of the MC (hereafter, KMC). Outgoing longwave radiation anomaly (OLRA) exhibits 3- to 7-yr periodicities over the KMC, and around 70% of the OLRA variance can be explained by the ENSO signal. However, distinct convection and precipitation anomalies still exist over this region after the ENSO and IOD signals are removed. Abnormally low precipitation always corresponds to positive OLRA over the KMC when negative diabatic heating anomalies and anomalous cooling of the atmospheric column lead to abnormal descending motion over this region. Correspondingly, abnormal divergence occurs in the lower troposphere while convergence occurs in the upper troposphere, triggering an East Asia-Pacific/Pacific-Japan (EAP/PJ)-like anomalous wave train that propagates northeastward and leads to a significant positive precipitation anomaly from the Yangtze River valley in China to the islands of Japan. This EAP/PJ-like wave pattern becomes even clearer after the removal of the ENSO signal and the combined effects of ENSO and IOD, suggesting that convective anomalies over the KMC have an important impact on EASM anomalies. The above results provide important clues for the prediction of EASM anomalies and associated summer precipitation anomalies in China.

Self-learning Monte Carlo with deep neural networks

NASA Astrophysics Data System (ADS)

Shen, Huitao; Liu, Junwei; Fu, Liang

2018-05-01

The self-learning Monte Carlo (SLMC) method is a general algorithm to speedup MC simulations. Its efficiency has been demonstrated in various systems by introducing an effective model to propose global moves in the configuration space. In this paper, we show that deep neural networks can be naturally incorporated into SLMC, and without any prior knowledge can learn the original model accurately and efficiently. Demonstrated in quantum impurity models, we reduce the complexity for a local update from O (β2) in Hirsch-Fye algorithm to O (β lnβ ) , which is a significant speedup especially for systems at low temperatures.

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.

Vectorization of a Monte Carlo simulation scheme for nonequilibrium gas dynamics

NASA Technical Reports Server (NTRS)

Boyd, Iain D.

1991-01-01

Significant improvement has been obtained in the numerical performance of a Monte Carlo scheme for the analysis of nonequilibrium gas dynamics through an implementation of the algorithm which takes advantage of vector hardware, as presently demonstrated through application to three different problems. These are (1) a 1D standing-shock wave; (2) the flow of an expanding gas through an axisymmetric nozzle; and (3) the hypersonic flow of Ar gas over a 3D wedge. Problem (3) is illustrative of the greatly increased number of molecules which the simulation may involve, thanks to improved algorithm performance.

Multicanonical hybrid Monte Carlo algorithm: Boosting simulations of compact QED

NASA Astrophysics Data System (ADS)

Arnold, G.; Schilling, K.; Lippert, Th.

1999-03-01

We demonstrate that substantial progress can be achieved in the study of the phase structure of four-dimensional compact QED by a joint use of hybrid Monte Carlo and multicanonical algorithms through an efficient parallel implementation. This is borne out by the observation of considerable speedup of tunnelling between the metastable states, close to the phase transition, on the Wilson line. We estimate that the creation of adequate samples (with order 100 flip-flops) becomes a matter of half a year's run time at 2 Gflops sustained performance for lattices of size up to 244.

A novel Monte Carlo algorithm for simulating crystals with McStas

NASA Astrophysics Data System (ADS)

Alianelli, L.; Sánchez del Río, M.; Felici, R.; Andersen, K. H.; Farhi, E.

2004-07-01

We developed an original Monte Carlo algorithm for the simulation of Bragg diffraction by mosaic, bent and gradient crystals. It has practical applications, as it can be used for simulating imperfect crystals (monochromators, analyzers and perhaps samples) in neutron ray-tracing packages, like McStas. The code we describe here provides a detailed description of the particle interaction with the microscopic homogeneous regions composing the crystal, therefore it can be used also for the calculation of quantities having a conceptual interest, as multiple scattering, or for the interpretation of experiments aiming at characterizing crystals, like diffraction topographs.

Probabilistic analysis algorithm for UA slope software program.

DOT National Transportation Integrated Search

2013-12-01

A reliability-based computational algorithm for using a single row and equally spaced drilled shafts to : stabilize an unstable slope has been developed in this research. The Monte-Carlo simulation (MCS) : technique was used in the previously develop...

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger

2008-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A inflight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger; Richard, Michael

2007-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A in-flight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

Estimating rare events in biochemical systems using conditional sampling.

PubMed

Sundar, V S

2017-01-28

The paper focuses on development of variance reduction strategies to estimate rare events in biochemical systems. Obtaining this probability using brute force Monte Carlo simulations in conjunction with the stochastic simulation algorithm (Gillespie's method) is computationally prohibitive. To circumvent this, important sampling tools such as the weighted stochastic simulation algorithm and the doubly weighted stochastic simulation algorithm have been proposed. However, these strategies require an additional step of determining the important region to sample from, which is not straightforward for most of the problems. In this paper, we apply the subset simulation method, developed as a variance reduction tool in the context of structural engineering, to the problem of rare event estimation in biochemical systems. The main idea is that the rare event probability is expressed as a product of more frequent conditional probabilities. These conditional probabilities are estimated with high accuracy using Monte Carlo simulations, specifically the Markov chain Monte Carlo method with the modified Metropolis-Hastings algorithm. Generating sample realizations of the state vector using the stochastic simulation algorithm is viewed as mapping the discrete-state continuous-time random process to the standard normal random variable vector. This viewpoint opens up the possibility of applying more sophisticated and efficient sampling schemes developed elsewhere to problems in stochastic chemical kinetics. The results obtained using the subset simulation method are compared with existing variance reduction strategies for a few benchmark problems, and a satisfactory improvement in computational time is demonstrated.

Parallel Monte Carlo Search for Hough Transform

NASA Astrophysics Data System (ADS)

Lopes, Raul H. C.; Franqueira, Virginia N. L.; Reid, Ivan D.; Hobson, Peter R.

2017-10-01

We investigate the problem of line detection in digital image processing and in special how state of the art algorithms behave in the presence of noise and whether CPU efficiency can be improved by the combination of a Monte Carlo Tree Search, hierarchical space decomposition, and parallel computing. The starting point of the investigation is the method introduced in 1962 by Paul Hough for detecting lines in binary images. Extended in the 1970s to the detection of space forms, what came to be known as Hough Transform (HT) has been proposed, for example, in the context of track fitting in the LHC ATLAS and CMS projects. The Hough Transform transfers the problem of line detection, for example, into one of optimization of the peak in a vote counting process for cells which contain the possible points of candidate lines. The detection algorithm can be computationally expensive both in the demands made upon the processor and on memory. Additionally, it can have a reduced effectiveness in detection in the presence of noise. Our first contribution consists in an evaluation of the use of a variation of the Radon Transform as a form of improving theeffectiveness of line detection in the presence of noise. Then, parallel algorithms for variations of the Hough Transform and the Radon Transform for line detection are introduced. An algorithm for Parallel Monte Carlo Search applied to line detection is also introduced. Their algorithmic complexities are discussed. Finally, implementations on multi-GPU and multicore architectures are discussed.

The Linked Neighbour List (LNL) method for fast off-lattice Monte Carlo simulations of fluids

NASA Astrophysics Data System (ADS)

Mazzeo, M. D.; Ricci, M.; Zannoni, C.

2010-03-01

We present a new algorithm, called linked neighbour list (LNL), useful to substantially speed up off-lattice Monte Carlo simulations of fluids by avoiding the computation of the molecular energy before every attempted move. We introduce a few variants of the LNL method targeted to minimise memory footprint or augment memory coherence and cache utilisation. Additionally, we present a few algorithms which drastically accelerate neighbour finding. We test our methods on the simulation of a dense off-lattice Gay-Berne fluid subjected to periodic boundary conditions observing a speedup factor of about 2.5 with respect to a well-coded implementation based on a conventional link-cell. We provide several implementation details of the different key data structures and algorithms used in this work.

Asteroid mass estimation with Markov-chain Monte Carlo

NASA Astrophysics Data System (ADS)

Siltala, L.; Granvik, M.

2017-09-01

We have developed a new Markov-chain Monte Carlo-based algorithm for asteroid mass estimation based on mutual encounters and tested it for several different asteroids. Our results are in line with previous literature values but suggest that uncertainties of prior estimates may be misleading as a consequence of using linearized methods.

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

Bolding, Simon R.; Cleveland, Mathew Allen; Morel, Jim E.

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

Kinetic Monte Carlo simulations of fluorine and vacancies concentration at the CeO2(111) surface

NASA Astrophysics Data System (ADS)

Mattiello, S.; Kolling, S.; Heiliger, C.

2017-09-01

Recently, a new identification of the experimental depressions of scanning tunnelling microscopy images on the {{CeO}}2(111) surface as fluorine impurities has been proposed in Kullgren et al (2014 Phys. Rev. Lett. 112 156102). In particular, the high immobility of the depressions seems to be in contradiction with the low diffusion barrier for the oxygen vacancies. Consequently, the oxygen vacancies concentration has to disappear. The first aim of this paper is to confirm dynamically the recent interpretation of the experimental finding. For this purpose, we investigate the competition between fluorine and oxygen vacancies using two dimensional kinetic Monte Carlo simulations (kMC) as compared to an appropriate Langmuir model. We calculate the concentration of the vacancies and of the fluorine for the surface (111) of {{CeO}}2 for a UHV condition as a function of the fluorine-oxygen mixture in the gas phase as well as of the binding energies of fluorine and oxygen. We found that at a temperature of T=573 {{K}}, at which the experimental measurements were conducted, vacancies cannot exist. This confirms the possibility of fluorine impurities in Kullgren et al (2014 Phys. Rev. Lett. 112 156102). The second aim of the present paper is to perform a first dynamical estimation of the fluorine binding energy value {E}{Fl} that allows one to describe the experimental data in Pieper et al (2012 Phys. Chem. Chem. Phys. 14 15361). Using 2D-kMC simulations, we found {E}{Fl}\\in [-5.53,-5.27] {eV} which can be used for comparison to density functional theory calculations in further works.

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.

A hybrid MD-kMC algorithm for folding proteins in explicit solvent.

PubMed

Peter, Emanuel Karl; Shea, Joan-Emma

2014-04-14

We present a novel hybrid MD-kMC algorithm that is capable of efficiently folding proteins in explicit solvent. We apply this algorithm to the folding of a small protein, Trp-Cage. Different kMC move sets that capture different possible rate limiting steps are implemented. The first uses secondary structure formation as a relevant rate event (a combination of dihedral rotations and hydrogen-bonding formation and breakage). The second uses tertiary structure formation events through formation of contacts via translational moves. Both methods fold the protein, but via different mechanisms and with different folding kinetics. The first method leads to folding via a structured helical state, with kinetics fit by a single exponential. The second method leads to folding via a collapsed loop, with kinetics poorly fit by single or double exponentials. In both cases, folding times are faster than experimentally reported values, The secondary and tertiary move sets are integrated in a third MD-kMC implementation, which now leads to folding of the protein via both pathways, with single and double-exponential fits to the rates, and to folding rates in good agreement with experimental values. The competition between secondary and tertiary structure leads to a longer search for the helix-rich intermediate in the case of the first pathway, and to the emergence of a kinetically trapped long-lived molten-globule collapsed state in the case of the second pathway. The algorithm presented not only captures experimentally observed folding intermediates and kinetics, but yields insights into the relative roles of local and global interactions in determining folding mechanisms and rates.

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…

SKIRT: The design of a suite of input models for Monte Carlo radiative transfer simulations

NASA Astrophysics Data System (ADS)

Baes, M.; Camps, P.

2015-09-01

The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the literature, and many different Monte Carlo codes are publicly available. On the contrary, the design of a suite of components that can be used for the distribution of sources and sinks in radiative transfer codes has received very little attention. The availability of such models, with different degrees of complexity, has many benefits. For example, they can serve as toy models to test new physical ingredients, or as parameterised models for inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires algorithms to efficiently generate random positions from 3D density distributions. We describe the design of a flexible suite of components for the Monte Carlo radiative transfer code SKIRT. The design is based on a combination of basic building blocks (which can be either analytical toy models or numerical models defined on grids or a set of particles) and the extensive use of decorators that combine and alter these building blocks to more complex structures. For a number of decorators, e.g. those that add spiral structure or clumpiness, we provide a detailed description of the algorithms that can be used to generate random positions. Advantages of this decorator-based design include code transparency, the avoidance of code duplication, and an increase in code maintainability. Moreover, since decorators can be chained without problems, very complex models can easily be constructed out of simple building blocks. Finally, based on a number of test simulations, we demonstrate that our design using customised random position generators is superior to a simpler design based on a generic black-box random position generator.

Wavelet Monte Carlo dynamics: A new algorithm for simulating the hydrodynamics of interacting Brownian particles

NASA Astrophysics Data System (ADS)

Dyer, Oliver T.; Ball, Robin C.

2017-03-01

We develop a new algorithm for the Brownian dynamics of soft matter systems that evolves time by spatially correlated Monte Carlo moves. The algorithm uses vector wavelets as its basic moves and produces hydrodynamics in the low Reynolds number regime propagated according to the Oseen tensor. When small moves are removed, the correlations closely approximate the Rotne-Prager tensor, itself widely used to correct for deficiencies in Oseen. We also include plane wave moves to provide the longest range correlations, which we detail for both infinite and periodic systems. The computational cost of the algorithm scales competitively with the number of particles simulated, N, scaling as N In N in homogeneous systems and as N in dilute systems. In comparisons to established lattice Boltzmann and Brownian dynamics algorithms, the wavelet method was found to be only a factor of order 1 times more expensive than the cheaper lattice Boltzmann algorithm in marginally semi-dilute simulations, while it is significantly faster than both algorithms at large N in dilute simulations. We also validate the algorithm by checking that it reproduces the correct dynamics and equilibrium properties of simple single polymer systems, as well as verifying the effect of periodicity on the mobility tensor.

Exact Dynamics via Poisson Process: a unifying Monte Carlo paradigm

NASA Astrophysics Data System (ADS)

Gubernatis, James

2014-03-01

A common computational task is solving a set of ordinary differential equations (o.d.e.'s). A little known theorem says that the solution of any set of o.d.e.'s is exactly solved by the expectation value over a set of arbitary Poisson processes of a particular function of the elements of the matrix that defines the o.d.e.'s. The theorem thus provides a new starting point to develop real and imaginary-time continous-time solvers for quantum Monte Carlo algorithms, and several simple observations enable various quantum Monte Carlo techniques and variance reduction methods to transfer to a new context. I will state the theorem, note a transformation to a very simple computational scheme, and illustrate the use of some techniques from the directed-loop algorithm in context of the wavefunction Monte Carlo method that is used to solve the Lindblad master equation for the dynamics of open quantum systems. I will end by noting that as the theorem does not depend on the source of the o.d.e.'s coming from quantum mechanics, it also enables the transfer of continuous-time methods from quantum Monte Carlo to the simulation of various classical equations of motion heretofore only solved deterministically.

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

NASA Astrophysics Data System (ADS)

Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik

2018-05-01

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.

Path-integral Monte Carlo method for Rényi entanglement entropies.

PubMed

Herdman, C M; Inglis, Stephen; Roy, P-N; Melko, R G; Del Maestro, A

2014-07-01

We introduce a quantum Monte Carlo algorithm to measure the Rényi entanglement entropies in systems of interacting bosons in the continuum. This approach is based on a path-integral ground state method that can be applied to interacting itinerant bosons in any spatial dimension with direct relevance to experimental systems of quantum fluids. We demonstrate how it may be used to compute spatial mode entanglement, particle partitioned entanglement, and the entanglement of particles, providing insights into quantum correlations generated by fluctuations, indistinguishability, and interactions. We present proof-of-principle calculations and benchmark against an exactly soluble model of interacting bosons in one spatial dimension. As this algorithm retains the fundamental polynomial scaling of quantum Monte Carlo when applied to sign-problem-free models, future applications should allow for the study of entanglement entropy in large-scale many-body systems of interacting bosons.

MUSiC - A general search for deviations from monte carlo predictions in CMS

NASA Astrophysics Data System (ADS)

Biallass, Philipp A.; CMS Collaboration

2009-06-01

A model independent analysis approach in CMS is presented, systematically scanning the data for deviations from the Monte Carlo expectation. Such an analysis can contribute to the understanding of the detector and the tuning of the event generators. Furthermore, due to the minimal theoretical bias this approach is sensitive to a variety of models of new physics, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. The importance of systematic uncertainties is outlined, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving Supersymmetry and new heavy gauge bosons are used as an input to the search algorithm.

MUSiC - A Generic Search for Deviations from Monte Carlo Predictions in CMS

NASA Astrophysics Data System (ADS)

Hof, Carsten

2009-05-01

We present a model independent analysis approach, systematically scanning the data for deviations from the Standard Model Monte Carlo expectation. Such an analysis can contribute to the understanding of the CMS detector and the tuning of the event generators. Furthermore, due to the minimal theoretical bias this approach is sensitive to a variety of models of new physics, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. We outline the importance of systematic uncertainties, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving supersymmetry and new heavy gauge bosons have been used as an input to the search algorithm.

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.

Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Jiang, Zhang; Smelyanskiy, Vadim N.; Boixo, Sergio; Isakov, Sergei V.; Neven, Hartmut; Mazzola, Guglielmo; Troyer, Matthias

2015-01-01

Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.

Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation

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

Shang, Yu; Lin, Yu; Yu, Guoqiang, E-mail: guoqiang.yu@uky.edu

2014-05-12

Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αD{sub B}) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction of αD{sub B}. The volume and geometry of the measured tissue were incorporated in the Monte Carlo simulation, which overcome the semi-infinite restrictions. The algorithm was tested using computer simulations on four tissue models with varied volumes/geometries and applied on an in vivo strokemore » model of mouse. Computer simulations shows that the high-order (N ≥ 5) linear algorithm was more accurate in extracting αD{sub B} (errors < ±2%) from the noise-free DCS data than the semi-infinite solution (errors: −5.3% to −18.0%) for different tissue models. Although adding random noises to DCS data resulted in αD{sub B} variations, the mean values of errors in extracting αD{sub B} were similar to those reconstructed from the noise-free DCS data. In addition, the errors in extracting the relative changes of αD{sub B} using both linear algorithm and semi-infinite solution were fairly small (errors < ±2.0%) and did not rely on the tissue volume/geometry. The experimental results from the in vivo stroke mice agreed with those in simulations, demonstrating the robustness of the linear algorithm. DCS with the high-order linear algorithm shows the potential for the inter-subject comparison and longitudinal monitoring of absolute BFI in a variety of tissues/organs with different volumes/geometries.« less

An Improved Elastic and Nonelastic Neutron Transport Algorithm for Space Radiation

NASA Technical Reports Server (NTRS)

Clowdsley, Martha S.; Wilson, John W.; Heinbockel, John H.; Tripathi, R. K.; Singleterry, Robert C., Jr.; Shinn, Judy L.

2000-01-01

A neutron transport algorithm including both elastic and nonelastic particle interaction processes for use in space radiation protection for arbitrary shield material is developed. The algorithm is based upon a multiple energy grouping and analysis of the straight-ahead Boltzmann equation by using a mean value theorem for integrals. The algorithm is then coupled to the Langley HZETRN code through a bidirectional neutron evaporation source term. Evaluation of the neutron fluence generated by the solar particle event of February 23, 1956, for an aluminum water shield-target configuration is then compared with MCNPX and LAHET Monte Carlo calculations for the same shield-target configuration. With the Monte Carlo calculation as a benchmark, the algorithm developed in this paper showed a great improvement in results over the unmodified HZETRN solution. In addition, a high-energy bidirectional neutron source based on a formula by Ranft showed even further improvement of the fluence results over previous results near the front of the water target where diffusion out the front surface is important. Effects of improved interaction cross sections are modest compared with the addition of the high-energy bidirectional source terms.

Delving Into Dissipative Quantum Dynamics: From Approximate to Numerically Exact Approaches

NASA Astrophysics Data System (ADS)

Chen, Hsing-Ta

In this thesis, I explore dissipative quantum dynamics of several prototypical model systems via various approaches, ranging from approximate to numerically exact schemes. In particular, in the realm of the approximate I explore the accuracy of Pade-resummed master equations and the fewest switches surface hopping (FSSH) algorithm for the spin-boson model, and non-crossing approximations (NCA) for the Anderson-Holstein model. Next, I develop new and exact Monte Carlo approaches and test them on the spin-boson model. I propose well-defined criteria for assessing the accuracy of Pade-resummed quantum master equations, which correctly demarcate the regions of parameter space where the Pade approximation is reliable. I continue the investigation of spin-boson dynamics by benchmark comparisons of the semiclassical FSSH algorithm to exact dynamics over a wide range of parameters. Despite small deviations from golden-rule scaling in the Marcus regime, standard surface hopping algorithm is found to be accurate over a large portion of parameter space. The inclusion of decoherence corrections via the augmented FSSH algorithm improves the accuracy of dynamical behavior compared to exact simulations, but the effects are generally not dramatic for the cases I consider. Next, I introduce new methods for numerically exact real-time simulation based on real-time diagrammatic Quantum Monte Carlo (dQMC) and the inchworm algorithm. These methods optimally recycle Monte Carlo information from earlier times to greatly suppress the dynamical sign problem. In the context of the spin-boson model, I formulate the inchworm expansion in two distinct ways: the first with respect to an expansion in the system-bath coupling and the second as an expansion in the diabatic coupling. In addition, a cumulant version of the inchworm Monte Carlo method is motivated by the latter expansion, which allows for further suppression of the growth of the sign error. I provide a comprehensive comparison of the performance of the inchworm Monte Carlo algorithms to other exact methodologies as well as a discussion of the relative advantages and disadvantages of each. Finally, I investigate the dynamical interplay between the electron-electron interaction and the electron-phonon coupling within the Anderson-Holstein model via two complementary NCAs: the first is constructed around the weak-coupling limit and the second around the polaron limit. The influence of phonons on spectral and transport properties is explored in equilibrium, for non-equilibrium steady state and for transient dynamics after a quench. I find the two NCAs disagree in nontrivial ways, indicating that more reliable approaches to the problem are needed. The complementary frameworks used here pave the way for numerically exact methods based on inchworm dQMC algorithms capable of treating open systems simultaneously coupled to multiple fermionic and bosonic baths.

Monte Carlo calculation of large and small-angle electron scattering in air

NASA Astrophysics Data System (ADS)

Cohen, B. I.; Higginson, D. P.; Eng, C. D.; Farmer, W. A.; Friedman, A.; Grote, D. P.; Larson, D. J.

2017-11-01

A Monte Carlo method for angle scattering of electrons in air that accommodates the small-angle multiple scattering and larger-angle single scattering limits is introduced. The algorithm is designed for use in a particle-in-cell simulation of electron transport and electromagnetic wave effects in air. The method is illustrated in example calculations.

Statistical hadronization and microcanonical ensemble

DOE PAGES

Becattini, F.; Ferroni, L.

2004-01-01

We present a Monte Carlo calculation of the microcanonical ensemble of the of the ideal hadron-resonance gas including all known states up to a mass of 1. 8 GeV, taking into account quantum statistics. The computing method is a development of a previous one based on a Metropolis Monte Carlo algorithm, with a the grand-canonical limit of the multi-species multiplicity distribution as proposal matrix. The microcanonical average multiplicities of the various hadron species are found to converge to the canonical ones for moderately low values of the total energy. This algorithm opens the way for event generators based for themore » statistical hadronization model.« less

Experimental evaluation of a GPU-based Monte Carlo dose calculation algorithm in the Monaco treatment planning system.

PubMed

Paudel, Moti R; Kim, Anthony; Sarfehnia, Arman; Ahmad, Sayed B; Beachey, David J; Sahgal, Arjun; Keller, Brian M

2016-11-08

A new GPU-based Monte Carlo dose calculation algorithm (GPUMCD), devel-oped by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios - tumor-in-lung, lung, and bone-in-tissue - was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correc-tion. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for 2 × 2 cm2, 5 × 5 cm2, and 10 × 10 cm2 field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within 2%/2 mm of film measurements and within 1% of ion chamber measurements. For the tumor-in-lung phantom, the calculated doses were within 2.5%/2.5 mm of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within 3%/3 mm of film measurements, except for the 2 × 2 cm2 field size where the CCC algorithm underestimated the depth dose by ~ 5% in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within 2%/2 mm of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly. © 2016 The Authors.

A clinical study of lung cancer dose calculation accuracy with Monte Carlo simulation.

PubMed

Zhao, Yanqun; Qi, Guohai; Yin, Gang; Wang, Xianliang; Wang, Pei; Li, Jian; Xiao, Mingyong; Li, Jie; Kang, Shengwei; Liao, Xiongfei

2014-12-16

The accuracy of dose calculation is crucial to the quality of treatment planning and, consequently, to the dose delivered to patients undergoing radiation therapy. Current general calculation algorithms such as Pencil Beam Convolution (PBC) and Collapsed Cone Convolution (CCC) have shortcomings in regard to severe inhomogeneities, particularly in those regions where charged particle equilibrium does not hold. The aim of this study was to evaluate the accuracy of the PBC and CCC algorithms in lung cancer radiotherapy using Monte Carlo (MC) technology. Four treatment plans were designed using Oncentra Masterplan TPS for each patient. Two intensity-modulated radiation therapy (IMRT) plans were developed using the PBC and CCC algorithms, and two three-dimensional conformal therapy (3DCRT) plans were developed using the PBC and CCC algorithms. The DICOM-RT files of the treatment plans were exported to the Monte Carlo system to recalculate. The dose distributions of GTV, PTV and ipsilateral lung calculated by the TPS and MC were compared. For 3DCRT and IMRT plans, the mean dose differences for GTV between the CCC and MC increased with decreasing of the GTV volume. For IMRT, the mean dose differences were found to be higher than that of 3DCRT. The CCC algorithm overestimated the GTV mean dose by approximately 3% for IMRT. For 3DCRT plans, when the volume of the GTV was greater than 100 cm(3), the mean doses calculated by CCC and MC almost have no difference. PBC shows large deviations from the MC algorithm. For the dose to the ipsilateral lung, the CCC algorithm overestimated the dose to the entire lung, and the PBC algorithm overestimated V20 but underestimated V5; the difference in V10 was not statistically significant. PBC substantially overestimates the dose to the tumour, but the CCC is similar to the MC simulation. It is recommended that the treatment plans for lung cancer be developed using an advanced dose calculation algorithm other than PBC. MC can accurately calculate the dose distribution in lung cancer and can provide a notably effective tool for benchmarking the performance of other dose calculation algorithms within patients.

Water Oxidation Catalysis for NiOOH by a Metropolis Monte Carlo Algorithm.

PubMed

Hareli, Chen; Caspary Toroker, Maytal

2018-05-08

Understanding catalytic mechanisms is important for discovering better catalysts, particularly for water splitting reactions that are of great interest to the renewable energy field. One of the best performing catalysts for water oxidation is nickel oxyhydroxide (NiOOH). However, only one mechanism has been adopted so far for modeling catalysis of the active plane: β-NiOOH(01̅5). In order to understand how a second reaction mechanism affects catalysis, we perform Density Functional Theory + U (DFT+U) calculations of a second mechanism for water oxidation reaction of NiOOH. Then, we use a Metropolis Monte Carlo algorithm to calculate how many catalytic cycles are completed when two reaction mechanisms are competing. We find that within the Metropolis algorithm, the second mechanism has a higher overpotential and is therefore not active even for large applied biases.

Improved cache performance in Monte Carlo transport calculations using energy banding

NASA Astrophysics Data System (ADS)

Siegel, A.; Smith, K.; Felker, K.; Romano, P.; Forget, B.; Beckman, P.

2014-04-01

We present an energy banding algorithm for Monte Carlo (MC) neutral particle transport simulations which depend on large cross section lookup tables. In MC codes, read-only cross section data tables are accessed frequently, exhibit poor locality, and are typically too much large to fit in fast memory. Thus, performance is often limited by long latencies to RAM, or by off-node communication latencies when the data footprint is very large and must be decomposed on a distributed memory machine. The proposed energy banding algorithm allows maximal temporal reuse of data in band sizes that can flexibly accommodate different architectural features. The energy banding algorithm is general and has a number of benefits compared to the traditional approach. In the present analysis we explore its potential to achieve improvements in time-to-solution on modern cache-based architectures.