On the Concept of Random Orientation in Far-Field Electromagnetic Scattering by Nonspherical Particles

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Yurkin, Maxim A.

2017-01-01

Although the model of randomly oriented nonspherical particles has been used in a great variety of applications of far-field electromagnetic scattering, it has never been defined in strict mathematical terms. In this Letter we use the formalism of Euler rigid-body rotations to clarify the concept of statistically random particle orientations and derive its immediate corollaries in the form of most general mathematical properties of the orientation-averaged extinction and scattering matrices. Our results serve to provide a rigorous mathematical foundation for numerous publications in which the notion of randomly oriented particles and its light-scattering implications have been considered intuitively obvious.

Structured filtering

NASA Astrophysics Data System (ADS)

Granade, Christopher; Wiebe, Nathan

2017-08-01

A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent probability. We address this problem here by proposing a form of particle filtering that clusters the particles that comprise the sequential Monte Carlo approximation to the posterior before applying a resampler. Through a new graphical approach to thinking about such models, we are able to devise an artificial-intelligence based strategy that automatically learns the shape and number of the clusters in the support of the posterior. We demonstrate the power of our approach by applying it to randomized gap estimation and a form of low circuit-depth phase estimation where existing methods from the physics literature either exhibit much worse performance or even fail completely.

Remediating radium contaminated legacy sites: Advances made through machine learning in routine monitoring of "hot" particles.

PubMed

Varley, Adam; Tyler, Andrew; Smith, Leslie; Dale, Paul; Davies, Mike

2015-07-15

The extensive use of radium during the 20th century for industrial, military and pharmaceutical purposes has led to a large number of contaminated legacy sites across Europe and North America. Sites that pose a high risk to the general public can present expensive and long-term remediation projects. Often the most pragmatic remediation approach is through routine monitoring operating gamma-ray detectors to identify, in real-time, the signal from the most hazardous heterogeneous contamination (hot particles); thus facilitating their removal and safe disposal. However, current detection systems do not fully utilise all spectral information resulting in low detection rates and ultimately an increased risk to the human health. The aim of this study was to establish an optimised detector-algorithm combination. To achieve this, field data was collected using two handheld detectors (sodium iodide and lanthanum bromide) and a number of Monte Carlo simulated hot particles were randomly injected into the field data. This allowed for the detection rate of conventional deterministic (gross counts) and machine learning (neural networks and support vector machines) algorithms to be assessed. The results demonstrated that a Neural Network operated on a sodium iodide detector provided the best detection capability. Compared to deterministic approaches, this optimised detection system could detect a hot particle on average 10cm deeper into the soil column or with half of the activity at the same depth. It was also found that noise presented by internal contamination restricted lanthanum bromide for this application. Copyright © 2015. Published by Elsevier B.V.

Evolution of the concentration PDF in random environments modeled by global random walk

NASA Astrophysics Data System (ADS)

Suciu, Nicolae; Vamos, Calin; Attinger, Sabine; Knabner, Peter

2013-04-01

The evolution of the probability density function (PDF) of concentrations of chemical species transported in random environments is often modeled by ensembles of notional particles. The particles move in physical space along stochastic-Lagrangian trajectories governed by Ito equations, with drift coefficients given by the local values of the resolved velocity field and diffusion coefficients obtained by stochastic or space-filtering upscaling procedures. A general model for the sub-grid mixing also can be formulated as a system of Ito equations solving for trajectories in the composition space. The PDF is finally estimated by the number of particles in space-concentration control volumes. In spite of their efficiency, Lagrangian approaches suffer from two severe limitations. Since the particle trajectories are constructed sequentially, the demanded computing resources increase linearly with the number of particles. Moreover, the need to gather particles at the center of computational cells to perform the mixing step and to estimate statistical parameters, as well as the interpolation of various terms to particle positions, inevitably produce numerical diffusion in either particle-mesh or grid-free particle methods. To overcome these limitations, we introduce a global random walk method to solve the system of Ito equations in physical and composition spaces, which models the evolution of the random concentration's PDF. The algorithm consists of a superposition on a regular lattice of many weak Euler schemes for the set of Ito equations. Since all particles starting from a site of the space-concentration lattice are spread in a single numerical procedure, one obtains PDF estimates at the lattice sites at computational costs comparable with those for solving the system of Ito equations associated to a single particle. The new method avoids the limitations concerning the number of particles in Lagrangian approaches, completely removes the numerical diffusion, and speeds up the computation by orders of magnitude. The approach is illustrated for the transport of passive scalars in heterogeneous aquifers, with hydraulic conductivity modeled as a random field.

A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

NASA Astrophysics Data System (ADS)

Bouaynaya, N.; Schonfeld, Dan

2005-03-01

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Vision system and three-dimensional modeling techniques for quantification of the morphology of irregular particles

NASA Astrophysics Data System (ADS)

Smith, Lyndon N.; Smith, Melvyn L.

2000-10-01

Particulate materials undergo processing in many industries, and therefore there are significant commercial motivators for attaining improvements in the flow and packing behavior of powders. This can be achieved by modeling the effects of particle size, friction, and most importantly, particle shape or morphology. The method presented here for simulating powders employs a random number generator to construct a model of a random particle by combining a sphere with a number of smaller spheres. The resulting 3D model particle has a nodular type of morphology, which is similar to that exhibited by the atomized powders that are used in the bulk of powder metallurgy (PM) manufacture. The irregularity of the model particles is dependent upon vision system data gathered from microscopic analysis of real powder particles. A methodology is proposed whereby randomly generated model particles of various sized and irregularities can be combined in a random packing simulation. The proposed Monte Carlo technique would allow incorporation of the effects of gravity, wall friction, and inter-particle friction. The improvements in simulation realism that this method is expected to provide would prove useful for controlling powder production, and for predicting die fill behavior during the production of PM parts.

MO-DE-BRA-01: Enhancing Radiation Physics Instruction Through Gamification and E-Learning

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

Driewer, J; Lei, Y; Morgan, B

Purpose: This project sought to “gamify” the instruction of radiation interaction physics concepts for technology students. Gamification applies game mechanics and user interactions in active learning contexts. In one part of this project, a self-guided eModule was developed for conceptual radiation interaction instruction. In a second part, a web-based game, Particle Launch (http://particle-launcher.ist.unomaha.edu), was created to challenge students to quickly apply radiation interaction concepts in a way that is stimulating and motivating. Methods: The eModule, focused on conceptual interaction physics, was designed in Adobe Captivate and incorporates animation, web videos, and assessment questions in order to generate student interest. Navigatingmore » the whole module takes 40 minutes for beginners. Assessments after three main sections are comprised of 3–4 questions randomly selected from a question pool. In collaboration with the University of Nebraska at Omaha’s College of Information Science and Technology, the Particle Launch game was created with the Unity gaming engine and designed with a game-play look and feel. The object of the game is to utilize different particles, energies, and directions to destroy a target given a limited number of resources and time to complete the task. A rewards system encourages accurate shots. Results: The eModule part of the project encourages a flipped classroom model in which class time is devoted to application of concepts rather than information-based lectures. Currently, eModule assessments are not tracked but this feature could be incorporated to encourage participation. Furthermore, in a class of five technology students, the game was found to be fun and engaging and had the effect of reinforcing basic concepts from the eModule. Conclusion: Gamification has significant potential to alter medical physics instruction. Game-play feedback is an important part of the learning process. Students found Particle Launch inviting and challenging and further research could help game design. This project was generously supported by the Office of the Vice-Chancellor for Academic Affairs and the University of Nebraska Medical Center.« less

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

Schulte, R.

Proton therapy, in particular, and ion therapy, just beginning, are becoming an increasing focus of attention in clinical radiation oncology and medical physics. Both modalities have been criticized of lacking convincing evidence from randomized trials proving their efficacy, justifying the higher costs involved in these therapies. This session will provide an overview of the current status of clinical trials in proton therapy, including recent developments in ion therapy. As alluded to in the introductory talk by Dr. Schulte, opinions are diverging widely as to the usefulness and need for clinical trials in particle therapy and the challenge of equipoise. Themore » lectures will highlight some of the challenges that surround clinical trials in particle therapy. One, presented by Dr. Choy from UT Southwestern, is that new technology and even different types of particles such as helium and carbon ions are introduced into this environment, increasing the phase space of clinical variables. The other is the issue of medical physics quality assurance with physical phantoms, presented by Mrs. Taylor from IROC Houston, which is more challenging because 3D and 4D image guidance and active delivery techniques are in relatively early stages of development. The role of digital phantoms in developing clinical treatment planning protocols and as a QA tool will also be highlighted by Dr. Lee from NCI. The symposium will be rounded off by a panel discussion among the Symposium speakers, arguing pro or con the need and readiness for clinical trials in proton and ion therapy. Learning Objectives: To get an update on the current status of clinical trials allowing or mandating proton therapy. Learn about the status of planned clinical trials in the U.S. and worldwide involving ion therapy. Discuss the challenges in the design and QA of clinical trials in particle therapy. Learn about existing and future physical and computational anthropomorphic phantoms for charged particle clinical trial development and support. Research reported in this presentation is supported by the National Cancer Institute of the National; Institutes of Health under Award Number P20CA183640.« less

TU-G-BRB-05: Panel Discussion: Clinical Trials in Proton and Ion Therapy - Are We Ready?

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

Schulte, R.

2015-06-15

Proton therapy, in particular, and ion therapy, just beginning, are becoming an increasing focus of attention in clinical radiation oncology and medical physics. Both modalities have been criticized of lacking convincing evidence from randomized trials proving their efficacy, justifying the higher costs involved in these therapies. This session will provide an overview of the current status of clinical trials in proton therapy, including recent developments in ion therapy. As alluded to in the introductory talk by Dr. Schulte, opinions are diverging widely as to the usefulness and need for clinical trials in particle therapy and the challenge of equipoise. Themore » lectures will highlight some of the challenges that surround clinical trials in particle therapy. One, presented by Dr. Choy from UT Southwestern, is that new technology and even different types of particles such as helium and carbon ions are introduced into this environment, increasing the phase space of clinical variables. The other is the issue of medical physics quality assurance with physical phantoms, presented by Mrs. Taylor from IROC Houston, which is more challenging because 3D and 4D image guidance and active delivery techniques are in relatively early stages of development. The role of digital phantoms in developing clinical treatment planning protocols and as a QA tool will also be highlighted by Dr. Lee from NCI. The symposium will be rounded off by a panel discussion among the Symposium speakers, arguing pro or con the need and readiness for clinical trials in proton and ion therapy. Learning Objectives: To get an update on the current status of clinical trials allowing or mandating proton therapy. Learn about the status of planned clinical trials in the U.S. and worldwide involving ion therapy. Discuss the challenges in the design and QA of clinical trials in particle therapy. Learn about existing and future physical and computational anthropomorphic phantoms for charged particle clinical trial development and support. Research reported in this presentation is supported by the National Cancer Institute of the National; Institutes of Health under Award Number P20CA183640.« less

TU-G-BRB-03: IROC Houston’s Proton Beam Validation for Clinical Trials

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

Taylor, P.

2015-06-15

Proton therapy, in particular, and ion therapy, just beginning, are becoming an increasing focus of attention in clinical radiation oncology and medical physics. Both modalities have been criticized of lacking convincing evidence from randomized trials proving their efficacy, justifying the higher costs involved in these therapies. This session will provide an overview of the current status of clinical trials in proton therapy, including recent developments in ion therapy. As alluded to in the introductory talk by Dr. Schulte, opinions are diverging widely as to the usefulness and need for clinical trials in particle therapy and the challenge of equipoise. Themore » lectures will highlight some of the challenges that surround clinical trials in particle therapy. One, presented by Dr. Choy from UT Southwestern, is that new technology and even different types of particles such as helium and carbon ions are introduced into this environment, increasing the phase space of clinical variables. The other is the issue of medical physics quality assurance with physical phantoms, presented by Mrs. Taylor from IROC Houston, which is more challenging because 3D and 4D image guidance and active delivery techniques are in relatively early stages of development. The role of digital phantoms in developing clinical treatment planning protocols and as a QA tool will also be highlighted by Dr. Lee from NCI. The symposium will be rounded off by a panel discussion among the Symposium speakers, arguing pro or con the need and readiness for clinical trials in proton and ion therapy. Learning Objectives: To get an update on the current status of clinical trials allowing or mandating proton therapy. Learn about the status of planned clinical trials in the U.S. and worldwide involving ion therapy. Discuss the challenges in the design and QA of clinical trials in particle therapy. Learn about existing and future physical and computational anthropomorphic phantoms for charged particle clinical trial development and support. Research reported in this presentation is supported by the National Cancer Institute of the National; Institutes of Health under Award Number P20CA183640.« less

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-09-01

Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in exascale simulations.

Implementing traceability using particle randomness-based textile printed tags

NASA Astrophysics Data System (ADS)

Agrawal, T. K.; Koehl, L.; Campagne, C.

2017-10-01

This article introduces a random particle-based traceability tag for textiles. The proposed tag not only act as a unique signature for the corresponding textile product but also possess the features such as easy to manufacture and hard to copy. It seeks applications in brand authentication and traceability in textile and clothing (T&C) supply chain. A prototype has been developed by screen printing process, in which micron-scale particles were mixed with the printing paste and printed on cotton fabrics to attain required randomness. To encode the randomness, the image of the developed tag was taken and analyzed using image processing. The randomness of the particles acts as a product key or unique signature which is required to decode the tag. Finally, washing and abrasion resistance tests were conducted to check the durability of the printed tag.

Patterns of particle distribution in multiparticle systems by random walks with memory enhancement and decay

NASA Astrophysics Data System (ADS)

Tan, Zhi-Jie; Zou, Xian-Wu; Huang, Sheng-You; Zhang, Wei; Jin, Zhun-Zhi

2002-07-01

We investigate the pattern of particle distribution and its evolution with time in multiparticle systems using the model of random walks with memory enhancement and decay. This model describes some biological intelligent walks. With decrease in the memory decay exponent α, the distribution of particles changes from a random dispersive pattern to a locally dense one, and then returns to the random one. Correspondingly, the fractal dimension Df,p characterizing the distribution of particle positions increases from a low value to a maximum and then decreases to the low one again. This is determined by the degree of overlap of regions consisting of sites with remanent information. The second moment of the density ρ(2) was introduced to investigate the inhomogeneity of the particle distribution. The dependence of ρ(2) on α is similar to that of Df,p on α. ρ(2) increases with time as a power law in the process of adjusting the particle distribution, and then ρ(2) tends to a stable equilibrium value.

Distribution of randomly diffusing particles in inhomogeneous media

NASA Astrophysics Data System (ADS)

Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A.

2017-09-01

Diffusion can be conceptualized, at microscopic scales, as the random hopping of particles between neighboring lattice sites. In the case of diffusion in inhomogeneous media, distinct spatial domains in the system may yield distinct particle hopping rates. Starting from the master equations (MEs) governing diffusion in inhomogeneous media we derive here, for arbitrary spatial dimensions, the deterministic lattice equations (DLEs) specifying the average particle number at each lattice site for randomly diffusing particles in inhomogeneous media. We consider the case of free (Fickian) diffusion with no steric constraints on the maximum particle number per lattice site as well as the case of diffusion under steric constraints imposing a maximum particle concentration. We find, for both transient and asymptotic regimes, excellent agreement between the DLEs and kinetic Monte Carlo simulations of the MEs. The DLEs provide a computationally efficient method for predicting the (average) distribution of randomly diffusing particles in inhomogeneous media, with the number of DLEs associated with a given system being independent of the number of particles in the system. From the DLEs we obtain general analytic expressions for the steady-state particle distributions for free diffusion and, in special cases, diffusion under steric constraints in inhomogeneous media. We find that, in the steady state of the system, the average fraction of particles in a given domain is independent of most system properties, such as the arrangement and shape of domains, and only depends on the number of lattice sites in each domain, the particle hopping rates, the number of distinct particle species in the system, and the total number of particles of each particle species in the system. Our results provide general insights into the role of spatially inhomogeneous particle hopping rates in setting the particle distributions in inhomogeneous media.

Scattering Properties of Heterogeneous Mineral Particles with Absorbing Inclusions

NASA Technical Reports Server (NTRS)

Dlugach, Janna M.; Mishchenko, Michael I.

2015-01-01

We analyze the results of numerically exact computer modeling of scattering and absorption properties of randomly oriented poly-disperse heterogeneous particles obtained by placing microscopic absorbing grains randomly on the surfaces of much larger spherical mineral hosts or by imbedding them randomly inside the hosts. These computations are paralleled by those for heterogeneous particles obtained by fully encapsulating fractal-like absorbing clusters in the mineral hosts. All computations are performed using the superposition T-matrix method. In the case of randomly distributed inclusions, the results are compared with the outcome of Lorenz-Mie computations for an external mixture of the mineral hosts and absorbing grains. We conclude that internal aggregation can affect strongly both the integral radiometric and differential scattering characteristics of the heterogeneous particle mixtures.

The Dynamical Classification of Centaurs which Evolve into Comets

NASA Astrophysics Data System (ADS)

Wood, Jeremy R.; Horner, Jonathan; Hinse, Tobias; Marsden, Stephen; Swinburne University of Technology

2016-10-01

Centaurs are small Solar system bodies with semi-major axes between Jupiter and Neptune and perihelia beyond Jupiter. Centaurs can be further subclassified into two dynamical categories - random walk and resonance hopping. Random walk Centaurs have mean square semi-major axes (< a2 >) which vary in time according to a generalized diffusion equation where < a2 > ~t2H. H is the Hurst exponent with 0 < H < 1, and t is time. The behavior of < a2 > for resonance hopping Centaurs is not well described by generalized diffusion.The aim of this study is to determine which dynamical type of Centaur is most likely to evolve into each class of comet. 31,722 fictional massless test particles were integrated for 3 Myr in the 6-body problem (Sun, Jovian planets, test particle). Initially each test particle was a member of one of four groups. The semi-major axes of all test particles in a group were clustered within 0.27 au from a first order, interior Mean Motion resonance of Neptune. The resonances were centered at 18.94 au, 22.95 au, 24.82 au and 28.37 au.If the perihelion of a test particle reached < 4 au then the test particle was considered to be a comet and classified as either a random walk or resonance hopping Centaur. The results showed that over 4,000 test particles evolved into comets within 3 Myr. 59% of these test particles were random walk and 41% were resonance hopping. The behavior of the semi-major axis in time was usually well described by generalized diffusion for random walk Centaurs (ravg = 0.98) and poorly described for resonance hopping Centaurs (ravg = 0.52). The average Hurst exponent was 0.48 for random walk Centaurs and 0.20 for resonance hopping Centaurs. Random walk Centaurs were more likely to evolve into short period comets while resonance hopping Centaurs were more likely to evolve into long period comets. For each initial cluster, resonance hopping Centaurs took longer to evolve into comets than random walk Centaurs. Overall the population of random walk Centaurs averaged 143 kyr to evolve into comets, and the population of resonance hopping Centaurs averaged 164 kyr.

A new fundamental model of moving particle for reinterpreting Schroedinger equation

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

Umar, Muhamad Darwis

2012-06-20

The study of Schroedinger equation based on a hypothesis that every particle must move randomly in a quantum-sized volume has been done. In addition to random motion, every particle can do relative motion through the movement of its quantum-sized volume. On the other way these motions can coincide. In this proposed model, the random motion is one kind of intrinsic properties of the particle. The every change of both speed of randomly intrinsic motion and or the velocity of translational motion of a quantum-sized volume will represent a transition between two states, and the change of speed of randomly intrinsicmore » motion will generate diffusion process or Brownian motion perspectives. Diffusion process can take place in backward and forward processes and will represent a dissipative system. To derive Schroedinger equation from our hypothesis we use time operator introduced by Nelson. From a fundamental analysis, we find out that, naturally, we should view the means of Newton's Law F(vector sign) = ma(vector sign) as no an external force, but it is just to describe both the presence of intrinsic random motion and the change of the particle energy.« less

Collision Models for Particle Orbit Code on SSX

NASA Astrophysics Data System (ADS)

Fisher, M. W.; Dandurand, D.; Gray, T.; Brown, M. R.; Lukin, V. S.

2011-10-01

Coulomb collision models are being developed and incorporated into the Hamiltonian particle pushing code (PPC) for applications to the Swarthmore Spheromak eXperiment (SSX). A Monte Carlo model based on that of Takizuka and Abe [JCP 25, 205 (1977)] performs binary collisions between test particles and thermal plasma field particles randomly drawn from a stationary Maxwellian distribution. A field-based electrostatic fluctuation model scatters particles from a spatially uniform random distribution of positive and negative spherical potentials generated throughout the plasma volume. The number, radii, and amplitude of these potentials are chosen to mimic the correct particle diffusion statistics without the use of random particle draws or collision frequencies. An electromagnetic fluctuating field model will be presented, if available. These numerical collision models will be benchmarked against known analytical solutions, including beam diffusion rates and Spitzer resistivity, as well as each other. The resulting collisional particle orbit models will be used to simulate particle collection with electrostatic probes in the SSX wind tunnel, as well as particle confinement in typical SSX fields. This work has been supported by US DOE, NSF and ONR.

Radiation Transport in Random Media With Large Fluctuations

NASA Astrophysics Data System (ADS)

Olson, Aaron; Prinja, Anil; Franke, Brian

2017-09-01

Neutral particle transport in media exhibiting large and complex material property spatial variation is modeled by representing cross sections as lognormal random functions of space and generated through a nonlinear memory-less transformation of a Gaussian process with covariance uniquely determined by the covariance of the cross section. A Karhunen-Loève decomposition of the Gaussian process is implemented to effciently generate realizations of the random cross sections and Woodcock Monte Carlo used to transport particles on each realization and generate benchmark solutions for the mean and variance of the particle flux as well as probability densities of the particle reflectance and transmittance. A computationally effcient stochastic collocation method is implemented to directly compute the statistical moments such as the mean and variance, while a polynomial chaos expansion in conjunction with stochastic collocation provides a convenient surrogate model that also produces probability densities of output quantities of interest. Extensive numerical testing demonstrates that use of stochastic reduced-order modeling provides an accurate and cost-effective alternative to random sampling for particle transport in random media.

Facilitation of learning induced by both random and gradual visuomotor task variation

PubMed Central

Braun, Daniel A.; Wolpert, Daniel M.

2012-01-01

Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between −60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→−30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes. PMID:22131385

Leveraging Random Number Generation for Mastery of Learning in Teaching Quantitative Research Courses via an E-Learning Method

ERIC Educational Resources Information Center

Boonsathorn, Wasita; Charoen, Danuvasin; Dryver, Arthur L.

2014-01-01

E-Learning brings access to a powerful but often overlooked teaching tool: random number generation. Using random number generation, a practically infinite number of quantitative problem-solution sets can be created. In addition, within the e-learning context, in the spirit of the mastery of learning, it is possible to assign online quantitative…

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy

PubMed Central

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system. PMID:27835638

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PubMed

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

Learning Particle Physics with DIY Play Dough Model

NASA Astrophysics Data System (ADS)

Thunyaniti, T.; Toedtanya, K.; Wuttiprom, S.

2017-09-01

The scientists once believed an atom was the smallest particle, nothing was smaller than this tiny particle. Later, they discovered an atom which consists of protons, neutrons and electrons, and they believed that these particles cannot be broken into the smaller particles. According to advanced technology, the scientists have discovered these particles are consisted of a smaller particles. The new particles are called quarks leptons and bosons which we called fundamental particle. Atomic structure cannot be observed directly, so it is complicated for studying these particles. To help the students get more understanding of its properties, so the researcher develops the learning pattern of fundamental particles from Play Dough Model for high school to graduate students. Four step of learning are 1) to introduces the concept of the fundamental particles discovery 2) to play the Happy Families game by using fundamental particles cards 3) to design and make their particle in a way that reflects its properties 4) to represents their particles from Play Dough Model. After doing activities, the students had more conceptual understanding and better memorability on fundamental particles. In addition, the students gained collaborative working experience among their friends also.

Inelastic collapse and near-wall localization of randomly accelerated particles.

PubMed

Belan, S; Chernykh, A; Lebedev, V; Falkovich, G

2016-05-01

Inelastic collapse of stochastic trajectories of a randomly accelerated particle moving in half-space z>0 has been discovered by McKean [J. Math. Kyoto Univ. 2, 227 (1963)] and then independently rediscovered by Cornell et al. [Phys. Rev. Lett. 81, 1142 (1998)PRLTAO0031-900710.1103/PhysRevLett.81.1142]. The essence of this phenomenon is that the particle arrives at the wall at z=0 with zero velocity after an infinite number of inelastic collisions if the restitution coefficient β of particle velocity is smaller than the critical value β_{c}=exp(-π/sqrt[3]). We demonstrate that inelastic collapse takes place also in a wide class of models with spatially inhomogeneous random forcing and, what is more, that the critical value β_{c} is universal. That class includes an important case of inertial particles in wall-bounded random flows. To establish how inelastic collapse influences the particle distribution, we derive the exact equilibrium probability density function ρ(z,v) for the particle position and velocity. The equilibrium distribution exists only at β<β_{c} and indicates that inelastic collapse does not necessarily imply near-wall localization.

Particle Swarm Optimization With Interswarm Interactive Learning Strategy.

PubMed

Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui

2016-10-01

The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.

Universal self-similarity of propagating populations.

PubMed

Eliazar, Iddo; Klafter, Joseph

2010-07-01

This paper explores the universal self-similarity of propagating populations. The following general propagation model is considered: particles are randomly emitted from the origin of a d-dimensional Euclidean space and propagate randomly and independently of each other in space; all particles share a statistically common--yet arbitrary--motion pattern; each particle has its own random propagation parameters--emission epoch, motion frequency, and motion amplitude. The universally self-similar statistics of the particles' displacements and first passage times (FPTs) are analyzed: statistics which are invariant with respect to the details of the displacement and FPT measurements and with respect to the particles' underlying motion pattern. Analysis concludes that the universally self-similar statistics are governed by Poisson processes with power-law intensities and by the Fréchet and Weibull extreme-value laws.

Collisional evolution of rotating, non-identical particles. [in Saturn rings

NASA Technical Reports Server (NTRS)

Salo, H.

1987-01-01

Hameen-Anttila's (1984) theory of self-gravitating collisional particle disks is extended to include the effects of particle spin. Equations are derived for the coupled evolution of random velocities and spins, showing that friction and surface irregularity both reduce the local velocity dispersion and transfer significant amounts of random kinetic energy to rotational energy. Results for the equilibrium ratio of rotational energy to random kinetic energy are exact not only for identical nongravitating mass points, but also if finite size, self-gravitating forces, or size distribution are included. The model is applied to the dynamics of Saturn's rings, showing that the inclusion of rotation reduces the geometrical thickness of the layer of cm-sized particles to, at most, about one-half, with large particles being less affected.

DISPERSION POLYMERIZATION OF STYRENE IN SUPERCRITICAL CARBON DIOXIDE UTILIZING RANDOM COPOLYMERS INCLUDING FLUORINATED ACRYLATE FOR PREPARING MICRON-SIZE POLYSTYRENE PARTICLES. (R826115)

EPA Science Inventory

The dispersion polymerization of styrene in supercritical CO₂ utilizing CO₂-philic random copolymers was investigated. The resulting high yield of polystyrene particles in the micron-size range was formed using various random copolymers as stabilizers. The p...

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

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

Li, Yongjun; Cheng, Weixing; Yu, Li Hua

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

NASA Astrophysics Data System (ADS)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

2018-05-01

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

DOE PAGES

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; ...

2018-05-29

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

Shock Interaction with Random Spherical Particle Beds

NASA Astrophysics Data System (ADS)

Neal, Chris; Mehta, Yash; Salari, Kambiz; Jackson, Thomas L.; Balachandar, S. "Bala"; Thakur, Siddharth

2016-11-01

In this talk we present results on fully resolved simulations of shock interaction with randomly distributed bed of particles. Multiple simulations were carried out by varying the number of particles to isolate the effect of volume fraction. Major focus of these simulations was to understand 1) the effect of the shockwave and volume fraction on the forces experienced by the particles, 2) the effect of particles on the shock wave, and 3) fluid mediated particle-particle interactions. Peak drag force for particles at different volume fractions show a downward trend as the depth of the bed increased. This can be attributed to dissipation of energy as the shockwave travels through the bed of particles. One of the fascinating observations from these simulations was the fluctuations in different quantities due to presence of multiple particles and their random distribution. These are large simulations with hundreds of particles resulting in large amount of data. We present statistical analysis of the data and make relevant observations. Average pressure in the computational domain is computed to characterize the strengths of the reflected and transmitted waves. We also present flow field contour plots to support our observations. U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program, under Contract No. DE-NA0002378.

Colloids exposed to random potential energy landscapes: From particle number density to particle-potential and particle-particle interactions

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

Bewerunge, Jörg; Capellmann, Ronja F.; Platten, Florian

2016-07-28

Colloidal particles were exposed to a random potential energy landscape that has been created optically via a speckle pattern. The mean particle density as well as the potential roughness, i.e., the disorder strength, were varied. The local probability density of the particles as well as its main characteristics were determined. For the first time, the disorder-averaged pair density correlation function g{sup (1)}(r) and an analogue of the Edwards-Anderson order parameter g{sup (2)}(r), which quantifies the correlation of the mean local density among disorder realisations, were measured experimentally and shown to be consistent with replica liquid state theory results.

Optical equivalence of isotropic ensembles of ellipsoidal particles in the Rayleigh-Gans-Debye and anomalous diffraction approximations and its consequences

NASA Astrophysics Data System (ADS)

Paramonov, L. E.

2012-05-01

Light scattering by isotropic ensembles of ellipsoidal particles is considered in the Rayleigh-Gans-Debye approximation. It is proved that randomly oriented ellipsoidal particles are optically equivalent to polydisperse randomly oriented spheroidal particles and polydisperse spherical particles. Density functions of the shape and size distributions for equivalent ensembles of spheroidal and spherical particles are presented. In the anomalous diffraction approximation, equivalent ensembles of particles are shown to also have equal extinction, scattering, and absorption coefficients. Consequences of optical equivalence are considered. The results are illustrated by numerical calculations of the angular dependence of the scattering phase function using the T-matrix method and the Mie theory.

Experimental and numerical analysis of the constitutive equation of rubber composites reinforced with random ceramic particle

NASA Astrophysics Data System (ADS)

Luo, D. M.; Xie, Y.; Su, X. R.; Zhou, Y. L.

2018-01-01

Based on the four classical models of Mooney-Rivlin (M-R), Yeoh, Ogden and Neo-Hookean (N-H) model, a strain energy constitutive equation with large deformation for rubber composites reinforced with random ceramic particles is proposed from the angle of continuum mechanics theory in this paper. By decoupling the interaction between matrix and random particles, the strain energy of each phase is obtained to derive the explicit constitutive equation for rubber composites. The tests results of uni-axial tensile, pure shear and equal bi-axial tensile are simulated by the non-linear finite element method on the ANSYS platform. The results from finite element method are compared with those from experiment, and the material parameters are determined by fitting the results from different test conditions, and the influence of radius of random ceramic particles on the effective mechanical properties are analyzed.

The invariant statistical rule of aerosol scattering pulse signal modulated by random noise

NASA Astrophysics Data System (ADS)

Yan, Zhen-gang; Bian, Bao-Min; Yang, Juan; Peng, Gang; Li, Zhen-hua

2010-11-01

A model of the random background noise acting on particle signals is established to study the impact of the background noise of the photoelectric sensor in the laser airborne particle counter on the statistical character of the aerosol scattering pulse signals. The results show that the noises broaden the statistical distribution of the particle's measurement. Further numerical research shows that the output of the signal amplitude still has the same distribution when the airborne particle with the lognormal distribution was modulated by random noise which has lognormal distribution. Namely it follows the statistics law of invariance. Based on this model, the background noise of photoelectric sensor and the counting distributions of random signal for aerosol's scattering pulse are obtained and analyzed by using a high-speed data acquisition card PCI-9812. It is found that the experiment results and simulation results are well consistent.

A multiple scattering theory for EM wave propagation in a dense random medium

NASA Technical Reports Server (NTRS)

Karam, M. A.; Fung, A. K.; Wong, K. W.

1985-01-01

For a dense medium of randomly distributed scatterers an integral formulation for the total coherent field has been developed. This formulation accounts for the multiple scattering of electromagnetic waves including both the twoand three-particle terms. It is shown that under the Markovian assumption the total coherent field and the effective field have the same effective wave number. As an illustration of this theory, the effective wave number and the extinction coefficient are derived in terms of the polarizability tensor and the pair distribution function for randomly distributed small spherical scatterers. It is found that the contribution of the three-particle term increases with the particle size, the volume fraction, the frequency and the permittivity of the particle. This increase is more significant with frequency and particle size than with other parameters.

Deleterious Thermal Effects Due To Randomized Flow Paths in Pebble Bed, and Particle Bed Style Reactors

NASA Technical Reports Server (NTRS)

Moran, Robert P.

2013-01-01

A review of literature associated with Pebble Bed and Particle Bed reactor core research has revealed a systemic problem inherent to reactor core concepts which utilize randomized rather than structured coolant channel flow paths. For both the Pebble Bed and Particle Bed Reactor designs; case studies reveal that for indeterminate reasons, regions within the core would suffer from excessive heating leading to thermal runaway and localized fuel melting. A thermal Computational Fluid Dynamics model was utilized to verify that In both the Pebble Bed and Particle Bed Reactor concepts randomized coolant channel pathways combined with localized high temperature regions would work together to resist the flow of coolant diverting it away from where it is needed the most to cooler less resistive pathways where it is needed the least. In other words given the choice via randomized coolant pathways the reactor coolant will take the path of least resistance, and hot zones offer the highest resistance. Having identified the relationship between randomized coolant channel pathways and localized fuel melting it is now safe to assume that other reactor concepts that utilize randomized coolant pathways such as the foam core reactor are also susceptible to this phenomenon.

Jet-images — deep learning edition

DOE PAGES

de Oliveira, Luke; Kagan, Michael; Mackey, Lester; ...

2016-07-13

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Jet-images — deep learning edition

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

de Oliveira, Luke; Kagan, Michael; Mackey, Lester

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Development of Contemporary Problem-Based Learning Projects in Particle Technology

ERIC Educational Resources Information Center

Harris, Andrew T.

2009-01-01

The University of Sydney has offered an undergraduate course in particle technology using a contemporary problem based learning (PBL) methodology since 2005. Student learning is developed through the solution of complex, open-ended problems drawn from modern chemical engineering practice. Two examples are presented; i) zero emission electricity…

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Accurate Quasiparticle Spectra from the T-Matrix Self-Energy and the Particle-Particle Random Phase Approximation.

PubMed

Zhang, Du; Su, Neil Qiang; Yang, Weitao

2017-07-20

The GW self-energy, especially G 0 W 0 based on the particle-hole random phase approximation (phRPA), is widely used to study quasiparticle (QP) energies. Motivated by the desirable features of the particle-particle (pp) RPA compared to the conventional phRPA, we explore the pp counterpart of GW, that is, the T-matrix self-energy, formulated with the eigenvectors and eigenvalues of the ppRPA matrix. We demonstrate the accuracy of the T-matrix method for molecular QP energies, highlighting the importance of the pp channel for calculating QP spectra.

Virus Particle Detection by Convolutional Neural Network in Transmission Electron Microscopy Images.

PubMed

Ito, Eisuke; Sato, Takaaki; Sano, Daisuke; Utagawa, Etsuko; Kato, Tsuyoshi

2018-06-01

A new computational method for the detection of virus particles in transmission electron microscopy (TEM) images is presented. Our approach is to use a convolutional neural network that transforms a TEM image to a probabilistic map that indicates where virus particles exist in the image. Our proposed approach automatically and simultaneously learns both discriminative features and classifier for virus particle detection by machine learning, in contrast to existing methods that are based on handcrafted features that yield many false positives and require several postprocessing steps. The detection performance of the proposed method was assessed against a dataset of TEM images containing feline calicivirus particles and compared with several existing detection methods, and the state-of-the-art performance of the developed method for detecting virus was demonstrated. Since our method is based on supervised learning that requires both the input images and their corresponding annotations, it is basically used for detection of already-known viruses. However, the method is highly flexible, and the convolutional networks can adapt themselves to any virus particles by learning automatically from an annotated dataset.

Machine learning for autonomous crystal structure identification.

PubMed

Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

2017-07-21

We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Tensor hypercontracted ppRPA: Reducing the cost of the particle-particle random phase approximation from O(r {sup 6}) to O(r {sup 4})

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

Shenvi, Neil; Yang, Yang; Yang, Weitao

In recent years, interest in the random-phase approximation (RPA) has grown rapidly. At the same time, tensor hypercontraction has emerged as an intriguing method to reduce the computational cost of electronic structure algorithms. In this paper, we combine the particle-particle random phase approximation with tensor hypercontraction to produce the tensor-hypercontracted particle-particle RPA (THC-ppRPA) algorithm. Unlike previous implementations of ppRPA which scale as O(r{sup 6}), the THC-ppRPA algorithm scales asymptotically as only O(r{sup 4}), albeit with a much larger prefactor than the traditional algorithm. We apply THC-ppRPA to several model systems and show that it yields the same results as traditionalmore » ppRPA to within mH accuracy. Our method opens the door to the development of post-Kohn Sham functionals based on ppRPA without the excessive asymptotic cost of traditional ppRPA implementations.« less

Tensor hypercontracted ppRPA: Reducing the cost of the particle-particle random phase approximation from O(r 6) to O(r 4)

NASA Astrophysics Data System (ADS)

Shenvi, Neil; van Aggelen, Helen; Yang, Yang; Yang, Weitao

2014-07-01

In recent years, interest in the random-phase approximation (RPA) has grown rapidly. At the same time, tensor hypercontraction has emerged as an intriguing method to reduce the computational cost of electronic structure algorithms. In this paper, we combine the particle-particle random phase approximation with tensor hypercontraction to produce the tensor-hypercontracted particle-particle RPA (THC-ppRPA) algorithm. Unlike previous implementations of ppRPA which scale as O(r6), the THC-ppRPA algorithm scales asymptotically as only O(r4), albeit with a much larger prefactor than the traditional algorithm. We apply THC-ppRPA to several model systems and show that it yields the same results as traditional ppRPA to within mH accuracy. Our method opens the door to the development of post-Kohn Sham functionals based on ppRPA without the excessive asymptotic cost of traditional ppRPA implementations.

Effects of random initial conditions on the dynamical scaling behaviors of a fixed-energy Manna sandpile model in one dimension

NASA Astrophysics Data System (ADS)

Kwon, Sungchul; Kim, Jin Min

2015-01-01

For a fixed-energy (FE) Manna sandpile model in one dimension, we investigate the effects of random initial conditions on the dynamical scaling behavior of an order parameter. In the FE Manna model, the density ρ of total particles is conserved, and an absorbing phase transition occurs at ρc as ρ varies. In this work, we show that, for a given ρ , random initial distributions of particles lead to the domain structure in which domains with particle densities higher and lower than ρc alternate with each other. In the domain structure, the dominant length scale is the average domain length, which increases via the coalescence of adjacent domains. At ρc, the domain structure slows down the decay of an order parameter and also causes anomalous finite-size effects, i.e., power-law decay followed by an exponential one before the quasisteady state. As a result, the interplay of particle conservation and random initial conditions causes the domain structure, which is the origin of the anomalous dynamical scaling behaviors for random initial conditions.

Micromechanics-based magneto-elastic constitutive modeling of particulate composites

NASA Astrophysics Data System (ADS)

Yin, Huiming

Modified Green's functions are derived for three situations: a magnetic field caused by a local magnetization, a displacement field caused by a local body force and a displacement field caused by a local prescribed eigenstrain. Based on these functions, an explicit solution is derived for two magnetic particles embedded in the infinite medium under external magnetic and mechanical loading. A general solution for numerable magnetic particles embedded in an infinite domain is then provided in integral form. Two-phase composites containing spherical magnetic particles of the same size are considered for three kinds of microstructures. With chain-structured composites, particle interactions in the same chain are considered and a transversely isotropic effective elasticity is obtained. For periodic composites, an eight-particle interaction model is developed and provides a cubic symmetric effective elasticity. In the random composite, pair-wise particle interactions are integrated from all possible positions and an isotropic effective property is reached. This method is further extended to functionally graded composites. Magneto-mechanical behavior is studied for the chain-structured composite and the random composite. Effective magnetic permeability, effective magnetostriction and field-dependent effective elasticity are investigated. It is seen that the chain-structured composite is more sensitive to the magnetic field than the random composite; a composite consisting of only 5% of chain-structured particles can provide a larger magnetostriction and a larger change of effective elasticity than an equivalent composite consisting of 30% of random dispersed particles. Moreover, the effective shear modulus of the chain-structured composite rapidly increases with the magnetic field, while that for the random composite decreases. An effective hyperelastic constitutive model is further developed for a magnetostrictive particle-filled elastomer, which is sampled by using a network of body-centered cubic lattices of particles connected by macromolecular chains. The proposed hyperelastic model is able to characterize overall nonlinear elastic stress-stretch relations of the composites under general three-dimensional loading. It is seen that the effective strain energy density is proportional to the length of stretched chains in unit volume and volume fraction of particles.

Dynamic Simulation of Random Packing of Polydispersive Fine Particles

NASA Astrophysics Data System (ADS)

Ferraz, Carlos Handrey Araujo; Marques, Samuel Apolinário

2018-02-01

In this paper, we perform molecular dynamic (MD) simulations to study the two-dimensional packing process of both monosized and random size particles with radii ranging from 1.0 to 7.0 μm. The initial positions as well as the radii of five thousand fine particles were defined inside a rectangular box by using a random number generator. Both the translational and rotational movements of each particle were considered in the simulations. In order to deal with interacting fine particles, we take into account both the contact forces and the long-range dispersive forces. We account for normal and static/sliding tangential friction forces between particles and between particle and wall by means of a linear model approach, while the long-range dispersive forces are computed by using a Lennard-Jones-like potential. The packing processes were studied assuming different long-range interaction strengths. We carry out statistical calculations of the different quantities studied such as packing density, mean coordination number, kinetic energy, and radial distribution function as the system evolves over time. We find that the long-range dispersive forces can strongly influence the packing process dynamics as they might form large particle clusters, depending on the intensity of the long-range interaction strength.

Local random configuration-tree theory for string repetition and facilitated dynamics of glass

NASA Astrophysics Data System (ADS)

Lam, Chi-Hang

2018-02-01

We derive a microscopic theory of glassy dynamics based on the transport of voids by micro-string motions, each of which involves particles arranged in a line hopping simultaneously displacing one another. Disorder is modeled by a random energy landscape quenched in the configuration space of distinguishable particles, but transient in the physical space as expected for glassy fluids. We study the evolution of local regions with m coupled voids. At a low temperature, energetically accessible local particle configurations can be organized into a random tree with nodes and edges denoting configurations and micro-string propagations respectively. Such trees defined in the configuration space naturally describe systems defined in two- or three-dimensional physical space. A micro-string propagation initiated by a void can facilitate similar motions by other voids via perturbing the random energy landscape, realizing path interactions between voids or equivalently string interactions. We obtain explicit expressions of the particle diffusion coefficient and a particle return probability. Under our approximation, as temperature decreases, random trees of energetically accessible configurations exhibit a sequence of percolation transitions in the configuration space, with local regions containing fewer coupled voids entering the non-percolating immobile phase first. Dynamics is dominated by coupled voids of an optimal group size, which increases as temperature decreases. Comparison with a distinguishable-particle lattice model (DPLM) of glass shows very good quantitative agreements using only two adjustable parameters related to typical energy fluctuations and the interaction range of the micro-strings.

Brownian Motion.

ERIC Educational Resources Information Center

Lavenda, Bernard H.

1985-01-01

Explains the phenomenon of Brownian motion, which serves as a mathematical model for random processes. Topics addressed include kinetic theory, Einstein's theory, particle displacement, and others. Points out that observations of the random course of a particle suspended in fluid led to the first accurate measurement of atomic mass. (DH)

The Effects of Team-Based Learning on Social Studies Knowledge Acquisition in High School

ERIC Educational Resources Information Center

Wanzek, Jeanne; Vaughn, Sharon; Kent, Shawn C.; Swanson, Elizabeth A.; Roberts, Greg; Haynes, Martha; Fall, Anna-Mária; Stillman-Spisak, Stephanie J.; Solis, Michael

2014-01-01

This randomized control trial examined the efficacy of team-based learning implemented within 11th-grade social studies classes. A randomized blocked design was implemented with 26 classes randomly assigned to treatment or comparison. In the treatment classes teachers implemented team-based learning practices to support students in engaging in…

Electromagnetic Scattering by Fully Ordered and Quasi-Random Rigid Particulate Samples

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Dlugach, Janna M.; Mackowski, Daniel W.

2016-01-01

In this paper we have analyzed circumstances under which a rigid particulate sample can behave optically as a true discrete random medium consisting of particles randomly moving relative to each other during measurement. To this end, we applied the numerically exact superposition T-matrix method to model far-field scattering characteristics of fully ordered and quasi-randomly arranged rigid multiparticle groups in fixed and random orientations. We have shown that, in and of itself, averaging optical observables over movements of a rigid sample as a whole is insufficient unless it is combined with a quasi-random arrangement of the constituent particles in the sample. Otherwise, certain scattering effects typical of discrete random media (including some manifestations of coherent backscattering) may not be accurately replicated.

Study of Nonlinear Dynamics of Intense Charged Particle Beams in the Paul Trap Simulator Experiment

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

Wang, Hua

The Paul Trap Simulator Experiment (PTSX) is a compact laboratory device that simulates the nonlinear dynamics of intense charged particle beams propagating over a large distance in an alternating-gradient magnetic transport system. The radial quadrupole electric eld forces on the charged particles in the Paul Trap are analogous to the radial forces on the charged particles in the quadrupole magnetic transport system. The amplitude of oscillating voltage applied to the cylindrical electrodes in PTSX is equivalent to the quadrupole magnetic eld gradient in accelerators. The temporal periodicity in PTSX corresponds to the spatial periodicity in magnetic transport system. This thesismore » focuses on investigations of envelope instabilities and collective mode excitations, properties of high-intensity beams with significant space-charge effects, random noise-induced beam degradation and a laser-induced-fluorescence diagnostic. To better understand the nonlinear dynamics of the charged particle beams, it is critical to understand the collective processes of the charged particles. Charged particle beams support a variety of collective modes, among which the quadrupole mode and the dipole mode are of the greatest interest. We used quadrupole and dipole perturbations to excite the quadrupole and dipole mode respectively and study the effects of those collective modes on the charge bunch. The experimental and particle-in-cell (PIC) simulation results both show that when the frequency and the spatial structure of the external perturbation are matched with the corresponding collective mode, that mode will be excited to a large amplitude and resonates strongly with the external perturbation, usually causing expansion of the charge bunch and loss of particles. Machine imperfections are inevitable for accelerator systems, and we use random noise to simulate the effects of machine imperfection on the charged particle beams. The random noise can be Fourier decomposed into various frequency components and experimental results show that when the random noise has a large frequency component that matches a certain collective mode, the mode will also be excited and cause heating of the charge bunch. It is also noted that by rearranging the order of the random noise, the adverse effects of the random noise may be eliminated. As a non-destructive diagnostic method, a laser-induced- fluorescence (LIF) diagnostic is developed to study the transverse dynamics of the charged particle beams. The accompanying barium ion source and dye laser system are developed and tested.« less

Comparing Algorithms for Graph Isomorphism Using Discrete- and Continuous-Time Quantum Random Walks

DOE PAGES

Rudinger, Kenneth; Gamble, John King; Bach, Eric; ...

2013-07-01

Berry and Wang [Phys. Rev. A 83, 042317 (2011)] show numerically that a discrete-time quan- tum random walk of two noninteracting particles is able to distinguish some non-isomorphic strongly regular graphs from the same family. Here we analytically demonstrate how it is possible for these walks to distinguish such graphs, while continuous-time quantum walks of two noninteracting parti- cles cannot. We show analytically and numerically that even single-particle discrete-time quantum random walks can distinguish some strongly regular graphs, though not as many as two-particle noninteracting discrete-time walks. Additionally, we demonstrate how, given the same quantum random walk, subtle di erencesmore » in the graph certi cate construction algorithm can nontrivially im- pact the walk's distinguishing power. We also show that no continuous-time walk of a xed number of particles can distinguish all strongly regular graphs when used in conjunction with any of the graph certi cates we consider. We extend this constraint to discrete-time walks of xed numbers of noninteracting particles for one kind of graph certi cate; it remains an open question as to whether or not this constraint applies to the other graph certi cates we consider.« less

Locally adaptive methods for KDE-based random walk models of reactive transport in porous media

NASA Astrophysics Data System (ADS)

Sole-Mari, G.; Fernandez-Garcia, D.

2017-12-01

Random Walk Particle Tracking (RWPT) coupled with Kernel Density Estimation (KDE) has been recently proposed to simulate reactive transport in porous media. KDE provides an optimal estimation of the area of influence of particles which is a key element to simulate nonlinear chemical reactions. However, several important drawbacks can be identified: (1) the optimal KDE method is computationally intensive and thereby cannot be used at each time step of the simulation; (2) it does not take advantage of the prior information about the physical system and the previous history of the solute plume; (3) even if the kernel is optimal, the relative error in RWPT simulations typically increases over time as the particle density diminishes by dilution. To overcome these problems, we propose an adaptive branching random walk methodology that incorporates the physics, the particle history and maintains accuracy with time. The method allows particles to efficiently split and merge when necessary as well as to optimally adapt their local kernel shape without having to recalculate the kernel size. We illustrate the advantage of the method by simulating complex reactive transport problems in randomly heterogeneous porous media.

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

Mehta, Y.; Neal, C.; Salari, K.

Propagation of a strong shock through a bed of particles results in complex wave dynamics such as a reflected shock, a transmitted shock, and highly unsteady flow inside the particle bed. In this paper we present three-dimensional numerical simulations of shock propagation in air over a random bed of particles. We assume the flow is inviscid and governed by the Euler equations of gas dynamics. Simulations are carried out by varying the volume fraction of the particle bed at a fixed shock Mach number. We compute the unsteady inviscid streamwise and transverse drag coefficients as a function of time formore » each particle in the random bed as a function of volume fraction. We show that (i) there are significant variations in the peak drag for the particles in the bed, (ii) the mean peak drag as a function of streamwise distance through the bed decreases with a slope that increases as the volume fraction increases, and (iii) the deviation from the mean peak drag does not correlate with local volume fraction. We also present the local Mach number and pressure contours for the different volume fractions to explain the various observed complex physical mechanisms occurring during the shock-particle interactions. Since the shock interaction with the random bed of particles leads to transmitted and reflected waves, we compute the average flow properties to characterize the strength of the transmitted and reflected shock waves and quantify the energy dissipation inside the particle bed. Finally, to better understand the complex wave dynamics in a random bed, we consider a simpler approximation of a planar shock propagating in a duct with a sudden area change. We obtain Riemann solutions to this problem, which are used to compare with fully resolved numerical simulations.« less

Lagrangian particles with mixing. I. Simulating scalar transport

NASA Astrophysics Data System (ADS)

Klimenko, A. Y.

2009-06-01

The physical similarity and mathematical equivalence of continuous diffusion and particle random walk forms one of the cornerstones of modern physics and the theory of stochastic processes. The randomly walking particles do not need to posses any properties other than location in physical space. However, particles used in many models dealing with simulating turbulent transport and turbulent combustion do posses a set of scalar properties and mixing between particle properties is performed to reflect the dissipative nature of the diffusion processes. We show that the continuous scalar transport and diffusion can be accurately specified by means of localized mixing between randomly walking Lagrangian particles with scalar properties and assess errors associated with this scheme. Particles with scalar properties and localized mixing represent an alternative formulation for the process, which is selected to represent the continuous diffusion. Simulating diffusion by Lagrangian particles with mixing involves three main competing requirements: minimizing stochastic uncertainty, minimizing bias introduced by numerical diffusion, and preserving independence of particles. These requirements are analyzed for two limited cases of mixing between two particles and mixing between a large number of particles. The problem of possible dependences between particles is most complicated. This problem is analyzed using a coupled chain of equations that has similarities with Bogolubov-Born-Green-Kirkwood-Yvon chain in statistical physics. Dependences between particles can be significant in close proximity of the particles resulting in a reduced rate of mixing. This work develops further ideas introduced in the previously published letter [Phys. Fluids 19, 031702 (2007)]. Paper I of this work is followed by Paper II [Phys. Fluids 19, 065102 (2009)] where modeling of turbulent reacting flows by Lagrangian particles with localized mixing is specifically considered.

Comparative Emissions of Random Orbital Sanding between Conventional and Self-Generated Vacuum Systems

PubMed Central

Liverseed, David R.

2013-01-01

Conventional abrasive sanding generates high concentrations of particles. Depending on the substrate being abraded and exposure duration, overexposure to the particles can cause negative health effects ranging from respiratory irritation to cancer. The goal of this study was to understand the differences in particle emissions between a conventional random orbital sanding system and a self-generated vacuum random orbital sanding system with attached particle filtration bag. Particle concentrations were sampled for each system in a controlled test chamber for oak wood, chromate painted (hexavalent chromium) steel panels, and gel-coated (titanium dioxide) fiberglass panels using a Gesamtstaub-Probenahmesystem (GSP) sampler at three different locations adjacent to the sanding. Elevated concentrations were reported for all particles in the samples collected during conventional sanding. The geometric mean concentration ratios for the three substrates ranged from 320 to 4640 times greater for the conventional sanding system than the self-generated vacuum sanding system. The differences in the particle concentration generated by the two sanding systems were statistically significant with the two sample t-test (P < 0.0001) for all three substances. The data suggest that workers using conventional sanding systems could utilize the self-generated vacuum sanding system technology to potentially reduce exposure to particles and mitigate negative health effects. PMID:23065674

Comparative emissions of random orbital sanding between conventional and self-generated vacuum systems.

PubMed

Liverseed, David R; Logan, Perry W; Johnson, Carl E; Morey, Sandy Z; Raynor, Peter C

2013-03-01

Conventional abrasive sanding generates high concentrations of particles. Depending on the substrate being abraded and exposure duration, overexposure to the particles can cause negative health effects ranging from respiratory irritation to cancer. The goal of this study was to understand the differences in particle emissions between a conventional random orbital sanding system and a self-generated vacuum random orbital sanding system with attached particle filtration bag. Particle concentrations were sampled for each system in a controlled test chamber for oak wood, chromate painted (hexavalent chromium) steel panels, and gel-coated (titanium dioxide) fiberglass panels using a Gesamtstaub-Probenahmesystem (GSP) sampler at three different locations adjacent to the sanding. Elevated concentrations were reported for all particles in the samples collected during conventional sanding. The geometric mean concentration ratios for the three substrates ranged from 320 to 4640 times greater for the conventional sanding system than the self-generated vacuum sanding system. The differences in the particle concentration generated by the two sanding systems were statistically significant with the two sample t-test (P < 0.0001) for all three substances. The data suggest that workers using conventional sanding systems could utilize the self-generated vacuum sanding system technology to potentially reduce exposure to particles and mitigate negative health effects.

Random walk, diffusion and mixing in simulations of scalar transport in fluid flows

NASA Astrophysics Data System (ADS)

Klimenko, A. Y.

2008-12-01

Physical similarity and mathematical equivalence of continuous diffusion and particle random walk form one of the cornerstones of modern physics and the theory of stochastic processes. In many applied models used in simulation of turbulent transport and turbulent combustion, mixing between particles is used to reflect the influence of the continuous diffusion terms in the transport equations. We show that the continuous scalar transport and diffusion can be accurately specified by means of mixing between randomly walking Lagrangian particles with scalar properties and assess errors associated with this scheme. This gives an alternative formulation for the stochastic process which is selected to represent the continuous diffusion. This paper focuses on statistical errors and deals with relatively simple cases, where one-particle distributions are sufficient for a complete description of the problem.

Phenomenological picture of fluctuations in branching random walks

NASA Astrophysics Data System (ADS)

Mueller, A. H.; Munier, S.

2014-10-01

We propose a picture of the fluctuations in branching random walks, which leads to predictions for the distribution of a random variable that characterizes the position of the bulk of the particles. We also interpret the 1 /√{t } correction to the average position of the rightmost particle of a branching random walk for large times t ≫1 , computed by Ebert and Van Saarloos, as fluctuations on top of the mean-field approximation of this process with a Brunet-Derrida cutoff at the tip that simulates discreteness. Our analytical formulas successfully compare to numerical simulations of a particular model of a branching random walk.

Simulating Pre-Asymptotic, Non-Fickian Transport Although Doing Simple Random Walks - Supported By Empirical Pore-Scale Velocity Distributions and Memory Effects

NASA Astrophysics Data System (ADS)

Most, S.; Jia, N.; Bijeljic, B.; Nowak, W.

2016-12-01

Pre-asymptotic characteristics are almost ubiquitous when analyzing solute transport processes in porous media. These pre-asymptotic aspects are caused by spatial coherence in the velocity field and by its heterogeneity. For the Lagrangian perspective of particle displacements, the causes of pre-asymptotic, non-Fickian transport are skewed velocity distribution, statistical dependencies between subsequent increments of particle positions (memory) and dependence between the x, y and z-components of particle increments. Valid simulation frameworks should account for these factors. We propose a particle tracking random walk (PTRW) simulation technique that can use empirical pore-space velocity distributions as input, enforces memory between subsequent random walk steps, and considers cross dependence. Thus, it is able to simulate pre-asymptotic non-Fickian transport phenomena. Our PTRW framework contains an advection/dispersion term plus a diffusion term. The advection/dispersion term produces time-series of particle increments from the velocity CDFs. These time series are equipped with memory by enforcing that the CDF values of subsequent velocities change only slightly. The latter is achieved through a random walk on the axis of CDF values between 0 and 1. The virtual diffusion coefficient for that random walk is our only fitting parameter. Cross-dependence can be enforced by constraining the random walk to certain combinations of CDF values between the three velocity components in x, y and z. We will show that this modelling framework is capable of simulating non-Fickian transport by comparison with a pore-scale transport simulation and we analyze the approach to asymptotic behavior.

Continuous time random walk with local particle-particle interaction

NASA Astrophysics Data System (ADS)

Xu, Jianping; Jiang, Guancheng

2018-05-01

The continuous time random walk (CTRW) is often applied to the study of particle motion in disordered media. Yet most such applications do not allow for particle-particle (walker-walker) interaction. In this paper, we consider a CTRW with particle-particle interaction; however, for simplicity, we restrain the interaction to be local. The generalized Chapman-Kolmogorov equation is modified by introducing a perturbation function that fluctuates around 1, which models the effect of interaction. Subsequently, a time-fractional nonlinear advection-diffusion equation is derived from this walking system. Under the initial condition of condensed particles at the origin and the free-boundary condition, we numerically solve this equation with both attractive and repulsive particle-particle interactions. Moreover, a Monte Carlo simulation is devised to verify the results of the above numerical work. The equation and the simulation unanimously predict that this walking system converges to the conventional one in the long-time limit. However, for systems where the free-boundary condition and long-time limit are not simultaneously satisfied, this convergence does not hold.

Charged-particle therapy in cancer: clinical uses and future perspectives.

PubMed

Durante, Marco; Orecchia, Roberto; Loeffler, Jay S

2017-08-01

Radiotherapy with high-energy charged particles has become an attractive therapeutic option for patients with several tumour types because this approach better spares healthy tissue from radiation than conventional photon therapy. The cost associated with the delivery of charged particles, however, is higher than that of even the most elaborate photon-delivery technologies. Reliable evidence of the relative cost-effectiveness of both modalities can only come from the results of randomized clinical trials. Thus, the hurdles that currently limit direct comparisons of these two approaches in clinical trials, especially those related to insurance coverage, should be removed. Herein, we review several randomized trials of charged-particle therapies that are ongoing, with results that will enable selective delivery to patients who are most likely to benefit from them. We also discuss aspects related to radiobiology, including the immune response and hypoxia, which will need to be taken into consideration in future randomized trials to fully exploit the potential of charged particles.

Effect of magnetic helicity upon rectilinear propagation of charged particles in random magnetic fields

NASA Technical Reports Server (NTRS)

Earl, James A.

1992-01-01

When charged particles spiral along a large constant magnetic field, their trajectories are scattered by any random field components that are superposed on the guiding field. If the random field configuration embodies helicity, the scattering is asymmetrical with respect to a plane perpendicular to the guiding field, for particles moving into the forward hemisphere are scattered at different rates from those moving into the backward hemisphere. This asymmetry gives rise to new terms in the transport equations that describe propagation of charged particles. Helicity has virtually no impact on qualitative features of the diffusive mode of propagation. However, characteristic velocities of the coherent modes that appear after a highly anisotropic injection exhibit an asymmetry related to helicity. Explicit formulas, which embody the effects of helicity, are given for the anisotropies, the coefficient diffusion, and the coherent velocities. Predictions derived from these expressions are in good agreement with Monte Carlo simulations of particle transport, but the simulations reveal certain phenomena whose explanation calls for further analytical work.

Secondary Students' Thinking about Familiar Phenomena: Learners' Explanations from a Curriculum Context Where "Particles" Is a Key Idea for Organising Teaching and Learning

ERIC Educational Resources Information Center

Garcia Franco, Alejandra; Taber, Keith S.

2009-01-01

Particle models of matter are widely recognised as being of fundamental importance in many branches of modern science, and particle ideas are commonly introduced and developed in the secondary school curriculum. However, research undertaken in a range of national contexts has identified significant learning difficulties in this topic, and suggests…

Exact solution of two interacting run-and-tumble random walkers with finite tumble duration

NASA Astrophysics Data System (ADS)

Slowman, A. B.; Evans, M. R.; Blythe, R. A.

2017-09-01

We study a model of interacting run-and-tumble random walkers operating under mutual hardcore exclusion on a one-dimensional lattice with periodic boundary conditions. We incorporate a finite, poisson-distributed, tumble duration so that a particle remains stationary whilst tumbling, thus generalising the persistent random walker model. We present the exact solution for the nonequilibrium stationary state of this system in the case of two random walkers. We find this to be characterised by two lengthscales, one arising from the jamming of approaching particles, and the other from one particle moving when the other is tumbling. The first of these lengthscales vanishes in a scaling limit where the continuous-space dynamics is recovered whilst the second remains finite. Thus the nonequilibrium stationary state reveals a rich structure of attractive, jammed and extended pieces.

Flow Navigation by Smart Microswimmers via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Colabrese, Simona; Biferale, Luca; Celani, Antonio; Gustavsson, Kristian

2017-11-01

We have numerically modeled active particles which are able to acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. We show that those swimmers can learn effective strategies just by experience, using a reinforcement learning algorithm. As an example, we focus on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, exploiting the underlying flow whenever possible. The reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This work paves the way towards the engineering of smart microswimmers that solve difficult navigation problems. ERC AdG NewTURB 339032.

Random deposition of particles of different sizes.

PubMed

Forgerini, F L; Figueiredo, W

2009-04-01

We study the surface growth generated by the random deposition of particles of different sizes. A model is proposed where the particles are aggregated on an initially flat surface, giving rise to a rough interface and a porous bulk. By using Monte Carlo simulations, a surface has grown by adding particles of different sizes, as well as identical particles on the substrate in (1+1) dimensions. In the case of deposition of particles of different sizes, they are selected from a Poisson distribution, where the particle sizes may vary by 1 order of magnitude. For the deposition of identical particles, only particles which are larger than one lattice parameter of the substrate are considered. We calculate the usual scaling exponents: the roughness, growth, and dynamic exponents alpha, beta, and z, respectively, as well as, the porosity in the bulk, determining the porosity as a function of the particle size. The results of our simulations show that the roughness evolves in time following three different behaviors. The roughness in the initial times behaves as in the random deposition model. At intermediate times, the surface roughness grows slowly and finally, at long times, it enters into the saturation regime. The bulk formed by depositing large particles reveals a porosity that increases very fast at the initial times and also reaches a saturation value. Excepting the case where particles have the size of one lattice spacing, we always find that the surface roughness and porosity reach limiting values at long times. Surprisingly, we find that the scaling exponents are the same as those predicted by the Villain-Lai-Das Sarma equation.

Symbiosis-Based Alternative Learning Multi-Swarm Particle Swarm Optimization.

PubMed

Niu, Ben; Huang, Huali; Tan, Lijing; Duan, Qiqi

2017-01-01

Inspired by the ideas from the mutual cooperation of symbiosis in natural ecosystem, this paper proposes a new variant of PSO, named Symbiosis-based Alternative Learning Multi-swarm Particle Swarm Optimization (SALMPSO). A learning probability to select one exemplar out of the center positions, the local best position, and the historical best position including the experience of internal and external multiple swarms, is used to keep the diversity of the population. Two different levels of social interaction within and between multiple swarms are proposed. In the search process, particles not only exchange social experience with others that are from their own sub-swarms, but also are influenced by the experience of particles from other fellow sub-swarms. According to the different exemplars and learning strategy, this model is instantiated as four variants of SALMPSO and a set of 15 test functions are conducted to compare with some variants of PSO including 10, 30 and 50 dimensions, respectively. Experimental results demonstrate that the alternative learning strategy in each SALMPSO version can exhibit better performance in terms of the convergence speed and optimal values on most multimodal functions in our simulation.

Particle Swarm Optimization with Double Learning Patterns.

PubMed

Shen, Yuanxia; Wei, Linna; Zeng, Chuanhua; Chen, Jian

2016-01-01

Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP) is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants.

Rare event simulation in radiation transport

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

Kollman, Craig

1993-10-01

This dissertation studies methods for estimating extremely small probabilities by Monte Carlo simulation. Problems in radiation transport typically involve estimating very rare events or the expected value of a random variable which is with overwhelming probability equal to zero. These problems often have high dimensional state spaces and irregular geometries so that analytic solutions are not possible. Monte Carlo simulation must be used to estimate the radiation dosage being transported to a particular location. If the area is well shielded the probability of any one particular particle getting through is very small. Because of the large number of particles involved,more » even a tiny fraction penetrating the shield may represent an unacceptable level of radiation. It therefore becomes critical to be able to accurately estimate this extremely small probability. Importance sampling is a well known technique for improving the efficiency of rare event calculations. Here, a new set of probabilities is used in the simulation runs. The results are multiple by the likelihood ratio between the true and simulated probabilities so as to keep the estimator unbiased. The variance of the resulting estimator is very sensitive to which new set of transition probabilities are chosen. It is shown that a zero variance estimator does exist, but that its computation requires exact knowledge of the solution. A simple random walk with an associated killing model for the scatter of neutrons is introduced. Large deviation results for optimal importance sampling in random walks are extended to the case where killing is present. An adaptive ``learning`` algorithm for implementing importance sampling is given for more general Markov chain models of neutron scatter. For finite state spaces this algorithm is shown to give with probability one, a sequence of estimates converging exponentially fast to the true solution.« less

DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.

PubMed

Wang, Feng; Gong, Huichao; Liu, Gaochao; Li, Meijing; Yan, Chuangye; Xia, Tian; Li, Xueming; Zeng, Jianyang

2016-09-01

Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep learning framework, called DeepPicker, to address this problem and fill the current gaps toward a fully automated cryo-EM pipeline. DeepPicker employs a novel cross-molecule training strategy to capture common features of particles from previously-analyzed micrographs, and thus does not require any human intervention during particle picking. Tests on the recently-published cryo-EM data of three complexes have demonstrated that our deep learning based scheme can successfully accomplish the human-level particle picking process and identify a sufficient number of particles that are comparable to those picked manually by human experts. These results indicate that DeepPicker can provide a practically useful tool to significantly reduce the time and manual effort spent in single-particle analysis and thus greatly facilitate high-resolution cryo-EM structure determination. DeepPicker is released as an open-source program, which can be downloaded from https://github.com/nejyeah/DeepPicker-python. Copyright © 2016 Elsevier Inc. All rights reserved.

Exits in order: How crowding affects particle lifetimes

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

Penington, Catherine J.; Simpson, Matthew J.; Baker, Ruth E.

2016-06-28

Diffusive processes are often represented using stochastic random walk frameworks. The amount of time taken for an individual in a random walk to intersect with an absorbing boundary is a fundamental property that is often referred to as the particle lifetime, or the first passage time. The mean lifetime of particles in a random walk model of diffusion is related to the amount of time required for the diffusive process to reach a steady state. Mathematical analysis describing the mean lifetime of particles in a standard model of diffusion without crowding is well known. However, the lifetime of agents inmore » a random walk with crowding has received much less attention. Since many applications of diffusion in biology and biophysics include crowding effects, here we study a discrete model of diffusion that incorporates crowding. Using simulations, we show that crowding has a dramatic effect on agent lifetimes, and we derive an approximate expression for the mean agent lifetime that includes crowding effects. Our expression matches simulation results very well, and highlights the importance of crowding effects that are sometimes overlooked.« less

Scale-invariant puddles in graphene: Geometric properties of electron-hole distribution at the Dirac point.

PubMed

Najafi, M N; Nezhadhaghighi, M Ghasemi

2017-03-01

We characterize the carrier density profile of the ground state of graphene in the presence of particle-particle interaction and random charged impurity in zero gate voltage. We provide detailed analysis on the resulting spatially inhomogeneous electron gas, taking into account the particle-particle interaction and the remote Coulomb disorder on an equal footing within the Thomas-Fermi-Dirac theory. We present some general features of the carrier density probability measure of the graphene sheet. We also show that, when viewed as a random surface, the electron-hole puddles at zero chemical potential show peculiar self-similar statistical properties. Although the disorder potential is chosen to be Gaussian, we show that the charge field is non-Gaussian with unusual Kondev relations, which can be regarded as a new class of two-dimensional random-field surfaces. Using Schramm-Loewner (SLE) evolution, we numerically demonstrate that the ungated graphene has conformal invariance and the random zero-charge density contours are SLE_{κ} with κ=1.8±0.2, consistent with c=-3 conformal field theory.

Second Graders' Emerging Particle Models of Matter in the Context of Learning through Model-Based Inquiry

ERIC Educational Resources Information Center

Samarapungavan, Ala; Bryan, Lynn; Wills, Jamison

2017-01-01

In this paper, we present a study of second graders' learning about the nature of matter in the context of content-rich, model-based inquiry instruction. The goal of instruction was to help students learn to use simple particle models to explain states of matter and phase changes. We examined changes in students' ideas about matter, the coherence…

Dynamics of planetary rings

NASA Technical Reports Server (NTRS)

Araki, Suguru

1991-01-01

The modeling of the dynamics of particle collisions within planetary rings is discussed. Particles in the rings collide with one another because they have small random motions in addition to their orbital velocity. The orbital speed is roughly 10 km/s, while the random motions have an average speed of about a tenth of a millimeter per second. As a result, the particle collisions are very gentle. Numerical analysis and simulation of the ring dynamics, performed with the aid of a supercomputer, is outlined.

Role of small-norm components in extended random-phase approximation

NASA Astrophysics Data System (ADS)

Tohyama, Mitsuru

2017-09-01

The role of the small-norm amplitudes in extended random-phase approximation (RPA) theories such as the particle-particle and hole-hole components of one-body amplitudes and the two-body amplitudes other than two-particle/two-hole components are investigated for the one-dimensional Hubbard model using an extended RPA derived from the time-dependent density matrix theory. It is found that these amplitudes cannot be neglected in strongly interacting regions where the effects of ground-state correlations are significant.

Brownian Motion in a Speckle Light Field: Tunable Anomalous Diffusion and Selective Optical Manipulation

PubMed Central

Volpe, Giorgio; Volpe, Giovanni; Gigan, Sylvain

2014-01-01

The motion of particles in random potentials occurs in several natural phenomena ranging from the mobility of organelles within a biological cell to the diffusion of stars within a galaxy. A Brownian particle moving in the random optical potential associated to a speckle pattern, i.e., a complex interference pattern generated by the scattering of coherent light by a random medium, provides an ideal model system to study such phenomena. Here, we derive a theory for the motion of a Brownian particle in a speckle field and, in particular, we identify its universal characteristic timescale. Based on this theoretical insight, we show how speckle light fields can be used to control the anomalous diffusion of a Brownian particle and to perform some basic optical manipulation tasks such as guiding and sorting. Our results might broaden the perspectives of optical manipulation for real-life applications. PMID:24496461

Development of multiple-eye PIV using mirror array

NASA Astrophysics Data System (ADS)

Maekawa, Akiyoshi; Sakakibara, Jun

2018-06-01

In order to reduce particle image velocimetry measurement error, we manufactured an ellipsoidal polyhedral mirror and placed it between a camera and flow target to capture n images of identical particles from n (=80 maximum) different directions. The 3D particle positions were determined from the ensemble average of n C2 intersecting points of a pair of line-of-sight back-projected points from a particle found in any combination of two images in the n images. The method was then applied to a rigid-body rotating flow and a turbulent pipe flow. In the former measurement, bias error and random error fell in a range of  ±0.02 pixels and 0.02–0.05 pixels, respectively; additionally, random error decreased in proportion to . In the latter measurement, in which the measured value was compared to direct numerical simulation, bias error was reduced and random error also decreased in proportion to .

Controlling dispersion forces between small particles with artificially created random light fields

PubMed Central

Brügger, Georges; Froufe-Pérez, Luis S.; Scheffold, Frank; José Sáenz, Juan

2015-01-01

Appropriate combinations of laser beams can be used to trap and manipulate small particles with optical tweezers as well as to induce significant optical binding forces between particles. These interaction forces are usually strongly anisotropic depending on the interference landscape of the external fields. This is in contrast with the familiar isotropic, translationally invariant, van der Waals and, in general, Casimir–Lifshitz interactions between neutral bodies arising from random electromagnetic waves generated by equilibrium quantum and thermal fluctuations. Here we show, both theoretically and experimentally, that dispersion forces between small colloidal particles can also be induced and controlled using artificially created fluctuating light fields. Using optical tweezers as a gauge, we present experimental evidence for the predicted isotropic attractive interactions between dielectric microspheres induced by laser-generated, random light fields. These light-induced interactions open a path towards the control of translationally invariant interactions with tuneable strength and range in colloidal systems. PMID:26096622

A Local-Realistic Model of Quantum Mechanics Based on a Discrete Spacetime

NASA Astrophysics Data System (ADS)

Sciarretta, Antonio

2018-01-01

This paper presents a realistic, stochastic, and local model that reproduces nonrelativistic quantum mechanics (QM) results without using its mathematical formulation. The proposed model only uses integer-valued quantities and operations on probabilities, in particular assuming a discrete spacetime under the form of a Euclidean lattice. Individual (spinless) particle trajectories are described as random walks. Transition probabilities are simple functions of a few quantities that are either randomly associated to the particles during their preparation, or stored in the lattice nodes they visit during the walk. QM predictions are retrieved as probability distributions of similarly-prepared ensembles of particles. The scenarios considered to assess the model comprise of free particle, constant external force, harmonic oscillator, particle in a box, the Delta potential, particle on a ring, particle on a sphere and include quantization of energy levels and angular momentum, as well as momentum entanglement.

Diffusion of massive particles around an Abelian-Higgs string

NASA Astrophysics Data System (ADS)

Saha, Abhisek; Sanyal, Soma

2018-03-01

We study the diffusion of massive particles in the space time of an Abelian Higgs string. The particles in the early universe plasma execute Brownian motion. This motion of the particles is modeled as a two dimensional random walk in the plane of the Abelian Higgs string. The particles move randomly in the space time of the string according to their geodesic equations. We observe that for certain values of their energy and angular momentum, an overdensity of particles is observed close to the string. We find that the string parameters determine the distribution of the particles. We make an estimate of the density fluctuation generated around the string as a function of the deficit angle. Though the thickness of the string is small, the length is large and the overdensity close to the string may have cosmological consequences in the early universe.

Flow Navigation by Smart Microswimmers via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Colabrese, Simona; Gustavsson, Kristian; Celani, Antonio; Biferale, Luca

2017-04-01

Smart active particles can acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. Their goal is to learn the best way to navigate by exploiting the underlying flow whenever possible. As an example, we focus our attention on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, given the constraints enforced by fluid mechanics. By means of numerical experiments, we show that swimmers indeed learn nearly optimal strategies just by experience. A reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This Letter illustrates the potential of reinforcement learning algorithms to model adaptive behavior in complex flows and paves the way towards the engineering of smart microswimmers that solve difficult navigation problems.

Lack of Interaction between Sensing-Intuitive Learning Styles and Problem-First versus Information-First Instruction: A Randomized Crossover Trial

ERIC Educational Resources Information Center

Cook, David A.; Thompson, Warren G.; Thomas, Kris G.; Thomas, Matthew R.

2009-01-01

Background: Adaptation to learning styles has been proposed to enhance learning. Objective: We hypothesized that learners with sensing learning style would perform better using a problem-first instructional method while intuitive learners would do better using an information-first method. Design: Randomized, controlled, crossover trial. Setting:…

Diffusion of strongly magnetized cosmic ray particles in a turbulent medium

NASA Technical Reports Server (NTRS)

Ptuskin, V. S.

1985-01-01

Cosmic ray (CR) propagation in a turbulent medium is usually considered in the diffusion approximation. Here, the diffusion equation is obtained for strongly magnetized particles in the general form. The influence of a large-scale random magnetic field on CR propagation in interstellar medium is discussed. Cosmic rays are assumed to propagate in a medium with a regular field H and an ensemble of random MHD waves. The energy density of waves on scales smaller than the free path 1 of CR particles is small. The collision integral of the general form which describes interaction between relativistic particles and waves in the quasilinear approximation is used.

Shearing Low-frictional 3D Granular Materials

NASA Astrophysics Data System (ADS)

Chen, David; Zheng, Hu; Behringer, Robert

Shear jamming occurs in frictional particles over a range of packing fractions, from random loose to random dense. Simulations show shear jamming for frictionless spheres, but over a vanishing range as the system size grows. We use packings of submerged and diffractive index-matched hydrogel particles to determine the shear-induced microscopic response of 3D, low-frictional granular systems near jamming, bridging the gap between frictionless and low friction packings. We visualize the particles by a laser scanning technique, and we track particle motion along with their interparticle contact forces from its 3D-reconstructions. NSF-DMF-1206351, NASA NNX15AD38G, William M. Keck Foundation, and DARPA.

Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements

NASA Astrophysics Data System (ADS)

Veselovskii, I.; Dubovik, O.; Kolgotin, A.; Lapyonok, T.; di Girolamo, P.; Summa, D.; Whiteman, D. N.; Mishchenko, M.; Tanré, D.

2010-11-01

Multiwavelength (MW) Raman lidars have demonstrated their potential to profile particle parameters; however, until now, the physical models used in retrieval algorithms for processing MW lidar data have been predominantly based on the Mie theory. This approach is applicable to the modeling of light scattering by spherically symmetric particles only and does not adequately reproduce the scattering by generally nonspherical desert dust particles. Here we present an algorithm based on a model of randomly oriented spheroids for the inversion of multiwavelength lidar data. The aerosols are modeled as a mixture of two aerosol components: one composed only of spherical and the second composed of nonspherical particles. The nonspherical component is an ensemble of randomly oriented spheroids with size-independent shape distribution. This approach has been integrated into an algorithm retrieving aerosol properties from the observations with a Raman lidar based on a tripled Nd:YAG laser. Such a lidar provides three backscattering coefficients, two extinction coefficients, and the particle depolarization ratio at a single or multiple wavelengths. Simulations were performed for a bimodal particle size distribution typical of desert dust particles. The uncertainty of the retrieved particle surface, volume concentration, and effective radius for 10% measurement errors is estimated to be below 30%. We show that if the effect of particle nonsphericity is not accounted for, the errors in the retrieved aerosol parameters increase notably. The algorithm was tested with experimental data from a Saharan dust outbreak episode, measured with the BASIL multiwavelength Raman lidar in August 2007. The vertical profiles of particle parameters as well as the particle size distributions at different heights were retrieved. It was shown that the algorithm developed provided substantially reasonable results consistent with the available independent information about the observed aerosol event.

The Learning Reconstruction of Particle System and Linear Momentum Conservation in Introductory Physics Course

NASA Astrophysics Data System (ADS)

Karim, S.; Saepuzaman, D.; Sriyansyah, S. P.

2016-08-01

This study is initiated by low achievement of prospective teachers in understanding concepts in introductory physics course. In this case, a problem has been identified that students cannot develop their thinking skills required for building physics concepts. Therefore, this study will reconstruct a learning process, emphasizing a physics concept building. The outcome will design physics lesson plans for the concepts of particle system as well as linear momentum conservation. A descriptive analysis method will be used in order to investigate the process of learning reconstruction carried out by students. In this process, the students’ conceptual understanding will be evaluated using essay tests for concepts of particle system and linear momentum conservation. The result shows that the learning reconstruction has successfully supported the students’ understanding of physics concept.

An Interactive Computer Model for Improved Student Understanding of Random Particle Motion and Osmosis

ERIC Educational Resources Information Center

Kottonau, Johannes

2011-01-01

Effectively teaching the concepts of osmosis to college-level students is a major obstacle in biological education. Therefore, a novel computer model is presented that allows students to observe the random nature of particle motion simultaneously with the seemingly directed net flow of water across a semipermeable membrane during osmotic…

A particle swarm optimization variant with an inner variable learning strategy.

PubMed

Wu, Guohua; Pedrycz, Witold; Ma, Manhao; Qiu, Dishan; Li, Haifeng; Liu, Jin

2014-01-01

Although Particle Swarm Optimization (PSO) has demonstrated competitive performance in solving global optimization problems, it exhibits some limitations when dealing with optimization problems with high dimensionality and complex landscape. In this paper, we integrate some problem-oriented knowledge into the design of a certain PSO variant. The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL) is particularly efficient for optimizing functions with symmetric variables. Symmetric variables of the optimized function have to satisfy a certain quantitative relation. Based on this knowledge, the inner variable learning (IVL) strategy helps the particle to inspect the relation among its inner variables, determine the exemplar variable for all other variables, and then make each variable learn from the exemplar variable in terms of their quantitative relations. In addition, we design a new trap detection and jumping out strategy to help particles escape from local optima. The trap detection operation is employed at the level of individual particles whereas the trap jumping out strategy is adaptive in its nature. Experimental simulations completed for some representative optimization functions demonstrate the excellent performance of PSO-IVL. The effectiveness of the PSO-IVL stresses a usefulness of augmenting evolutionary algorithms by problem-oriented domain knowledge.

The Demand for, and Impact of, Learning HIV Status

PubMed Central

Thornton, Rebecca L.

2011-01-01

This paper evaluates an experiment in which individuals in rural Malawi were randomly assigned monetary incentives to learn their HIV results after being tested. Distance to the HIV results centers was also randomly assigned. Without any incentive, 34 percent of the participants learned their HIV results. However, even the smallest incentive doubled that share. Using the randomly assigned incentives and distance from results centers as instruments for the knowledge of HIV status, sexually active HIV-positive individuals who learned their results are three times more likely to purchase condoms two months later than sexually active HIV-positive individuals who did not learn their results; however, HIV-positive individuals who learned their results purchase only two additional condoms than those who did not. There is no significant effect of learning HIV-negative status on the purchase of condoms. PMID:21687831

Measurements of orientation, sedimentation, and dispersal of ramified particles in isotropic turbulence

NASA Astrophysics Data System (ADS)

Voth, Greg A.; Kramel, Stefan; Menon, Udayshankar K.; Koch, Donald L.

2017-11-01

We experimentally measure the sedimentation of non-spherical particles in isotropic turbulence. We obtain time-resolved 3D orientations of the particles along with the fluid velocity field around them in a vertical water tunnel. An active jet array with 40 individually controllable jets enables us to adjust the turbulence intensity and observe the transition from strongly aligned to randomized particle orientations. We focus on the orientation statistics of ramified particles formed from several slender arms, including fibers and particles with three arms in planar symmetry (triads), which allows us to study alignment of both fibers and disk-like particles. We can predict the turbulent intensity at which the transition from aligned to randomized particle orientations occurs using a non-dimensional settling factor given by the ratio of rotation timescale of the turbulence at the scale of the particle to the rotation timescale of a particles in quiescent flow due to inertial torques. A model of ramified particle motion based on slender body theory provides accurate predictions of the vertical and horizontal particle velocities relative to the turbulent fluid. Supported by Army Research Office Grant W911NF1510205.

Particle Swarm Optimization with Double Learning Patterns

PubMed Central

Shen, Yuanxia; Wei, Linna; Zeng, Chuanhua; Chen, Jian

2016-01-01

Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP) is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants. PMID:26858747

Microstructure, mixing rules and interfacial behavior in high k barium titanate epoxy composite

NASA Astrophysics Data System (ADS)

Shi, Yitong (Thomas)

2001-07-01

In this thesis, we have demonstrated the importance of two issues in BaTiO3/epoxy composites. They are (1) the miscibility of a particle blend in organic vehicle, i.e. the capability of particles with different particle sizes to mix at the particle level, and (2) the ceramic/polymer interface as a role in determining the effective dielectric constant. The epoxy matrix between the BaTiO3 particles is not homogeneous and has to be modeled as a two-layer structure. The inhomogeneity causes not only failure of the existing mixing rules but also the particle size dependence of the effective dielectric constant. Since the interfacial behavior is determined by the materials chemistry, the effective dielectric properties experimentally demonstrate strong dependence on the materials selection and processing. If BaTiO3 particles in liquid epoxy resin has a bimodal particle size distribution, the smaller particles do not experimentally fit into the interstitial spaces between the larger spheres in an organic vehicle. ESEM observations indicated that the large particles separated from the small ones. Depending on the paste formula, the particle separation led to either a layer-like or cluster-like microstructure. The mixing free energy of blending smaller particles with larger particles explains the observed phenomena and suggests general criteria for particle miscibility. Whenever the mixing free energy is negative and the mixing free energy curve is convex, the particle blend remains in a random particle distribution. Otherwise, the particles separate into a larger-particle rich "phase" and a smaller-particle rich "phase". A random particle distribution may be the largest degree of mixing we can achieve in an organic vehicle. If there is no specific interaction between the small particles and the large particles, there is no thermodynamic driving force for small particles to fill preferentially into the interstitial spaces between the large spheres. The Hamaker constant H significantly influences the miscibility of a particle blend. An increase in Hamaker constant H causes not only greater driving force for a particle blend to separate but also a more narrowed convex shape---the mixing window. At a specific composition, a particle blend separates in one vehicle but may remain in a random distribution in another vehicle if the later vehicle has significantly reduced the Hamaker constant H.

Learning with the ATLAS Experiment at CERN

ERIC Educational Resources Information Center

Barnett, R. M.; Johansson, K. E.; Kourkoumelis, C.; Long, L.; Pequenao, J.; Reimers, C.; Watkins, P.

2012-01-01

With the start of the LHC, the new particle collider at CERN, the ATLAS experiment is also providing high-energy particle collisions for educational purposes. Several education projects--education scenarios--have been developed and tested on students and teachers in several European countries within the Learning with ATLAS@CERN project. These…

Scattering by randomly oriented ellipsoids: Application to aerosol and cloud problems

NASA Technical Reports Server (NTRS)

Asano, S.; Sato, M.; Hansen, J. E.

1979-01-01

A program was developed for computing the scattering and absorption by arbitrarily oriented and randomly oriented prolate and oblate spheroids. This permits examination of the effect of particle shape for cases ranging from needles through spheres to platelets. Applications of this capability to aerosol and cloud problems are discussed. Initial results suggest that the effect of nonspherical particle shape on transfer of radiation through aerosol layers and cirrus clouds, as required for many climate studies, can be readily accounted for by defining an appropriate effective spherical particle radius.

Random bearings and their stability.

PubMed

Mahmoodi Baram, Reza; Herrmann, Hans J

2005-11-25

Self-similar space-filling bearings have been proposed some time ago as models for the motion of tectonic plates and appearance of seismic gaps. These models have two features which, however, seem unrealistic, namely, high symmetry in the arrangement of the particles, and lack of a lower cutoff in the size of the particles. In this work, an algorithm for generating random bearings in both two and three dimensions is presented. Introducing a lower cutoff for the sizes of the particles, the instabilities of the bearing under an external force such as gravity, are studied.

A distribution model for the aerial application of granular agricultural particles

NASA Technical Reports Server (NTRS)

Fernandes, S. T.; Ormsbee, A. I.

1978-01-01

A model is developed to predict the shape of the distribution of granular agricultural particles applied by aircraft. The particle is assumed to have a random size and shape and the model includes the effect of air resistance, distributor geometry and aircraft wake. General requirements for the maintenance of similarity of the distribution for scale model tests are derived and are addressed to the problem of a nongeneral drag law. It is shown that if the mean and variance of the particle diameter and density are scaled according to the scaling laws governing the system, the shape of the distribution will be preserved. Distributions are calculated numerically and show the effect of a random initial lateral position, particle size and drag coefficient. A listing of the computer code is included.

Demonstration of Numerical Equivalence of Ensemble and Spectral Averaging in Electromagnetic Scattering by Random Particulate Media

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Dlugach, Janna M.; Zakharova, Nadezhda T.

2016-01-01

The numerically exact superposition T-matrix method is used to model far-field electromagnetic scattering by two types of particulate object. Object 1 is a fixed configuration which consists of N identical spherical particles (with N 200 or 400) quasi-randomly populating a spherical volume V having a median size parameter of 50. Object 2 is a true discrete random medium (DRM) comprising the same number N of particles randomly moving throughout V. The median particle size parameter is fixed at 4. We show that if Object 1 is illuminated by a quasi-monochromatic parallel beam then it generates a typical speckle pattern having no resemblance to the scattering pattern generated by Object 2. However, if Object 1 is illuminated by a parallel polychromatic beam with a 10 bandwidth then it generates a scattering pattern that is largely devoid of speckles and closely reproduces the quasi-monochromatic pattern generated by Object 2. This result serves to illustrate the capacity of the concept of electromagnetic scattering by a DRM to encompass fixed quasi-random particulate samples provided that they are illuminated by polychromatic light.

Experimental investigation of clogging dynamics in homogeneous porous medium

NASA Astrophysics Data System (ADS)

Shen, Jikang; Ni, Rui

2017-03-01

A 3-D refractive-index matching Lagrangian particle tracking (3D-RIM-LPT) system was developed to study the filtration and the clogging process inside a homogeneous porous medium. A small subset of particles flowing through the porous medium was dyed and tracked. As this subset was randomly chosen, its dynamics is representative of all the rest. The statistics of particle locations, number, and velocity were obtained as functions of different volumetric concentrations. It is found that in our system the clogging time decays with the particle concentration following a power law relationship. As the concentration increases, there is a transition from depth filtration to cake filtration. At high concentration, more clogged pores lead to frequent flow redirections and more transverse migrations of particles. In addition, the velocity distribution in the transverse direction is symmetrical around zero, and it is slightly more intermittent than the random Gaussian curve due to particle-particle and particle-grain interactions. In contrast, as clogging develops, the longitudinal velocity of particles along the mean flow direction peaks near zero because of many trapped particles. But at the same time, the remaining open pores will experience larger pressure and, as a result, particles through those pores tend to have larger longitudinal velocities.

Relative distance between tracers as a measure of diffusivity within moving aggregates

NASA Astrophysics Data System (ADS)

Pönisch, Wolfram; Zaburdaev, Vasily

2018-02-01

Tracking of particles, be it a passive tracer or an actively moving bacterium in the growing bacterial colony, is a powerful technique to probe the physical properties of the environment of the particles. One of the most common measures of particle motion driven by fluctuations and random forces is its diffusivity, which is routinely obtained by measuring the mean squared displacement of the particles. However, often the tracer particles may be moving in a domain or an aggregate which itself experiences some regular or random motion and thus masks the diffusivity of tracers. Here we provide a method for assessing the diffusivity of tracer particles within mobile aggregates by measuring the so-called mean squared relative distance (MSRD) between two tracers. We provide analytical expressions for both the ensemble and time averaged MSRD allowing for direct identification of diffusivities from experimental data.

Dynamics of the one-dimensional Anderson insulator coupled to various bosonic baths

NASA Astrophysics Data System (ADS)

Bonča, Janez; Trugman, Stuart A.; Mierzejewski, Marcin

2018-05-01

We study a particle which propagates in a one-dimensional strong random potential and is coupled to a bosonic bath. We independently test various properties of bosons (hopping term, hard-core effects, and generic boson-boson interaction) and show that bosonic itineracy is the essential ingredient governing the dynamics of the particle. Coupling of the particle to itinerant phonons or hard-core bosons alike leads to delocalization of the particle by virtue of a subdiffusive (or diffusive) spread from the initially localized state. Delocalization remains in effect even when the boson frequency and the bandwidth of itinerant bosons remain an order of magnitude smaller than the magnitude of the random potential. When the particle is coupled to localized bosons, its spread remains logarithmic or even sublogarithmic. The latter result together with the survival probability shows that the particle remains localized despite being coupled to bosons.

Quantitative organic vapor-particle sampler

DOEpatents

Gundel, Lara; Daisey, Joan M.; Stevens, Robert K.

1998-01-01

A quantitative organic vapor-particle sampler for sampling semi-volatile organic gases and particulate components. A semi-volatile organic reversible gas sorbent macroreticular resin agglomerates of randomly packed microspheres with the continuous porous structure of particles ranging in size between 0.05-10 .mu.m for use in an integrated diffusion vapor-particle sampler.

Coherent light scattering of heterogeneous randomly rough films and effective medium in the theory of electromagnetic wave multiple scattering

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

Berginc, G

2013-11-30

We have developed a general formalism based on Green's functions to calculate the coherent electromagnetic field scattered by a random medium with rough boundaries. The approximate expression derived makes it possible to determine the effective permittivity, which is generalised for a layer of an inhomogeneous random medium with different types of particles and bounded with randomly rough interfaces. This effective permittivity describes the coherent propagation of an electromagnetic wave in a random medium with randomly rough boundaries. We have obtained an expression, which contains the Maxwell – Garnett formula at the low-frequency limit, and the Keller formula; the latter hasmore » been proved to be in good agreement with experiments for particles whose dimensions are larger than a wavelength. (coherent light scattering)« less

Motion Among Random Obstacles on a Hyperbolic Space

NASA Astrophysics Data System (ADS)

Orsingher, Enzo; Ricciuti, Costantino; Sisti, Francesco

2016-02-01

We consider the motion of a particle along the geodesic lines of the Poincaré half-plane. The particle is specularly reflected when it hits randomly-distributed obstacles that are assumed to be motionless. This is the hyperbolic version of the well-known Lorentz Process studied in the Euclidean context. We analyse the limit in which the density of the obstacles increases to infinity and the size of each obstacle vanishes: under a suitable scaling, we prove that our process converges to a Markovian process, namely a random flight on the hyperbolic manifold.

Stochastic Fermi Energization of Coronal Plasma during Explosive Magnetic Energy Release

NASA Astrophysics Data System (ADS)

Pisokas, Theophilos; Vlahos, Loukas; Isliker, Heinz; Tsiolis, Vassilis; Anastasiadis, Anastasios

2017-02-01

The aim of this study is to analyze the interaction of charged particles (ions and electrons) with randomly formed particle scatterers (e.g., large-scale local “magnetic fluctuations” or “coherent magnetic irregularities”) using the setup proposed initially by Fermi. These scatterers are formed by the explosive magnetic energy release and propagate with the Alfvén speed along the irregular magnetic fields. They are large-scale local fluctuations (δB/B ≈ 1) randomly distributed inside the unstable magnetic topology and will here be called Alfvénic Scatterers (AS). We constructed a 3D grid on which a small fraction of randomly chosen grid points are acting as AS. In particular, we study how a large number of test particles evolves inside a collection of AS, analyzing the evolution of their energy distribution and their escape-time distribution. We use a well-established method to estimate the transport coefficients directly from the trajectories of the particles. Using the estimated transport coefficients and solving the Fokker-Planck equation numerically, we can recover the energy distribution of the particles. We have shown that the stochastic Fermi energization of mildly relativistic and relativistic plasma can heat and accelerate the tail of the ambient particle distribution as predicted by Parker & Tidman and Ramaty. The temperature of the hot plasma and the tail of the energetic particles depend on the mean free path (λsc) of the particles between the scatterers inside the energization volume.

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

Pisokas, Theophilos; Vlahos, Loukas; Isliker, Heinz

The aim of this study is to analyze the interaction of charged particles (ions and electrons) with randomly formed particle scatterers (e.g., large-scale local “magnetic fluctuations” or “coherent magnetic irregularities”) using the setup proposed initially by Fermi. These scatterers are formed by the explosive magnetic energy release and propagate with the Alfvén speed along the irregular magnetic fields. They are large-scale local fluctuations ( δB / B ≈ 1) randomly distributed inside the unstable magnetic topology and will here be called Alfvénic Scatterers (AS). We constructed a 3D grid on which a small fraction of randomly chosen grid points aremore » acting as AS. In particular, we study how a large number of test particles evolves inside a collection of AS, analyzing the evolution of their energy distribution and their escape-time distribution. We use a well-established method to estimate the transport coefficients directly from the trajectories of the particles. Using the estimated transport coefficients and solving the Fokker–Planck equation numerically, we can recover the energy distribution of the particles. We have shown that the stochastic Fermi energization of mildly relativistic and relativistic plasma can heat and accelerate the tail of the ambient particle distribution as predicted by Parker and Tidman and Ramaty. The temperature of the hot plasma and the tail of the energetic particles depend on the mean free path ( λ {sub sc}) of the particles between the scatterers inside the energization volume.« less

Liver glycogen in type 2 diabetic mice is randomly branched as enlarged aggregates with blunted glucose release.

PubMed

Besford, Quinn Alexander; Zeng, Xiao-Yi; Ye, Ji-Ming; Gray-Weale, Angus

2016-02-01

Glycogen is a vital highly branched polymer of glucose that is essential for blood glucose homeostasis. In this article, the structure of liver glycogen from mice is investigated with respect to size distributions, degradation kinetics, and branching structure, complemented by a comparison of normal and diabetic liver glycogen. This is done to screen for differences that may result from disease. Glycogen α-particle (diameter ∼ 150 nm) and β-particle (diameter ∼ 25 nm) size distributions are reported, along with in vitro γ-amylase degradation experiments, and a small angle X-ray scattering analysis of mouse β-particles. Type 2 diabetic liver glycogen upon extraction was found to be present as large loosely bound, aggregates, not present in normal livers. Liver glycogen was found to aggregate in vitro over a period of 20 h, and particle size is shown to be related to rate of glucose release, allowing a structure-function relationship to be inferred for the tissue specific distribution of particle types. Application of branching theories to small angle X-ray scattering data for mouse β-particles revealed these particles to be randomly branched polymers, not fractal polymers. Together, this article shows that type 2 diabetic liver glycogen is present as large aggregates in mice, which may contribute to the inflexibility of interconversion between glucose and glycogen in type 2 diabetes, and further that glycogen particles are randomly branched with a size that is related to the rate of glucose release.

SILICON CARBIDE GRAIN BOUNDARY DISTRIBUTIONS, IRRADIATION CONDITIONS, AND SILVER RETENTION IN IRRADIATED AGR-1 TRISO FUEL PARTICLES

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

Lillo, T. M.; Rooyen, I. J.; Aguiar, J. A.

Precession electron diffraction in the transmission electron microscope was used to map grain orientation and ultimately determine grain boundary misorientation angle distributions, relative fractions of grain boundary types (random high angle, low angle or coincident site lattice (CSL)-related boundaries) and the distributions of CSL-related grain boundaries in the SiC layer of irradiated TRISO-coated fuel particles. Two particles from the AGR-1 experiment exhibiting high Ag-110m retention (>80%) were compared to a particle exhibiting low Ag-110m retention (<19%). Irradiated particles with high Ag-110m retention exhibited a lower fraction of random, high angle grain boundaries compared to the low Ag-110m retention particle. Anmore » inverse relationship between the random, high angle grain boundary fraction and Ag-110m retention is found and is consistent with grain boundary percolation theory. Also, comparison of the grain boundary distributions with previously reported unirradiated grain boundary distributions, based on SEM-based EBSD for similarly fabricated particles, showed only small differences, i.e. a greater low angle grain boundary fraction in unirradiated SiC. It was, thus, concluded that SiC layers with grain boundary distributions susceptible to Ag-110m release were present prior to irradiation. Finally, irradiation parameters were found to have little effect on the association of fission product precipitates with specific grain boundary types.« less

An Empirical and Methodological Analysis of the Role of Embodied Resources in Supporting Learning

NASA Astrophysics Data System (ADS)

Saleh, Asmalina

This dissertation presents three papers centered on understanding how we might learn using the body to learn. The data for these papers is drawn from classroom data where 2nd graders (N = 17) learn about particle behavior by engaging with the Science Through Technologically Enhanced Play (STEP) simulation. The first paper focuses on how two interfaces, a full-body motion tracking (OpenPtrack) and the iPad, illuminate the ways that the body and other semiotic resources can be used in student's collective explanations about particle behavior. It demonstrates how the subjective experience of using one's body to articulate ideas about aspects of particle behavior such as attraction can be qualitatively different from how one articulates particle behavior at the collective level (e.g., arrangement or movement). Moreover, even when students did not use their entire bodies to express their understanding of particle behavior, they often used bodied resources as they talked about particle behavior. Additionally, findings suggest that conceptually difficult ideas about particle behavior could be supported by allowing students to coordinate particle behavior at the aggregate level. The second paper examined how the same students use these semiotic resources but in the context of individual explanations in a series of one-on-one interviews. The verbal analysis approach (Chi, 1997) highlight that manipulatives are better suited than the full body to support students' explanations of spatial ideas such as particle arrangement. The embodied interaction perspective (Streeck, Goodwin, & LeBaron, 2011) provided further insights into how students used manipulatives in their articulations about particle behavior, and more importantly, how the body might sometimes constrain their ideas. At a more methodological level, the dissertation has also contributed to studies of epistemics by attending to how embodiment can be used to index epistemic stances and statuses of material objects during moment-to-moment information exchange.

Universal self-similarity of propagating populations

NASA Astrophysics Data System (ADS)

Eliazar, Iddo; Klafter, Joseph

2010-07-01

This paper explores the universal self-similarity of propagating populations. The following general propagation model is considered: particles are randomly emitted from the origin of a d -dimensional Euclidean space and propagate randomly and independently of each other in space; all particles share a statistically common—yet arbitrary—motion pattern; each particle has its own random propagation parameters—emission epoch, motion frequency, and motion amplitude. The universally self-similar statistics of the particles’ displacements and first passage times (FPTs) are analyzed: statistics which are invariant with respect to the details of the displacement and FPT measurements and with respect to the particles’ underlying motion pattern. Analysis concludes that the universally self-similar statistics are governed by Poisson processes with power-law intensities and by the Fréchet and Weibull extreme-value laws.

e-Learning versus lecture-based courses in ECG interpretation for undergraduate medical students: a randomized noninferiority study.

PubMed

Montassier, Emmanuel; Hardouin, Jean-Benoît; Segard, Julien; Batard, Eric; Potel, Gilles; Planchon, Bernard; Trochu, Jean-Noël; Pottier, Pierre

2016-04-01

An ECG is pivotal for the diagnosis of coronary heart disease. Previous studies have reported deficiencies in ECG interpretation skills that have been responsible for misdiagnosis. However, the optimal way to acquire ECG interpretation skills is still under discussion. Thus, our objective was to compare the effectiveness of e-learning and lecture-based courses for learning ECG interpretation skills in a large randomized study. We conducted a prospective, randomized, controlled, noninferiority study. Participants were recruited from among fifth-year medical students and were assigned to the e-learning group or the lecture-based group using a computer-generated random allocation sequence. The e-learning and lecture-based groups were compared on a score of effectiveness, comparing the 95% unilateral confidence interval (95% UCI) of the score of effectiveness with the mean effectiveness in the lecture-based group, adjusted for a noninferiority margin. Ninety-eight students were enrolled. As compared with the lecture-based course, e-learning was noninferior with regard to the postcourse test score (15.1; 95% UCI 14.2; +∞), which can be compared with 12.5 [the mean effectiveness in the lecture-based group (15.0) minus the noninferiority margin (2.5)]. Furthermore, there was a significant increase in the test score points in both the e-learning and lecture-based groups during the study period (both P<0.0001). Our randomized study showed that the e-learning course is an effective tool for the acquisition of ECG interpretation skills by medical students. These preliminary results should be confirmed with further multicenter studies before the implementation of e-learning courses for learning ECG interpretation skills during medical school.

Random-subset fitting of digital holograms for fast three-dimensional particle tracking [invited].

PubMed

Dimiduk, Thomas G; Perry, Rebecca W; Fung, Jerome; Manoharan, Vinothan N

2014-09-20

Fitting scattering solutions to time series of digital holograms is a precise way to measure three-dimensional dynamics of microscale objects such as colloidal particles. However, this inverse-problem approach is computationally expensive. We show that the computational time can be reduced by an order of magnitude or more by fitting to a random subset of the pixels in a hologram. We demonstrate our algorithm on experimentally measured holograms of micrometer-scale colloidal particles, and we show that 20-fold increases in speed, relative to fitting full frames, can be attained while introducing errors in the particle positions of 10 nm or less. The method is straightforward to implement and works for any scattering model. It also enables a parallelization strategy wherein random-subset fitting is used to quickly determine initial guesses that are subsequently used to fit full frames in parallel. This approach may prove particularly useful for studying rare events, such as nucleation, that can only be captured with high frame rates over long times.

Particles. Learning in Science Project. Working Paper No. 18.

ERIC Educational Resources Information Center

Happs, John

One area explored in the second (in-depth) phase of the Learning in Science Project was "children's science," defined as views of the world and the meanings for words that children have and bring with them to science lessons. The investigation reported focuses on students' thinking regarding their views on particles and particle…

Biking with Particles: Junior Triathletes' Learning about Drafting through Exploring Agent-Based Models and Inventing New Tactics

ERIC Educational Resources Information Center

Hirsh, Alon; Levy, Sharona T.

2013-01-01

The present research addresses a curious finding: how learning physical principles enhanced athletes' biking performance but not their conceptual understanding. The study involves a model-based triathlon training program, Biking with Particles, concerning aerodynamics of biking in groups (drafting). A conceptual framework highlights several…

Methods of Learning in Statistical Education: A Randomized Trial of Public Health Graduate Students

ERIC Educational Resources Information Center

Enders, Felicity Boyd; Diener-West, Marie

2006-01-01

A randomized trial of 265 consenting students was conducted within an introductory biostatistics course: 69 received eight small group cooperative learning sessions; 97 accessed internet learning sessions; 96 received no intervention. Effect on examination score (95% CI) was assessed by intent-to-treat analysis and by incorporating reported…

Particle chaos and pitch angle scattering

NASA Technical Reports Server (NTRS)

Burkhart, G. R.; Dusenbery, P. B.; Speiser, T. W.

1995-01-01

Pitch angle scattering is a factor that helps determine the dawn-to-dusk current, controls particle energization, and it has also been used as a remote probe of the current sheet structure. Previous studies have interpreted their results under the exception that randomization will be greatest when the ratio of the two timescales of motion (gyration parallel to and perpendicular to the current sheet) is closet to one. Recently, the average expotential divergence rate (AEDR) has been calculated for particle motion in a hyperbolic current sheet (Chen, 1992). It is claimed that this AEDR measures the degree of chaos and therefore may be thought to measure the randomization. In contrast to previous expectations, the AEDR is not maximized when Kappa is approximately equal to 1 but instead increases with decreasing Kappa. Also contrary to previous expectations, the AEDR is dependent upon the parameter b(sub z). In response to the challenge to previous expectations that has been raised by this calculation of the AEDR, we have investigated the dependence of a measure of particle pitch angle scattering on both the parameters Kappa and b(sub z). We find that, as was previously expected, particle pitch angle scattering is maximized near Kappa = 1 provided that Kappa/b(sub z) greater than 1. In the opposite regime, Kappa/b(sub z) less than 1, we find that particle pitch angle scattering is still largest when the two timescales are equal, but the ratio of the timescales is proportional to b(sub z). In this second regime, particle pitch angle scattering is not due to randomization, but is instead due to a systematic pitch angle change. This result shows that particle pitch angle scattering need not be due to randomization and indicates how a measure of pitch angle scattering can exhibit a different behavior than a measure of chaos.

Characterizing pixel and point patterns with a hyperuniformity disorder length

NASA Astrophysics Data System (ADS)

Chieco, A. T.; Dreyfus, R.; Durian, D. J.

2017-09-01

We introduce the concept of a "hyperuniformity disorder length" h that controls the variance of volume fraction fluctuations for randomly placed windows of fixed size. In particular, fluctuations are determined by the average number of particles within a distance h from the boundary of the window. We first compute special expectations and bounds in d dimensions, and then illustrate the range of behavior of h versus window size L by analyzing several different types of simulated two-dimensional pixel patterns—where particle positions are stored as a binary digital image in which pixels have value zero if empty and one if they contain a particle. The first are random binomial patterns, where pixels are randomly flipped from zero to one with probability equal to area fraction. These have long-ranged density fluctuations, and simulations confirm the exact result h =L /2 . Next we consider vacancy patterns, where a fraction f of particles on a lattice are randomly removed. These also display long-range density fluctuations, but with h =(L /2 )(f /d ) for small f , and h =L /2 for f →1 . And finally, for a hyperuniform system with no long-range density fluctuations, we consider "Einstein patterns," where each particle is independently displaced from a lattice site by a Gaussian-distributed amount. For these, at large L ,h approaches a constant equal to about half the root-mean-square displacement in each dimension. Then we turn to gray-scale pixel patterns that represent simulated arrangements of polydisperse particles, where the volume of a particle is encoded in the value of its central pixel. And we discuss the continuum limit of point patterns, where pixel size vanishes. In general, we thus propose to quantify particle configurations not just by the scaling of the density fluctuation spectrum but rather by the real-space spectrum of h (L ) versus L . We call this approach "hyperuniformity disorder length spectroscopy".

Characterizing pixel and point patterns with a hyperuniformity disorder length.

PubMed

Chieco, A T; Dreyfus, R; Durian, D J

2017-09-01

We introduce the concept of a "hyperuniformity disorder length" h that controls the variance of volume fraction fluctuations for randomly placed windows of fixed size. In particular, fluctuations are determined by the average number of particles within a distance h from the boundary of the window. We first compute special expectations and bounds in d dimensions, and then illustrate the range of behavior of h versus window size L by analyzing several different types of simulated two-dimensional pixel patterns-where particle positions are stored as a binary digital image in which pixels have value zero if empty and one if they contain a particle. The first are random binomial patterns, where pixels are randomly flipped from zero to one with probability equal to area fraction. These have long-ranged density fluctuations, and simulations confirm the exact result h=L/2. Next we consider vacancy patterns, where a fraction f of particles on a lattice are randomly removed. These also display long-range density fluctuations, but with h=(L/2)(f/d) for small f, and h=L/2 for f→1. And finally, for a hyperuniform system with no long-range density fluctuations, we consider "Einstein patterns," where each particle is independently displaced from a lattice site by a Gaussian-distributed amount. For these, at large L,h approaches a constant equal to about half the root-mean-square displacement in each dimension. Then we turn to gray-scale pixel patterns that represent simulated arrangements of polydisperse particles, where the volume of a particle is encoded in the value of its central pixel. And we discuss the continuum limit of point patterns, where pixel size vanishes. In general, we thus propose to quantify particle configurations not just by the scaling of the density fluctuation spectrum but rather by the real-space spectrum of h(L) versus L. We call this approach "hyperuniformity disorder length spectroscopy".

Timing the Random and Anomalous Arrival of Particles in a Geiger Counter with GPS Devices

ERIC Educational Resources Information Center

Blanco, F.; La Rocca, P.; Riggi, F.; Riggi, S.

2008-01-01

The properties of the arrival time distribution of particles in a detector have been studied by the use of a small Geiger counter, with a GPS device to tag the event time. The experiment is intended to check the basic properties of the random arrival time distribution between successive events and to simulate the investigations carried out by…

Composition, morphology, and growth of clusters in a gas of particles with random interactions

NASA Astrophysics Data System (ADS)

Azizi, Itay; Rabin, Yitzhak

2018-03-01

We use Langevin dynamics simulations to study the growth kinetics and the steady-state properties of condensed clusters in a dilute two-dimensional system of particles that are all different (APD) in the sense that each particle is characterized by a randomly chosen interaction parameter. The growth exponents, the transition temperatures, and the steady-state properties of the clusters and of the surrounding gas phase are obtained and compared with those of one-component systems. We investigate the fractionation phenomenon, i.e., how particles of different identities are distributed between the coexisting mother (gas) and daughter (clusters) phases. We study the local organization of particles inside clusters, according to their identity—neighbourhood identity ordering (NIO)—and compare the results with those of previous studies of NIO in dense APD systems.

A scattering database of marine particles and its application in optical analysis

NASA Astrophysics Data System (ADS)

Xu, G.; Yang, P.; Kattawar, G.; Zhang, X.

2016-12-01

In modeling the scattering properties of marine particles (e.g. phytoplankton), the laboratory studies imply a need to properly account for the influence of particle morphology, in addition to size and composition. In this study, a marine particle scattering database is constructed using a collection of distorted hexahedral shapes. Specifically, the scattering properties of each size bin and refractive index are obtained by the ensemble average associated with distorted hexahedra with randomly tilted facets and selected aspect ratios (from elongated to flattened). The randomness degree in shape-generation process defines the geometric irregularity of the particles in the group. The geometric irregularity and particle aspect ratios constitute a set of "shape factors" to be accounted for (e.g. in best-fit analysis). To cover most of the marine particle size range, we combine the Invariant Imbedding T-matrix (II-TM) method and the Physical-Geometric Optics Hybrid (PGOH) method in the calculations. The simulated optical properties are shown and compared with those obtained from Lorenz-Mie Theory. Using the scattering database, we present a preliminary optical analysis of laboratory-measured optical properties of marine particles.

Randomized Trial to Reduce Air Particle Levels in Homes of Smokers and Children.

PubMed

Hughes, Suzanne C; Bellettiere, John; Nguyen, Benjamin; Liles, Sandy; Klepeis, Neil E; Quintana, Penelope J E; Berardi, Vincent; Obayashi, Saori; Bradley, Savannah; Hofstetter, C Richard; Hovell, Melbourne F

2018-03-01

Exposure to fine particulate matter in the home from sources such as smoking, cooking, and cleaning may put residents, especially children, at risk for detrimental health effects. A randomized clinical trial was conducted from 2011 to 2016 to determine whether real-time feedback in the home plus brief coaching of parents or guardians could reduce fine particle levels in homes with smokers and children. A randomized trial with two groups-intervention and control. A total of 298 participants from predominantly low-income households with an adult smoker and a child aged <14 years. Participants were recruited during 2012-2015 from multiple sources in San Diego, mainly Women, Infants and Children Program sites. The multicomponent intervention consisted of continuous lights and brief sound alerts based on fine particle levels in real time and four brief coaching sessions using particle level graphs and motivational interviewing techniques. Motivational interviewing coaching focused on particle reduction to protect children and other occupants from elevated particle levels, especially from tobacco-related sources. In-home air particle levels were measured by laser particle counters continuously in both study groups. The two outcomes were daily mean particle counts and percentage time with high particle concentrations (>15,000 particles/0.01 ft 3 ). Linear mixed models were used to analyze the differential change in the outcomes over time by group, during 2016-2017. Intervention homes had significantly larger reductions than controls in daily geometric mean particle concentrations (18.8% reduction vs 6.5% reduction, p<0.001). Intervention homes' average percentage time with high particle concentrations decreased 45.1% compared with a 4.2% increase among controls (difference between groups p<0.001). Real-time feedback for air particle levels and brief coaching can reduce fine particle levels in homes with smokers and young children. Results set the stage for refining feedback and possible reinforcing consequences for not generating smoke-related particles. This study is registered at www.clinicaltrials.gov NCT01634334. Copyright © 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

PubMed Central

Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

2014-01-01

Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

Spatial Variability of Organic Carbon in a Fractured Mudstone and Its Effect on the Retention and Release of Trichloroethene (TCE)

NASA Astrophysics Data System (ADS)

Sole-Mari, G.; Fernandez-Garcia, D.

2016-12-01

Random Walk Particle Tracking (RWPT) coupled with Kernel Density Estimation (KDE) has been recently proposed to simulate reactive transport in porous media. KDE provides an optimal estimation of the area of influence of particles which is a key element to simulate nonlinear chemical reactions. However, several important drawbacks can be identified: (1) the optimal KDE method is computationally intensive and thereby cannot be used at each time step of the simulation; (2) it does not take advantage of the prior information about the physical system and the previous history of the solute plume; (3) even if the kernel is optimal, the relative error in RWPT simulations typically increases over time as the particle density diminishes by dilution. To overcome these problems, we propose an adaptive branching random walk methodology that incorporates the physics, the particle history and maintains accuracy with time. The method allows particles to efficiently split and merge when necessary as well as to optimally adapt their local kernel shape without having to recalculate the kernel size. We illustrate the advantage of the method by simulating complex reactive transport problems in randomly heterogeneous porous media.

Numerical Simulation of the Anomalous Transport of High-Energy Cosmic Rays in Galactic Superbubble

NASA Technical Reports Server (NTRS)

Barghouty, A. F.; Price, E. M.; MeWaldt, R. A.

2013-01-01

A continuous-time random-walk (CTRW) model to simulate the transport and acceleration of high-energy cosmic rays in galactic superbubbles has recently been put forward (Barghouty & Schnee 2102). The new model has been developed to simulate and highlight signatures of anomalous transport on particles' evolution and their spectra in a multi-shock, collective acceleration context. The superbubble is idealized as a heterogeneous region of particle sources and sinks bounded by a random surface. This work concentrates on the effects of the bubble's assumed astrophysical characteristics (cf. geometry and roughness) on the particles' spectra.

Absorption and scattering of light by nonspherical particles. [in atmosphere

NASA Technical Reports Server (NTRS)

Bohren, C. F.

1986-01-01

Using the example of the polarization of scattered light, it is shown that the scattering matrices for identical, randomly ordered particles and for spherical particles are unequal. The spherical assumptions of Mie theory are therefore inconsistent with the random shapes and sizes of atmospheric particulates. The implications for corrections made to extinction measurements of forward scattering light are discussed. Several analytical methods are examined as potential bases for developing more accurate models, including Rayleigh theory, Fraunhoffer Diffraction theory, anomalous diffraction theory, Rayleigh-Gans theory, the separation of variables technique, the Purcell-Pennypacker method, the T-matrix method, and finite difference calculations.

Mediating Parent Learning to Promote Social Communication for Toddlers with Autism: Effects from a Randomized Controlled Trial

ERIC Educational Resources Information Center

Schertz, Hannah H.; Odom, Samuel L.; Baggett, Kathleen M.; Sideris, John H.

2018-01-01

A randomized controlled trial was conducted to evaluate effects of the Joint Attention Mediated Learning (JAML) intervention. Toddlers with autism spectrum disorders (ASD) aged 16-30 months (n = 144) were randomized to intervention and community control conditions. Parents, who participated in 32 weekly home-based sessions, followed a mediated…

Improving Classroom Learning Environments by Cultivating Awareness and Resilience in Education (CARE): Results of a Randomized Controlled Trial

ERIC Educational Resources Information Center

Jennings, Patricia A.; Frank, Jennifer L.; Snowberg, Karin E.; Coccia, Michael A.; Greenberg, Mark T.

2013-01-01

Cultivating Awareness and Resilience in Education (CARE for Teachers) is a mindfulness-based professional development program designed to reduce stress and improve teachers' performance and classroom learning environments. A randomized controlled trial examined program efficacy and acceptability among a sample of 50 teachers randomly assigned to…

Non-fixation for Conservative Stochastic Dynamics on the Line

NASA Astrophysics Data System (ADS)

Basu, Riddhipratim; Ganguly, Shirshendu; Hoffman, Christopher

2018-03-01

We consider activated random walk (ARW), a model which generalizes the stochastic sandpile, one of the canonical examples of self organized criticality. Informally ARW is a particle system on Z with mass conservation. One starts with a mass density {μ > 0} of initially active particles, each of which performs a symmetric random walk at rate one and falls asleep at rate {λ > 0}. Sleepy particles become active on coming in contact with other active particles. We investigate the question of fixation/non-fixation of the process and show for small enough {λ} the critical mass density for fixation is strictly less than one. Moreover, the critical density goes to zero as {λ} tends to zero. This settles a long standing open question.

Comparison of Collaboration and Performance in Groups of Learners Assembled Randomly or Based on Learners' Topic Preferences

ERIC Educational Resources Information Center

Cela, Karina L.; Sicilia, Miguel Ángel; Sánchez, Salvador

2015-01-01

Teachers and instructional designers frequently incorporate collaborative learning approaches into their e-learning environments. A key factor of collaborative learning that may affect learner outcomes is whether the collaborative groups are assigned project topics randomly or based on a shared interest in the topic. This is a particularly…

Reform-Based-Instructional Method and Learning Styles on Students' Achievement and Retention in Mathematics: Administrative Implications

ERIC Educational Resources Information Center

Modebelu, M. N.; Ogbonna, C. C.

2014-01-01

This study aimed at determining the effect of reform-based-instructional method learning styles on students' achievement and retention in mathematics. A sample size of 119 students was randomly selected. The quasiexperimental design comprising pre-test, post-test, and randomized control group were employed. The Collin Rose learning styles…

Interactive Computer Simulation and Animation for Improving Student Learning of Particle Kinetics

ERIC Educational Resources Information Center

Fang, N.; Guo, Y.

2016-01-01

Computer simulation and animation (CSA) has been receiving growing attention and wide application in engineering education in recent years. A new interactive CSA module was developed in the present study to improve student learning of particle kinetics in an undergraduate engineering dynamics course. The unique feature of this CSA module is that…

Learning with LEGO

NASA Astrophysics Data System (ADS)

Durrani, Matin

2017-12-01

I have lost count of the number of wheezes to get people hooked on particle physics. There have been straightforward scientific accounts, personal tales of discovery, books filled with cartoons, essays and even historical vignettes. In Particle Physics Brick by Brick, science communicator Ben Still has decided to use LEGO bricks to coax readers into learning more about the subatomic world.

Accelerating Pseudo-Random Number Generator for MCNP on GPU

NASA Astrophysics Data System (ADS)

Gong, Chunye; Liu, Jie; Chi, Lihua; Hu, Qingfeng; Deng, Li; Gong, Zhenghu

2010-09-01

Pseudo-random number generators (PRNG) are intensively used in many stochastic algorithms in particle simulations, artificial neural networks and other scientific computation. The PRNG in Monte Carlo N-Particle Transport Code (MCNP) requires long period, high quality, flexible jump and fast enough. In this paper, we implement such a PRNG for MCNP on NVIDIA's GTX200 Graphics Processor Units (GPU) using CUDA programming model. Results shows that 3.80 to 8.10 times speedup are achieved compared with 4 to 6 cores CPUs and more than 679.18 million double precision random numbers can be generated per second on GPU.

Does Graft Particle Type and Size Affect Ridge Dimensional Changes After Alveolar Ridge Split Procedure?

PubMed

Kheur, Mohit G; Kheur, Supriya; Lakha, Tabrez; Jambhekar, Shantanu; Le, Bach; Jain, Vinay

2018-04-01

The absence of an adequate volume of bone at implant sites requires augmentation procedures before the placement of implants. The aim of the present study was to assess the ridge width gain with the use of allografts and biphasic β-tricalcium phosphate with hydroxyapatite (alloplast) in ridge split procedures, when each were used in small (0.25 to 1 mm) and large (1 to 2 mm) particle sizes. A randomized controlled trial of 23 subjects with severe atrophy of the mandible in the horizontal dimension was conducted in a private institute. The patients underwent placement of 49 dental implants after a staged ridge split procedure. The patients were randomly allocated to alloplast and allograft groups (predictor variable). In each group, the patients were randomly assigned to either small graft particle or large graft particle size (predictor variable). The gain in ridge width (outcome variable) was assessed before implant placement. A 2-way analysis of variance test and the Student unpaired t test were used for evaluation of the ridge width gain between the allograft and alloplast groups (predictor variable). Differences were considered significant if P values were < .05. The sample included 23 patients (14 men and 9 women). The patients were randomly allocated to the alloplast (n = 11) or allograft (n = 12) group before the ridge split procedure. In each group, they were assigned to a small graft particle or large graft particle size (alloplast group, small particle in 5 and large particle size in 6 patients; allograft group, small particle in 6 and large particle size in 6). A statistically significant difference was observed between the 2 graft types. The average ridge width gain was significantly greater in the alloplast group (large, 4.40 ± 0.24 mm; small, 3.52 ± 0.59 mm) than in the allograft group (large, 3.82 ± 0.19 mm; small, 2.57 ± 0.16 mm). For both graft types (alloplast and allograft), the large particle size graft resulted in a greater ridge width gain compared with the small particle size graft (P < .05). Within the limitations of the present study, we suggest the use of large particle alloplast as the graft material of choice for staged ridge split procedures in the posterior mandible. Copyright © 2017 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

White Matter Microstructural Correlates of Superior Long-term Skill Gained Implicitly under Randomized Practice

PubMed Central

Song, Sunbin; Sharma, Nikhil; Buch, Ethan R.

2012-01-01

We value skills we have learned intentionally, but equally important are skills acquired incidentally without ability to describe how or what is learned, referred to as implicit. Randomized practice schedules are superior to grouped schedules for long-term skill gained intentionally, but its relevance for implicit learning is not known. In a parallel design, we studied healthy subjects who learned a motor sequence implicitly under randomized or grouped practice schedule and obtained diffusion-weighted images to identify white matter microstructural correlates of long-term skill. Randomized practice led to superior long-term skill compared with grouped practice. Whole-brain analyses relating interindividual variability in fractional anisotropy (FA) to long-term skill demonstrated that 1) skill in randomized learners correlated with FA within the corticostriatal tract connecting left sensorimotor cortex to posterior putamen, while 2) skill in grouped learners correlated with FA within the right forceps minor connecting homologous regions of the prefrontal cortex (PFC) and the corticostriatal tract connecting lateral PFC to anterior putamen. These results demonstrate first that randomized practice schedules improve long-term implicit skill more than grouped practice schedules and, second, that the superior skill acquired through randomized practice can be related to white matter microstructure in the sensorimotor corticostriatal network. PMID:21914632

Methods of learning in statistical education: Design and analysis of a randomized trial

NASA Astrophysics Data System (ADS)

Boyd, Felicity Turner

Background. Recent psychological and technological advances suggest that active learning may enhance understanding and retention of statistical principles. A randomized trial was designed to evaluate the addition of innovative instructional methods within didactic biostatistics courses for public health professionals. Aims. The primary objectives were to evaluate and compare the addition of two active learning methods (cooperative and internet) on students' performance; assess their impact on performance after adjusting for differences in students' learning style; and examine the influence of learning style on trial participation. Methods. Consenting students enrolled in a graduate introductory biostatistics course were randomized to cooperative learning, internet learning, or control after completing a pretest survey. The cooperative learning group participated in eight small group active learning sessions on key statistical concepts, while the internet learning group accessed interactive mini-applications on the same concepts. Controls received no intervention. Students completed evaluations after each session and a post-test survey. Study outcome was performance quantified by examination scores. Intervention effects were analyzed by generalized linear models using intent-to-treat analysis and marginal structural models accounting for reported participation. Results. Of 376 enrolled students, 265 (70%) consented to randomization; 69, 100, and 96 students were randomized to the cooperative, internet, and control groups, respectively. Intent-to-treat analysis showed no differences between study groups; however, 51% of students in the intervention groups had dropped out after the second session. After accounting for reported participation, expected examination scores were 2.6 points higher (of 100 points) after completing one cooperative learning session (95% CI: 0.3, 4.9) and 2.4 points higher after one internet learning session (95% CI: 0.0, 4.7), versus nonparticipants or controls, adjusting for other performance predictors. Students who preferred learning by reflective observation and active experimentation experienced improved performance through internet learning (5.9 points, 95% CI: 1.2, 10.6) and cooperative learning (2.9 points, 95% CI: 0.6, 5.2), respectively. Learning style did not influence study participation. Conclusions. No performance differences by group were observed by intent-to-treat analysis. Participation in active learning appears to improve student performance in an introductory biostatistics course and provides opportunities for enhancing understanding beyond that attained in traditional didactic classrooms.

Electrolytic plating apparatus for discrete microsized particles

DOEpatents

Mayer, Anton

1976-11-30

Method and apparatus are disclosed for electrolytically producing very uniform coatings of a desired material on discrete microsized particles. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with a powered cathode for a time sufficient for such to occur.

Electroless plating apparatus for discrete microsized particles

DOEpatents

Mayer, Anton

1978-01-01

Method and apparatus are disclosed for producing very uniform coatings of a desired material on discrete microsized particles by electroless techniques. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with each other for a time sufficient for such to occur.

Energy mechanics of rock and snow avalanches and the role of fragmentation (invited)

NASA Astrophysics Data System (ADS)

Bartelt, Perry; Buser, Othmar; Glover, James

2014-05-01

The energy mechanics of rock and snow avalanches are traditionally described using a two-step transformation: potential energy is first converted into kinetic energy; kinetic energy is dissipated to heat by frictional processes. If the frictional processes are known, the energy fluxes of avalanches can be calculated completely. The break-up of the released mass, however, introduces several new energy fluxes into the avalanche problem. The first energy is associated with the fragmentation, which generates random particle motions. This is true kinetic energy. Inter-particle interactions (collisions, abrasion, fracture) cause the energy of the random particle motion to dissipate to heat. A constraint on the random motions is the basal boundary. It is at this interface that the dispersive pressure is created by vertical particle motions that are directed upwards into the flow. The integral of the upward particle motions can induce a change in avalanche flow volume and density, depending on the relationship between the weight of the flow and the dispersive pressure. Interestingly, normal pressures will only diverge from hydrostatic when there are changes in flow density. We are therefore confronted with the problem of calculating not only the vertical acceleration of the dispersive pressure, but also the change in vertical acceleration. In this contribution we discuss a method to calculate random particle motions, dispersive pressure and changes in avalanche flow density. These are dependent not only on the absolute mass, but also on the material properties of the disintegrating mass. This becomes particularly interesting when considering the motion of snow and rock avalanches as it allows the prediction of flow regime changes and therefore extreme avalanche run-out potential.

Game-Based Learning as a Vehicle to Teach First Aid Content: A Randomized Experiment

ERIC Educational Resources Information Center

Charlier, Nathalie; De Fraine, Bieke

2013-01-01

Background: Knowledge of first aid (FA), which constitutes lifesaving treatments for injuries or illnesses, is important for every individual. In this study, we have set up a group-randomized controlled trial to assess the effectiveness of a board game for learning FA. Methods: Four class groups (120 students) were randomly assigned to 2…

Optimization of laser-induced breakdown spectroscopy for coal powder analysis with different particle flow diameters

NASA Astrophysics Data System (ADS)

Yao, Shunchun; Xu, Jialong; Dong, Xuan; Zhang, Bo; Zheng, Jianping; Lu, Jidong

2015-08-01

The on-line measurement of coal is extremely useful for emission control and combustion process optimization in coal-fired plant. Laser-induced breakdown spectroscopy was employed to directly analyze coal particle flow. A set of tapered tubes were proposed for beam-focusing the coal particle flow to different diameters. For optimizing the measurement of coal particle flow, the characteristics of laser-induced plasma, including optical breakdown, the relative standard deviation of repeated measurement, partial breakdown spectra ratio and line intensity, were carefully analyzed. The comparison of the plasma characteristics among coal particle flow with different diameters showed that air breakdown and the random change in plasma position relative to the collection optics could significantly influence on the line intensity and the reproducibility of measurement. It is demonstrated that the tapered tube with a diameter of 5.5 mm was particularly useful to enrich the coal particles in laser focus spot as well as to reduce the influence of air breakdown and random changes of plasma in the experiment.

Observation of arrival times of EAS with energies or = 6 x 10 (14) eV

NASA Technical Reports Server (NTRS)

Sun, L.

1985-01-01

The Earth's atmosphere is continually being bombarded by primary cosmic ray particles which are generally believed to be high-energy nuclei. The fact that the majority of cosmic ray primaries are charged particles and that space is permeated with random magnetic fields, means that the particles do not travel in straight lines. The arrival time distribution of EAS may also transfer some information about the primary particles. Actually, if the particles come to our Earth in a completely random process, the arrival time distribution of pairs of successive particles should fit an exponential law. The work reported here was arried out at Sydney University from May 1982 to January 1983. All the data are used to plot the arrival-time distribution of the events, that is, the distribution of time-separation between consecutive events on a 1 minute bin size. During this period more than 2300 showers were recorded. The results are discussed and compared with that of some other experiments.

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

NASA Astrophysics Data System (ADS)

Najafi, Amin

2014-05-01

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

Charged particle dynamics in multiple colliding electromagnetic waves. Survey of random walk, Lévy flights, limit circles, attractors and structurally determinate patterns

NASA Astrophysics Data System (ADS)

Bulanov, S. V.; Esirkepov, T. Zh.; Koga, J. K.; Bulanov, S. S.; Gong, Z.; Yan, X. Q.; Kando, M.

2017-04-01

The multiple colliding laser pulse concept formulated by Bulanov et al. (Phys. Rev. Lett., vol. 104, 2010b, 220404) is beneficial for achieving an extremely high amplitude of coherent electromagnetic field. Since the topology of electric and magnetic fields of multiple colliding laser pulses oscillating in time is far from trivial and the radiation friction effects are significant in the high field limit, the dynamics of charged particles interacting with the multiple colliding laser pulses demonstrates remarkable features corresponding to random walk trajectories, limit circles, attractors, regular patterns and Lévy flights. Under extremely high intensity conditions the nonlinear dissipation mechanism stabilizes the particle motion resulting in the charged particle trajectory being located within narrow regions and in the occurrence of a new class of regular patterns made by the particle ensembles.

Charged particle dynamics in multiple colliding electromagnetic waves. Survey of random walk, Lévy flights, limit circles, attractors and structurally determinate patterns

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

Bulanov, S. V.; Esirkepov, T. Zh.; Koga, J. K.

The multiple colliding laser pulse concept formulated by Bulanovet al.(Phys. Rev. Lett., vol. 104, 2010b, 220404) is beneficial for achieving an extremely high amplitude of coherent electromagnetic field. Since the topology of electric and magnetic fields of multiple colliding laser pulses oscillating in time is far from trivial and the radiation friction effects are significant in the high field limit, the dynamics of charged particles interacting with the multiple colliding laser pulses demonstrates remarkable features corresponding to random walk trajectories, limit circles, attractors, regular patterns and Lévy flights. Lastly, under extremely high intensity conditions the nonlinear dissipation mechanism stabilizes the particle motionmore » resulting in the charged particle trajectory being located within narrow regions and in the occurrence of a new class of regular patterns made by the particle ensembles.« less

Charged particle dynamics in multiple colliding electromagnetic waves. Survey of random walk, Lévy flights, limit circles, attractors and structurally determinate patterns

DOE PAGES

Bulanov, S. V.; Esirkepov, T. Zh.; Koga, J. K.; ...

2017-03-09

The multiple colliding laser pulse concept formulated by Bulanovet al.(Phys. Rev. Lett., vol. 104, 2010b, 220404) is beneficial for achieving an extremely high amplitude of coherent electromagnetic field. Since the topology of electric and magnetic fields of multiple colliding laser pulses oscillating in time is far from trivial and the radiation friction effects are significant in the high field limit, the dynamics of charged particles interacting with the multiple colliding laser pulses demonstrates remarkable features corresponding to random walk trajectories, limit circles, attractors, regular patterns and Lévy flights. Lastly, under extremely high intensity conditions the nonlinear dissipation mechanism stabilizes the particle motionmore » resulting in the charged particle trajectory being located within narrow regions and in the occurrence of a new class of regular patterns made by the particle ensembles.« less

Particle Swarm Learning Algorithm Based on Adjustment of Parameter and its Applications Assessment of Agricultural Projects

NASA Astrophysics Data System (ADS)

Yang, Shanlin; Zhu, Weidong; Chen, Li

The particle swarm, which optimizes neural networks, has overcome its disadvantage of slow convergent speed and shortcoming of local optimum. The parameter that the particle swarm optimization relates to is not much. But it has strongly sensitivity to the parameter. In this paper, we applied PSO-BP to evaluate the environmental effect of an agricultural project, and researched application and Particle Swarm learning algorithm based on adjustment of parameter. This paper, we use MATLAB language .The particle number is 5, 30, 50, 90, and the inertia weight is 0.4, 0.6, and 0.8 separately. Calculate 10 times under each same parameter, and analyze the influence under the same parameter. Result is indicated that the number of particles is in 25 ~ 30 and the inertia weight is in 0.6 ~ 0.7, and the result of optimization is satisfied.

Student Test Performances on Behavior of Gas Particles and Mismatch of Teacher Predictions

ERIC Educational Resources Information Center

Liang, Jia-Chi; Chou, Chin-Cheng; Chiu, Mei-Hung

2011-01-01

The nature and behavior of gas particles are essential concepts in teaching and learning of school chemistry. However, findings about students' understanding of gas particles--their composition, structure, and interactions involving movement and distribution--revealed that the difficulties students encounter in understanding gas particles vary…

Randomized Study of the Impact of Cooperative Learning: Distance Education in Public Health

ERIC Educational Resources Information Center

Riley, William; Anderson, Paige

2006-01-01

The purpose of this study is to explore the effects of cooperative learning on cognitive outcomes in a public health graduate level Web-based distance education course. Specifically, the authors use a randomized control trial to determine the impact of two teaching pedagogies on learning effectiveness in three areas of the cognitive domain: (1)…

Pileup Mitigation with Machine Learning (PUMML)

NASA Astrophysics Data System (ADS)

Komiske, Patrick T.; Metodiev, Eric M.; Nachman, Benjamin; Schwartz, Matthew D.

2017-12-01

Pileup involves the contamination of the energy distribution arising from the primary collision of interest (leading vertex) by radiation from soft collisions (pileup). We develop a new technique for removing this contamination using machine learning and convolutional neural networks. The network takes as input the energy distribution of charged leading vertex particles, charged pileup particles, and all neutral particles and outputs the energy distribution of particles coming from leading vertex alone. The PUMML algorithm performs remarkably well at eliminating pileup distortion on a wide range of simple and complex jet observables. We test the robustness of the algorithm in a number of ways and discuss how the network can be trained directly on data.

Heterogeneous Suppression of Sequential Effects in Random Sequence Generation, but Not in Operant Learning.

PubMed

Shteingart, Hanan; Loewenstein, Yonatan

2016-01-01

There is a long history of experiments in which participants are instructed to generate a long sequence of binary random numbers. The scope of this line of research has shifted over the years from identifying the basic psychological principles and/or the heuristics that lead to deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of participants' choices. Surprisingly, a population analysis indicated that the contribution of the most recent trial has only a weak effect on behavior, compared to more preceding trials, a result that seems irreconcilable with standard sequential effects that decay monotonously with the delay. However, when considering each participant separately, we found that the magnitudes of the sequential effect are a monotonous decreasing function of the delay, yet these individual sequential effects are largely averaged out in a population analysis because of heterogeneity. The substantial behavioral heterogeneity in this task is further demonstrated quantitatively by considering the predictive power of the model. We show that a heterogeneous model of sequential dependencies captures the structure available in random sequence generation. Finally, we show that the results of the logistic regression analysis can be interpreted in the framework of reinforcement learning, allowing us to compare the sequential effects in the random sequence generation task to those in an operant learning task. We show that in contrast to the random sequence generation task, sequential effects in operant learning are far more homogenous across the population. These results suggest that in the random sequence generation task, different participants adopt different cognitive strategies to suppress sequential dependencies when generating the "random" sequences.

Perpendicular diffusion of a dilute beam of charged particles in the PK-4 dusty plasma

NASA Astrophysics Data System (ADS)

Liu, Bin; Goree, John

2015-09-01

We study the random walk of a dilute beam of projectile dust particles that drift through a target dusty plasma. This random walk is a diffusion that occurs mainly due to Coulomb collisions with target particles that have a different size. In the direction parallel to the drift, projectiles exhibit mobility-limited motion with a constant average velocity. We use a 3D molecular dynamics (MD) simulation of the dust particle motion to determine the diffusion and mobility coefficients for the dilute beam. The dust particles are assumed to interact with a shielded Coulomb repulsion. They also experience gas drag. The beam particles are driven by a prescribed net force that is not applied to the target particles; in the experiments this net force is due to an imbalance of the electric and ion drag forces. This simulation is motivated by microgravity experiments, with the expectation that the scattering of projectiles studied here will be observed in upcoming PK-4 experiments on the International Space Station. Supported by NASA and DOE.

Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

NASA Astrophysics Data System (ADS)

Izah Anuar, Nurul; Saptari, Adi

2016-02-01

This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.

Stochastic analysis of particle movement over a dune bed

USGS Publications Warehouse

Lee, Baum K.; Jobson, Harvey E.

1977-01-01

Stochastic models are available that can be used to predict the transport and dispersion of bed-material sediment particles in an alluvial channel. These models are based on the proposition that the movement of a single bed-material sediment particle consists of a series of steps of random length separated by rest periods of random duration and, therefore, application of the models requires a knowledge of the probability distributions of the step lengths, the rest periods, the elevation of particle deposition, and the elevation of particle erosion. The procedure was tested by determining distributions from bed profiles formed in a large laboratory flume with a coarse sand as the bed material. The elevation of particle deposition and the elevation of particle erosion can be considered to be identically distributed, and their distribution can be described by either a ' truncated Gaussian ' or a ' triangular ' density function. The conditional probability distribution of the rest period given the elevation of particle deposition closely followed the two-parameter gamma distribution. The conditional probability distribution of the step length given the elevation of particle erosion and the elevation of particle deposition also closely followed the two-parameter gamma density function. For a given flow, the scale and shape parameters describing the gamma probability distributions can be expressed as functions of bed-elevation. (Woodard-USGS)

Implementation of Chaotic Gaussian Particle Swarm Optimization for Optimize Learning-to-Rank Software Defect Prediction Model Construction

NASA Astrophysics Data System (ADS)

Buchari, M. A.; Mardiyanto, S.; Hendradjaya, B.

2018-03-01

Finding the existence of software defect as early as possible is the purpose of research about software defect prediction. Software defect prediction activity is required to not only state the existence of defects, but also to be able to give a list of priorities which modules require a more intensive test. Therefore, the allocation of test resources can be managed efficiently. Learning to rank is one of the approach that can provide defect module ranking data for the purposes of software testing. In this study, we propose a meta-heuristic chaotic Gaussian particle swarm optimization to improve the accuracy of learning to rank software defect prediction approach. We have used 11 public benchmark data sets as experimental data. Our overall results has demonstrated that the prediction models construct using Chaotic Gaussian Particle Swarm Optimization gets better accuracy on 5 data sets, ties in 5 data sets and gets worse in 1 data sets. Thus, we conclude that the application of Chaotic Gaussian Particle Swarm Optimization in Learning-to-Rank approach can improve the accuracy of the defect module ranking in data sets that have high-dimensional features.

Critical spreading dynamics of parity conserving annihilating random walks with power-law branching

NASA Astrophysics Data System (ADS)

Laise, T.; dos Anjos, F. C.; Argolo, C.; Lyra, M. L.

2018-09-01

We investigate the critical spreading of the parity conserving annihilating random walks model with Lévy-like branching. The random walks are considered to perform normal diffusion with probability p on the sites of a one-dimensional lattice, annihilating in pairs by contact. With probability 1 - p, each particle can also produce two offspring which are placed at a distance r from the original site following a power-law Lévy-like distribution P(r) ∝ 1 /rα. We perform numerical simulations starting from a single particle. A finite-time scaling analysis is employed to locate the critical diffusion probability pc below which a finite density of particles is developed in the long-time limit. Further, we estimate the spreading dynamical exponents related to the increase of the average number of particles at the critical point and its respective fluctuations. The critical exponents deviate from those of the counterpart model with short-range branching for small values of α. The numerical data suggest that continuously varying spreading exponents sets up while the branching process still results in a diffusive-like spreading.

Strong Shock Propagating Over A Random Bed of Spherical Particles

NASA Astrophysics Data System (ADS)

Mehta, Yash; Salari, Kambiz; Jackson, Thomas L.; Balachandar, S.; Thakur, Siddharth

2017-11-01

The study of shock interaction with particles has been largely motivated because of its wide-ranging applications. The complex interaction between the compressible flow features, such as shock wave and expansion fan, and the dispersed phase makes this multi-phase flow very difficult to predict and control. In this talk we will be presenting results on fully resolved inviscid simulations of shock interaction with random bed of particles. One of the fascinating observations from these simulations are the flow field fluctuations due to the presence of randomly distributed particles. Rigorous averaging (Favre averaging) of the governing equations results in Reynolds stress like term, which can be classified as pseudo turbulence in this case. We have computed this ``Reynolds stress'' term along with individual fluctuations and the turbulent kinetic energy. Average pressure was also computed to characterize the strength of the transmitted and the reflected waves. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program.

Cryptotomography: reconstructing 3D Fourier intensities from randomly oriented single-shot diffraction patterns (CXIDB ID 9)

DOE Data Explorer

Loh, Ne-Te Duane

2011-08-01

These 2000 single-shot diffraction patterns include were either background-scattering only or hits (background-scattering plus diffraction signal from sub-micron ellipsoidal particles at random, undetermined orientations). Candidate hits were identified by eye, and the remainder were presumed as background. 54 usable, background-subtracted hits in this set (procedure in referenced article) were used to reconstruct the 3D diffraction intensities of the average ellipsoidal particle.

Constraints on Martian Aerosol Particles Using MGS/TES and HST Data: Shapes

NASA Astrophysics Data System (ADS)

Wolff, M. J.; Clancy, R. T.; Pitman, K. M.; Bell, J. F.; James, P. B.

2001-12-01

In order to constrain the shape of water ice and dust aerosols, we have combined a numerical approach for axisymmetric particle shapes, i.e., cylinders, disks, spheroids (Waterman's T-Matrix approach as improved by Mishchenko and collaborators; cf., Mishchenko et al. 1997, JGR, 102, D14, 16,831), with a multiple-scattering radiative transfer algorithm. We utilize a two-stage iterative process. First, we empirically derive a scattering phase function for each aerosol component from radiative transfer models of Mars Global Surveyor Thermal Emission Spectrometer Emission Phase Function (EPF) sequences. Next, we perform a series of scattering calculations, adjusting our parameters to arrive at a ``best-fit'' theoretical phase function. It is important to note that in addition to randomly-oriented particles, we explicitly consider the possibility of (partially) aligned aerosol particles as well. Thus far, we have been analyzing the three empirically-derived presented by Clancy et al. (this meeting): dust, Type I ice particles (effective radii ~ 1-2 microns), and Type II ice particles (effective radii ~ 3-4 microns). We find that the ``dust'' phase function is best fit by randomly-oriented cylinders with an axial ratio (D/L = diameter-to-length) of either 2.3 or 0.6. Similarly, the shape of the Type II ice curve is reasonably reproduced by randomly-oriented spheroids with an axial ratio of either 0.7 or 1.4. However, neither of the two shapes (nor that of spheres or randomly-oriented hexagonal prisms) can reproduce the phase function derived for the Type I ice. This led to the direct consideration of oriented or aligned particles. which, at least qualitatively, have the ability to account for the phase function shapes for both Type I and II ice particles. The difference between these two phase functions may represent the degree of alignment, with the Type II particles being much less-aligned. The calculations for partially aligned particles is quite numerically intensive and this avenue of research is currently in progress. Additional work is also being done to further constrain the dust aerosol properties using both TES visible/IR and Hubble Space Telescope UV-NIR spectroscopy/imaging data of the recent (and ongoing) Martian global dust storm. Our work has been supported through NASA (MDAP) grant NAG5-9820, (MED) JPL contract 961471, STScI GO programs #8577 and #9052.

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.

Saddlepoint approximation to the distribution of the total distance of the continuous time random walk

NASA Astrophysics Data System (ADS)

Gatto, Riccardo

2017-12-01

This article considers the random walk over Rp, with p ≥ 2, where a given particle starts at the origin and moves stepwise with uniformly distributed step directions and step lengths following a common distribution. Step directions and step lengths are independent. The case where the number of steps of the particle is fixed and the more general case where it follows an independent continuous time inhomogeneous counting process are considered. Saddlepoint approximations to the distribution of the distance from the position of the particle to the origin are provided. Despite the p-dimensional nature of the random walk, the computations of the saddlepoint approximations are one-dimensional and thus simple. Explicit formulae are derived with dimension p = 3: for uniformly and exponentially distributed step lengths, for fixed and for Poisson distributed number of steps. In these situations, the high accuracy of the saddlepoint approximations is illustrated by numerical comparisons with Monte Carlo simulation. Contribution to the "Topical Issue: Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Weak scattering of scalar and electromagnetic random fields

NASA Astrophysics Data System (ADS)

Tong, Zhisong

This dissertation encompasses several studies relating to the theory of weak potential scattering of scalar and electromagnetic random, wide-sense statistically stationary fields from various types of deterministic or random linear media. The proposed theory is largely based on the first Born approximation for potential scattering and on the angular spectrum representation of fields. The main focus of the scalar counterpart of the theory is made on calculation of the second-order statistics of scattered light fields in cases when the scattering medium consists of several types of discrete particles with deterministic or random potentials. It is shown that the knowledge of the correlation properties for the particles of the same and different types, described with the newly introduced pair-scattering matrix, is crucial for determining the spectral and coherence states of the scattered radiation. The approach based on the pair-scattering matrix is then used for solving an inverse problem of determining the location of an "alien" particle within the scattering collection of "normal" particles, from several measurements of the spectral density of scattered light. Weak scalar scattering of light from a particulate medium in the presence of optical turbulence existing between the scattering centers is then approached using the combination of the Born's theory for treating the light interaction with discrete particles and the Rytov's theory for light propagation in extended turbulent medium. It is demonstrated how the statistics of scattered radiation depend on scattering potentials of particles and the power spectra of the refractive index fluctuations of turbulence. This theory is of utmost importance for applications involving atmospheric and oceanic light transmission. The second part of the dissertation includes the theoretical procedure developed for predicting the second-order statistics of the electromagnetic random fields, such as polarization and linear momentum, scattered from static media. The spatial distribution of these properties of scattered fields is shown to be substantially dependent on the correlation and polarization properties of incident fields and on the statistics of the refractive index distribution within the scatterers. Further, an example is considered which illustrates the usefulness of the electromagnetic scattering theory of random fields in the case when the scattering medium is a thin bio-tissue layer with the prescribed power spectrum of the refractive index fluctuations. The polarization state of the scattered light is shown to be influenced by correlation and polarization states of the illumination as well as by the particle size distribution of the tissue slice.

WWC Review of the Report "Interactive Learning Online at Public Universities: Evidence from a Six-Campus Randomized Trial." What Works Clearinghouse Single Study Review

ERIC Educational Resources Information Center

What Works Clearinghouse, 2014

2014-01-01

The 2013 study, "Interactive Learning Online at Public Universities: Evidence From a Six-Campus Randomized Trial," examined the impact of interactive learning online (ILO) on the pass rates of 605 students enrolled in introductory statistics courses at six public universities. ILO is a form of online course instruction in which…

Comparing Learning Style to Performance in On-Line Teaching: Impact of Proctored v. Un-Proctored Testing

ERIC Educational Resources Information Center

Wellman, Gregory S.

2005-01-01

The purpose of this study was to examine the impact that proctored versus un-proctored testing would have on learning for an on-line content module; and examine the relationship between LASSI variables and learning. A randomized, pre-test/post-test control group design was employed. College students in a pharmacy curriculum, were randomized to two…

Distribution of breakage events in random packings of rodlike particles.

PubMed

Grof, Zdeněk; Štěpánek, František

2013-07-01

Uniaxial compaction and breakage of rodlike particle packing has been studied using a discrete element method simulation. A scaling relationship between the applied stress, the number of breakage events, and the number-mean particle length has been derived and compared with computational experiments. Based on results for a wide range of intrinsic particle strengths and initial particle lengths, it seems that a single universal relation can be used to describe the incidence of breakage events during compaction of rodlike particle layers.

Transport of Charged Particles in Turbulent Magnetic Fields

NASA Astrophysics Data System (ADS)

Parashar, T.; Subedi, P.; Sonsrettee, W.; Blasi, P.; Ruffolo, D. J.; Matthaeus, W. H.; Montgomery, D.; Chuychai, P.; Dmitruk, P.; Wan, M.; Chhiber, R.

2017-12-01

Magnetic fields permeate the Universe. They are found in planets, stars, galaxies, and the intergalactic medium. The magnetic field found in these astrophysical systems are usually chaotic, disordered, and turbulent. The investigation of the transport of cosmic rays in magnetic turbulence is a subject of considerable interest. One of the important aspects of cosmic ray transport is to understand their diffusive behavior and to calculate the diffusion coefficient in the presence of these turbulent fields. Research has most frequently concentrated on determining the diffusion coefficient in the presence of a mean magnetic field. Here, we will particularly focus on calculating diffusion coefficients of charged particles and magnetic field lines in a fully three-dimensional isotropic turbulent magnetic field with no mean field, which may be pertinent to many astrophysical situations. For charged particles in isotropic turbulence we identify different ranges of particle energy depending upon the ratio of the Larmor radius of the charged particle to the characteristic outer length scale of the turbulence. Different theoretical models are proposed to calculate the diffusion coefficient, each applicable to a distinct range of particle energies. The theoretical ideas are tested against results of detailed numerical experiments using Monte-Carlo simulations of particle propagation in stochastic magnetic fields. We also discuss two different methods of generating random magnetic field to study charged particle propagation using numerical simulation. One method is the usual way of generating random fields with a specified power law in wavenumber space, using Gaussian random variables. Turbulence, however, is non-Gaussian, with variability that comes in bursts called intermittency. We therefore devise a way to generate synthetic intermittent fields which have many properties of realistic turbulence. Possible applications of such synthetically generated intermittent fields are discussed.

A model study of aggregates composed of spherical soot monomers with an acentric carbon shell

NASA Astrophysics Data System (ADS)

Luo, Jie; Zhang, Yongming; Zhang, Qixing

2018-01-01

Influences of morphology on the optical properties of soot particles have gained increasing attentions. However, studies on the effect of the way primary particles are coated on the optical properties is few. Aimed to understand how the primary particles are coated affect the optical properties of soot particles, the coated soot particle was simulated using the acentric core-shell monomers model (ACM), which was generated by randomly moving the cores of concentric core-shell monomers (CCM) model. Single scattering properties of the CCM model with identical fractal parameters were calculated 50 times at first to evaluate the optical diversities of different realizations of fractal aggregates with identical parameters. The results show that optical diversities of different realizations for fractal aggregates with identical parameters cannot be eliminated by averaging over ten random realizations. To preserve the fractal characteristics, 10 realizations of each model were generated based on the identical 10 parent fractal aggregates, and then the results were averaged over each 10 realizations, respectively. The single scattering properties of all models were calculated using the numerically exact multiple-sphere T-matrix (MSTM) method. It is found that the single scattering properties of randomly coated soot particles calculated using the ACM model are extremely close to those using CCM model and homogeneous aggregate (HA) model using Maxwell-Garnett effective medium theory. Our results are different from previous studies. The reason may be that the differences in previous studies were caused by fractal characteristics but not models. Our findings indicate that how the individual primary particles are coated has little effect on the single scattering properties of soot particles with acentric core-shell monomers. This work provides a suggestion for scattering model simplification and model selection.

Parsing anomalous versus normal diffusive behavior of bedload sediment particles

USGS Publications Warehouse

Fathel, Siobhan; Furbish, David; Schmeeckle, Mark

2016-01-01

Bedload sediment transport is the basic physical ingredient of river evolution. Formulae exist for estimating transport rates, but the diffusive contribution to the sediment flux, and the associated spreading rate of tracer particles, are not clearly understood. The start-and-stop motions of sediment particles transported as bedload on a streambed mimic aspects of the Einstein–Smoluchowski description of the random-walk motions of Brownian particles. Using this touchstone description, recent work suggests the presence of anomalous diffusion, where the particle spreading rate differs from the linear dependence with time of Brownian behavior. We demonstrate that conventional measures of particle spreading reveal different attributes of bedload particle behavior depending on details of the calculation. When we view particle motions over start-and-stop timescales obtained from high-speed (250 Hz) imaging of coarse-sand particles, high-resolution measurements reveal ballistic-like behavior at the shortest (10−2 s) timescale, followed by apparent anomalous behavior due to correlated random walks in transition to normal diffusion (>10−1 s) – similar to Brownian particle behavior but involving distinctly different physics. However, when treated as a ‘virtual plume’ over this timescale range, particles exhibit inhomogeneous diffusive behavior because both the mean and the variance of particle travel distances increase nonlinearly with increasing travel times, a behavior that is unrelated to anomalous diffusion or to Brownian-like behavior. Our results indicate that care is needed in suggesting anomalous behavior when appealing to conventional measures of diffusion formulated for ideal particle systems.

Global diffusion of cosmic rays in random magnetic fields

NASA Astrophysics Data System (ADS)

Snodin, A. P.; Shukurov, A.; Sarson, G. R.; Bushby, P. J.; Rodrigues, L. F. S.

2016-04-01

The propagation of charged particles, including cosmic rays, in a partially ordered magnetic field is characterized by a diffusion tensor whose components depend on the particle's Larmor radius RL and the degree of order in the magnetic field. Most studies of the particle diffusion presuppose a scale separation between the mean and random magnetic fields (e.g. there being a pronounced minimum in the magnetic power spectrum at intermediate scales). Scale separation is often a good approximation in laboratory plasmas, but not in most astrophysical environments such as the interstellar medium (ISM). Modern simulations of the ISM have numerical resolution of the order of 1 pc, so the Larmor radius of the cosmic rays that dominate in energy density is at least 106 times smaller than the resolved scales. Large-scale simulations of cosmic ray propagation in the ISM thus rely on oversimplified forms of the diffusion tensor. We take the first steps towards a more realistic description of cosmic ray diffusion for such simulations, obtaining direct estimates of the diffusion tensor from test particle simulations in random magnetic fields (with the Larmor radius scale being fully resolved), for a range of particle energies corresponding to 10-2 ≲ RL/lc ≲ 103, where lc is the magnetic correlation length. We obtain explicit expressions for the cosmic ray diffusion tensor for RL/lc ≪ 1, that might be used in a sub-grid model of cosmic ray diffusion. The diffusion coefficients obtained are closely connected with existing transport theories that include the random walk of magnetic lines.

Sequential Multiple Assignment Randomized Trial (SMART) with Adaptive Randomization for Quality Improvement in Depression Treatment Program

PubMed Central

Chakraborty, Bibhas; Davidson, Karina W.

2015-01-01

Summary Implementation study is an important tool for deploying state-of-the-art treatments from clinical efficacy studies into a treatment program, with the dual goals of learning about effectiveness of the treatments and improving the quality of care for patients enrolled into the program. In this article, we deal with the design of a treatment program of dynamic treatment regimens (DTRs) for patients with depression post acute coronary syndrome. We introduce a novel adaptive randomization scheme for a sequential multiple assignment randomized trial of DTRs. Our approach adapts the randomization probabilities to favor treatment sequences having comparatively superior Q-functions used in Q-learning. The proposed approach addresses three main concerns of an implementation study: it allows incorporation of historical data or opinions, it includes randomization for learning purposes, and it aims to improve care via adaptation throughout the program. We demonstrate how to apply our method to design a depression treatment program using data from a previous study. By simulation, we illustrate that the inputs from historical data are important for the program performance measured by the expected outcomes of the enrollees, but also show that the adaptive randomization scheme is able to compensate poorly specified historical inputs by improving patient outcomes within a reasonable horizon. The simulation results also confirm that the proposed design allows efficient learning of the treatments by alleviating the curse of dimensionality. PMID:25354029

On aggregation in CA models in biology

NASA Astrophysics Data System (ADS)

Alber, Mark S.; Kiskowski, Audi

2001-12-01

Aggregation of randomly distributed particles into clusters of aligned particles is modeled using a cellular automata (CA) approach. The CA model accounts for interactions between more than one type of particle, in which pressures for angular alignment with neighbors compete with pressures for grouping by cell type. In the case of only one particle type clusters tend to unite into one big cluster. In the case of several types of particles the dynamics of clusters is more complicated and for specific choices of parameters particle sorting occurs simultaneously with the formation of clusters of aligned particles.

Mechanical instability and percolation of deformable particles through porous networks

NASA Astrophysics Data System (ADS)

Benet, Eduard; Lostec, Guillaume; Pellegrino, John; Vernerey, Franck

2018-04-01

The transport of micron-sized particles such as bacteria, cells, or synthetic lipid vesicles through porous spaces is a process relevant to drug delivery, separation systems, or sensors, to cite a few examples. Often, the motion of these particles depends on their ability to squeeze through small constrictions, making their capacity to deform an important factor for their permeation. However, it is still unclear how the mechanical behavior of these particles affects collective transport through porous networks. To address this issue, we present a method to reconcile the pore-scale mechanics of the particles with the Darcy scale to understand the motion of a deformable particle through a porous network. We first show that particle transport is governed by a mechanical instability occurring at the pore scale, which leads to a binary permeation response on each pore. Then, using the principles of directed bond percolation, we are able to link this microscopic behavior to the probability of permeating through a random porous network. We show that this instability, together with network uniformity, are key to understanding the nonlinear permeation of particles at a given pressure gradient. The results are then summarized by a phase diagram that predicts three distinct permeation regimes based on particle properties and the randomness of the pore network.

Random close packing of disks and spheres in confined geometries

NASA Astrophysics Data System (ADS)

Desmond, Kenneth W.; Weeks, Eric R.

2009-11-01

Studies of random close packing of spheres have advanced our knowledge about the structure of systems such as liquids, glasses, emulsions, granular media, and amorphous solids. In confined geometries, the structural properties of random-packed systems will change. To understand these changes, we study random close packing in finite-sized confined systems, in both two and three dimensions. Each packing consists of a 50-50 binary mixture with particle size ratio of 1.4. The presence of confining walls significantly lowers the overall maximum area fraction (or volume fraction in three dimensions). A simple model is presented, which quantifies the reduction in packing due to wall-induced structure. This wall-induced structure decays rapidly away from the wall, with characteristic length scales comparable to the small particle diameter.

Achieving a strongly negative scattering asymmetry factor in random media composed of dual-dipolar particles

NASA Astrophysics Data System (ADS)

Wang, B. X.; Zhao, C. Y.

2018-02-01

Understanding radiative transfer in random media like micro- or nanoporous and particulate materials, allows people to manipulate the scattering and absorption of radiation, as well as opens new possibilities in applications such as imaging through turbid media, photovoltaics, and radiative cooling. A strong-backscattering phase function, i.e., a negative scattering asymmetry parameter g , is of great interest, which can possibly lead to unusual radiative transport phenomena, for instance, Anderson localization of light. Here we demonstrate that by utilizing the structural correlations and second Kerker condition for a disordered medium composed of randomly distributed silicon nanoparticles, a strongly negative scattering asymmetry factor (g ˜-0.5 ) for multiple light scattering can be realized in the near infrared. Based on the multipole expansion of Foldy-Lax equations and quasicrystalline approximation (QCA), we have rigorously derived analytical expressions for the effective propagation constant and scattering phase function for a random system containing spherical particles, by taking the effect of structural correlations into account. We show that as the concentration of scattering particles rises, the backscattering is also enhanced. Moreover, in this circumstance, the transport mean free path is largely reduced and even becomes smaller than that predicted by independent scattering approximation. We further explore the dependent scattering effects, including the modification of electric and magnetic dipole excitations and far-field interference effect, both induced and influenced by the structural correlations, for volume fraction of particles up to fv˜0.25 . Our results have profound implications in harnessing micro- or nanoscale radiative transfer through random media.

Physical interrelation between Fokker-Planck and random walk models with application to Coulomb interactions.

NASA Technical Reports Server (NTRS)

Englert, G. W.

1971-01-01

A model of the random walk is formulated to allow a simple computing procedure to replace the difficult problem of solution of the Fokker-Planck equation. The step sizes and probabilities of taking steps in the various directions are expressed in terms of Fokker-Planck coefficients. Application is made to many particle systems with Coulomb interactions. The relaxation of a highly peaked velocity distribution of particles to equilibrium conditions is illustrated.

Numerically Exact Computer Simulations of Light Scattering by Densely Packed, Random Particulate Media

NASA Technical Reports Server (NTRS)

Dlugach, Janna M.; Mishchenko, Michael I.; Liu, Li; Mackowski, Daniel W.

2011-01-01

Direct computer simulations of electromagnetic scattering by discrete random media have become an active area of research. In this progress review, we summarize and analyze our main results obtained by means of numerically exact computer solutions of the macroscopic Maxwell equations. We consider finite scattering volumes with size parameters in the range, composed of varying numbers of randomly distributed particles with different refractive indices. The main objective of our analysis is to examine whether all backscattering effects predicted by the low-density theory of coherent backscattering (CB) also take place in the case of densely packed media. Based on our extensive numerical data we arrive at the following conclusions: (i) all backscattering effects predicted by the asymptotic theory of CB can also take place in the case of densely packed media; (ii) in the case of very large particle packing density, scattering characteristics of discrete random media can exhibit behavior not predicted by the low-density theories of CB and radiative transfer; (iii) increasing the absorptivity of the constituent particles can either enhance or suppress typical manifestations of CB depending on the particle packing density and the real part of the refractive index. Our numerical data strongly suggest that spectacular backscattering effects identified in laboratory experiments and observed for a class of high-albedo Solar System objects are caused by CB.

The Effect of Practice Schedule on Context-Dependent Learning.

PubMed

Lee, Ya-Yun; Fisher, Beth E

2018-03-02

It is well established that random practice compared to blocked practice enhances motor learning. Additionally, while information in the environment may be incidental, learning is also enhanced when an individual performs a task within the same environmental context in which the task was originally practiced. This study aimed to disentangle the effects of practice schedule and incidental/environmental context on motor learning. Participants practiced three finger sequences under either a random or blocked practice schedule. Each sequence was associated with specific incidental context (i.e., color and location on the computer screen) during practice. The participants were tested under the conditions when the sequence-context associations remained the same or were changed from that of practice. When the sequence-context association was changed, the participants who practiced under blocked schedule demonstrated greater performance decrement than those who practiced under random schedule. The findings suggested that those participants who practiced under random schedule were more resistant to the change of environmental context.

Medical Students' and Tutors' Experiences of Directed and Self-Directed Learning Programs in Evidence-Based Medicine: A Qualitative Evaluation Accompanying a Randomized Controlled Trial

ERIC Educational Resources Information Center

Bradley, Peter; Oterholt, Christina; Nordheim, Lena; Bjorndal, Arild

2005-01-01

This qualitative study aims to interpret the results of a randomized controlled trial comparing two educational programs (directed learning and self-directed learning) in evidence-based medicine (EBM) for medical students at the University of Oslo from 2002 to 2003. There is currently very little comparative educational research in this field. In…

From particle systems to learning processes. Comment on "Collective learning modeling based on the kinetic theory of active particles" by Diletta Burini, Silvana De Lillo, and Livio Gibelli

NASA Astrophysics Data System (ADS)

Lachowicz, Mirosław

2016-03-01

The very stimulating paper [6] discusses an approach to perception and learning in a large population of living agents. The approach is based on a generalization of kinetic theory methods in which the interactions between agents are described in terms of game theory. Such an approach was already discussed in Ref. [2-4] (see also references therein) in various contexts. The processes of perception and learning are based on the interactions between agents and therefore the general kinetic theory is a suitable tool for modeling them. However the main question that rises is how the perception and learning processes may be treated in the mathematical modeling. How may we precisely deliver suitable mathematical structures that are able to capture various aspects of perception and learning?

Vector solution for the mean electromagnetic fields in a layer of random particles

NASA Technical Reports Server (NTRS)

Lang, R. H.; Seker, S. S.; Levine, D. M.

1986-01-01

The mean electromagnetic fields are found in a layer of randomly oriented particles lying over a half space. A matrix-dyadic formulation of Maxwell's equations is employed in conjunction with the Foldy-Lax approximation to obtain equations for the mean fields. A two variable perturbation procedure, valid in the limit of small fractional volume, is then used to derive uncoupled equations for the slowly varying amplitudes of the mean wave. These equations are solved to obtain explicit expressions for the mean electromagnetic fields in the slab region in the general case of arbitrarily oriented particles and arbitrary polarization of the incident radiation. Numerical examples are given for the application to remote sensing of vegetation.

Laser-induced rocket force on a microparticle in a complex (dusty) plasma

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

Nosenko, V.; Ivlev, A. V.; Morfill, G. E.

2010-12-15

The interaction of a focused powerful laser beam with micron-sized melamine formaldehyde (MF) particles was studied experimentally. The microspheres had a thin palladium coating on their surface and were suspended in a radio frequency argon plasma as a single layer (plasma crystal). A particle hit by the laser beam usually accelerated in the direction of the laser beam, consistent with the radiation pressure force mechanism. However, random-direction acceleration up to the speeds on the order 1 m/s was sometimes observed. Rocket-force mechanism is proposed to account for the random-direction acceleration. Similar, but much less pronounced, effect was also observed formore » MF particles without palladium coating.« less

APM_GUI: analyzing particle movement on the cell membrane and determining confinement.

PubMed

Menchón, Silvia A; Martín, Mauricio G; Dotti, Carlos G

2012-02-20

Single-particle tracking is a powerful tool for tracking individual particles with high precision. It provides useful information that allows the study of diffusion properties as well as the dynamics of movement. Changes in particle movement behavior, such as transitions between Brownian motion and temporary confinement, can reveal interesting biophysical interactions. Although useful applications exist to determine the paths of individual particles, only a few software implementations are available to analyze these data, and these implementations are generally not user-friendly and do not have a graphical interface,. Here, we present APM_GUI (Analyzing Particle Movement), which is a MatLab-implemented application with a Graphical User Interface. This user-friendly application detects confined movement considering non-random confinement when a particle remains in a region longer than a Brownian diffusant would remain. In addition, APM_GUI exports the results, which allows users to analyze this information using software that they are familiar with. APM_GUI provides an open-source tool that quantifies diffusion coefficients and determines whether trajectories have non-random confinements. It also offers a simple and user-friendly tool that can be used by individuals without programming skills.

Tracking Snowballs

NASA Image and Video Library

2010-11-18

Icy particles in the cloud around Hartley 2, as seen by NASA EPOXI mission spacecraft. A star moving through the background is marked with red and moves in a particular direction, with a particular speed; icy particles move in random directions.

Random walks of colloidal probes in viscoelastic materials

NASA Astrophysics Data System (ADS)

Khan, Manas; Mason, Thomas G.

2014-04-01

To overcome limitations of using a single fixed time step in random walk simulations, such as those that rely on the classic Wiener approach, we have developed an algorithm for exploring random walks based on random temporal steps that are uniformly distributed in logarithmic time. This improvement enables us to generate random-walk trajectories of probe particles that span a highly extended dynamic range in time, thereby facilitating the exploration of probe motion in soft viscoelastic materials. By combining this faster approach with a Maxwell-Voigt model (MVM) of linear viscoelasticity, based on a slowly diffusing harmonically bound Brownian particle, we rapidly create trajectories of spherical probes in soft viscoelastic materials over more than 12 orders of magnitude in time. Appropriate windowing of these trajectories over different time intervals demonstrates that random walk for the MVM is neither self-similar nor self-affine, even if the viscoelastic material is isotropic. We extend this approach to spatially anisotropic viscoelastic materials, using binning to calculate the anisotropic mean square displacements and creep compliances along different orthogonal directions. The elimination of a fixed time step in simulations of random processes, including random walks, opens up interesting possibilities for modeling dynamics and response over a highly extended temporal dynamic range.

Correlated random walks induced by dynamical wavefunction collapse

NASA Astrophysics Data System (ADS)

Bedingham, Daniel

2015-03-01

Wavefunction collapse models modify Schrödinger's equation so that it describes the collapse of a superposition of macroscopically distinguishable states as a genuine physical process [PRA 42, 78 (1990)]. This provides a basis for the resolution of the quantum measurement problem. An additional generic consequence of the collapse mechanism is that it causes particles to exhibit a tiny random diffusive motion. Furthermore, the diffusions of two sufficiently nearby particles are positively correlated -- it is more likely that the particles diffuse in the same direction than would happen if they behaved independently [PRA 89, 032713 (2014)]. The use of this effect is proposed as an experimental test of wave function collapse models in which pairs of nanoparticles are simultaneously released from nearby traps and allowed a brief period of free fall. The random displacements of the particles are then measured. The experiment must be carried out at sufficiently low temperature and pressure for the collapse effects to dominate over the ambient environmental noise. It is argued that these constraints can be satisfied by current technologies for a large class of viable wavefunction collapse models. Work supported by the Templeton World Charity Foundation.

Lipoprotein Particle Concentrations May Explain the Absence of Coronary Protection in the Women's Health Initiative Hormone Trials

PubMed Central

Hsia, Judith; Otvos, James D.; Rossouw, Jacques E.; Wu, LieLing; Wassertheil-Smoller, Sylvia; Hendrix, Susan L.; Robinson, Jennifer G.; Lund, Bernedine; Kuller, Lewis H.

2009-01-01

Objective The Women's Health Initiative randomized hormone trials unexpectedly demonstrated an increase in early coronary events. In an effort to explain this finding, we examined lipoprotein particle concentrations and their interactions with hormone therapy in a case–control substudy. Methods and Results We randomized 16 608 postmenopausal women with intact uterus to conjugated estrogens 0.625 mg with medroxyprogesterone acetate 2.5 mg daily or to placebo, and 10 739 women with prior hysterectomy to conjugated estrogens 0.625 mg daily or placebo, and measured lipoprotein subclasses by nuclear magnetic resonance spectroscopy at baseline and year 1 in 354 women with early coronary events and matched controls. Postmenopausal hormone therapy raised high-density lipoprotein cholesterol and particle concentration and reduced low-density lipoprotein cholesterol (LDL-C; all P<0.001 versus placebo). In contrast, neither unopposed estrogen nor estrogen with progestin lowered low-density lipoprotein particle concentration (LDL-P). Conclusions Postmenopausal hormone therapy–induced reductions in LDL-C were not paralleled by favorable effects on LDL-P. This finding may account for the absence of coronary protection conferred by estrogen in the randomized hormone trials. PMID:18599797

Residual Defect Density in Random Disks Deposits.

PubMed

Topic, Nikola; Pöschel, Thorsten; Gallas, Jason A C

2015-08-03

We investigate the residual distribution of structural defects in very tall packings of disks deposited randomly in large channels. By performing simulations involving the sedimentation of up to 50 × 10(9) particles we find all deposits to consistently show a non-zero residual density of defects obeying a characteristic power-law as a function of the channel width. This remarkable finding corrects the widespread belief that the density of defects should vanish algebraically with growing height. A non-zero residual density of defects implies a type of long-range spatial order in the packing, as opposed to only local ordering. In addition, we find deposits of particles to involve considerably less randomness than generally presumed.

Fermilab | Science | Particle Accelerators

Science.gov Websites

2,300 physicists from all over the world come to Fermilab to conduct experiments using particle particle physics to the next level, collaborating with scientists and laboratories around the world to help world leader in accelerator research, development and industrialization. Learn more about IARC. Fermilab

Modeling Human Performance in Restless Bandits with Particle Filters (Preprint)

DTIC Science & Technology

2009-01-01

respond to changes ( Gallistel , 2001). Here, we use a particle filter approach to finding solutions to the restless bandit problem. Particle...Experimental Psychology: Learning, Memory, and Cognition, 10(2), 258-270. Gallistel , C. R., Mark, T., King, A., & Latham, P. E. (2001). The rat

Computer-Assisted Learning in Elementary Reading: A Randomized Control Trial

ERIC Educational Resources Information Center

Shannon, Lisa Cassidy; Styers, Mary Koenig; Wilkerson, Stephanie Baird; Peery, Elizabeth

2015-01-01

This study evaluated the efficacy of Accelerated Reader, a computer-based learning program, at improving student reading. Accelerated Reader is a progress-monitoring, assessment, and practice tool that supports classroom instruction and guides independent reading. Researchers used a randomized controlled trial to evaluate the program with 344…

Hyperuniformity, quasi-long-range correlations, and void-space constraints in maximally random jammed particle packings. I. Polydisperse spheres.

PubMed

Zachary, Chase E; Jiao, Yang; Torquato, Salvatore

2011-05-01

Hyperuniform many-particle distributions possess a local number variance that grows more slowly than the volume of an observation window, implying that the local density is effectively homogeneous beyond a few characteristic length scales. Previous work on maximally random strictly jammed sphere packings in three dimensions has shown that these systems are hyperuniform and possess unusual quasi-long-range pair correlations decaying as r(-4), resulting in anomalous logarithmic growth in the number variance. However, recent work on maximally random jammed sphere packings with a size distribution has suggested that such quasi-long-range correlations and hyperuniformity are not universal among jammed hard-particle systems. In this paper, we show that such systems are indeed hyperuniform with signature quasi-long-range correlations by characterizing the more general local-volume-fraction fluctuations. We argue that the regularity of the void space induced by the constraints of saturation and strict jamming overcomes the local inhomogeneity of the disk centers to induce hyperuniformity in the medium with a linear small-wave-number nonanalytic behavior in the spectral density, resulting in quasi-long-range spatial correlations scaling with r(-(d+1)) in d Euclidean space dimensions. A numerical and analytical analysis of the pore-size distribution for a binary maximally random jammed system in addition to a local characterization of the n-particle loops governing the void space surrounding the inclusions is presented in support of our argument. This paper is the first part of a series of two papers considering the relationships among hyperuniformity, jamming, and regularity of the void space in hard-particle packings.

Multiswarm comprehensive learning particle swarm optimization for solving multiobjective optimization problems.

PubMed

Yu, Xiang; Zhang, Xueqing

2017-01-01

Comprehensive learning particle swarm optimization (CLPSO) is a powerful state-of-the-art single-objective metaheuristic. Extending from CLPSO, this paper proposes multiswarm CLPSO (MSCLPSO) for multiobjective optimization. MSCLPSO involves multiple swarms, with each swarm associated with a separate original objective. Each particle's personal best position is determined just according to the corresponding single objective. Elitists are stored externally. MSCLPSO differs from existing multiobjective particle swarm optimizers in three aspects. First, each swarm focuses on optimizing the associated objective using CLPSO, without learning from the elitists or any other swarm. Second, mutation is applied to the elitists and the mutation strategy appropriately exploits the personal best positions and elitists. Third, a modified differential evolution (DE) strategy is applied to some extreme and least crowded elitists. The DE strategy updates an elitist based on the differences of the elitists. The personal best positions carry useful information about the Pareto set, and the mutation and DE strategies help MSCLPSO discover the true Pareto front. Experiments conducted on various benchmark problems demonstrate that MSCLPSO can find nondominated solutions distributed reasonably over the true Pareto front in a single run.

Three-Dimensional Visualization of Wave Functions for Rotating Molecule: Plot of Spherical Harmonics

ERIC Educational Resources Information Center

Nagaoka, Shin-ichi; Teramae, Hiroyuki; Nagashima, Umpei

2013-01-01

At an early stage of learning quantum chemistry, undergraduate students usually encounter the concepts of the particle in a box, the harmonic oscillator, and then the particle on a sphere. Rotational levels of a diatomic molecule can be well approximated by the energy levels of the particle on a sphere. Wave functions for the particle in a…

Simulation study on characteristics of long-range interaction in randomly asymmetric exclusion process

NASA Astrophysics Data System (ADS)

Zhao, Shi-Bo; Liu, Ming-Zhe; Yang, Lan-Ying

2015-04-01

In this paper we investigate the dynamics of an asymmetric exclusion process on a one-dimensional lattice with long-range hopping and random update via Monte Carlo simulations theoretically. Particles in the model will firstly try to hop over successive unoccupied sites with a probability q, which is different from previous exclusion process models. The probability q may represent the random access of particles. Numerical simulations for stationary particle currents, density profiles, and phase diagrams are obtained. There are three possible stationary phases: the low density (LD) phase, high density (HD) phase, and maximal current (MC) in the system, respectively. Interestingly, bulk density in the LD phase tends to zero, while the MC phase is governed by α, β, and q. The HD phase is nearly the same as the normal TASEP, determined by exit rate β. Theoretical analysis is in good agreement with simulation results. The proposed model may provide a better understanding of random interaction dynamics in complex systems. Project supported by the National Natural Science Foundation of China (Grant Nos. 41274109 and 11104022), the Fund for Sichuan Youth Science and Technology Innovation Research Team (Grant No. 2011JTD0013), and the Creative Team Program of Chengdu University of Technology.

Enhanced hyperuniformity from random reorganization.

PubMed

Hexner, Daniel; Chaikin, Paul M; Levine, Dov

2017-04-25

Diffusion relaxes density fluctuations toward a uniform random state whose variance in regions of volume [Formula: see text] scales as [Formula: see text] Systems whose fluctuations decay faster, [Formula: see text] with [Formula: see text], are called hyperuniform. The larger [Formula: see text], the more uniform, with systems like crystals achieving the maximum value: [Formula: see text] Although finite temperature equilibrium dynamics will not yield hyperuniform states, driven, nonequilibrium dynamics may. Such is the case, for example, in a simple model where overlapping particles are each given a small random displacement. Above a critical particle density [Formula: see text], the system evolves forever, never finding a configuration where no particles overlap. Below [Formula: see text], however, it eventually finds such a state, and stops evolving. This "absorbing state" is hyperuniform up to a length scale [Formula: see text], which diverges at [Formula: see text] An important question is whether hyperuniformity survives noise and thermal fluctuations. We find that hyperuniformity of the absorbing state is not only robust against noise, diffusion, or activity, but that such perturbations reduce fluctuations toward their limiting behavior, [Formula: see text], a uniformity similar to random close packing and early universe fluctuations, but with arbitrary controllable density.

Active Learning Not Associated with Student Learning in a Random Sample of College Biology Courses

PubMed Central

Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.

2011-01-01

Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning. PMID:22135373

Toward efficiency in heterogeneous multispecies reactive transport modeling: A particle-tracking solution for first-order network reactions

NASA Astrophysics Data System (ADS)

Henri, Christopher; Fernàndez-Garcia, Daniel

2015-04-01

Modeling multi-species reactive transport in natural systems with strong heterogeneities and complex biochemical reactions is a major challenge for assessing groundwater polluted sites with organic and inorganic contaminants. A large variety of these contaminants react according to serial-parallel reaction networks commonly simplified by a combination of first-order kinetic reactions. In this context, a random-walk particle tracking method is presented. This method is capable of efficiently simulating the motion of particles affected by first-order network reactions in three-dimensional systems, which are represented by spatially variable physical and biochemical coefficients described at high resolution. The approach is based on the development of transition probabilities that describe the likelihood that particles belonging to a given species and location at a given time will be transformed into and moved to another species and location afterwards. These probabilities are derived from the solution matrix of the spatial moments governing equations. The method is fully coupled with reactions, free of numerical dispersion and overcomes the inherent numerical problems stemming from the incorporation of heterogeneities to reactive transport codes. In doing this, we demonstrate that the motion of particles follows a standard random walk with time-dependent effective retardation and dispersion parameters that depend on the initial and final chemical state of the particle. The behavior of effective parameters develops as a result of differential retardation effects among species. Moreover, explicit analytic solutions of the transition probability matrix and related particle motions are provided for serial reactions. An example of the effect of heterogeneity on the dechlorination of organic solvents in a three-dimensional random porous media shows that the power-law behavior typically observed in conservative tracers breakthrough curves can be largely compromised by the effect of biochemical reactions.

Toward efficiency in heterogeneous multispecies reactive transport modeling: A particle-tracking solution for first-order network reactions

NASA Astrophysics Data System (ADS)

Henri, Christopher V.; Fernàndez-Garcia, Daniel

2014-09-01

Modeling multispecies reactive transport in natural systems with strong heterogeneities and complex biochemical reactions is a major challenge for assessing groundwater polluted sites with organic and inorganic contaminants. A large variety of these contaminants react according to serial-parallel reaction networks commonly simplified by a combination of first-order kinetic reactions. In this context, a random-walk particle tracking method is presented. This method is capable of efficiently simulating the motion of particles affected by first-order network reactions in three-dimensional systems, which are represented by spatially variable physical and biochemical coefficients described at high resolution. The approach is based on the development of transition probabilities that describe the likelihood that particles belonging to a given species and location at a given time will be transformed into and moved to another species and location afterward. These probabilities are derived from the solution matrix of the spatial moments governing equations. The method is fully coupled with reactions, free of numerical dispersion and overcomes the inherent numerical problems stemming from the incorporation of heterogeneities to reactive transport codes. In doing this, we demonstrate that the motion of particles follows a standard random walk with time-dependent effective retardation and dispersion parameters that depend on the initial and final chemical state of the particle. The behavior of effective parameters develops as a result of differential retardation effects among species. Moreover, explicit analytic solutions of the transition probability matrix and related particle motions are provided for serial reactions. An example of the effect of heterogeneity on the dechlorination of organic solvents in a three-dimensional random porous media shows that the power-law behavior typically observed in conservative tracers breakthrough curves can be largely compromised by the effect of biochemical reactions.

Cosmic ray sources, acceleration and propagation

NASA Technical Reports Server (NTRS)

Ptuskin, V. S.

1986-01-01

A review is given of selected papers on the theory of cosmic ray (CR) propagation and acceleration. The high isotropy and a comparatively large age of galactic CR are explained by the effective interaction of relativistic particles with random and regular electromagnetic fields in interstellar medium. The kinetic theory of CR propagation in the Galaxy is formulated similarly to the elaborate theory of CR propagation in heliosphere. The substantial difference between these theories is explained by the necessity to take into account in some cases the collective effects due to a rather high density of relativisitc particles. In particular, the kinetic CR stream instability and the hydrodynamic Parker instability is studied. The interaction of relativistic particles with an ensemble of given weak random magnetic fields is calculated by perturbation theory. The theory of CR transfer is considered to be basically completed for this case. The main problem consists in poor information about the structure of the regular and the random galactic magnetic fields. An account is given of CR transfer in a turbulent medium.

A new logistic dynamic particle swarm optimization algorithm based on random topology.

PubMed

Ni, Qingjian; Deng, Jianming

2013-01-01

Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.

A dynamic programming-based particle swarm optimization algorithm for an inventory management problem under uncertainty

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Zeng, Ziqiang; Han, Bernard; Lei, Xiao

2013-07-01

This article presents a dynamic programming-based particle swarm optimization (DP-based PSO) algorithm for solving an inventory management problem for large-scale construction projects under a fuzzy random environment. By taking into account the purchasing behaviour and strategy under rules of international bidding, a multi-objective fuzzy random dynamic programming model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform fuzzy random parameters into fuzzy variables that are subsequently defuzzified by using an expected value operator with optimistic-pessimistic index. The iterative nature of the authors' model motivates them to develop a DP-based PSO algorithm. More specifically, their approach treats the state variables as hidden parameters. This in turn eliminates many redundant feasibility checks during initialization and particle updates at each iteration. Results and sensitivity analysis are presented to highlight the performance of the authors' optimization method, which is very effective as compared to the standard PSO algorithm.

Multimode resource-constrained multiple project scheduling problem under fuzzy random environment and its application to a large scale hydropower construction project.

PubMed

Xu, Jiuping; Feng, Cuiying

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project

PubMed Central

Xu, Jiuping

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Dependent scattering and absorption by densely packed discrete spherical particles: Effects of complex refractive index

NASA Astrophysics Data System (ADS)

Ma, L. X.; Tan, J. Y.; Zhao, J. M.; Wang, F. Q.; Wang, C. A.; Wang, Y. Y.

2017-07-01

Due to the dependent scattering and absorption effects, the radiative transfer equation (RTE) may not be suitable for dealing with radiative transfer in dense discrete random media. This paper continues previous research on multiple and dependent scattering in densely packed discrete particle systems, and puts emphasis on the effects of particle complex refractive index. The Mueller matrix elements of the scattering system with different complex refractive indexes are obtained by both electromagnetic method and radiative transfer method. The Maxwell equations are directly solved based on the superposition T-matrix method, while the RTE is solved by the Monte Carlo method combined with the hard sphere model in the Percus-Yevick approximation (HSPYA) to consider the dependent scattering effects. The results show that for densely packed discrete random media composed of medium size parameter particles (equals 6.964 in this study), the demarcation line between independent and dependent scattering has remarkable connections with the particle complex refractive index. With the particle volume fraction increase to a certain value, densely packed discrete particles with higher refractive index contrasts between the particles and host medium and higher particle absorption indexes are more likely to show stronger dependent characteristics. Due to the failure of the extended Rayleigh-Debye scattering condition, the HSPYA has weak effect on the dependent scattering correction at large phase shift parameters.

Light-activated self-propelled colloids

PubMed Central

Palacci, J.; Sacanna, S.; Kim, S.-H.; Yi, G.-R.; Pine, D. J.; Chaikin, P. M.

2014-01-01

Light-activated self-propelled colloids are synthesized and their active motion is studied using optical microscopy. We propose a versatile route using different photoactive materials, and demonstrate a multiwavelength activation and propulsion. Thanks to the photoelectrochemical properties of two semiconductor materials (α-Fe2O3 and TiO2), a light with an energy higher than the bandgap triggers the reaction of decomposition of hydrogen peroxide and produces a chemical cloud around the particle. It induces a phoretic attraction with neighbouring colloids as well as an osmotic self-propulsion of the particle on the substrate. We use these mechanisms to form colloidal cargos as well as self-propelled particles where the light-activated component is embedded into a dielectric sphere. The particles are self-propelled along a direction otherwise randomized by thermal fluctuations, and exhibit a persistent random walk. For sufficient surface density, the particles spontaneously form ‘living crystals’ which are mobile, break apart and reform. Steering the particle with an external magnetic field, we show that the formation of the dense phase results from the collisions heads-on of the particles. This effect is intrinsically non-equilibrium and a novel principle of organization for systems without detailed balance. Engineering families of particles self-propelled by different wavelength demonstrate a good understanding of both the physics and the chemistry behind the system and points to a general route for designing new families of self-propelled particles. PMID:25332383

The structure of evaporating and combusting sprays: Measurements and predictions

NASA Technical Reports Server (NTRS)

Shuen, J. S.; Solomon, A. S. P.; Faeth, F. M.

1983-01-01

The structure of particle-laden jets and nonevaporating and evaporating sprays was measured in order to evaluate models of these processes. Three models are being evaluated: (1) a locally homogeneous flow model, where slip between the phases is neglected and the flow is assumed to be in local thermodynamic equilibrium; (2) a deterministic separated flow model, where slip and finite interphase transport rates are considered but effects of particle/drop dispersion by turbulence and effects of turbulence on interphase transport rates are ignored; and (3) a stochastic separated flow model, where effects of interphase slip, turbulent dispersion and turbulent fluctuations are considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. All three models use a k-e-g turbulence model. All testing and data reduction are completed for the particle laden jets. Mean and fluctuating velocities of the continuous phase and mean mixture fraction were measured in the evaporating sprays.

A cubic scaling algorithm for excited states calculations in particle-particle random phase approximation

NASA Astrophysics Data System (ADS)

Lu, Jianfeng; Yang, Haizhao

2017-07-01

The particle-particle random phase approximation (pp-RPA) has been shown to be capable of describing double, Rydberg, and charge transfer excitations, for which the conventional time-dependent density functional theory (TDDFT) might not be suitable. It is thus desirable to reduce the computational cost of pp-RPA so that it can be efficiently applied to larger molecules and even solids. This paper introduces an O (N3) algorithm, where N is the number of orbitals, based on an interpolative separable density fitting technique and the Jacobi-Davidson eigensolver to calculate a few low-lying excitations in the pp-RPA framework. The size of the pp-RPA matrix can also be reduced by keeping only a small portion of orbitals with orbital energy close to the Fermi energy. This reduced system leads to a smaller prefactor of the cubic scaling algorithm, while keeping the accuracy for the low-lying excitation energies.

Emergent dynamics of Cucker-Smale particles under the effects of random communication and incompressible fluids

NASA Astrophysics Data System (ADS)

Ha, Seung-Yeal; Xiao, Qinghua; Zhang, Xiongtao

2018-04-01

We study the dynamics of infinitely many Cucker-Smale (C-S) flocking particles under the interplay of random communication and incompressible fluids. For the dynamics of an ensemble of flocking particles, we use the kinetic Cucker-Smale-Fokker-Planck (CS-FP) equation with a degenerate diffusion, whereas for the fluid component, we use the incompressible Navier-Stokes (N-S) equations. These two subsystems are coupled via the drag force. For this coupled model, we present the global existence of weak and strong solutions in Rd (d = 2 , 3). Under the extra regularity assumptions of the initial data, the unique solvability of strong solutions is also established in R2. In a large coupling regime and periodic spatial domain T2 : =R2 /Z2, we show that the velocities of C-S particles and fluids are asymptotically aligned to two constant velocities which may be different.

Initial Considerations of a Dust Dispenser for Injecting Tungsten Particles in Space

DTIC Science & Technology

2014-09-26

INTRODUCTION We began to learn how to work with tungsten particles as fine as corn starch , which must be ejected as individual particles. Several designs...purchased a quantity of tungsten carbide spheres, with diameters in our desired range, because of their shape and improved resistance to oxidation... resistance . When ignoring air resistance the only force acting on the particle after it leaves the dispenser is gravity. The particle motion can be

An Alternative Proposal for the Graphical Representation of Anticolor Charge

ERIC Educational Resources Information Center

Wiener, Gergried J.; Schmeling, Sascha M.; Hopf, Martin

2017-01-01

We have developed a learning unit based on the Standard Model of particle physics, featuring novel typographic illustrations of elementary particles and particle systems. Since the unit includes antiparticles and systems of antiparticles, a visualization of anticolor charge was required. We propose an alternative to the commonly used…

Effectiveness of the clinical teaching associate model to improve clinical learning outcomes: a randomized controlled trial.

PubMed

Parchebafieh, Samaneh; Gholizadeh, Leila; Lakdizaji, Sima; Ghiasvandiyan, Shahrzad; Davoodi, Arefeh

2014-01-01

This study examined the effectiveness of the clinical teaching associate (CTA) model to improve clinical learning outcomes in nursing students. Students were randomly allocated to either the CTA (n = 28) or traditional training group (n = 32), and their clinical knowledge, skills, and satisfaction with the learning experience were assessed and compared. The results showed that the CTA model was equally effective in improving clinical knowledge, skills, and satisfaction of nursing students.

A new time domain random walk method for solute transport in 1-D heterogeneous media

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

Banton, O.; Delay, F.; Porel, G.

A new method to simulate solute transport in 1-D heterogeneous media is presented. This time domain random walk method (TDRW), similar in concept to the classical random walk method, calculates the arrival time of a particle cloud at a given location (directly providing the solute breakthrough curve). The main advantage of the method is that the restrictions on the space increments and the time steps which exist with the finite differences and random walk methods are avoided. In a homogeneous zone, the breakthrough curve (BTC) can be calculated directly at a given distance using a few hundred particles or directlymore » at the boundary of the zone. Comparisons with analytical solutions and with the classical random walk method show the reliability of this method. The velocity and dispersivity calculated from the simulated results agree within two percent with the values used as input in the model. For contrasted heterogeneous media, the random walk can generate high numerical dispersion, while the time domain approach does not.« less

Randomized Prediction Games for Adversarial Machine Learning.

PubMed

Rota Bulo, Samuel; Biggio, Battista; Pillai, Ignazio; Pelillo, Marcello; Roli, Fabio

In spam and malware detection, attackers exploit randomization to obfuscate malicious data and increase their chances of evading detection at test time, e.g., malware code is typically obfuscated using random strings or byte sequences to hide known exploits. Interestingly, randomization has also been proposed to improve security of learning algorithms against evasion attacks, as it results in hiding information about the classifier to the attacker. Recent work has proposed game-theoretical formulations to learn secure classifiers, by simulating different evasion attacks and modifying the classification function accordingly. However, both the classification function and the simulated data manipulations have been modeled in a deterministic manner, without accounting for any form of randomization. In this paper, we overcome this limitation by proposing a randomized prediction game, namely, a noncooperative game-theoretic formulation in which the classifier and the attacker make randomized strategy selections according to some probability distribution defined over the respective strategy set. We show that our approach allows one to improve the tradeoff between attack detection and false alarms with respect to the state-of-the-art secure classifiers, even against attacks that are different from those hypothesized during design, on application examples including handwritten digit recognition, spam, and malware detection.In spam and malware detection, attackers exploit randomization to obfuscate malicious data and increase their chances of evading detection at test time, e.g., malware code is typically obfuscated using random strings or byte sequences to hide known exploits. Interestingly, randomization has also been proposed to improve security of learning algorithms against evasion attacks, as it results in hiding information about the classifier to the attacker. Recent work has proposed game-theoretical formulations to learn secure classifiers, by simulating different evasion attacks and modifying the classification function accordingly. However, both the classification function and the simulated data manipulations have been modeled in a deterministic manner, without accounting for any form of randomization. In this paper, we overcome this limitation by proposing a randomized prediction game, namely, a noncooperative game-theoretic formulation in which the classifier and the attacker make randomized strategy selections according to some probability distribution defined over the respective strategy set. We show that our approach allows one to improve the tradeoff between attack detection and false alarms with respect to the state-of-the-art secure classifiers, even against attacks that are different from those hypothesized during design, on application examples including handwritten digit recognition, spam, and malware detection.

Development of an E-learning System for the Endoscopic Diagnosis of Early Gastric Cancer: An International Multicenter Randomized Controlled Trial.

PubMed

Yao, K; Uedo, N; Muto, M; Ishikawa, H; Cardona, H J; Filho, E C Castro; Pittayanon, R; Olano, C; Yao, F; Parra-Blanco, A; Ho, S H; Avendano, A G; Piscoya, A; Fedorov, E; Bialek, A P; Mitrakov, A; Caro, L; Gonen, C; Dolwani, S; Farca, A; Cuaresma, L F; Bonilla, J J; Kasetsermwiriya, W; Ragunath, K; Kim, S E; Marini, M; Li, H; Cimmino, D G; Piskorz, M M; Iacopini, F; So, J B; Yamazaki, K; Kim, G H; Ang, T L; Milhomem-Cardoso, D M; Waldbaum, C A; Carvajal, W A Piedra; Hayward, C M; Singh, R; Banerjee, R; Anagnostopoulos, G K; Takahashi, Y

2016-07-01

In many countries, gastric cancer is not diagnosed until an advanced stage. An Internet-based e-learning system to improve the ability of endoscopists to diagnose gastric cancer at an early stage was developed and was evaluated for its effectiveness. The study was designed as a randomized controlled trial. After receiving a pre-test, participants were randomly allocated to either an e-learning or non-e-learning group. Only those in the e-learning group gained access to the e-learning system. Two months after the pre-test, both groups received a post-test. The primary endpoint was the difference between the two groups regarding the rate of improvement of their test results. 515 endoscopists from 35 countries were assessed for eligibility, and 332 were enrolled in the study, with 166 allocated to each group. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group were included in the analysis. The mean improvement rate (standard deviation) in the e-learning and non-e-learning groups was 1·24 (0·26) and 1·00 (0·16), respectively (P<0·001). This global study clearly demonstrated the efficacy of an e-learning system to expand knowledge and provide invaluable experience regarding the endoscopic detection of early gastric cancer (R000012039). Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Effect of particle size distribution on permeability in the randomly packed porous media

NASA Astrophysics Data System (ADS)

Markicevic, Bojan

2017-11-01

An answer of how porous medium heterogeneity influences the medium permeability is still inconclusive, where both increase and decrease in the permeability value are reported. A numerical procedure is used to generate a randomly packed porous material consisting of spherical particles. Six different particle size distributions are used including mono-, bi- and three-disperse particles, as well as uniform, normal and log-normal particle size distribution with the maximum to minimum particle size ratio ranging from three to eight for different distributions. In all six cases, the average particle size is kept the same. For all media generated, the stochastic homogeneity is checked from distribution of three coordinates of particle centers, where uniform distribution of x-, y- and z- positions is found. The medium surface area remains essentially constant except for bi-modal distribution in which medium area decreases, while no changes in the porosity are observed (around 0.36). The fluid flow is solved in such domain, and after checking for the pressure axial linearity, the permeability is calculated from the Darcy law. The permeability comparison reveals that the permeability of the mono-disperse medium is smallest, and the permeability of all poly-disperse samples is less than ten percent higher. For bi-modal particles, the permeability is for a quarter higher compared to the other media which can be explained by volumetric contribution of larger particles and larger passages for fluid flow to take place.

Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

PubMed

Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

2013-07-01

Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effect of Improving the Usability of an E-Learning Resource: A Randomized Trial

ERIC Educational Resources Information Center

Davids, Mogamat Razeen; Chikte, Usuf M. E.; Halperin, Mitchell L.

2014-01-01

Optimizing the usability of e-learning materials is necessary to reduce extraneous cognitive load and maximize their potential educational impact. However, this is often neglected, especially when time and other resources are limited. We conducted a randomized trial to investigate whether a usability evaluation of our multimedia e-learning…

Efficacy Trial of the Second Step Early Learning (SSEL) Curriculum: Preliminary Outcomes

ERIC Educational Resources Information Center

Upshur, Carole C.; Heyman, Miriam; Wenz-Gross, Melodie

2017-01-01

A classroom randomized trial (n = 31 classrooms) was conducted using the Second Step Early Learning (SSEL) curriculum compared to usual curricula. Head Start and community preschool classrooms enrolling low income children were randomly assigned to deliver SSEL (n = 16) or usual curricula (n = 15). Data are reported for four year olds…

Improving Learning in Primary Schools of Developing Countries: A Meta-Analysis of Randomized Experiments

ERIC Educational Resources Information Center

McEwan, Patrick J.

2015-01-01

I gathered 77 randomized experiments (with 111 treatment arms) that evaluated the effects of school-based interventions on learning in developing-country primary schools. On average, monetary grants and deworming treatments had mean effect sizes that were close to zero and not statistically significant. Nutritional treatments, treatments that…

Single-particle structure determination by correlations of snapshot X-ray diffraction patterns (CXIDB ID 20)

DOE Data Explorer

Starodub, D.

2013-03-25

This deposition includes the diffraction images generated by the paired polystyrene spheres in random orientations. These images were used to determine and phase the single particle diffraction volume from their autocorrelation functions.

An Integrated approach to the Space Situational Awareness Problem

DTIC Science & Technology

2016-12-15

data coming from the sensors. We developed particle-based Gaussian Mixture Filters that are immune to the “curse of dimensionality”/ “particle...depletion” problem inherent in particle filtering . This method maps the data assimilation/ filtering problem into an unsupervised learning problem. Results...Gaussian Mixture Filters ; particle depletion; Finite Set Statistics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 1

Half Lives for ``Irradiated'' Nonscience Majors

NASA Astrophysics Data System (ADS)

Geise, Kathleen; Hallam, Peter; Rattray, Rebecca; Stencel, Robert; Wolfe, Tristan

2014-03-01

We launched new hands-on radiation labs to supplement lecture material for undergraduate, non-science majors at the University of Denver to reinforce learning objectives during winter quarter 2014 and in order to help educate the public about nuclear energy decisions. Our learning objectives included: 1. differentiate between particle radiation and electro-magnetic radiation, 2. understand that particle radiation comes in alpha, beta and gamma types, 3. atomic and nuclear structure, 4. decay and half-life, 5. understand safe vs. unsafe doses and issues surrounding nuclear waste disposal. We used prelab surveys, prelab assessments, laboratory write-ups and quizzes to measure success with the learning objectives.

Gift from statistical learning: Visual statistical learning enhances memory for sequence elements and impairs memory for items that disrupt regularities.

PubMed

Otsuka, Sachio; Saiki, Jun

2016-02-01

Prior studies have shown that visual statistical learning (VSL) enhances familiarity (a type of memory) of sequences. How do statistical regularities influence the processing of each triplet element and inserted distractors that disrupt the regularity? Given that increased attention to triplets induced by VSL and inhibition of unattended triplets, we predicted that VSL would promote memory for each triplet constituent, and degrade memory for inserted stimuli. Across the first two experiments, we found that objects from structured sequences were more likely to be remembered than objects from random sequences, and that letters (Experiment 1) or objects (Experiment 2) inserted into structured sequences were less likely to be remembered than those inserted into random sequences. In the subsequent two experiments, we examined an alternative account for our results, whereby the difference in memory for inserted items between structured and random conditions is due to individuation of items within random sequences. Our findings replicated even when control letters (Experiment 3A) or objects (Experiment 3B) were presented before or after, rather than inserted into, random sequences. Our findings suggest that statistical learning enhances memory for each item in a regular set and impairs memory for items that disrupt the regularity. Copyright © 2015 Elsevier B.V. All rights reserved.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

NASA Astrophysics Data System (ADS)

Crevillén-García, D.; Power, H.

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Anomalous Diffusion of Single Particles in Cytoplasm

PubMed Central

Regner, Benjamin M.; Vučinić, Dejan; Domnisoru, Cristina; Bartol, Thomas M.; Hetzer, Martin W.; Tartakovsky, Daniel M.; Sejnowski, Terrence J.

2013-01-01

The crowded intracellular environment poses a formidable challenge to experimental and theoretical analyses of intracellular transport mechanisms. Our measurements of single-particle trajectories in cytoplasm and their random-walk interpretations elucidate two of these mechanisms: molecular diffusion in crowded environments and cytoskeletal transport along microtubules. We employed acousto-optic deflector microscopy to map out the three-dimensional trajectories of microspheres migrating in the cytosolic fraction of a cellular extract. Classical Brownian motion (BM), continuous time random walk, and fractional BM were alternatively used to represent these trajectories. The comparison of the experimental and numerical data demonstrates that cytoskeletal transport along microtubules and diffusion in the cytosolic fraction exhibit anomalous (nonFickian) behavior and posses statistically distinct signatures. Among the three random-walk models used, continuous time random walk provides the best representation of diffusion, whereas microtubular transport is accurately modeled with fractional BM. PMID:23601312

Memory formation and evolution of the vortex configuration associated with random organization

NASA Astrophysics Data System (ADS)

Dobroka, M.; Kawamura, Y.; Ienaga, K.; Kaneko, S.; Okuma, S.

2017-05-01

We study the general phenomenon of random organization using a vortex system. When a periodic shear with a small shear amplitude d inp is applied to many-particle (vortex) assemblies with a random distribution, the particles (vortices) gradually self-organize to avoid future collisions and transform into an organized configuration. This is detected from the time-evolution of the voltage V(t) (average velocity) that increases towards a steady-state value. From the subsequent readout measurements of V(t) using various shear amplitudes, we find that the information of the input shear amplitude d inp is memorized in the configuration of the vortex distributions in the transient as well as the steady state, and that it is readable. We also find that the transient vortex configuration formed during random organization is not microscopically homogeneous but consists of disordered and organized regions.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media.

PubMed

Crevillén-García, D; Power, H

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

PubMed Central

Power, H.

2017-01-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen–Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error. PMID:28878974

Modeling the effects of small turbulent scales on the drag force for particles below and above the Kolmogorov scale

NASA Astrophysics Data System (ADS)

Gorokhovski, Mikhael; Zamansky, Rémi

2018-03-01

Consistently with observations from recent experiments and DNS, we focus on the effects of strong velocity increments at small spatial scales for the simulation of the drag force on particles in high Reynolds number flows. In this paper, we decompose the instantaneous particle acceleration in its systematic and residual parts. The first part is given by the steady-drag force obtained from the large-scale energy-containing motions, explicitly resolved by the simulation, while the second denotes the random contribution due to small unresolved turbulent scales. This is in contrast with standard drag models in which the turbulent microstructures advected by the large-scale eddies are deemed to be filtered by the particle inertia. In our paper, the residual term is introduced as the particle acceleration conditionally averaged on the instantaneous dissipation rate along the particle path. The latter is modeled from a log-normal stochastic process with locally defined parameters obtained from the resolved field. The residual term is supplemented by an orientation model which is given by a random walk on the unit sphere. We propose specific models for particles with diameter smaller and larger size than the Kolmogorov scale. In the case of the small particles, the model is assessed by comparison with direct numerical simulation (DNS). Results showed that by introducing this modeling, the particle acceleration statistics from DNS is predicted fairly well, in contrast with the standard LES approach. For the particles bigger than the Kolmogorov scale, we propose a fluctuating particle response time, based on an eddy viscosity estimated at the particle scale. This model gives stretched tails of the particle acceleration distribution and dependence of its variance consistent with experiments.

Cosmic Rays in Intermittent Magnetic Fields

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

Shukurov, Anvar; Seta, Amit; Bushby, Paul J.

The propagation of cosmic rays in turbulent magnetic fields is a diffusive process driven by the scattering of the charged particles by random magnetic fluctuations. Such fields are usually highly intermittent, consisting of intense magnetic filaments and ribbons surrounded by weaker, unstructured fluctuations. Studies of cosmic-ray propagation have largely overlooked intermittency, instead adopting Gaussian random magnetic fields. Using test particle simulations, we calculate cosmic-ray diffusivity in intermittent, dynamo-generated magnetic fields. The results are compared with those obtained from non-intermittent magnetic fields having identical power spectra. The presence of magnetic intermittency significantly enhances cosmic-ray diffusion over a wide range of particlemore » energies. We demonstrate that the results can be interpreted in terms of a correlated random walk.« less

Randomizing Roaches: Exploring the "Bugs" of Randomization in Experimental Design

ERIC Educational Resources Information Center

Wagler, Amy; Wagler, Ron

2014-01-01

Understanding the roles of random selection and random assignment in experimental design is a central learning objective in most introductory statistics courses. This article describes an activity, appropriate for a high school or introductory statistics course, designed to teach the concepts, values and pitfalls of random selection and assignment…

Query construction, entropy, and generalization in neural-network models

NASA Astrophysics Data System (ADS)

Sollich, Peter

1994-05-01

We study query construction algorithms, which aim at improving the generalization ability of systems that learn from examples by choosing optimal, nonredundant training sets. We set up a general probabilistic framework for deriving such algorithms from the requirement of optimizing a suitable objective function; specifically, we consider the objective functions entropy (or information gain) and generalization error. For two learning scenarios, the high-low game and the linear perceptron, we evaluate the generalization performance obtained by applying the corresponding query construction algorithms and compare it to training on random examples. We find qualitative differences between the two scenarios due to the different structure of the underlying rules (nonlinear and ``noninvertible'' versus linear); in particular, for the linear perceptron, random examples lead to the same generalization ability as a sequence of queries in the limit of an infinite number of examples. We also investigate learning algorithms which are ill matched to the learning environment and find that, in this case, minimum entropy queries can in fact yield a lower generalization ability than random examples. Finally, we study the efficiency of single queries and its dependence on the learning history, i.e., on whether the previous training examples were generated randomly or by querying, and the difference between globally and locally optimal query construction.

Evaluating the Bias of Alternative Cost Progress Models: Tests Using Aerospace Industry Acquisition Programs

DTIC Science & Technology

1992-12-01

suspect :mat, -n2 extent predict:.on cas jas ccsiziveiv crrei:=e amonc e v:arious models, :he fandom *.;aik, learn ha r ur e, i;<ea- variable and Bemis...Functions, Production Rate Adjustment Model, Learning Curve Model. Random Walk Model. Bemis Model. Evaluating Model Bias, Cost Prediction Bias. Cost...of four cost progress models--a random walk model, the tradiuonai learning curve model, a production rate model Ifixed-variable model). and a model

Flocking dynamics with voter-like interactions

NASA Astrophysics Data System (ADS)

Baglietto, Gabriel; Vazquez, Federico

2018-03-01

We study the collective motion of a large set of self-propelled particles subject to voter-like interactions. Each particle moves on a 2D space at a constant speed in a direction that is randomly assigned initially. Then, at every step of the dynamics, each particle adopts the direction of motion of a randomly chosen neighboring particle. We investigate the time evolution of the global alignment of particles measured by the order parameter φ, until complete order \\varphi=1.0 is reached (polar consensus). We find that φ increases as t 1/2 for short times and approaches 1.0 exponentially fast for longer times. Also, the mean time to consensus τ varies non-monotonically with the density of particles ρ, reaching a minimum at some intermediate density ρmin . At ρmin , the mean consensus time scales with the system size N as τmin ∼ N0.765 , and thus the consensus is faster than in the case of all-to-all interactions (large ρ) where τ=2N . We show that the fast consensus, also observed at intermediate and high densities, is a consequence of the segregation of the system into clusters of equally-oriented particles which breaks the balance of transitions between directional states in well mixed systems.

Stochastically gated local and occupation times of a Brownian particle

NASA Astrophysics Data System (ADS)

Bressloff, Paul C.

2017-01-01

We generalize the Feynman-Kac formula to analyze the local and occupation times of a Brownian particle moving in a stochastically gated one-dimensional domain. (i) The gated local time is defined as the amount of time spent by the particle in the neighborhood of a point in space where there is some target that only receives resources from (or detects) the particle when the gate is open; the target does not interfere with the motion of the Brownian particle. (ii) The gated occupation time is defined as the amount of time spent by the particle in the positive half of the real line, given that it can only cross the origin when a gate placed at the origin is open; in the closed state the particle is reflected. In both scenarios, the gate randomly switches between the open and closed states according to a two-state Markov process. We derive a stochastic, backward Fokker-Planck equation (FPE) for the moment-generating function of the two types of gated Brownian functional, given a particular realization of the stochastic gate, and analyze the resulting stochastic FPE using a moments method recently developed for diffusion processes in randomly switching environments. In particular, we obtain dynamical equations for the moment-generating function, averaged with respect to realizations of the stochastic gate.

Influence of structure of iron nanoparticles in aggregates on their magnetic properties

PubMed Central

2011-01-01

Zero-valent iron nanoparticles rapidly aggregate. One of the reasons is magnetic forces among the nanoparticles. Magnetic field around particles is caused by composition of the particles. Their core is formed from zero-valent iron, and shell is a layer of magnetite. The magnetic forces contribute to attractive forces among the nanoparticles and that leads to increasing of aggregation of the nanoparticles. This effect is undesirable for decreasing of remediation properties of iron particles and limited transport possibilities. The aggregation of iron nanoparticles was established for consequent processes: Brownian motion, sedimentation, velocity gradient of fluid around particles and electrostatic forces. In our previous work, an introduction of influence of magnetic forces among particles on the aggregation was presented. These forces have significant impact on the rate of aggregation. In this article, a numerical computation of magnetic forces between an aggregate and a nanoparticle and between two aggregates is shown. It is done for random position of nanoparticles in an aggregate and random or arranged directions of magnetic polarizations and for structured aggregates with arranged vectors of polarizations. Statistical computation by Monte Carlo is done, and range of dominant area of magnetic forces around particles is assessed. PMID:21917152

Direct numerical simulation of moderate-Reynolds-number flow past arrays of rotating spheres

NASA Astrophysics Data System (ADS)

Zhou, Qiang; Fan, Liang-Shih

2015-07-01

Direct numerical simulations with an immersed boundary-lattice Boltzmann method are used to investigate the effects of particle rotation on flows past random arrays of mono-disperse spheres at moderate particle Reynolds numbers. This study is an extension of a previous study of the authors [Q. Zhou and L.-S. Fan, "Direct numerical simulation of low-Reynolds-number flow past arrays of rotating spheres," J. Fluid Mech. 765, 396-423 (2015)] that explored the effects of particle rotation at low particle Reynolds numbers. The results of this study indicate that as the particle Reynolds number increases, the normalized Magnus lift force decreases rapidly when the particle Reynolds number is in the range lower than 50. For the particle Reynolds number greater than 50, the normalized Magnus lift force approaches a constant value that is invariant with solid volume fractions. The proportional dependence of the Magnus lift force on the rotational Reynolds number (based on the angular velocity and the diameter of the spheres) observed at low particle Reynolds numbers does not change in the present study, making the Magnus lift force another possible factor that can significantly affect the overall dynamics of fluid-particle flows other than the drag force. Moreover, it is found that both the normalized drag force and the normalized torque increase with the increase of the particle Reynolds number and the solid volume fraction. Finally, correlations for the drag force, the Magnus lift force, and the torque in random arrays of rotating spheres at arbitrary solids volume fractions, rotational Reynolds numbers, and particle Reynolds numbers are formulated.

A stylistic classification of Russian-language texts based on the random walk model

NASA Astrophysics Data System (ADS)

Kramarenko, A. A.; Nekrasov, K. A.; Filimonov, V. V.; Zhivoderov, A. A.; Amieva, A. A.

2017-09-01

A formal approach to text analysis is suggested that is based on the random walk model. The frequencies and reciprocal positions of the vowel letters are matched up by a process of quasi-particle migration. Statistically significant difference in the migration parameters for the texts of different functional styles is found. Thus, a possibility of classification of texts using the suggested method is demonstrated. Five groups of the texts are singled out that can be distinguished from one another by the parameters of the quasi-particle migration process.

The surgical learning and instructional portfolio: what residents at a single institution are learning.

PubMed

Webb, Travis P; Merkley, Taylor R

2011-03-01

The Accreditation Council for Graduate Medical Education (ACGME) Learning Portfolio is recommended as a tool to develop and document reflective, practice-based learning and improvement. There is no consensus regarding the appropriate content of a learning portfolio in medical education. Studying lessons selected for inclusion in their learning portfolios by surgical trainees could help identify useful subject matter for this purpose. Each month, all residents in our surgery residency program submit entries into their individual Surgical Learning and Instructional Portfolio (SLIP). The SLIP entries from July 2008 to 2009 (n = 420) were deidentified and randomized using a random number generator. We conducted a thematic content analysis of 50 random portfolio entries to identify lessons learned. Two independent raters analyzed the "3 lessons learned" portion of the portfolio entries and identified themes and subthemes using the constant comparative method used in grounded theory. The collaborative coding process resulted in theme saturation after the identification of 7 themes and their subthemes. Themes in decreasing order of frequency included complications, disease epidemiology, disease presentation, surgical management of disease, medical management of disease, operative techniques, and pathophysiology. Junior residents chose to focus on a broad array of foundational topics including disease presentation, epidemiology, and overall management of diseases, whereas postgraduate year-4 (PGY-4) and PGY-5 residents most frequently chose to focus on complications as learning points. Lessons learned reflect perceived needs of the trainees based on training year. When given a template to follow, junior and senior residents choose to reflect on different subject matter to meet their learning goals.

Belle2VR: A Virtual-Reality Visualization of Subatomic Particle Physics in the Belle II Experiment.

PubMed

Duer, Zach; Piilonen, Leo; Glasson, George

2018-05-01

Belle2VR is an interactive virtual-reality visualization of subatomic particle physics, designed by an interdisciplinary team as an educational tool for learning about and exploring subatomic particle collisions. This article describes the tool, discusses visualization design decisions, and outlines our process for collaborative development.

Acute effects of exposure to 56Fe and 16O particles on learning and memory

USDA-ARS?s Scientific Manuscript database

Although it has been shown that exposure to HZE particles disrupts cognitive performance when tested 2-4 weeks after irradiation, it has not been determined whether exposure to HZE particles can exert acute effects on cognitive performance; i.e., effects within 4-48 hrs after exposure. The present ...

Plastic fluctuations in empty crystals formed by cubic wireframe particles

NASA Astrophysics Data System (ADS)

McBride, John M.; Avendaño, Carlos

2018-05-01

We present a computer simulation study of the phase behavior of colloidal hard cubic frames, i.e., particles with nonconvex cubic wireframe geometry interacting purely by excluded volume. Despite the propensity of cubic wireframe particles to form cubic phases akin to their convex counterparts, these particles exhibit unusual plastic fluctuations in which a random and dynamic fraction of particles rotate around their lattice positions in the crystal lattice while the remainder of the particles remains fully ordered. We argue that this unexpected effect stems from the nonconvex geometry of the particles in which the faces of a particle can be penetrated by the vertices of the nearest neighbors even at high number densities.

Radiation Force Caused by Scattering, Absorption, and Emission of Light by Nonspherical Particles

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Hansen, James E. (Technical Monitor)

2001-01-01

General formulas for computing the radiation force exerted on arbitrarily oriented and arbitrarily shaped nonspherical particles due to scattering, absorption, and emission of electromagnetic radiation are derived. For randomly oriented particles with a plane of symmetry, the formula for the average radiation force caused by the particle response to external illumination reduces to the standard Debye formula derived from the Lorenz-Mie theory, whereas the average radiation force caused by emission vanishes.

Collective rotations of active particles interacting with obstacles

NASA Astrophysics Data System (ADS)

Mokhtari, Zahra; Aspelmeier, Timo; Zippelius, Annette

2017-10-01

We consider active particles in a heterogeneous medium, modeled by static, random obstacles. In accordance with the known tendency of active particles to cluster, we observe accumulation and crystallization of active particles around the obstacles which serve as nucleation sites. In the limit of high activity, the crystals start to rotate spontaneously, resembling a rotating rigid body. We trace the occurrence of these oscillations to the enhanced attraction of particles whose orientation points along the rotational velocity as compared to those whose orientation points in the opposite direction.

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

PubMed Central

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Learned Helplessness in Exceptional Children.

ERIC Educational Resources Information Center

Brock, Herman B.; Kowitz, Gerald T.

The research literature on learned helplessness in exceptional children is reviewed and the authors' efforts to identify and retrain learning disabled (LD) children who have characteristics typical of learned helplessness are reported. Twenty-eight elementary aged LD children viewed as "learned helpless" were randomly assigned to one of four…

LETTER TO THE EDITOR: Single-species reactions on a random catalytic chain

NASA Astrophysics Data System (ADS)

Oshanin, G.; Burlatsky, S. F.

2002-11-01

We present an exact solution for a catalytically activated annihilation A + A → 0 reaction taking place on a one-dimensional chain in which some segments (placed at random, with mean concentration p) possess special, catalytic properties. An annihilation reaction takes place as soon as any two A particles land from the reservoir onto two vacant sites at the extremities of the catalytic segment, or when any A particle lands onto a vacant site on a catalytic segment while the site at the other extremity of this segment is already occupied by another A particle. We find that the disorder-average pressure P(quen) per site of such a chain is given by P(quen) = P(Lan) + β-1F, where P(Lan) = β-1 ln(1 + z) is the Langmuir adsorption pressure, (z being the activity and β-1 the temperature), while β-1F is the reaction-induced contribution, which can be expressed, under appropriate change of notation, as the Lyapunov exponent for the product of 2 × 2 random matrices, obtained exactly by Derrida and Hilhorst (1983 J. Phys. A: Math. Gen. 16 2641). Explicit asymptotic formulae for the particle mean density and the compressibility are also presented.

A random walk model to simulate the atmospheric dispersion of radionuclide

NASA Astrophysics Data System (ADS)

Zhuo, Jun; Huang, Liuxing; Niu, Shengli; Xie, Honggang; Kuang, Feihong

2018-01-01

To investigate the atmospheric dispersion of radionuclide in large-medium scale, a numerical simulation method based on random walk model for radionuclide atmospheric dispersion was established in the paper. The route of radionuclide migration and concentration distribution of radionuclide can be calculated out by using the method with the real-time or historical meteorological fields. In the simulation, a plume of radionuclide is treated as a lot of particles independent of each other. The particles move randomly by the fluctuations of turbulence, and disperse, so as to enlarge the volume of the plume and dilute the concentration of radionuclide. The dispersion of the plume over time is described by the variance of the particles. Through statistical analysis, the relationships between variance of the particles and radionuclide dispersion characteristics can be derived. The main mechanisms considered in the physical model are: (1) advection of radionuclide by mean air motion, (2) mixing of radionuclide by atmospheric turbulence, (3) dry and wet deposition, (4) disintegration. A code named RADES was developed according the method. And then, the European Tracer Experiment (ETEX) in 1994 is simulated by the RADES and FLEXPART codes, the simulation results of the concentration distribution of tracer are in good agreement with the experimental data.

On the Asymmetric Zero-Range in the Rarefaction Fan

NASA Astrophysics Data System (ADS)

Gonçalves, Patrícia

2014-02-01

We consider one-dimensional asymmetric zero-range processes starting from a step decreasing profile leading, in the hydrodynamic limit, to the rarefaction fan of the associated hydrodynamic equation. Under that initial condition, and for totally asymmetric jumps, we show that the weighted sum of joint probabilities for second class particles sharing the same site is convergent and we compute its limit. For partially asymmetric jumps, we derive the Law of Large Numbers for a second class particle, under the initial configuration in which all positive sites are empty, all negative sites are occupied with infinitely many first class particles and there is a single second class particle at the origin. Moreover, we prove that among the infinite characteristics emanating from the position of the second class particle it picks randomly one of them. The randomness is given in terms of the weak solution of the hydrodynamic equation, through some sort of renormalization function. By coupling the constant-rate totally asymmetric zero-range with the totally asymmetric simple exclusion, we derive limiting laws for more general initial conditions.

Evidence of Magnetic Inversion in Single Ni Nanoparticles

DOE PAGES

Jiang, W.; Gartland, P.; Davidović, D.

2016-11-08

Superparamagnetism is an unwanted property of small magnetic particles where the magnetization of the particle flips randomly in time, due to thermal noise. There has been an increased attention in the properties of superparamagnetic particles recently, because of their potential applications in high density storage and medicine. In electron transport through single nanometer scale magnetic particles, the current can also cause the magnetization to flip randomly in time, even at low temperature. Here we show experimental evidence that when the current is then reduced towards zero in the applied magnetic field, the magnetization can reliably freeze about a higher anisotropy-energymore » minimum, where it tends to be inverted with respect to the magnetic field direction. Specifically, we use spin-unpolarized tunneling spectroscopy of discrete levels in single Ni particles 2–4 nm in diameter at mK-temperature, and find that the the magnetic excitation energy at the onset of current decreases when the magnetic field increases, reaching near degeneracy at nonzero magnetic field. We discuss the potential for spintronic applications such as current induced magnetization switching without any spin-polarized leads.« less

Evidence of Magnetic Inversion in Single Ni Nanoparticles

PubMed Central

Jiang, W.; Gartland, P.; Davidović, D.

2016-01-01

Superparamagnetism is an unwanted property of small magnetic particles where the magnetization of the particle flips randomly in time, due to thermal noise. There has been an increased attention in the properties of superparamagnetic particles recently, because of their potential applications in high density storage and medicine. In electron transport through single nanometer scale magnetic particles, the current can also cause the magnetization to flip randomly in time, even at low temperature. Here we show experimental evidence that when the current is then reduced towards zero in the applied magnetic field, the magnetization can reliably freeze about a higher anisotropy-energy minimum, where it tends to be inverted with respect to the magnetic field direction. Specifically, we use spin-unpolarized tunneling spectroscopy of discrete levels in single Ni particles 2–4 nm in diameter at mK-temperature, and find that the the magnetic excitation energy at the onset of current decreases when the magnetic field increases, reaching near degeneracy at nonzero magnetic field. We discuss the potential for spintronic applications such as current induced magnetization switching without any spin-polarized leads. PMID:27824076

The Effects of a STEM Professional Development Intervention on Elementary Teachers' Science Process Skills

ERIC Educational Resources Information Center

Cotabish, Alicia; Dailey, Deborah; Hughes, Gail D.; Robinson, Ann

2011-01-01

In order to increase the quality and quantity of science instruction, elementary teachers must receive professional development in science learning processes. The current study was part of a larger randomized field study of teacher and student learning in science. In two districts in a southern state, researchers randomly assigned teacher…

Fraction Intervention for Students with Mathematics Difficulties: Lessons Learned from Five Randomized Controlled Trials

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Malone, Amelia S.; Schumacher, Robin F.; Namkung, Jessica; Wang, Amber

2017-01-01

In this article, the authors summarize results from 5 randomized controlled trials assessing the effects of intervention to improve the fraction performance of fourth-grade students at risk for difficulty in learning about fractions. The authors begin by explaining the importance of competence with fractions and why an instructional focus on…

Modeling the Stress Complexities of Teaching and Learning of School Physics in Nigeria

ERIC Educational Resources Information Center

Emetere, Moses E.

2014-01-01

This study was designed to investigate the validity of the stress complexity model (SCM) to teaching and learning of school physics in Abuja municipal area council of Abuja, North. About two hundred students were randomly selected by a simple random sampling technique from some schools within the Abuja municipal area council. A survey research…

Particle Tracking on the BNL Relativistic Heavy Ion Collider

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

Dell, G. F.

1986-08-07

Tracking studies including the effects of random multipole errors as well as the effects of random and systematic multipole errors have been made for RHIC. Initial results for operating at an off diagonal working point are discussed.

Wordless intervention for epilepsy in learning disabilities (WIELD): study protocol for a randomized controlled feasibility trial.

PubMed

Durand, Marie-Anne; Gates, Bob; Parkes, Georgina; Zia, Asif; Friedli, Karin; Barton, Garry; Ring, Howard; Oostendorp, Linda; Wellsted, David

2014-11-20

Epilepsy is the most common neurological problem that affects people with learning disabilities. The high seizure frequency, resistance to treatments, associated skills deficit and co-morbidities make the management of epilepsy particularly challenging for people with learning disabilities. The Books Beyond Words booklet for epilepsy uses images to help people with learning disabilities manage their condition and improve quality of life. Our aim is to conduct a randomized controlled feasibility trial exploring key methodological, design and acceptability issues, in order to subsequently undertake a large-scale randomized controlled trial of the Books Beyond Words booklet for epilepsy. We will use a two-arm, single-centre randomized controlled feasibility design, over a 20-month period, across five epilepsy clinics in Hertfordshire, United Kingdom. We will recruit 40 eligible adults with learning disabilities and a confirmed diagnosis of epilepsy and will randomize them to use either the Books Beyond Words booklet plus usual care (intervention group) or to receive routine information and services (control group). We will collect quantitative data about the number of eligible participants, number of recruited participants, demographic data, discontinuation rates, variability of the primary outcome measure (quality of life: Epilepsy and Learning Disabilities Quality of Life scale), seizure severity, seizure control, intervention's patterns of use, use of other epilepsy-related information, resource use and the EQ-5D-5L health questionnaire. We will also gather qualitative data about the feasibility and acceptability of the study procedures and the Books Beyond Words booklet. Ethical approval for this study was granted on 28 April 2014, by the Wales Research Ethics Committee 5. Recruitment began on 1 July 2014. The outcomes of this feasibility study will be used to inform the design and methodology of a definitive study, adequately powered to determine the impact of the Books Beyond Words intervention to improve the management of epilepsy in people with learning disabilities. http://ISRCTN80067039 (Date of ISRCTN assignation: 23 April 2014).

Arterial blood pressure responses to short-term exposure to fine and ultrafine particles from indoor sources - A randomized sham-controlled exposure study of healthy volunteers.

PubMed

Soppa, Vanessa J; Schins, Roel P F; Hennig, Frauke; Nieuwenhuijsen, Mark J; Hellack, Bryan; Quass, Ulrich; Kaminski, Heinz; Sasse, Birgitta; Shinnawi, Samir; Kuhlbusch, Thomas A J; Hoffmann, Barbara

2017-10-01

Particulate air pollution is linked to adverse cardiovascular effects. The aim of the study was to investigate the effect of short-term exposure to indoor particles on blood pressure (BP). We analyzed the association of particle emissions from indoor sources (candle burning, toasting bread, frying sausages) with BP changes in 54 healthy volunteers in a randomized cross-over controlled exposure study. Particle mass concentration (PMC), size-specific particle number concentration (PNC) and lung-deposited particle surface area concentration (PSC) were measured during the 2h exposure. Systolic and diastolic blood pressure were measured before, during, directly, 2, 4 and 24h after exposure. We performed multiple mixed linear regression analyses of different particle metrics and BP. BP significantly increased with increasing PMC, PSC and PNC resulting from toasting bread. For example, an increase per 10µg/m 3 PM 10 and PM 2.5 , systolic BP increased at all time points with largest changes 1h after exposure initiation of 1.5mmHg (95%-CI: 1.1; 1.9) and of 2.2mmHg (95%-CI: 1.3; 3.1), respectively. Our study suggests an association of short-term exposure to fine and ultrafine particles emitted from toasting bread with increases in BP. Particles emitted from frying sausages and candle burning did not consistently affect BP. Copyright © 2017. Published by Elsevier Inc.

A novel device for delivery of intranasal particulate medication: a pilot study.

PubMed

Khalili, Sammy; Tkachenko, Natalia; Rotenberg, Brian

2013-11-01

Intranasal medication delivery for allergic rhinitis (AR) is considered a mainstay of therapy but is hampered by poor compliance. Among reasons given are unpleasant sensations associated with spray penetration into the pharynx. Our objective was to study a novel method of particle delivery to the nose that would abrogate these issues. This was a double-blind, randomized study. Subjects who met study criteria underwent intranasal particle delivery using a novel device (Trivair Nasal Deposition System; Trimel Pharmaceuticals, Toronto, Canada) that delivered anhydrous lactose particles into the nose via a transoral air puff (thus elevating soft palate and blocking the nasopharynx). Subjects had nostrils randomized into 4 groups (particle sizes 5 μm and 50 μm × doses 12.5 mg and 25 mg). Particle deposition was assessed at 1 minute, 10 minutes, and 30 minutes on the inferior turbinate, middle turbinate, and nasopharynx, respectively, using high-definition endoscopic photography. Each image was compared using an expert blinded 2-person panel for percentage particles remaining. Nonparametric data was assessed using the Wilcoxon signed-rank test via Strata software. Twelve nostrils in total met study criteria. The results showed no difference in effectiveness of nasal particle retention between the groups based on particle size or dose. No particles entered the nasopharynx or oropharynx. This study provides proof-of-principle data that the Trivair Nasal Deposition System is effective at retaining medication in the nose without pharyngeal penetration. Larger studies on this device are warranted. © 2013 ARS-AAOA, LLC.

Computational analysis of electrical conduction in hybrid nanomaterials with embedded non-penetrating conductive particles

NASA Astrophysics Data System (ADS)

Cai, Jizhe; Naraghi, Mohammad

2016-08-01

In this work, a comprehensive multi-resolution two-dimensional (2D) resistor network model is proposed to analyze the electrical conductivity of hybrid nanomaterials made of insulating matrix with conductive particles such as CNT reinforced nanocomposites and thick film resistors. Unlike existing approaches, our model takes into account the impenetrability of the particles and their random placement within the matrix. Moreover, our model presents a detailed description of intra-particle conductivity via finite element analysis, which to the authors’ best knowledge has not been addressed before. The inter-particle conductivity is assumed to be primarily due to electron tunneling. The model is then used to predict the electrical conductivity of electrospun carbon nanofibers as a function of microstructural parameters such as turbostratic domain alignment and aspect ratio. To simulate the microstructure of single CNF, randomly positioned nucleation sites were seeded and grown as turbostratic particles with anisotropic growth rates. Particle growth was in steps and growth of each particle in each direction was stopped upon contact with other particles. The study points to the significant contribution of both intra-particle and inter-particle conductivity to the overall conductivity of hybrid composites. Influence of particle alignment and anisotropic growth rate ratio on electrical conductivity is also discussed. The results show that partial alignment in contrast to complete alignment can result in maximum electrical conductivity of whole CNF. High degrees of alignment can adversely affect conductivity by lowering the probability of the formation of a conductive path. The results demonstrate approaches to enhance electrical conductivity of hybrid materials through controlling their microstructure which is applicable not only to carbon nanofibers, but also many other types of hybrid composites such as thick film resistors.

Mental health first aid training by e-learning: a randomized controlled trial.

PubMed

Jorm, Anthony F; Kitchener, Betty A; Fischer, Julie-Anne; Cvetkovski, Stefan

2010-12-01

Mental Health First Aid training is a course for the public that teaches how to give initial help to a person developing a mental health problem or in a mental health crisis. The present study evaluated the effects of Mental Health First Aid training delivered by e-learning on knowledge about mental disorders, stigmatizing attitudes and helping behaviour. A randomized controlled trial was carried out with 262 members of the Australian public. Participants were randomly assigned to complete an e-learning CD, read a Mental Health First Aid manual or be in a waiting list control group. The effects of the interventions were evaluated using online questionnaires pre- and post-training and at 6-months follow up. The questionnaires covered mental health knowledge, stigmatizing attitudes, confidence in providing help to others, actions taken to implement mental health first aid and participant mental health. Both e-learning and the printed manual increased aspects of knowledge, reduced stigma and increased confidence compared to waiting list. E-learning also improved first aid actions taken more than waiting list, and was superior to the printed manual in reducing stigma and disability due to mental ill health. Mental Health First Aid information received by either e-learning or printed manual had positive effects, but e-learning was better at reducing stigma.

Collaborative emitter tracking using Rao-Blackwellized random exchange diffusion particle filtering

NASA Astrophysics Data System (ADS)

Bruno, Marcelo G. S.; Dias, Stiven S.

2014-12-01

We introduce in this paper the fully distributed, random exchange diffusion particle filter (ReDif-PF) to track a moving emitter using multiple received signal strength (RSS) sensors. We consider scenarios with both known and unknown sensor model parameters. In the unknown parameter case, a Rao-Blackwellized (RB) version of the random exchange diffusion particle filter, referred to as the RB ReDif-PF, is introduced. In a simulated scenario with a partially connected network, the proposed ReDif-PF outperformed a PF tracker that assimilates local neighboring measurements only and also outperformed a linearized random exchange distributed extended Kalman filter (ReDif-EKF). Furthermore, the novel ReDif-PF matched the tracking error performance of alternative suboptimal distributed PFs based respectively on iterative Markov chain move steps and selective average gossiping with an inter-node communication cost that is roughly two orders of magnitude lower than the corresponding cost for the Markov chain and selective gossip filters. Compared to a broadcast-based filter which exactly mimics the optimal centralized tracker or its equivalent (exact) consensus-based implementations, ReDif-PF showed a degradation in steady-state error performance. However, compared to the optimal consensus-based trackers, ReDif-PF is better suited for real-time applications since it does not require iterative inter-node communication between measurement arrivals.

The Surgical Learning and Instructional Portfolio: What Residents at a Single Institution Are Learning

PubMed Central

Webb, Travis P; Merkley, Taylor R

2011-01-01

Background The Accreditation Council for Graduate Medical Education (ACGME) Learning Portfolio is recommended as a tool to develop and document reflective, practice-based learning and improvement. There is no consensus regarding the appropriate content of a learning portfolio in medical education. Studying lessons selected for inclusion in their learning portfolios by surgical trainees could help identify useful subject matter for this purpose. Methods Each month, all residents in our surgery residency program submit entries into their individual Surgical Learning and Instructional Portfolio (SLIP). The SLIP entries from July 2008 to 2009 (n = 420) were deidentified and randomized using a random number generator. We conducted a thematic content analysis of 50 random portfolio entries to identify lessons learned. Two independent raters analyzed the “3 lessons learned” portion of the portfolio entries and identified themes and subthemes using the constant comparative method used in grounded theory. Results The collaborative coding process resulted in theme saturation after the identification of 7 themes and their subthemes. Themes in decreasing order of frequency included complications, disease epidemiology, disease presentation, surgical management of disease, medical management of disease, operative techniques, and pathophysiology. Junior residents chose to focus on a broad array of foundational topics including disease presentation, epidemiology, and overall management of diseases, whereas postgraduate year-4 (PGY-4) and PGY-5 residents most frequently chose to focus on complications as learning points. Conclusions Lessons learned reflect perceived needs of the trainees based on training year. When given a template to follow, junior and senior residents choose to reflect on different subject matter to meet their learning goals. PMID:22379531

Determinants of Teachers' Attitudes towards E- Learning in Tanzanian Higher Learning Institutions

ERIC Educational Resources Information Center

Kisanga, Dalton H.

2016-01-01

This survey research study presents the findings on determinants of teachers' attitudes towards e-learning in Tanzanian higher learning institutions. The study involved 258 teachers from 4 higher learning institutions obtained through stratified, simple random sampling. Questionnaires and documentary review were used in data collection. Data were…

eEduHeart I: A Multicenter, Randomized, Controlled Trial Investigating the Effectiveness of a Cardiac Web-Based eLearning Platform - Rationale and Study Design.

PubMed

Frederix, Ines; Vandenberk, Thijs; Janssen, Leen; Geurden, Anne; Vandervoort, Pieter; Dendale, Paul

Cardiac telerehabilitation includes, in its most comprehensive format, telemonitoring, telecoaching, social interaction, and eLearning. The specific role of eLearning, however, was seldom assessed. The aim of eEduHeart I is to investigate the medium-term effectiveness of the addition of a cardiac web-based eLearing platform to conventional cardiac care. In this prospective, multicenter randomized, controlled trial, 1,000 patients with coronary artery disease will be randomized 1:1 to an intervention group (receiving 1-month unrestricted access to the cardiac eLearning platform in addition to conventional cardiac care) or to conventional cardiac care alone. The primary endpoint is health-related quality of life, assessed by the HeartQoL questionnaire at the 1- and 3-month follow-ups. Secondary endpoints include pathology-specific knowledge and self-reported eLearning platform user experience. Data on the eLearning platform usage will be gathered through web logging during the study period. eEduHeart I will be one of the first studies to report on the added value of eLearning. If the intervention is proven effective, current cardiac telerehabilitation programs can be augmented by including eLearning, too. The platform can then be used as a model for other chronic diseases in which patient education plays a key role. © 2016 S. Karger AG, Basel.

Classification of nanoparticle diffusion processes in vital cells by a multifeature random forests approach: application to simulated data, darkfield, and confocal laser scanning microscopy

NASA Astrophysics Data System (ADS)

Wagner, Thorsten; Kroll, Alexandra; Wiemann, Martin; Lipinski, Hans-Gerd

2016-04-01

Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking makes it possible to characterize the particle and the surrounding cell. In case of free diffusion, the mean squared displacement for each trajectory of a nanoparticle can be measured which allows computing the corresponding diffusion coefficient and, if desired, converting it into the hydrodynamic diameter using the Stokes-Einstein equation and the viscosity of the fluid. However, within the more complex system of a cell's cytoplasm unrestrained diffusion is scarce and several other types of movements may occur. Thus, confined or anomalous diffusion (e.g. diffusion in porous media), active transport, and combinations thereof were described by several authors. To distinguish between these types of particle movement we developed an appropriate classification method, and simulated three types of particle motion in a 2D plane using a Monte Carlo approach: (1) normal diffusion, using random direction and step-length, (2) subdiffusion, using confinements like a reflective boundary with defined radius or reflective objects in the closer vicinity, and (3) superdiffusion, using a directed flow added to the normal diffusion. To simulate subdiffusion we devised a new method based on tracks of different length combined with equally probable obstacle interaction. Next we estimated the fractal dimension, elongation and the ratio of long-time / short-time diffusion coefficients. These features were used to train a random forests classification algorithm. The accuracy for simulated trajectories with 180 steps was 97% (95%-CI: 0.9481-0.9884). The balanced accuracy was 94%, 99% and 98% for normal-, sub- and superdiffusion, respectively. Nanoparticle tracking analysis was used with 100 nm polystyrene particles to get trajectories for normal diffusion. As a next step we identified diffusion types of nanoparticles in vital cells and incubated V79 fibroblasts with 50 nm gold nanoparticles, which appeared as intensely bright objects due to their surface plasmon resonance. The movement of particles in both the extracellular and intracellular space was observed by dark field and confocal laser scanning microscopy. After reducing background noise from the video it became possible to identify individual particle spots by a maximum detection algorithm and trace them using the robust single-particle tracking algorithm proposed by Jaqaman, which is able to handle motion heterogeneity and particle disappearance. The particle trajectories inside cells indicated active transport (superdiffusion) as well as subdiffusion. Eventually, the random forest classification algorithm, after being trained by the above simulations, successfully classified the trajectories observed in live cells.

Geometrical effects on the electron residence time in semiconductor nano-particles.

PubMed

Koochi, Hakimeh; Ebrahimi, Fatemeh

2014-09-07

We have used random walk (RW) numerical simulations to investigate the influence of the geometry on the statistics of the electron residence time τ(r) in a trap-limited diffusion process through semiconductor nano-particles. This is an important parameter in coarse-grained modeling of charge carrier transport in nano-structured semiconductor films. The traps have been distributed randomly on the surface (r(2) model) or through the whole particle (r(3) model) with a specified density. The trap energies have been taken from an exponential distribution and the traps release time is assumed to be a stochastic variable. We have carried out (RW) simulations to study the effect of coordination number, the spatial arrangement of the neighbors and the size of nano-particles on the statistics of τ(r). It has been observed that by increasing the coordination number n, the average value of electron residence time, τ̅(r) rapidly decreases to an asymptotic value. For a fixed coordination number n, the electron's mean residence time does not depend on the neighbors' spatial arrangement. In other words, τ̅(r) is a porosity-dependence, local parameter which generally varies remarkably from site to site, unless we are dealing with highly ordered structures. We have also examined the effect of nano-particle size d on the statistical behavior of τ̅(r). Our simulations indicate that for volume distribution of traps, τ̅(r) scales as d(2). For a surface distribution of traps τ(r) increases almost linearly with d. This leads to the prediction of a linear dependence of the diffusion coefficient D on the particle size d in ordered structures or random structures above the critical concentration which is in accordance with experimental observations.

The stochastic dynamics of intermittent porescale particle motion

NASA Astrophysics Data System (ADS)

Dentz, Marco; Morales, Veronica; Puyguiraud, Alexandre; Gouze, Philippe; Willmann, Matthias; Holzner, Markus

2017-04-01

Numerical and experimental data for porescale particle dynamics show intermittent patterns in Lagrangian velocities and accelerations, which manifest in long time intervals of low and short durations of high velocities [1, 2]. This phenomenon is due to the spatial persistence of particle velocities on characteristic heterogeneity length scales. In order to systematically quantify these behaviors and extract the stochastic dynamics of particle motion, we focus on the analysis of Lagrangian velocities sampled equidistantly along trajectories [3]. This method removes the intermittency observed under isochrone sampling. The space-Lagrangian velocity series can be quantified by a Markov process that is continuous in distance along streamline. It is fully parameterized in terms of the flux-weighted Eulerian velocity PDF and the characteristic pore-length. The resulting stochastic particle motion describes a continuous time random walk (CTRW). This approach allows for the process based interpretation of experimental and numerical porescale velocity, acceleration and displacement data. It provides a framework for the characterization and upscaling of particle transport and dispersion from the pore to the Darcy-scale based on the medium geometry and Eulerian flow attributes. [1] P. De Anna, T. Le Borgne, M. Dentz, A.M. Tartakovsky, D. Bolster, and P. Davy, "Flow intermittency, dispersion, and correlated continuous time random walks in porous media," Phys. Rev. Lett. 110, 184502 (2013). [2] M. Holzner, V. L. Morales, M. Willmann, and M. Dentz, "Intermittent Lagrangian velocities and accelerations in three- dimensional porous medium flow," Phys. Rev. E 92, 013015 (2015). [3] M. Dentz, P. K. Kang, A. Comolli, T. Le Borgne, and D. R. Lester, "Continuous time random walks for the evolution of Lagrangian velocities," Phys. Rev. Fluids (2016).

Comparison of Machine Learning methods for incipient motion in gravel bed rivers

NASA Astrophysics Data System (ADS)

Valyrakis, Manousos

2013-04-01

Soil erosion and sediment transport of natural gravel bed streams are important processes which affect both the morphology as well as the ecology of earth's surface. For gravel bed rivers at near incipient flow conditions, particle entrainment dynamics are highly intermittent. This contribution reviews the use of modern Machine Learning (ML) methods implemented for short term prediction of entrainment instances of individual grains exposed in fully developed near boundary turbulent flows. Results obtained by network architectures of variable complexity based on two different ML methods namely the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are compared in terms of different error and performance indices, computational efficiency and complexity as well as predictive accuracy and forecast ability. Different model architectures are trained and tested with experimental time series obtained from mobile particle flume experiments. The experimental setup consists of a Laser Doppler Velocimeter (LDV) and a laser optics system, which acquire data for the instantaneous flow and particle response respectively, synchronously. The first is used to record the flow velocity components directly upstream of the test particle, while the later tracks the particle's displacements. The lengthy experimental data sets (millions of data points) are split into the training and validation subsets used to perform the corresponding learning and testing of the models. It is demonstrated that the ANFIS hybrid model, which is based on neural learning and fuzzy inference principles, better predicts the critical flow conditions above which sediment transport is initiated. In addition, it is illustrated that empirical knowledge can be extracted, validating the theoretical assumption that particle ejections occur due to energetic turbulent flow events. Such a tool may find application in management and regulation of stream flows downstream of dams for stream restoration, implementation of sustainable practices in river and estuarine ecosystems and design of stable river bed and banks.

Implicit learning in cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia).

PubMed

Locurto, Charles; Fox, Maura; Mazzella, Andrea

2015-06-01

There is considerable interest in the conditions under which human subjects learn patterned information without explicit instructions to learn that information. This form of learning, termed implicit or incidental learning, can be approximated in nonhumans by exposing subjects to patterned information but delivering reinforcement randomly, thereby not requiring the subjects to learn the information in order to be reinforced. Following acquisition, nonhuman subjects are queried as to what they have learned about the patterned information. In the present experiment, we extended the study of implicit learning in nonhumans by comparing two species, cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia), on an implicit learning task that used an artificial grammar to generate the patterned elements for training. We equated the conditions of training and testing as much as possible between the two species. The results indicated that both species demonstrated approximately the same magnitude of implicit learning, judged both by a random test and by choice tests between pairs of training elements. This finding suggests that the ability to extract patterned information from situations in which such learning is not demanded is of longstanding origin.

Mixing by Unstirring: Hyperuniform Dispersion of Interacting Particles upon Chaotic Advection

NASA Astrophysics Data System (ADS)

Weijs, Joost H.; Bartolo, Denis

2017-07-01

We show how to achieve both fast and hyperuniform dispersions of particles in viscous fluids. To do so, we first extend the concept of critical random organization to chaotic drives. We show how palindromic sequences of chaotic advection cause microscopic particles to effectively interact at long range, thereby inhibiting critical self-organization. Based on this understanding we go around this limitation and design sequences of stirring and unstirring which simultaneously optimize the speed of particle spreading and the homogeneity of the resulting dispersions.

Quantum walks of two interacting particles on percolation graphs

NASA Astrophysics Data System (ADS)

Siloi, Ilaria; Benedetti, Claudia; Piccinini, Enrico; Paris, Matteo G. A.; Bordone, Paolo

2017-10-01

We address the dynamics of two indistinguishable interacting particles moving on a dynamical percolation graph, i.e., a graph where the edges are independent random telegraph processes whose values jump between 0 and 1, thus mimicking percolation. The interplay between the particle interaction strength, initial state and the percolation rate determine different dynamical regimes for the walkers. We show that, whenever the walkers are initially localised within the interaction range, fast noise enhances the particle spread compared to the noiseless case.

Concept Learning versus Problem Solving: Evaluating a Threat to the Validity of a Particulate Gas Law Question

ERIC Educational Resources Information Center

Sanger, Michael J.; Vaughn, C. Kevin; Binkley, David A.

2013-01-01

Three different samples of students were asked to answer five multiple-choice questions concerning the properties of a sample of helium gas (particle speed, state of matter, sample volume, sample pressure, and particle distribution), including a particulate question first used by Nurrenbern and Pickering (particle distribution). In the first…

Changes in gene expression in the rat hippocampus following exposure to 56 fe particles and protection by berry diets

USDA-ARS?s Scientific Manuscript database

Exposing young rats to particles of high energy and charge (HZE particles), such as 56Fe, enhances indices of oxidative stress and inflammation and disrupts behavior, including spatial learning and memory. In the present study, we examined whether gene expression in the hippocampus, an area of the b...

Contextual Interference in Complex Bimanual Skill Learning Leads to Better Skill Persistence

PubMed Central

Pauwels, Lisa; Swinnen, Stephan P.; Beets, Iseult A. M.

2014-01-01

The contextual interference (CI) effect is a robust phenomenon in the (motor) skill learning literature. However, CI has yielded mixed results in complex task learning. The current study addressed whether the CI effect is generalizable to bimanual skill learning, with a focus on the temporal evolution of memory processes. In contrast to previous studies, an extensive training schedule, distributed across multiple days of practice, was provided. Participants practiced three frequency ratios across three practice days following either a blocked or random practice schedule. During the acquisition phase, better overall performance for the blocked practice group was observed, but this difference diminished as practice progressed. At immediate and delayed retention, the random practice group outperformed the blocked practice group, except for the most difficult frequency ratio. Our main finding is that the random practice group showed superior performance persistence over a one week time interval in all three frequency ratios compared to the blocked practice group. This study contributes to our understanding of learning, consolidation and memory of complex motor skills, which helps optimizing training protocols in future studies and rehabilitation settings. PMID:24960171

Random close packing of polydisperse jammed emulsions

NASA Astrophysics Data System (ADS)

Brujic, Jasna

2010-03-01

Packing problems are everywhere, ranging from oil extraction through porous rocks to grain storage in silos and the compaction of pharmaceutical powders into tablets. At a given density, particulate systems pack into a mechanically stable and amorphous jammed state. Theoretical frameworks have proposed a connection between this jammed state and the glass transition, a thermodynamics of jamming, as well as geometric modeling of random packings. Nevertheless, a simple underlying mechanism for the random assembly of athermal particles, analogous to crystalline ordering, remains unknown. Here we use 3D measurements of polydisperse packings of emulsion droplets to build a simple statistical model in which the complexity of the global packing is distilled into a local stochastic process. From the perspective of a single particle the packing problem is reduced to the random formation of nearest neighbors, followed by a choice of contacts among them. The two key parameters in the model, the available space around a particle and the ratio of contacts to neighbors, are directly obtained from experiments. Remarkably, we demonstrate that this ``granocentric'' view captures the properties of the polydisperse emulsion packing, ranging from the microscopic distributions of nearest neighbors and contacts to local density fluctuations and all the way to the global packing density. Further applications to monodisperse and bidisperse systems quantitatively agree with previously measured trends in global density. This model therefore reveals a general principle of organization for random packing and lays the foundations for a theory of jammed matter.

Nonlinear machine learning and design of reconfigurable digital colloids.

PubMed

Long, Andrew W; Phillips, Carolyn L; Jankowksi, Eric; Ferguson, Andrew L

2016-09-14

Digital colloids, a cluster of freely rotating "halo" particles tethered to the surface of a central particle, were recently proposed as ultra-high density memory elements for information storage. Rational design of these digital colloids for memory storage applications requires a quantitative understanding of the thermodynamic and kinetic stability of the configurational states within which information is stored. We apply nonlinear machine learning to Brownian dynamics simulations of these digital colloids to extract the low-dimensional intrinsic manifold governing digital colloid morphology, thermodynamics, and kinetics. By modulating the relative size ratio between halo particles and central particles, we investigate the size-dependent configurational stability and transition kinetics for the 2-state tetrahedral (N = 4) and 30-state octahedral (N = 6) digital colloids. We demonstrate the use of this framework to guide the rational design of a memory storage element to hold a block of text that trades off the competing design criteria of memory addressability and volatility.

Analysis of Machine Learning Techniques for Heart Failure Readmissions.

PubMed

Mortazavi, Bobak J; Downing, Nicholas S; Bucholz, Emily M; Dharmarajan, Kumar; Manhapra, Ajay; Li, Shu-Xia; Negahban, Sahand N; Krumholz, Harlan M

2016-11-01

The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates. © 2016 American Heart Association, Inc.

Learning in the Machine: Random Backpropagation and the Deep Learning Channel.

PubMed

Baldi, Pierre; Sadowski, Peter; Lu, Zhiqin

2018-07-01

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the taxing requirement of maintaining symmetric weights in a physical neural system. To better understand random backpropagation, we first connect it to the notions of local learning and learning channels. Through this connection, we derive several alternatives to RBP, including skipped RBP (SRPB), adaptive RBP (ARBP), sparse RBP, and their combinations (e.g. ASRBP) and analyze their computational complexity. We then study their behavior through simulations using the MNIST and CIFAR-10 bechnmark datasets. These simulations show that most of these variants work robustly, almost as well as backpropagation, and that multiplication by the derivatives of the activation functions is important. As a follow-up, we study also the low-end of the number of bits required to communicate error information over the learning channel. We then provide partial intuitive explanations for some of the remarkable properties of RBP and its variations. Finally, we prove several mathematical results, including the convergence to fixed points of linear chains of arbitrary length, the convergence to fixed points of linear autoencoders with decorrelated data, the long-term existence of solutions for linear systems with a single hidden layer and convergence in special cases, and the convergence to fixed points of non-linear chains, when the derivative of the activation functions is included.

An Empirical and Methodological Analysis of the Role of Embodied Resources in Supporting Learning

ERIC Educational Resources Information Center

Saleh, Asmalina

2017-01-01

This dissertation presents three papers centered on understanding how we might learn using the body to learn. The data for these papers is drawn from classroom data where 2nd graders (N = 17) learn about particle behavior by engaging with the Science Through Technologically Enhanced Play (STEP) simulation. The first paper focuses on how two…

A Wiki-Based Teaching Material Development Environment with Enhanced Particle Swarm Optimization

ERIC Educational Resources Information Center

Lin, Yen-Ting; Lin, Yi-Chun; Huang, Yueh-Min; Cheng, Shu-Chen

2013-01-01

One goal of e-learning is to enhance the interoperability and reusability of learning resources. However, current e-learning systems do little to adequately support this. In order to achieve this aim, the first step is to consider how to assist instructors in re-organizing the existing learning objects. However, when instructors are dealing with a…

Light scattering and random lasing in aqueous suspensions of hexagonal boron nitride nanoflakes

NASA Astrophysics Data System (ADS)

O'Brien, S. A.; Harvey, A.; Griffin, A.; Donnelly, T.; Mulcahy, D.; Coleman, J. N.; Donegan, J. F.; McCloskey, D.

2017-11-01

Liquid phase exfoliation allows large scale production of 2D materials in solution. The particles are highly anisotropic and strongly scatter light. While spherical particles can be accurately and precisely described by a single parameter—the radius, 2D nanoflakes, however, cannot be so easily described. We investigate light scattering in aqueous solutions of 2D hexagonal boron nitride nanoflakes in the single and multiple scattering regimes. In the single scattering regime, the anisotropic 2D materials show a much stronger depolarization of light when compared to spherical particles of similar size. In the multiple scattering regime, the scattering as a function of optical path for hexagonal boron nitride nanoflakes of a given lateral length was found to be qualitatively equivalent to scattering from spheres with the same diameter. We also report the presence of random lasing in high concentration suspensions of aqueous h-BN mixed with Rhodamine B dye. The h-BN works as a scattering agent and Rhodamine B as a gain medium for the process. We observed random lasing at 587 nm with a threshold energy of 0.8 mJ.

Light scattering and random lasing in aqueous suspensions of hexagonal boron nitride nanoflakes.

PubMed

O'Brien, S A; Harvey, A; Griffin, A; Donnelly, T; Mulcahy, D; Coleman, J N; Donegan, J F; McCloskey, D

2017-11-24

Liquid phase exfoliation allows large scale production of 2D materials in solution. The particles are highly anisotropic and strongly scatter light. While spherical particles can be accurately and precisely described by a single parameter-the radius, 2D nanoflakes, however, cannot be so easily described. We investigate light scattering in aqueous solutions of 2D hexagonal boron nitride nanoflakes in the single and multiple scattering regimes. In the single scattering regime, the anisotropic 2D materials show a much stronger depolarization of light when compared to spherical particles of similar size. In the multiple scattering regime, the scattering as a function of optical path for hexagonal boron nitride nanoflakes of a given lateral length was found to be qualitatively equivalent to scattering from spheres with the same diameter. We also report the presence of random lasing in high concentration suspensions of aqueous h-BN mixed with Rhodamine B dye. The h-BN works as a scattering agent and Rhodamine B as a gain medium for the process. We observed random lasing at 587 nm with a threshold energy of 0.8 mJ.

Quincke random walkers

NASA Astrophysics Data System (ADS)

Pradillo, Gerardo; Heintz, Aneesh; Vlahovska, Petia

2017-11-01

The spontaneous rotation of a sphere in an applied uniform DC electric field (Quincke effect) has been utilized to engineer self-propelled particles: if the sphere is initially resting on a surface, it rolls. The Quincke rollers have been widely used as a model system to study collective behavior in ``active'' suspensions. If the applied field is DC, an isolated Quincke roller follows a straight line trajectory. In this talk, we discuss the design of a Quincke roller that executes a random-walk-like behavior. We utilize AC field - upon reversal of the field direction a fluctuation in the axis of rotation (which is degenerate in the plane perpendicular to the field and parallel to the surface) introduces randomness in the direction of motion. The MSD of an isolated Quincke walker depends on frequency, amplitude, and waveform of the electric field. Experiment and theory are compared. We also investigate the collective behavior of Quincke walkers,the transport of inert particles in a bath of Quincke walkers, and the spontaneous motion of a drop containing Quincke active particle. supported by NSF Grant CBET 1437545.

Learning by Preparing to Teach: Fostering Self-Regulatory Processes and Achievement during Complex Mathematics Problem Solving

ERIC Educational Resources Information Center

Muis, Krista R.; Psaradellis, Cynthia; Chevrier, Marianne; Di Leo, Ivana; Lajoie, Susanne P.

2016-01-01

We developed an intervention based on the learning by teaching paradigm to foster self-regulatory processes and better learning outcomes during complex mathematics problem solving in a technology-rich learning environment. Seventy-eight elementary students were randomly assigned to 1 of 2 conditions: learning by preparing to teach, or learning for…

Opening and retraction of particulate soap films

NASA Astrophysics Data System (ADS)

Timounay, Yousra; Lorenceau, Elise; Rouyer, Florence

2015-07-01

We study for the first time the bursting dynamics of thin liquid films laden with hydrophobic micronic particles either with free or constrained edges. We highlight that the particles can arrange in bilayer or monolayer configurations and explore a range of particles coverage from zero to random close packing. When the particles bridge the two interfaces (monolayer configuration) of free-edge films, the hole opens intermittently. For the other cases, we observe constant retraction velocities, modeled by balancing liquid and particles inertia against surface tension as in Taylor-Culick theory. But, this approach is only valid up to a critical value of particles coverage due to the interplay between the interfaces and the friction between particles.

Synthesis, characterization, and evaluation of a superficially porous particle with unique, elongated pore channels normal to the surface.

PubMed

Wei, Ta-Chen; Mack, Anne; Chen, Wu; Liu, Jia; Dittmann, Monika; Wang, Xiaoli; Barber, William E

2016-04-01

In recent years, superficially porous particles (SPPs) have drawn great interest because of their special particle characteristics and improvement in separation efficiency. Superficially porous particles are currently manufactured by adding silica nanoparticles onto solid cores using either a multistep multilayer process or one-step coacervation process. The pore size is mainly controlled by the size of the silica nanoparticles and the tortuous pore channel geometry is determined by how those nanoparticles randomly aggregate. Such tortuous pore structure is also similar to that of all totally porous particles used in HPLC today. In this article, we report on the development of a next generation superficially porous particle with a unique pore structure that includes a thinner shell thickness and ordered pore channels oriented normal to the particle surface. The method of making the new superficially porous particles is a process called pseudomorphic transformation (PMT), which is a form of micelle templating. Porosity is no longer controlled by randomly aggregated nanoparticles but rather by micelles that have an ordered liquid crystal structure. The new particle possesses many advantages such as a narrower particle size distribution, thinner porous layer with high surface area and, most importantly, highly ordered, non-tortuous pore channels oriented normal to the particle surface. This PMT process has been applied to make 1.8-5.1μm SPPs with pore size controlled around 75Å and surface area around 100m(2)/g. All particles with different sizes show the same unique pore structure with tunable pore size and shell thickness. The impact of the novel pore structure on the performance of these particles is characterized by measuring van Deemter curves and constructing kinetic plots. Reduced plate heights as low as 1.0 have been achieved on conventional LC instruments. This indicates higher efficiency of such particles compared to conventional totally porous and superficially porous particles. Copyright © 2016 Elsevier B.V. All rights reserved.

Machine-learning techniques for fast and accurate feature localization in holograms of colloidal particles

NASA Astrophysics Data System (ADS)

Hannel, Mark D.; Abdulali, Aidan; O'Brien, Michael; Grier, David G.

2018-06-01

Holograms of colloidal particles can be analyzed with the Lorenz-Mie theory of light scattering to measure individual particles' three-dimensional positions with nanometer precision while simultaneously estimating their sizes and refractive indexes. Extracting this wealth of information begins by detecting and localizing features of interest within individual holograms. Conventionally approached with heuristic algorithms, this image analysis problem can be solved faster and more generally with machine-learning techniques. We demonstrate that two popular machine-learning algorithms, cascade classifiers and deep convolutional neural networks (CNN), can solve the feature-localization problem orders of magnitude faster than current state-of-the-art techniques. Our CNN implementation localizes holographic features precisely enough to bootstrap more detailed analyses based on the Lorenz-Mie theory of light scattering. The wavelet-based Haar cascade proves to be less precise, but is so computationally efficient that it creates new opportunities for applications that emphasize speed and low cost. We demonstrate its use as a real-time targeting system for holographic optical trapping.

Supporting Students in Learning with Multiple Representation to Improve Student Mental Models on Atomic Structure Concepts

ERIC Educational Resources Information Center

Sunyono; Yuanita, L.; Ibrahim, M.

2015-01-01

The aim of this research is identify the effectiveness of a multiple representation-based learning model, which builds a mental model within the concept of atomic structure. The research sample of 108 students in 3 classes is obtained randomly from among students of Mathematics and Science Education Studies using a stratified random sampling…

Fraction Intervention for Students with Mathematics Difficulties: Lessons Learned from Five Randomized Control Trials

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Malone, Amelia S.; Schumacher, Robin F.; Namkung, Jessica; Wang, Amber

2016-01-01

The purpose of this article was to summarize results from 5 randomized control trials assessing the effects of intervention to improve the fraction performance of 4th-grade students at-risk for difficulty in learning about fractions. We begin by explaining the importance of competence with fractions and why an instructional focus on fractions…

The Effects of Self- and Peer-Monitoring in Social Studies Performance of Students with Learning Disabilities and Low Achieving Students

ERIC Educational Resources Information Center

Kim, Woori; Ok, Min Wook; Yoo, Yongseok

2018-01-01

This study employed group randomized trials to investigate the effects of self- and peer-monitoring on the academic vocabulary and content knowledge of students with learning disabilities and low achieving students in social studies. Fourth grade students were randomly assigned to either treatment or control groups on a class level. Results…

Can Distance Learning Improve Smoking Cessation Advice in Family Practice? A Randomized Trial.

ERIC Educational Resources Information Center

Young, Jane M.; Ward, Jeanette

2002-01-01

Family physicians were randomly assigned either to a distance learning module (n=26) or preventive care guidelines (n=27) on smoking cessation. No differences appeared in knowledge or attitudes. The distance group had significantly greater change in self-rated competence, but the magnitude of change was not greater than that of the control group.…

A School-Randomized Clinical Trial of an Integrated Social-Emotional Learning and Literacy Intervention: Impacts after 1 School Year

ERIC Educational Resources Information Center

Jones, Stephanie M.; Brown, Joshua L.; Hoglund, Wendy L. G.; Aber, J. Lawrence

2010-01-01

Objective: To report experimental impacts of a universal, integrated school-based intervention in social-emotional learning and literacy development on change over 1 school year in 3rd-grade children's social-emotional, behavioral, and academic outcomes. Method: This study employed a school-randomized, experimental design and included 942…

Understanding Randomness and Its Impact on Student Learning: Lessons Learned from Building the Biology Concept Inventory (BCI)

ERIC Educational Resources Information Center

Garvin-Doxas, Kathy; Klymkowsky, Michael W.

2008-01-01

While researching student assumptions for the development of the Biology Concept Inventory (BCI; http://bioliteracy.net), we found that a wide class of student difficulties in molecular and evolutionary biology appears to be based on deep-seated, and often unaddressed, misconceptions about random processes. Data were based on more than 500…

The Effects of Math Video Games on Learning: A Randomized Evaluation Study with Innovative Impact Estimation Techniques. CRESST Report 841

ERIC Educational Resources Information Center

Chung, Gregory K. W. K.; Choi, Kilchan; Baker, Eva L.; Cai, Li

2014-01-01

A large-scale randomized controlled trial tested the effects of researcher-developed learning games on a transfer measure of fractions knowledge. The measure contained items similar to standardized assessments. Thirty treatment and 29 control classrooms (~1500 students, 9 districts, 26 schools) participated in the study. Students in treatment…

Effects of Joint Attention Mediated Learning for Toddlers with Autism Spectrum Disorders: An Initial Randomized Controlled Study

ERIC Educational Resources Information Center

Schertz, Hannah H.; Odom, Samuel L.; Baggett, Kathleen M.; Sideris, John H.

2013-01-01

The purpose of this study was to determine effects of the Joint Attention Mediated Learning (JAML) intervention on acquisition of joint attention and other early social communication competencies for toddlers with autism spectrum disorders (ASD). Twenty-three parents and their toddlers were randomly assigned to JAML or a control condition.…

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

Gasser, U., E-mail: urs.gasser@psi.ch; Hyatt, J. S.; Lietor-Santos, J.-J.

We study the form factor of thermoresponsive microgels based on poly(N-isopropylacrylamide) at high generalized volume fractions, ζ, where the particles must shrink or interpenetrate to fit into the available space. Small-angle neutron scattering with contrast matching techniques is used to determine the particle form factor. We find that the particle size is constant up to a volume fraction roughly between random close packing and space filling. Beyond this point, the particle size decreases with increasing particle concentration; this decrease is found to occur with little interpenetration. Noteworthily, the suspensions remain liquid-like for ζ larger than 1, emphasizing the importance ofmore » particle softness in determining suspension behavior.« less

Learning basic life support (BLS) with tablet PCs in reciprocal learning at school: are videos superior to pictures? A randomized controlled trial.

PubMed

Iserbyt, Peter; Charlier, Nathalie; Mols, Liesbet

2014-06-01

It is often assumed that animations (i.e., videos) will lead to higher learning compared to static media (i.e., pictures) because they provide a more realistic demonstration of the learning task. To investigate whether learning basic life support (BLS) and cardiopulmonary resuscitation (CPR) from video produce higher learning outcomes compared to pictures in reciprocal learning. A randomized controlled trial. A total of 128 students (mean age: 17 years) constituting eight intact classes from a secondary school learned BLS in reciprocal roles of doer and helper with tablet PCs. Student pairs in each class were randomized over a Picture and a Video group. In the Picture group, students learned BLS by means of pictures combined with written instructions. In the Video group, BLS was learned through videos with on-screen instructions. Informational equivalence was assured since instructions in both groups comprised exactly the same words. BLS assessment occurred unannounced, three weeks following intervention. Analysis of variance demonstrated no significant differences in chest compression depths between the Picture group (M=42 mm, 95% CI=40-45) and the Video group (M=39 mm, 95% CI=36-42). In the Picture group significantly higher percentages of chest compressions with correct hand placement were achieved (M=67%, CI=58-77) compared to the Video group (M=53%, CI=43-63), P=.03, η(p)(2)=.03. No other significant differences were found. Results do not support the assumption that videos are superior to pictures for learning BLS and CPR in reciprocal learning. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

E-learning in pediatric basic life support: a randomized controlled non-inferiority study.

PubMed

Krogh, Lise Qvirin; Bjørnshave, Katrine; Vestergaard, Lone Due; Sharma, Maja Bendtsen; Rasmussen, Stinne Eika; Nielsen, Henrik Vendelbo; Thim, Troels; Løfgren, Bo

2015-05-01

Dissemination of pediatric basic life support (PBLS) skills is recommended. E-learning is accessible and cost-effective, but it is currently unknown whether laypersons can learn PBLS through e-learning. The hypothesis of this study was to investigate whether e-learning PBLS is non-inferior to instructor-led training. Participants were recruited among child-minders and parents of children aged 0-6 years. Participants were randomized to either 2-h instructor-led training or e-learning using an e-learning program (duration 17 min) including an inflatable manikin. After training, participants were assessed in a simulated pediatric cardiac arrest scenario. Tests were video recorded and PBLS skills were assessed independently by two assessors blinded to training method. Primary outcome was the pass rate of the PBLS test (≥8 of 15 skills adequately performed) with a pre-specified non-inferiority margin of 20%. In total 160 participants were randomized 1:1. E-learning was non-inferior to instructor-led training (difference in pass rate -4%; 95% CI -9:0.5). Pass rates were 100% among instructor-led trained (n=67) and 96% among e-learned (n=71). E-learners median time spent on the e-learning program was 30 min (range: 15-120 min) and the median number of log-ons was 2 (range: 1-5). After the study, all participants felt that their skills had improved. E-learning PBLS is non-inferior to instructor-led training among child-minders and parents with children aged 0-6 years, although the pass rate was 4% (95% CI -9:0.5) lower with e-learning. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

NASA Astrophysics Data System (ADS)

Zhang, G.

2018-04-01

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation" limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles and could thus determine the saturation density of spheres with high accuracy. In this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides and obtain results that are consistent with previous, extrapolation-based studies.

Precise algorithm to generate random sequential adsorption of hard polygons at saturation.

PubMed

Zhang, G

2018-04-01

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation" limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles and could thus determine the saturation density of spheres with high accuracy. In this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides and obtain results that are consistent with previous, extrapolation-based studies.

Brownian motion on random dynamical landscapes

NASA Astrophysics Data System (ADS)

Suñé Simon, Marc; Sancho, José María; Lindenberg, Katja

2016-03-01

We present a study of overdamped Brownian particles moving on a random landscape of dynamic and deformable obstacles (spatio-temporal disorder). The obstacles move randomly, assemble, and dissociate following their own dynamics. This landscape may account for a soft matter or liquid environment in which large obstacles, such as macromolecules and organelles in the cytoplasm of a living cell, or colloids or polymers in a liquid, move slowly leading to crowding effects. This representation also constitutes a novel approach to the macroscopic dynamics exhibited by active matter media. We present numerical results on the transport and diffusion properties of Brownian particles under this disorder biased by a constant external force. The landscape dynamics are characterized by a Gaussian spatio-temporal correlation, with fixed time and spatial scales, and controlled obstacle concentrations.

Continuous-Time Classical and Quantum Random Walk on Direct Product of Cayley Graphs

NASA Astrophysics Data System (ADS)

Salimi, S.; Jafarizadeh, M. A.

2009-06-01

In this paper we define direct product of graphs and give a recipe for obtaining probability of observing particle on vertices in the continuous-time classical and quantum random walk. In the recipe, the probability of observing particle on direct product of graph is obtained by multiplication of probability on the corresponding to sub-graphs, where this method is useful to determining probability of walk on complicated graphs. Using this method, we calculate the probability of continuous-time classical and quantum random walks on many of finite direct product Cayley graphs (complete cycle, complete Kn, charter and n-cube). Also, we inquire that the classical state the stationary uniform distribution is reached as t → ∞ but for quantum state is not always satisfied.

Motion of Colloidal Particles near Plateau Border in Freely Suspended Soap Film

NASA Astrophysics Data System (ADS)

Pak, Hyuk Kyu; Sur, Jeanman

2000-03-01

We study the motion of colloidal particle near Plateau border in free-standing soap film which is placed perpendicularly to the gravitational direction. When the thickness of soap film is a micron order, two air/water interfacial surfaces of the film can be deformed by the presence of the colloidal particle. When the colloidal particles are in the central area of soap film, they move in random directions. But, as the particles approach near Plateau border, they are accelerated to the border of the film. The travelling distance, before the accelerated particle stops, depends on particle size. We propose a simple model to explain the motion of particle near Plateau border using a surface energy argument and compare the results with experimental measurements.

Active motion assisted by correlated stochastic torques.

PubMed

Weber, Christian; Radtke, Paul K; Schimansky-Geier, Lutz; Hänggi, Peter

2011-07-01

The stochastic dynamics of an active particle undergoing a constant speed and additionally driven by an overall fluctuating torque is investigated. The random torque forces are expressed by a stochastic differential equation for the angular dynamics of the particle determining the orientation of motion. In addition to a constant torque, the particle is supplemented by random torques, which are modeled as an Ornstein-Uhlenbeck process with given correlation time τ(c). These nonvanishing correlations cause a persistence of the particles' trajectories and a change of the effective spatial diffusion coefficient. We discuss the mean square displacement as a function of the correlation time and the noise intensity and detect a nonmonotonic dependence of the effective diffusion coefficient with respect to both correlation time and noise strength. A maximal diffusion behavior is obtained if the correlated angular noise straightens the curved trajectories, interrupted by small pirouettes, whereby the correlated noise amplifies a straightening of the curved trajectories caused by the constant torque.

Kinetic Models for Topological Nearest-Neighbor Interactions

NASA Astrophysics Data System (ADS)

Blanchet, Adrien; Degond, Pierre

2017-12-01

We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

Excitation energies from particle-particle random phase approximation with accurate optimized effective potentials

NASA Astrophysics Data System (ADS)

Jin, Ye; Yang, Yang; Zhang, Du; Peng, Degao; Yang, Weitao

2017-10-01

The optimized effective potential (OEP) that gives accurate Kohn-Sham (KS) orbitals and orbital energies can be obtained from a given reference electron density. These OEP-KS orbitals and orbital energies are used here for calculating electronic excited states with the particle-particle random phase approximation (pp-RPA). Our calculations allow the examination of pp-RPA excitation energies with the exact KS density functional theory (DFT). Various input densities are investigated. Specifically, the excitation energies using the OEP with the electron densities from the coupled-cluster singles and doubles method display the lowest mean absolute error from the reference data for the low-lying excited states. This study probes into the theoretical limit of the pp-RPA excitation energies with the exact KS-DFT orbitals and orbital energies. We believe that higher-order correlation contributions beyond the pp-RPA bare Coulomb kernel are needed in order to achieve even higher accuracy in excitation energy calculations.

Magnetic orientation of nontronite clay in aqueous dispersions and its effect on water diffusion.

PubMed

Abrahamsson, Christoffer; Nordstierna, Lars; Nordin, Matias; Dvinskikh, Sergey V; Nydén, Magnus

2015-01-01

The diffusion rate of water in dilute clay dispersions depends on particle concentration, size, shape, aggregation and water-particle interactions. As nontronite clay particles magnetically align parallel to the magnetic field, directional self-diffusion anisotropy can be created within such dispersion. Here we study water diffusion in exfoliated nontronite clay dispersions by diffusion NMR and time-dependant 1H-NMR-imaging profiles. The dispersion clay concentration was varied between 0.3 and 0.7 vol%. After magnetic alignment of the clay particles in these dispersions a maximum difference of 20% was measured between the parallel and perpendicular self-diffusion coefficients in the dispersion with 0.7 vol% clay. A method was developed to measure water diffusion within the dispersion in the absence of a magnetic field (random clay orientation) as this is not possible with standard diffusion NMR. However, no significant difference in self-diffusion coefficient between random and aligned dispersions could be observed. Copyright © 2014 Elsevier Inc. All rights reserved.

REVIEWS OF TOPICAL PROBLEMS: Transition radiation in media with random inhomogeneities

NASA Astrophysics Data System (ADS)

Platonov, Konstantin Yu; Fleishman, G. D.

2002-03-01

This review analyzes radiation produced by randomly inhomogeneous media excited by fast particles — i.e., polarization bremsstrahlung for thermodynamically equilibrium inhomogeneities or transition radiation for nonthermal ones — taking into account all the effects important for natural sources. Magnetic field effects on both the motion of fast particles and the dispersion of background plasma are considered, and the multiple scattering of fast particles in the medium is examined. Various resonant effects occurring under the conditions of Cherenkov (or cyclotron) emission for a particular eigenmode are discussed. The transition radiation intensity and absorption (amplification) coefficients are calculated for ensembles of fast particles with realistic distributions over momentum and angles. The value of the developed theory of transition radiation is illustrated by applying it to astrophysical objects. Transition radiation is shown to contribute significantly to the radio emission of the Sun, planets (including Earth), and interplanetary and interstellar media. Possible further applications of transition radiation (particularly stimulated) are discussed.

Long-term Results of the UCSF-LBNL Randomized Trial: Charged Particle With Helium Ion Versus Iodine-125 Plaque Therapy for Choroidal and Ciliary Body Melanoma

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

Mishra, Kavita K., E-mail: Kavita.mishra@ucsf.edu; Quivey, Jeanne M.; Daftari, Inder K.

Purpose: Relevant clinical data are needed given the increasing national interest in charged particle radiation therapy (CPT) programs. Here we report long-term outcomes from the only randomized, stratified trial comparing CPT with iodine-125 plaque therapy for choroidal and ciliary body melanoma. Methods and Materials: From 1985 to 1991, 184 patients met eligibility criteria and were randomized to receive particle (86 patients) or plaque therapy (98 patients). Patients were stratified by tumor diameter, thickness, distance to disc/fovea, anterior extension, and visual acuity. Tumors close to the optic disc were included. Local tumor control, as well as eye preservation, metastases due tomore » melanoma, and survival were evaluated. Results: Median follow-up times for particle and plaque arm patients were 14.6 years and 12.3 years, respectively (P=.22), and for those alive at last follow-up, 18.5 and 16.5 years, respectively (P=.81). Local control (LC) for particle versus plaque treatment was 100% versus 84% at 5 years, and 98% versus 79% at 12 years, respectively (log rank: P=.0006). If patients with tumors close to the disc (<2 mm) were excluded, CPT still resulted in significantly improved LC: 100% versus 90% at 5 years and 98% versus 86% at 12 years, respectively (log rank: P=.048). Enucleation rate was lower after CPT: 11% versus 22% at 5 years and 17% versus 37% at 12 years, respectively (log rank: P=.01). Using Cox regression model, likelihood ratio test, treatment was the most important predictor of LC (P=.0002) and eye preservation (P=.01). CPT was a significant predictor of prolonged disease-free survival (log rank: P=.001). Conclusions: Particle therapy resulted in significantly improved local control, eye preservation, and disease-free survival as confirmed by long-term outcomes from the only randomized study available to date comparing radiation modalities in choroidal and ciliary body melanoma.« less

Does peer learning or higher levels of e-learning improve learning abilities? A randomized controlled trial

PubMed Central

Worm, Bjarne Skjødt; Jensen, Kenneth

2013-01-01

Background and aims The fast development of e-learning and social forums demands us to update our understanding of e-learning and peer learning. We aimed to investigate if higher, pre-defined levels of e-learning or social interaction in web forums improved students’ learning ability. Methods One hundred and twenty Danish medical students were randomized to six groups all with 20 students (eCases level 1, eCases level 2, eCases level 2+, eTextbook level 1, eTextbook level 2, and eTextbook level 2+). All students participated in a pre-test, Group 1 participated in an interactive case-based e-learning program, while Group 2 was presented with textbook material electronically. The 2+ groups were able to discuss the material between themselves in a web forum. The subject was head injury and associated treatment and observation guidelines in the emergency room. Following the e-learning, all students completed a post-test. Pre- and post-tests both consisted of 25 questions randomly chosen from a pool of 50 different questions. Results All students concluded the study with comparable pre-test results. Students at Level 2 (in both groups) improved statistically significant compared to students at level 1 (p>0.05). There was no statistically significant difference between level 2 and level 2+. However, level 2+ was associated with statistically significant greater student's satisfaction than the rest of the students (p>0.05). Conclusions This study applies a new way of comparing different types of e-learning using a pre-defined level division and the possibility of peer learning. Our findings show that higher levels of e-learning does in fact provide better results when compared with the same type of e-learning at lower levels. While social interaction in web forums increase student satisfaction, learning ability does not seem to change. Both findings are relevant when designing new e-learning materials. PMID:24229729

Does peer learning or higher levels of e-learning improve learning abilities? A randomized controlled trial.

PubMed

Worm, Bjarne Skjødt; Jensen, Kenneth

2013-01-01

Background and aims The fast development of e-learning and social forums demands us to update our understanding of e-learning and peer learning. We aimed to investigate if higher, pre-defined levels of e-learning or social interaction in web forums improved students' learning ability. Methods One hundred and twenty Danish medical students were randomized to six groups all with 20 students (eCases level 1, eCases level 2, eCases level 2+, eTextbook level 1, eTextbook level 2, and eTextbook level 2+). All students participated in a pre-test, Group 1 participated in an interactive case-based e-learning program, while Group 2 was presented with textbook material electronically. The 2+ groups were able to discuss the material between themselves in a web forum. The subject was head injury and associated treatment and observation guidelines in the emergency room. Following the e-learning, all students completed a post-test. Pre- and post-tests both consisted of 25 questions randomly chosen from a pool of 50 different questions. Results All students concluded the study with comparable pre-test results. Students at Level 2 (in both groups) improved statistically significant compared to students at level 1 (p>0.05). There was no statistically significant difference between level 2 and level 2+. However, level 2+ was associated with statistically significant greater student's satisfaction than the rest of the students (p>0.05). Conclusions This study applies a new way of comparing different types of e-learning using a pre-defined level division and the possibility of peer learning. Our findings show that higher levels of e-learning does in fact provide better results when compared with the same type of e-learning at lower levels. While social interaction in web forums increase student satisfaction, learning ability does not seem to change. Both findings are relevant when designing new e-learning materials.

Probability machines: consistent probability estimation using nonparametric learning machines.

PubMed

Malley, J D; Kruppa, J; Dasgupta, A; Malley, K G; Ziegler, A

2012-01-01

Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications.

The design of instructional tools affects secondary school students' learning of cardiopulmonary resuscitation (CPR) in reciprocal peer learning: a randomized controlled trial.

PubMed

Iserbyt, Peter; Byra, Mark

2013-11-01

Research investigating design effects of instructional tools for learning Basic Life Support (BLS) is almost non-existent. To demonstrate the design of instructional tools matter. The effect of spatial contiguity, a design principle stating that people learn more deeply when words and corresponding pictures are placed close (i.e., integrated) rather than far from each other on a page was investigated on task cards for learning Cardiopulmonary Resuscitation (CPR) during reciprocal peer learning. A randomized controlled trial. A total of 111 students (mean age: 13 years) constituting six intact classes learned BLS through reciprocal learning with task cards. Task cards combine a picture of the skill with written instructions about how to perform it. In each class, students were randomly assigned to the experimental group or the control. In the control, written instructions were placed under the picture on the task cards. In the experimental group, written instructions were placed close to the corresponding part of the picture on the task cards reflecting application of the spatial contiguity principle. One-way analysis of variance found significantly better performances in the experimental group for ventilation volumes (P=.03, ηp2=.10) and flow rates (P=.02, ηp2=.10). For chest compression depth, compression frequency, compressions with correct hand placement, and duty cycles no significant differences were found. This study shows that the design of instructional tools (i.e., task cards) affects student learning. Research-based design of learning tools can enhance BLS and CPR education. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Effects of Situated Learning on Students' Knowledge Acquisition: An Individual Differences Perspective

ERIC Educational Resources Information Center

Zheng, Robert

2010-01-01

This study focuses on the effects of situated learning on students' knowledge acquisition by investigating the influence of individual differences in such learning. Seventy-nine graduates were recruited from an educational department and were assigned to situated learning and traditional learning based on a randomized block design. Results…

Non-random distribution of DNA double-strand breaks induced by particle irradiation

NASA Technical Reports Server (NTRS)

Lobrich, M.; Cooper, P. K.; Rydberg, B.; Chatterjee, A. (Principal Investigator)

1996-01-01

Induction of DNA double-strand breaks (dsbs) in mammalian cells is dependent on the spatial distribution of energy deposition from the ionizing radiation. For high LET particle radiations the primary ionization sites occur in a correlated manner along the track of the particles, while for X-rays these sites are much more randomly distributed throughout the volume of the cell. It can therefore be expected that the distribution of dsbs linearly along the DNA molecule also varies with the type of radiation and the ionization density. Using pulsed-field gel and conventional gel techniques, we measured the size distribution of DNA molecules from irradiated human fibroblasts in the total range of 0.1 kbp-10 Mbp for X-rays and high LET particles (N ions, 97 keV/microns and Fe ions, 150 keV/microns). On a mega base pair scale we applied conventional pulsed-field gel electrophoresis techniques such as measurement of the fraction of DNA released from the well (FAR) and measurement of breakage within a specific NotI restriction fragment (hybridization assay). The induction rate for widely spaced breaks was found to decrease with LET. However, when the entire distribution of radiation-induced fragments was analysed, we detected an excess of fragments with sizes below about 200 kbp for the particles compared with X-irradiation. X-rays are thus more effective than high LET radiations in producing large DNA fragments but less effective in the production of smaller fragments. We determined the total induction rate of dsbs for the three radiations based on a quantitative analysis of all the measured radiation-induced fragments and found that the high LET particles were more efficient than X-rays at inducing dsbs, indicating an increasing total efficiency with LET. Conventional assays that are based only on the measurement of large fragments are therefore misleading when determining total dsb induction rates of high LET particles. The possible biological significance of this non-randomness for dsb induction is discussed.

Anomalous dispersion in correlated porous media: a coupled continuous time random walk approach

NASA Astrophysics Data System (ADS)

Comolli, Alessandro; Dentz, Marco

2017-09-01

We study the causes of anomalous dispersion in Darcy-scale porous media characterized by spatially heterogeneous hydraulic properties. Spatial variability in hydraulic conductivity leads to spatial variability in the flow properties through Darcy's law and thus impacts on solute and particle transport. We consider purely advective transport in heterogeneity scenarios characterized by broad distributions of heterogeneity length scales and point values. Particle transport is characterized in terms of the stochastic properties of equidistantly sampled Lagrangian velocities, which are determined by the flow and conductivity statistics. The persistence length scales of flow and transport velocities are imprinted in the spatial disorder and reflect the distribution of heterogeneity length scales. Particle transitions over the velocity length scales are kinematically coupled with the transition time through velocity. We show that the average particle motion follows a coupled continuous time random walk (CTRW), which is fully parameterized by the distribution of flow velocities and the medium geometry in terms of the heterogeneity length scales. The coupled CTRW provides a systematic framework for the investigation of the origins of anomalous dispersion in terms of heterogeneity correlation and the distribution of conductivity point values. We derive analytical expressions for the asymptotic scaling of the moments of the spatial particle distribution and first arrival time distribution (FATD), and perform numerical particle tracking simulations of the coupled CTRW to capture the full average transport behavior. Broad distributions of heterogeneity point values and lengths scales may lead to very similar dispersion behaviors in terms of the spatial variance. Their mechanisms, however are very different, which manifests in the distributions of particle positions and arrival times, which plays a central role for the prediction of the fate of dissolved substances in heterogeneous natural and engineered porous materials. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Regular oscillations and random motion of glass microspheres levitated by a single optical beam in air

DOE PAGES

Moore, Jeremy; Martin, Leopoldo L.; Maayani, Shai; ...

2016-02-03

We experimentally reporton optical binding of many glass particles in air that levitate in a single optical beam. A diversity of particle sizes and shapes interact at long range in a single Gaussian beam. Our system dynamics span from oscillatory to random and dimensionality ranges from 1 to 3D. In conclusion, the low loss for the center of mass motion of the beads could allow this system to serve as a standard many body testbed, similar to what is done today with atoms, but at the mesoscopic scale.

Reproduction of exact solutions of Lipkin model by nonlinear higher random-phase approximation

NASA Astrophysics Data System (ADS)

Terasaki, J.; Smetana, A.; Šimkovic, F.; Krivoruchenko, M. I.

2017-10-01

It is shown that the random-phase approximation (RPA) method with its nonlinear higher generalization, which was previously considered as approximation except for a very limited case, reproduces the exact solutions of the Lipkin model. The nonlinear higher RPA is based on an equation nonlinear on eigenvectors and includes many-particle-many-hole components in the creation operator of the excited states. We demonstrate the exact character of solutions analytically for the particle number N = 2 and numerically for N = 8. This finding indicates that the nonlinear higher RPA is equivalent to the exact Schrödinger equation.

Rare Event Simulation in Radiation Transport

NASA Astrophysics Data System (ADS)

Kollman, Craig

This dissertation studies methods for estimating extremely small probabilities by Monte Carlo simulation. Problems in radiation transport typically involve estimating very rare events or the expected value of a random variable which is with overwhelming probability equal to zero. These problems often have high dimensional state spaces and irregular geometries so that analytic solutions are not possible. Monte Carlo simulation must be used to estimate the radiation dosage being transported to a particular location. If the area is well shielded the probability of any one particular particle getting through is very small. Because of the large number of particles involved, even a tiny fraction penetrating the shield may represent an unacceptable level of radiation. It therefore becomes critical to be able to accurately estimate this extremely small probability. Importance sampling is a well known technique for improving the efficiency of rare event calculations. Here, a new set of probabilities is used in the simulation runs. The results are multiplied by the likelihood ratio between the true and simulated probabilities so as to keep our estimator unbiased. The variance of the resulting estimator is very sensitive to which new set of transition probabilities are chosen. It is shown that a zero variance estimator does exist, but that its computation requires exact knowledge of the solution. A simple random walk with an associated killing model for the scatter of neutrons is introduced. Large deviation results for optimal importance sampling in random walks are extended to the case where killing is present. An adaptive "learning" algorithm for implementing importance sampling is given for more general Markov chain models of neutron scatter. For finite state spaces this algorithm is shown to give, with probability one, a sequence of estimates converging exponentially fast to the true solution. In the final chapter, an attempt to generalize this algorithm to a continuous state space is made. This involves partitioning the space into a finite number of cells. There is a tradeoff between additional computation per iteration and variance reduction per iteration that arises in determining the optimal grid size. All versions of this algorithm can be thought of as a compromise between deterministic and Monte Carlo methods, capturing advantages of both techniques.

Packing Fraction of a Two-dimensional Eden Model with Random-Sized Particles

NASA Astrophysics Data System (ADS)

Kobayashi, Naoki; Yamazaki, Hiroshi

2018-01-01

We have performed a numerical simulation of a two-dimensional Eden model with random-size particles. In the present model, the particle radii are generated from a Gaussian distribution with mean μ and standard deviation σ. First, we have examined the bulk packing fraction for the Eden cluster and investigated the effects of the standard deviation and the total number of particles NT. We show that the bulk packing fraction depends on the number of particles and the standard deviation. In particular, for the dependence on the standard deviation, we have determined the asymptotic value of the bulk packing fraction in the limit of the dimensionless standard deviation. This value is larger than the packing fraction obtained in a previous study of the Eden model with uniform-size particles. Secondly, we have investigated the packing fraction of the entire Eden cluster including the effect of the interface fluctuation. We find that the entire packing fraction depends on the number of particles while it is independent of the standard deviation, in contrast to the bulk packing fraction. In a similar way to the bulk packing fraction, we have obtained the asymptotic value of the entire packing fraction in the limit NT → ∞. The obtained value of the entire packing fraction is smaller than that of the bulk value. This fact suggests that the interface fluctuation of the Eden cluster influences the packing fraction.

Wave-particle interaction in the Faraday waves.

PubMed

Francois, N; Xia, H; Punzmann, H; Shats, M

2015-10-01

Wave motion in disordered Faraday waves is analysed in terms of oscillons or quasi-particles. The motion of these oscillons is measured using particle tracking tools and it is compared with the motion of fluid particles on the water surface. Both the real floating particles and the oscillons, representing the collective fluid motion, show Brownian-type dispersion exhibiting ballistic and diffusive mean squared displacement at short and long times, respectively. While the floating particles motion has been previously explained in the context of two-dimensional turbulence driven by Faraday waves, no theoretical description exists for the random walk type motion of oscillons. It is found that the r.m.s velocity ⟨μ̃(osc)⟩(rms) of oscillons is directly related to the turbulent r.m.s. velocity ⟨μ̃⟩(rms) of the fluid particles in a broad range of vertical accelerations. The measured ⟨μ̃(osc)⟩(rms) accurately explains the broadening of the frequency spectra of the surface elevation observed in disordered Faraday waves. These results suggest that 2D turbulence is the driving force behind both the randomization of the oscillons motion and the resulting broadening of the wave frequency spectra. The coupling between wave motion and hydrodynamic turbulence demonstrated here offers new perspectives for predicting complex fluid transport from the knowledge of wave field spectra and vice versa.

Random Feedback Makes Listeners Tone-Deaf.

PubMed

Vuvan, Dominique T; Zendel, Benjamin Rich; Peretz, Isabelle

2018-05-08

The mental representation of pitch structure (tonal knowledge) is a core component of musical experience and is learned implicitly through exposure to music. One theory of congenital amusia (tone deafness) posits that conscious access to tonal knowledge is disrupted, leading to a severe deficit of music cognition. We tested this idea by providing random performance feedback to neurotypical listeners while they listened to melodies for tonal incongruities and had their electrical brain activity monitored. The introduction of random feedback was associated with a reduction of accuracy and confidence, and a suppression of the late positive brain response usually elicited by conscious detection of a tonal violation. These effects mirror the behavioural and neurophysiological profile of amusia. In contrast, random feedback was associated with an increase in the amplitude of the early right anterior negativity, possibly due to heightened attention to the experimental task. This successful simulation of amusia in a normal brain highlights the key role of feedback in learning, and thereby provides a new avenue for the rehabilitation of learning disorders.

The distribution of cotransformed transgenes in particle bombardment-mediated transformed wheat

USDA-ARS?s Scientific Manuscript database

Although particle bombardment is the predominant method of foreign DNA direct transfer, whether transgene is integrated randomly into the genome has not been determined. In this study, we identified the distribution of transgene loci in 45 transgenic wheat (Triticum aestivum L.) lines containing c...

Microstructure Evolution and Composition Control during the Processing of Thin-gage Metallic Foil (Preprint)

DTIC Science & Technology

2012-02-01

the presence of somewhat randomly-distributed carbides and borides (white particles in BSE images), this grain size was comparable to that observed...pinned by carbide/ boride particles (imaging white in Figure 8c). The very fine gamma-prime precipitates likely produced during magnetron sputtering...sputtered material. First, the carbide/ boride particles were nucleated and hence located preferentially at the grain boundaries in the sputtered

Radiation dosimetry using three-dimensional optical random access memories

NASA Technical Reports Server (NTRS)

Moscovitch, M.; Phillips, G. W.

2001-01-01

Three-dimensional optical random access memories (3D ORAMs) are a new generation of high-density data storage devices. Binary information is stored and retrieved via a light induced reversible transformation of an ensemble of bistable photochromic molecules embedded in a polymer matrix. This paper describes the application of 3D ORAM materials to radiation dosimetry. It is shown both theoretically and experimentally, that ionizing radiation in the form of heavy charged particles is capable of changing the information originally stored on the ORAM material. The magnitude and spatial distribution of these changes are used as a measure of the absorbed dose, particle type and energy. The effects of exposure on 3D ORAM materials have been investigated for a variety of particle types and energies, including protons, alpha particles and 12C ions. The exposed materials are observed to fluoresce when exposed to laser light. The intensity and the depth of the fluorescence is dependent on the type and energy of the particle to which the materials were exposed. It is shown that these effects can be modeled using Monte Carlo calculations. The model provides a better understanding of the properties of these materials. which should prove useful for developing systems for charged particle and neutron dosimetry/detector applications. c2001 Published by Elsevier Science B.V.

Modeling and Compensation of Random Drift of MEMS Gyroscopes Based on Least Squares Support Vector Machine Optimized by Chaotic Particle Swarm Optimization.

PubMed

Xing, Haifeng; Hou, Bo; Lin, Zhihui; Guo, Meifeng

2017-10-13

MEMS (Micro Electro Mechanical System) gyroscopes have been widely applied to various fields, but MEMS gyroscope random drift has nonlinear and non-stationary characteristics. It has attracted much attention to model and compensate the random drift because it can improve the precision of inertial devices. This paper has proposed to use wavelet filtering to reduce noise in the original data of MEMS gyroscopes, then reconstruct the random drift data with PSR (phase space reconstruction), and establish the model for the reconstructed data by LSSVM (least squares support vector machine), of which the parameters were optimized using CPSO (chaotic particle swarm optimization). Comparing the effect of modeling the MEMS gyroscope random drift with BP-ANN (back propagation artificial neural network) and the proposed method, the results showed that the latter had a better prediction accuracy. Using the compensation of three groups of MEMS gyroscope random drift data, the standard deviation of three groups of experimental data dropped from 0.00354°/s, 0.00412°/s, and 0.00328°/s to 0.00065°/s, 0.00072°/s and 0.00061°/s, respectively, which demonstrated that the proposed method can reduce the influence of MEMS gyroscope random drift and verified the effectiveness of this method for modeling MEMS gyroscope random drift.

Fraction Intervention for Students With Mathematics Difficulties: Lessons Learned From Five Randomized Controlled Trials.

PubMed

Fuchs, Lynn S; Malone, Amelia S; Schumacher, Robin F; Namkung, Jessica; Wang, Amber

In this article, the authors summarize results from 5 randomized controlled trials assessing the effects of intervention to improve the fraction performance of fourth-grade students at risk for difficulty in learning about fractions. The authors begin by explaining the importance of competence with fractions and why an instructional focus on fractions magnitude understanding may improve learning. They then describe an intervention that relies strongly on this type of understanding about fractions instruction, and they provide an overview of the intervention's overall effects. This is followed by an overview of 5 intervention components for which the authors isolated effects. They conclude by discussing some of the lessons learned from this research program.

Imbalanced Learning for Functional State Assessment

NASA Technical Reports Server (NTRS)

Li, Feng; McKenzie, Frederick; Li, Jiang; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

2011-01-01

This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classes and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random undersampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving lest dataset show thai accuracies for minority classes could be improved dramatically with a cost of slight performance degradations for majority classes,

An Evaluation of the Particle Physics Masterclass as a Context for Student Learning about the Nature of Science

ERIC Educational Resources Information Center

Wadness, Michael J.

2010-01-01

This dissertation addresses the research question: To what extent do secondary school science students attending the U.S. Particle Physics Masterclass change their view of the nature of science (NOS)? The U.S. Particle Physics Masterclass is a physics outreach program run by QuarkNet, a national organization of secondary school physics teachers…

Effect of Methods of Learning and Self Regulated Learning toward Outcomes of Learning Social Studies

ERIC Educational Resources Information Center

Tjalla, Awaluddin; Sofiah, Evi

2015-01-01

This research aims to reveal the influence of learning methods and self-regulated learning on students learning scores for Social Studies object. The research was done in Islamic Junior High School (MTs Manba'ul Ulum), Batuceper City Tangerang using quasi-experimental method. The research employed simple random technique to 28 students. Data were…

Effect of Demographic Factors on E-Learning Effectiveness in a Higher Learning Institution in Malaysia

ERIC Educational Resources Information Center

Islam, Md. Aminul; Rahim, Noor Asliza Abdul; Liang, Tan Chee; Momtaz, Hasina

2011-01-01

This research attempted to find out the effect of demographic factors on the effectiveness of the e-learning system in a higher learning Institution. The students from this institution were randomly selected in order to evaluate the effectiveness of learning system in student's learning process. The primary data source is the questionnaires that…

The (kinetic) theory of active particles applied to learning dynamics. Comment on "Collective learning modeling based on the kinetic theory of active particles" by D. Burini et al.

NASA Astrophysics Data System (ADS)

Nieto, J.

2016-03-01

The learning phenomena, their complexity, concepts, structure, suitable theories and models, have been extensively treated in the mathematical literature in the last century, and [4] contains a very good introduction to the literature describing the many approaches and lines of research developed about them. Two main schools have to be pointed out [5] in order to understand the two -not exclusive- kinds of existing models: the stimulus sampling models and the stochastic learning models. Also [6] should be mentioned as a survey where two methods of learning are pointed out, the cognitive and the social, and where the knowledge looks like a mathematical unknown. Finally, as the authors do, we refer to the works [9,10], where the concept of population thinking was introduced and which motivate the game theory rules as a tool (both included in [4] to develop their theory) and [7], where the ideas of developing a mathematical kinetic theory of perception and learning were proposed.

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

PubMed Central

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition.

PubMed

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-06-13

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).

Transverse eV Ion Heating by Random Electric Field Fluctuations in the Plasmasphere

NASA Technical Reports Server (NTRS)

Artemyev, A. V.; Mourenas, D.; Agapitov, O. V.; Blum, L.

2017-01-01

Charged particle acceleration in the Earth inner magnetosphere is believed to be mainly due to the local resonant wave-particle interaction or particle transport processes. However, the Van Allen Probes have recently provided interesting evidence of a relatively slow transverse heating of eV ions at distances about 2-3 Earth radii during quiet times. Waves that are able to resonantly interact with such very cold ions are generally rare in this region of space, called the plasmasphere. Thus, non-resonant wave-particle interactions are expected to play an important role in the observed ion heating. We demonstrate that stochastic heating by random transverse electric field fluctuations of whistler (and possibly electromagnetic ion cyclotron) waves could explain this weak and slow transverse heating of H+ and O+ ions in the inner magnetosphere. The essential element of the proposed model of ion heating is the presence of trains of random whistler (hiss) wave packets, with significant amplitude modulations produced by strong wave damping, rapid wave growth, or a superposition of wave packets of different frequencies, phases, and amplitudes. Such characteristics correspond to measured characteristics of hiss waves in this region. Using test particle simulations with typical wave and plasma parameters, we demonstrate that the corresponding stochastic transverse ion heating reaches 0.07-0.2 eV/h for protons and 0.007-0.015 eV/h for O+ ions. This global temperature increase of the Maxwellian ion population from an initial Ti approx. 0.3 eV could potentially explain the observations.

New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

Treesearch

L.R. Iverson; A.M. Prasad; A. Liaw

2004-01-01

More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

Effect of Peer-Led Team Learning (PLTL) on Student Achievement, Attitude, and Self-Concept in College General Chemistry in Randomized and Quasi Experimental Designs

ERIC Educational Resources Information Center

Chan, Julia Y. K.; Bauer, Christopher F.

2015-01-01

This study investigated exam achievement and affective characteristics of students in general chemistry in a fully-randomized experimental design, contrasting Peer-Led Team Learning (PLTL) participation with a control group balanced for time-on-task and study activity. This study population included two independent first-semester courses with…

An Evaluation of the Implementation of Hand Held Health Records with Adults with Learning Disabilities: A Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Turk, Vicky; Burchell, Sarah; Burrha, Sukhjinder; Corney, Roslyn; Elliott, Sandra; Kerry, Sally; Molloy, Catherine; Painter, Kerry

2010-01-01

Background: Personal health records were implemented with adults with learning disabilities (AWLD) to try to improve their health-care. Materials and Method: Forty GP practices were randomized to the Personal Health Profile (PHP) implementation or control group. Two hundred and one AWLD were interviewed at baseline and 163 followed up after 12…

Preschool Teachers Can Use a PBS KIDS Transmedia Curriculum Supplement to Support Young Children's Mathematics Learning: Results of a Randomized Controlled Trial

ERIC Educational Resources Information Center

Llorente, Carlin; Pasnik, Shelley; Moorthy, Savitha; Hupert, Naomi; Rosenfeld, Deborah; Gerard, Sarah

2015-01-01

The current study, a randomized controlled trial, explores how technology and educational transmedia resources can enhance prekindergarten math teaching and learning in preschools, especially those serving children who may be at risk for academic difficulties due to economic and social disadvantages. This research is part of a multi-year summative…

Random fiber laser.

PubMed

de Matos, Christiano J S; de S Menezes, Leonardo; Brito-Silva, Antônio M; Martinez Gámez, M A; Gomes, Anderson S L; de Araújo, Cid B

2007-10-12

We investigate the effects of two-dimensional confinement on the lasing properties of a classical random laser system operating in the incoherent feedback (diffusive) regime. A suspension of 250 nm rutile (TiO2) particles in a rhodamine 6G solution was inserted into the hollow core of a photonic crystal fiber generating the first random fiber laser and a novel quasi-one-dimensional random laser geometry. A comparison with similar systems in bulk format shows that the random fiber laser presents an efficiency that is at least 2 orders of magnitude higher.

Development of a software framework for data assimilation and its applications for streamflow forecasting in Japan

NASA Astrophysics Data System (ADS)

Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.

2012-04-01

Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.

A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks.

PubMed

Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias

2008-12-01

We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest.

Threat captures attention but does not affect learning of contextual regularities.

PubMed

Yamaguchi, Motonori; Harwood, Sarah L

2017-04-01

Some of the stimulus features that guide visual attention are abstract properties of objects such as potential threat to one's survival, whereas others are complex configurations such as visual contexts that are learned through past experiences. The present study investigated the two functions that guide visual attention, threat detection and learning of contextual regularities, in visual search. Search arrays contained images of threat and non-threat objects, and their locations were fixed on some trials but random on other trials. Although they were irrelevant to the visual search task, threat objects facilitated attention capture and impaired attention disengagement. Search time improved for fixed configurations more than for random configurations, reflecting learning of visual contexts. Nevertheless, threat detection had little influence on learning of the contextual regularities. The results suggest that factors guiding visual attention are different from factors that influence learning to guide visual attention.

Comparison of Learning Styles of Pharmacy Students and Faculty Members

PubMed Central

Crawford, Stephanie Y.; Alhreish, Suhail K.

2012-01-01

Objectives. To compare dominant learning styles of pharmacy students and faculty members and between faculty members in different tracks. Methods. Gregorc Style Delineator (GSD) and Zubin’s Pharmacists’ Inventory of Learning Styles (PILS) were administered to students and faculty members at an urban, Midwestern college of pharmacy. Results. Based on responses from 299 students (classes of 2008, 2009, and 2010) and 59 faculty members, GSD styles were concrete sequential (48%), abstract sequential (18%), abstract random (13%), concrete random (13%), and multimodal (8%). With PILS, dominant styles were assimilator (47%) and converger (30%). There were no significant differences between faculty members and student learning styles nor across pharmacy student class years (p>0.05). Learning styles differed between men and women across both instruments (p<0.01), and between faculty members in tenure and clinical tracks for the GSD styles (p=0.01). Conclusion. Learning styles differed among respondents based on gender and faculty track. PMID:23275657

Nonstandard convergence to jamming in random sequential adsorption: The case of patterned one-dimensional substrates

NASA Astrophysics Data System (ADS)

Verma, Arjun; Privman, Vladimir

2018-02-01

We study approach to the large-time jammed state of the deposited particles in the model of random sequential adsorption. The convergence laws are usually derived from the argument of Pomeau which includes the assumption of the dominance, at large enough times, of small landing regions into each of which only a single particle can be deposited without overlapping earlier deposited particles and which, after a certain time are no longer created by depositions in larger gaps. The second assumption has been that the size distribution of gaps open for particle-center landing in this large-time small-gaps regime is finite in the limit of zero gap size. We report numerical Monte Carlo studies of a recently introduced model of random sequential adsorption on patterned one-dimensional substrates that suggest that the second assumption must be generalized. We argue that a region exists in the parameter space of the studied model in which the gap-size distribution in the Pomeau large-time regime actually linearly vanishes at zero gap sizes. In another region, the distribution develops a threshold property, i.e., there are no small gaps below a certain gap size. We discuss the implications of these findings for new asymptotic power-law and exponential-modified-by-a-power-law convergences to jamming in irreversible one-dimensional deposition.

Local synaptic signaling enhances the stochastic transport of motor-driven cargo in neurons

NASA Astrophysics Data System (ADS)

Newby, Jay; Bressloff, Paul C.

2010-09-01

The tug-of-war model of motor-driven cargo transport is formulated as an intermittent trapping process. An immobile trap, representing the cellular machinery that sequesters a motor-driven cargo for eventual use, is located somewhere within a microtubule track. A particle representing a motor-driven cargo that moves randomly with a forward bias is introduced at the beginning of the track. The particle switches randomly between a fast moving phase and a slow moving phase. When in the slow moving phase, the particle can be captured by the trap. To account for the possibility that the particle avoids the trap, an absorbing boundary is placed at the end of the track. Two local signaling mechanisms—intended to improve the chances of capturing the target—are considered by allowing the trap to affect the tug-of-war parameters within a small region around itself. The first is based on a localized adenosine triphosphate (ATP) concentration gradient surrounding a synapse, and the second is based on a concentration of tau—a microtubule-associated protein involved in Alzheimer's disease—coating the microtubule near the synapse. It is shown that both mechanisms can lead to dramatic improvements in the capture probability, with a minimal increase in the mean capture time. The analysis also shows that tau can cause a cargo to undergo random oscillations, which could explain some experimental observations.

Parallelization of a Monte Carlo particle transport simulation code

NASA Astrophysics Data System (ADS)

Hadjidoukas, P.; Bousis, C.; Emfietzoglou, D.

2010-05-01

We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.

Defect reduction for semiconductor memory applications using jet and flash imprint lithography

NASA Astrophysics Data System (ADS)

Ye, Zhengmao; Luo, Kang; Lu, Xiaoming; Fletcher, Brian; Liu, Weijun; Xu, Frank; LaBrake, Dwayne; Resnick, Douglas J.; Sreenivasan, S. V.

2012-07-01

Acceptance of imprint lithography for manufacturing will require demonstration that it can attain defect levels commensurate with the defect specifications of high-end memory devices. Defects occurring during imprinting can generally be broken into two categories; random defects and repeating defects. Examples of random defects include fluid phase imprint defects, such as bubbles, and solid phase imprint defects, such as line collapse. Examples of repeater defects include mask fabrication defects and particle induced defects. Previous studies indicated that soft particles cause nonrepeating defects. Hard particles, on the other hand, can cause either permanent resist plugging or mask damage. In a previous study, two specific defect types were examined; random nonfill defects occurring during the resist filling process and repeater defects caused by interactions with particles on the substrate. We attempted to identify the different types of imprint defect types using a mask with line/space patterns at dimensions as small as 26 nm. An Imprio 500 twenty-wafer per hour development tool was used to study the various defect types. The imprint defect density was reduced nearly four orders of magnitude, down to ˜4/cm2 in a period of two years following the availability of low defect imprint masks at 26-nm half-pitch. This reduction was achieved by identifying the root cause of various defects and then taking the appropriate corrective action.

Tabletop Traffic Jams: Modeling Traffic Jams using Self Propelled Particles

NASA Astrophysics Data System (ADS)

Yadav, Vikrant; Kudrolli, Arshad

2015-03-01

We model behavior of traffic using Self Propelled Particles (SPPs). Granular rods with asymmetric mass distribution confined to move in a circular channel on a vibrated substrate and interact with each other through inelastic collision serve as our model vehicle. Motion of a single vehicle is observed to be composed of 2 parts, a linear velocity in the direction of lighter end of particle and a non-Gaussian random velocity. We find that the collective mean speed of the SPPs is constant over a wide range of line densities before decreasing rapidly as the maximum packing is approached indicating the spontaneous formation of Phantom jams. This decrease in speed is observed to be far greater than any small differences in the mean drift speed of individual SPPs , and occurs as the collision frequency between SPPs increase exponentially with line density. However the random velocity component of SPPs remain super-diffusive over entire range of line densities. While the collective motion at low densities is characterized by caravan following behind the slowest particle leading to clustering, at higher densities we see formation of jamming waves travelling in direction opposite to that of motion of particles.

Negative Particles and Morphemes in Jordanian Arabic Dialects

ERIC Educational Resources Information Center

Mrayat, Ahmad

2015-01-01

This paper aims at investigating the negative particles and morphemes in three main Jordanian dialects (Urban, Rural and Bedouin). This quantitative and qualitative study includes 30 teachers from different disciplines who use these dialects. The sample of the study was selected randomly. The research used two research instruments, a checklist and…

Investigations of turbulent motions and particle acceleration in solar flares

NASA Technical Reports Server (NTRS)

Jakimiec, J.; Fludra, A.; Lemen, J. R.; Dennis, B. R.; Sylwester, J.

1986-01-01

Investigations of X-raya spectra of solar flares show that intense random (turbulent) motions are present in hot flare plasma. Here it is argued that the turbulent motions are of great importance for flare development. They can efficiently enhance flare energy release and accelerate particles to high energies.

Linear kinetic theory and particle transport in stochastic mixtures

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

Pomraning, G.C.

We consider the formulation of linear transport and kinetic theory describing energy and particle flow in a random mixture of two or more immiscible materials. Following an introduction, we summarize early and fundamental work in this area, and we conclude with a brief discussion of recent results.

Investigations of Students' Motivation Towards Learning Secondary School Physics through Mastery Learning Approach

ERIC Educational Resources Information Center

Changeiywo, Johnson M.; Wambugu, P. W.; Wachanga, S. W.

2011-01-01

Teaching method is a major factor that affects students' motivation to learn physics. This study investigated the effects of using mastery learning approach (MLA) on secondary school students' motivation to learn physics. Solomon four non-equivalent control group design under the quasi-experimental research method was used in which a random sample…

The Temporal and Dynamic Nature of Self-Regulatory Processes during Independent and Externally Assisted Hypermedia Learning

ERIC Educational Resources Information Center

Johnson, Amy M.; Azevedo, Roger; D'Mello, Sidney K.

2011-01-01

This study examined the temporal and dynamic nature of students' self-regulatory processes while learning about the circulatory system with hypermedia. A total of 74 undergraduate students were randomly assigned to 1 of 2 conditions: independent learning or externally assisted learning. Participants in the independent learning condition used a…

Why Is Externally-Facilitated Regulated Learning More Effective than Self-Regulated Learning with Hypermedia?

ERIC Educational Resources Information Center

Azevedo, Roger; Moos, Daniel C.; Greene, Jeffrey A.; Winters, Fielding I.; Cromley, Jennifer G.

2008-01-01

We examined how self-regulated learning (SRL) and externally-facilitated self-regulated learning (ERL) differentially affected adolescents' learning about the circulatory system while using hypermedia. A total of 128 middle-school and high school students with little prior knowledge of the topic were randomly assigned to either the SRL or ERL…

Using Learning Decomposition and Bootstrapping with Randomization to Compare the Impact of Different Educational Interventions on Learning

ERIC Educational Resources Information Center

Feng, Mingyu; Beck, Joseph E.; Heffernan, Neil T.

2009-01-01

A basic question of instructional interventions is how effective it is in promoting student learning. This paper presents a study to determine the relative efficacy of different instructional strategies by applying an educational data mining technique, learning decomposition. We use logistic regression to determine how much learning is caused by…

Dusty gas influences on transport in turbulent erosive propellant flow

NASA Astrophysics Data System (ADS)

Buckingham, A. C.

1980-01-01

A theoretical-numerical model is introduced which relates the influences of particles on erosive transport in a turbulent reactive boundary layer. Specifically, this discussion concerns additive particles used to suppress wall erosion in gun barrel turbulent propellant combustion. The turbulent-particle interactions are modeled with random particulate motion computations. These produce particulate trajectories, distributions and momenta. The interaction model includes effects of particle size, mass, and rotation as well as two-particle hard sphere collisions. The main purpose of this work is to evaluate the effects of the particles on the energy, mass, and momentum transport in the erosive wall boundary layer region. Neglecting thermal relaxation, the heat transfer rates are found to be substantially reduced when smaller diameter (0.2 micron) particles are introduced as compared to larger diameter particles (5 microns).

Hindrance Velocity Model for Phase Segregation in Suspensions of Poly-dispersed Randomly Oriented Spheroids

NASA Astrophysics Data System (ADS)

Faroughi, S. A.; Huber, C.

2015-12-01

Crystal settling and bubbles migration in magmas have significant effects on the physical and chemical evolution of magmas. The rate of phase segregation is controlled by the force balance that governs the migration of particles suspended in the melt. The relative velocity of a single particle or bubble in a quiescent infinite fluid (melt) is well characterized; however, the interplay between particles or bubbles in suspensions and emulsions and its effect on their settling/rising velocity remains poorly quantified. We propose a theoretical model for the hindered velocity of non-Brownian emulsions of nondeformable droplets, and suspensions of spherical solid particles in the creeping flow regime. The model is based on three sets of hydrodynamic corrections: two on the drag coefficient experienced by each particle to account for both return flow and Smoluchowski effects and a correction on the mixture rheology to account for nonlocal interactions between particles. The model is then extended for mono-disperse non-spherical solid particles that are randomly oriented. The non-spherical particles are idealized as spheroids and characterized by their aspect ratio. The poly-disperse nature of natural suspensions is then taken into consideration by introducing an effective volume fraction of particles for each class of mono-disperse particles sizes. Our model is tested against new and published experimental data over a wide range of particle volume fraction and viscosity ratios between the constituents of dispersions. We find an excellent agreement between our model and experiments. We also show two significant applications for our model: (1) We demonstrate that hindered settling can increase mineral residence time by up to an order of magnitude in convecting magma chambers. (2) We provide a model to correct for particle interactions in the conventional hydrometer test to estimate the particle size distribution in soils. Our model offers a greatly improved agreement with the results obtained with direct measurement methods such as laser diffraction.

Do we really need a large number of particles to simulate bimolecular reactive transport with random walk methods? A kernel density estimation approach

NASA Astrophysics Data System (ADS)

Rahbaralam, Maryam; Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier

2015-12-01

Random walk particle tracking methods are a computationally efficient family of methods to solve reactive transport problems. While the number of particles in most realistic applications is in the order of 106-109, the number of reactive molecules even in diluted systems might be in the order of fractions of the Avogadro number. Thus, each particle actually represents a group of potentially reactive molecules. The use of a low number of particles may result not only in loss of accuracy, but also may lead to an improper reproduction of the mixing process, limited by diffusion. Recent works have used this effect as a proxy to model incomplete mixing in porous media. In this work, we propose using a Kernel Density Estimation (KDE) of the concentrations that allows getting the expected results for a well-mixed solution with a limited number of particles. The idea consists of treating each particle as a sample drawn from the pool of molecules that it represents; this way, the actual location of a tracked particle is seen as a sample drawn from the density function of the location of molecules represented by that given particle, rigorously represented by a kernel density function. The probability of reaction can be obtained by combining the kernels associated to two potentially reactive particles. We demonstrate that the observed deviation in the reaction vs time curves in numerical experiments reported in the literature could be attributed to the statistical method used to reconstruct concentrations (fixed particle support) from discrete particle distributions, and not to the occurrence of true incomplete mixing. We further explore the evolution of the kernel size with time, linking it to the diffusion process. Our results show that KDEs are powerful tools to improve computational efficiency and robustness in reactive transport simulations, and indicates that incomplete mixing in diluted systems should be modeled based on alternative mechanistic models and not on a limited number of particles.

Performance, Cognitive Load, and Behaviour of Technology-Assisted English Listening Learning: From CALL to MALL

ERIC Educational Resources Information Center

Chang, Chi-Cheng; Warden, Clyde A.; Liang, Chaoyun; Chou, Pao-Nan

2018-01-01

This study examines differences in English listening comprehension, cognitive load, and learning behaviour between outdoor ubiquitous learning and indoor computer-assisted learning. An experimental design, employing a pretest-posttest control group is employed. Randomly assigned foreign language university majors joined either the experimental…

Theory of activated glassy dynamics in randomly pinned fluids.

PubMed

Phan, Anh D; Schweizer, Kenneth S

2018-02-07

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.

Theory of activated glassy dynamics in randomly pinned fluids

NASA Astrophysics Data System (ADS)

Phan, Anh D.; Schweizer, Kenneth S.

2018-02-01

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.

Filling of a Poisson trap by a population of random intermittent searchers.

PubMed

Bressloff, Paul C; Newby, Jay M

2012-03-01

We extend the continuum theory of random intermittent search processes to the case of N independent searchers looking to deliver cargo to a single hidden target located somewhere on a semi-infinite track. Each searcher randomly switches between a stationary state and either a leftward or rightward constant velocity state. We assume that all of the particles start at one end of the track and realize sample trajectories independently generated from the same underlying stochastic process. The hidden target is treated as a partially absorbing trap in which a particle can only detect the target and deliver its cargo if it is stationary and within range of the target; the particle is removed from the system after delivering its cargo. As a further generalization of previous models, we assume that up to n successive particles can find the target and deliver its cargo. Assuming that the rate of target detection scales as 1/N, we show that there exists a well-defined mean-field limit N→∞, in which the stochastic model reduces to a deterministic system of linear reaction-hyperbolic equations for the concentrations of particles in each of the internal states. These equations decouple from the stochastic process associated with filling the target with cargo. The latter can be modeled as a Poisson process in which the time-dependent rate of filling λ(t) depends on the concentration of stationary particles within the target domain. Hence, we refer to the target as a Poisson trap. We analyze the efficiency of filling the Poisson trap with n particles in terms of the waiting time density f(n)(t). The latter is determined by the integrated Poisson rate μ(t)=∫(0)(t)λ(s)ds, which in turn depends on the solution to the reaction-hyperbolic equations. We obtain an approximate solution for the particle concentrations by reducing the system of reaction-hyperbolic equations to a scalar advection-diffusion equation using a quasisteady-state analysis. We compare our analytical results for the mean-field model with Monte Carlo simulations for finite N. We thus determine how the mean first passage time (MFPT) for filling the target depends on N and n.

Transition From Peer Review to Peer Learning: Experience in a Radiology Department.

PubMed

Donnelly, Lane F; Dorfman, Scott R; Jones, Jeremy; Bisset, George S

2017-10-18

To describe the process by which a radiology department moved from peer review to peer collaborative improvement (PCI) and review data from the first 16 months of the PCI process. Data from the first 16 months after PCI were reviewed: number of case reviews performed, number of learning opportunities identified, percentage yield of learning opportunities identified, type of learning opportunities identified, and comparison of the previous parameters between case randomly reviewed versus actively pushed (issues actively identified and entered). Changes in actively pushed cases were also assessed as volume per month over the 16 months (run chart). Faculty members were surveyed about their perception of the conversion to PCI. In all, 12,197 cases were peer reviewed, yielding 1,140 learning opportunities (9.34%). The most common types of learning opportunities for all reviewed cases included perception (5.1%) and reporting (1.9%). The yield of learning opportunities from actively pushed cases was 96.3% compared with 3.88% for randomly reviewed cases. The number of actively pushed cases per month increased over the course of the period and established two new confidence intervals. The faculty survey revealed that the faculty perceived the new PCI process as positive, nonpunitive, and focused on improvement. The study demonstrates that a switch to PCI is perceived as nonpunitive and associated with increased radiologist submission of learning opportunities. Active entering of identified learning opportunities had a greater yield and perceived value, compared with random review of cases. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Motor Task Variation Induces Structural Learning

PubMed Central

Braun, Daniel A.; Aertsen, Ad; Wolpert, Daniel M.; Mehring, Carsten

2009-01-01

Summary When we have learned a motor skill, such as cycling or ice-skating, we can rapidly generalize to novel tasks, such as motorcycling or rollerblading [1–8]. Such facilitation of learning could arise through two distinct mechanisms by which the motor system might adjust its control parameters. First, fast learning could simply be a consequence of the proximity of the original and final settings of the control parameters. Second, by structural learning [9–14], the motor system could constrain the parameter adjustments to conform to the control parameters' covariance structure. Thus, facilitation of learning would rely on the novel task parameters' lying on the structure of a lower-dimensional subspace that can be explored more efficiently. To test between these two hypotheses, we exposed subjects to randomly varying visuomotor tasks of fixed structure. Although such randomly varying tasks are thought to prevent learning, we show that when subsequently presented with novel tasks, subjects exhibit three key features of structural learning: facilitated learning of tasks with the same structure, strong reduction in interference normally observed when switching between tasks that require opposite control strategies, and preferential exploration along the learned structure. These results suggest that skill generalization relies on task variation and structural learning. PMID:19217296

Motor task variation induces structural learning.

PubMed

Braun, Daniel A; Aertsen, Ad; Wolpert, Daniel M; Mehring, Carsten

2009-02-24

When we have learned a motor skill, such as cycling or ice-skating, we can rapidly generalize to novel tasks, such as motorcycling or rollerblading [1-8]. Such facilitation of learning could arise through two distinct mechanisms by which the motor system might adjust its control parameters. First, fast learning could simply be a consequence of the proximity of the original and final settings of the control parameters. Second, by structural learning [9-14], the motor system could constrain the parameter adjustments to conform to the control parameters' covariance structure. Thus, facilitation of learning would rely on the novel task parameters' lying on the structure of a lower-dimensional subspace that can be explored more efficiently. To test between these two hypotheses, we exposed subjects to randomly varying visuomotor tasks of fixed structure. Although such randomly varying tasks are thought to prevent learning, we show that when subsequently presented with novel tasks, subjects exhibit three key features of structural learning: facilitated learning of tasks with the same structure, strong reduction in interference normally observed when switching between tasks that require opposite control strategies, and preferential exploration along the learned structure. These results suggest that skill generalization relies on task variation and structural learning.

Altering surface charge nonuniformity on individual colloidal particles.

PubMed

Feick, Jason D; Chukwumah, Nkiru; Noel, Alexandra E; Velegol, Darrell

2004-04-13

Charge nonuniformity (sigmazeta) was altered on individual polystyrene latex particles and measured using the novel experimental technique of rotational electrophoresis. It has recently been shown that unaltered sulfated latices often have significant charge nonuniformity (sigmazeta = 100 mV) on individual particles. Here it is shown that anionic polyelectrolytes and surfactants reduce the native charge nonuniformity on negatively charged particles by 80% (sigmazeta = 20 mV), even while leaving the average surface charge density almost unchanged. Reduction of charge uniformity occurs as large domains of nonuniformity are minimized, giving a more random distribution of charge on individual particle surfaces. Targeted reduction of charge nonuniformity opens new opportunities for the dispersion of nanoparticles and the oriented assembly of particles.

A Mechanical Model of Brownian Motion for One Massive Particle Including Slow Light Particles

NASA Astrophysics Data System (ADS)

Liang, Song

2018-01-01

We provide a connection between Brownian motion and a classical mechanical system. Precisely, we consider a system of one massive particle interacting with an ideal gas, evolved according to non-random mechanical principles, via interaction potentials, without any assumption requiring that the initial velocities of the environmental particles should be restricted to be "fast enough". We prove the convergence of the (position, velocity)-process of the massive particle under a certain scaling limit, such that the mass of the environmental particles converges to 0 while the density and the velocities of them go to infinity, and give the precise expression of the limiting process, a diffusion process.

Charge-fluctuation-induced heating of dust particles in a plasma.

PubMed

Vaulina, O S; Khrapak, S A; Nefedov, A P; Petrov, O F

1999-11-01

Random charge fluctuations are always present in dusty plasmas due to the discrete nature of currents charging the dust particle. These fluctuations can be a reason for the heating of the dust particle system. Such unexpected heating leading to the melting of the dust crystals was observed recently in several experiments. In this paper we show by analytical evaluations and numerical simulation that charge fluctuations provide an effective source of energy and can heat the dust particles up to several eV, in conditions close to experimental ones.

Diffusion, subdiffusion, and localization of active colloids in random post lattices

NASA Astrophysics Data System (ADS)

Morin, Alexandre; Lopes Cardozo, David; Chikkadi, Vijayakumar; Bartolo, Denis

2017-10-01

Combining experiments and theory, we address the dynamics of self-propelled particles in crowded environments. We first demonstrate that motile colloids cruising at constant speed through random lattices undergo a smooth transition from diffusive to subdiffusive to localized dynamics upon increasing the obstacle density. We then elucidate the nature of these transitions by performing extensive simulations constructed from a detailed analysis of the colloid-obstacle interactions. We evidence that repulsion at a distance and hard-core interactions both contribute to slowing down the long-time diffusion of the colloids. In contrast, the localization transition stems solely from excluded-volume interactions and occurs at the void-percolation threshold. Within this critical scenario, equivalent to that of the random Lorentz gas, genuine asymptotic subdiffusion is found only at the critical density where the motile particles explore a fractal maze.

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

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

Zhang, G.

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation'' limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles, and could thus determine the saturation density of spheres with high accuracy. Here in this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensionalmore » polygons. We also calculate the saturation density for regular polygons of three to ten sides, and obtain results that are consistent with previous, extrapolation-based studies.« less

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

DOE PAGES

Zhang, G.

2018-04-30

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation'' limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles, and could thus determine the saturation density of spheres with high accuracy. Here in this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensionalmore » polygons. We also calculate the saturation density for regular polygons of three to ten sides, and obtain results that are consistent with previous, extrapolation-based studies.« less

Implicit learning of non-spatial sequences in schizophrenia

PubMed Central

MARVEL, CHERIE L.; SCHWARTZ, BARBARA L.; HOWARD, DARLENE V.; HOWARD, JAMES H.

2006-01-01

Recent studies have reported abnormal implicit learning of sequential patterns in patients with schizophrenia. Because these studies were based on visuospatial cues, the question remained whether patients were impaired simply due to the demands of spatial processing. This study examined implicit sequence learning in 24 patients with schizophrenia and 24 healthy controls using a non-spatial variation of the serial reaction time test (SRT) in which pattern stimuli alternated with random stimuli on every other trial. Both groups showed learning by responding faster and more accurately to pattern trials than to random trials. Patients, however, showed a smaller magnitude of sequence learning. Both groups were unable to demonstrate explicit knowledge of the nature of the pattern, confirming that learning occurred without awareness. Clinical variables were not correlated with the patients' learning deficits. Patients with schizophrenia have a decreased ability to develop sensitivity to regularly occurring sequences of events within their environment. This type of deficit may affect an array of cognitive and motor functions that rely on the perception of event regularity. PMID:16248901

Particle Dynamics in the Sea: Processes of Production and Loss Governing the Abundance of Marine Snow

DTIC Science & Technology

1990-01-05

pumping sys - tems. CARDER, STEWARD and BETZER (1982) describe a holographic device (HMV = "holographic microvelocimeter": COSTELLO, YOUNG, CARDER and BETZER...similar to aggregate porosities determined using collision calculations based on random particle trajectories in computer models (Tambo and Wata- nabe ...Similarly, sinking patterns of particles, behavior of zooplankton and processes occurring at boundary layers may be 202 obse’rved di rectly. I This sy

All about Solids, Liquids & Gases. Physical Science for Children[TM]. Schlessinger Science Library. [Videotape].

ERIC Educational Resources Information Center

2000

In All About Solids, Liquids and Gases, young students will be introduced to the three common forms of matter. They'll learn that all things are made up of tiny particles called atoms and that the movement of these particles determines the form that matter takes. In solids, the particles are packed tightly together and move very little. The…

App-based serious gaming for training of chest tube insertion: study protocol for a randomized controlled trial.

PubMed

Friedrich, Mirco; Bergdolt, Christian; Haubruck, Patrick; Bruckner, Thomas; Kowalewski, Karl-Friedrich; Müller-Stich, Beat Peter; Tanner, Michael C; Nickel, Felix

2017-02-06

Chest tube insertion is a standard intervention for management of various injuries of the thorax. Quick and accurate execution facilitates efficient therapy without further complications. Here, we propose a new training concept comprised of e-learning elements as well as continuous rating using an objective structured assessment of technical skills (OSATS) tool. The study protocol is presented for a randomized trial to evaluate e-learning with app-based serious gaming for chest drain insertion. The proposed randomized trial will be carried out at the Department of Orthopedics and Traumatology at Heidelberg University in the context of regular curricular teaching for medical students (n = 90, 3rd to 6th year). The intervention group will use e-learning with the serious gaming app Touch Surgery (TM) for chest drain insertion, whereas the control group uses serious gaming for an unrelated procedure. Primary endpoint is operative performance of chest drain insertion in a porcine cadaveric model according to OSATS. The randomized trial will help determine the value of e-learning with the serious gaming app Touch Surgery (TM) for chest drain insertion by using the OSATS score. The study will improve surgical training for trauma situations. Trial Registration Number, DRKS00009994 . Registered on 27 May 2016.

Random learning units using WIRIS quizzes in Moodle

NASA Astrophysics Data System (ADS)

Mora, Ángel; Mérida, Enrique; Eixarch, Ramon

2011-09-01

Moodle is an extended learning management system for developing learning units, including mathematically-based subjects. A wide variety of material can be developed in Moodle which contains facilities for forums, questionnaires, lessons, tasks, wikis, glossaries and chats. Therefore, the Moodle platform provides a meeting point for those working in a mathematics course. Mathematics requires special materials and activities: The material must include mathematical objects and the activities included in the virtual course must be able to do mathematical computations. WIRIS is a powerful software for educational environments. It has libraries for calculus, algebra, geometry and much more. In this article, examples showing the use of WIRIS in numerical methods and examples of using a new tool, WIRIS quizzes, are illustrated. By enhancing Moodle with WIRIS, we can add random learning questions to modules. Moodle has a simpler version of this capability, but WIRIS extends the method in which the random material is presented to the students. Random objects can appear in a question, in a variable of a question, in a plot or in the definition of a mathematical object. This article illustrates material prepared for numerical methods using a WIRIS library integrated in WIRIS quizzes. As a result, WIRIS in Moodle can be considered as a global solution for mathematics education.

A random forest learning assisted "divide and conquer" approach for peptide conformation search.

PubMed

Chen, Xin; Yang, Bing; Lin, Zijing

2018-06-11

Computational determination of peptide conformations is challenging as it is a problem of finding minima in a high-dimensional space. The "divide and conquer" approach is promising for reliably reducing the search space size. A random forest learning model is proposed here to expand the scope of applicability of the "divide and conquer" approach. A random forest classification algorithm is used to characterize the distributions of the backbone φ-ψ units ("words"). A random forest supervised learning model is developed to analyze the combinations of the φ-ψ units ("grammar"). It is found that amino acid residues may be grouped as equivalent "words", while the φ-ψ combinations in low-energy peptide conformations follow a distinct "grammar". The finding of equivalent words empowers the "divide and conquer" method with the flexibility of fragment substitution. The learnt grammar is used to improve the efficiency of the "divide and conquer" method by removing unfavorable φ-ψ combinations without the need of dedicated human effort. The machine learning assisted search method is illustrated by efficiently searching the conformations of GGG/AAA/GGGG/AAAA/GGGGG through assembling the structures of GFG/GFGG. Moreover, the computational cost of the new method is shown to increase rather slowly with the peptide length.

Particle-laden weakly swirling free jets: Measurements and predictions. Ph.D. Thesis - Pennsylvania State Univ.

NASA Technical Reports Server (NTRS)

Bulzan, Daniel L.

1988-01-01

A theoretical and experimental investigation of particle-laden, weakly swirling, turbulent free jets was conducted. Glass particles, having a Sauter mean diameter of 39 microns, with a standard deviation of 15 microns, were used. A single loading ratio (the mass flow rate of particles per unit mass flow rate of air) of 0.2 was used in the experiments. Measurements are reported for three swirl numbers, ranging from 0 to 0.33. The measurements included mean and fluctuating velocities of both phases, and particle mass flux distributions. Measurements were also completed for single-phase non-swirling and swirling jets, as baselines. Measurements were compared with predictions from three types of multiphase flow analysis, as follows: (1) locally homogeneous flow (LHF) where slip between the phases was neglected; (2) deterministic separated flow (DSF), where slip was considered but effects of turbulence/particle interactions were neglected; and (3) stochastic separated flow (SSF), where effects of both interphase slip and turbulence/particle interactions were considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. Single-phase weakly swirling jets were considered first. Predictions using a standard k-epsilon turbulence model, as well as two versions modified to account for effects of streamline curvature, were compared with measurements. Predictions using a streamline curvature modification based on the flux Richardson number gave better agreement with measurements for the single-phase swirling jets than the standard k-epsilon model. For the particle-laden jets, the LHF and DSF models did not provide very satisfactory predictions. The LHF model generally overestimated the rate of decay of particle mean axial and angular velocities with streamwise distance, and predicted particle mass fluxes also showed poor agreement with measurements, due to the assumption of no-slip between phases. The DSF model also performed quite poorly for predictions of particle mass flux because turbulent dispersion of the particles was neglected. The SSF model, which accounts for both particle inertia and turbulent dispersion of the particles, yielded reasonably good predictions throughout the flow field for the particle-laden jets.

Random elements on lattices: Review and statistical applications

NASA Astrophysics Data System (ADS)

Potocký, Rastislav; Villarroel, Claudia Navarro; Sepúlveda, Maritza; Luna, Guillermo; Stehlík, Milan

2017-07-01

We discuss important contributions to random elements on lattices. We relate to both algebraic and probabilistic properties. Several applications and concepts are discussed, e.g. positive dependence, Random walks and distributions on lattices, Super-lattices, learning. The application to Chilean Ecology is given.

Lessons Learned from Large-Scale Randomized Experiments

ERIC Educational Resources Information Center

Slavin, Robert E.; Cheung, Alan C. K.

2017-01-01

Large-scale randomized studies provide the best means of evaluating practical, replicable approaches to improving educational outcomes. This article discusses the advantages, problems, and pitfalls of these evaluations, focusing on alternative methods of randomization, recruitment, ensuring high-quality implementation, dealing with attrition, and…

On the phase behavior of hard aspherical particles

NASA Astrophysics Data System (ADS)

Miller, William L.; Cacciuto, Angelo

2010-12-01

We use numerical simulations to understand how random deviations from the ideal spherical shape affect the ability of hard particles to form fcc crystalline structures. Using a system of hard spheres as a reference, we determine the fluid-solid coexistence pressures of both shape-polydisperse and monodisperse systems of aspherical hard particles. We find that when particles are sufficiently isotropic, the coexistence pressure can be predicted from a linear relation involving the product of two simple geometric parameters characterizing the asphericity of the particles. Finally, our results allow us to gain direct insight into the crystallizability limits of these systems by rationalizing empirical data obtained for analogous monodisperse systems.

Evaluation of an e-learning system for diagnosis of gastric lesions using magnifying narrow-band imaging: a multicenter randomized controlled study.

PubMed

Nakanishi, Hiroyoshi; Doyama, Hisashi; Ishikawa, Hideki; Uedo, Noriya; Gotoda, Takuji; Kato, Mototsugu; Nagao, Shigeaki; Nagami, Yasuaki; Aoyagi, Hiroyuki; Imagawa, Atsushi; Kodaira, Junichi; Mitsui, Shinya; Kobayashi, Nozomu; Muto, Manabu; Takatori, Hajime; Abe, Takashi; Tsujii, Masahiko; Watari, Jiro; Ishiyama, Shuhei; Oda, Ichiro; Ono, Hiroyuki; Kaneko, Kazuhiro; Yokoi, Chizu; Ueo, Tetsuya; Uchita, Kunihisa; Matsumoto, Kenshi; Kanesaka, Takashi; Morita, Yoshinori; Katsuki, Shinichi; Nishikawa, Jun; Inamura, Katsuhisa; Kinjo, Tetsu; Yamamoto, Katsumi; Yoshimura, Daisuke; Araki, Hiroshi; Kashida, Hiroshi; Hosokawa, Ayumu; Mori, Hirohito; Yamashita, Haruhiro; Motohashi, Osamu; Kobayashi, Kazuhiko; Hirayama, Michiaki; Kobayashi, Hiroyuki; Endo, Masaki; Yamano, Hiroo; Murakami, Kazunari; Koike, Tomoyuki; Hirasawa, Kingo; Miyaoka, Youichi; Hamamoto, Hidetaka; Hikichi, Takuto; Hanabata, Norihiro; Shimoda, Ryo; Hori, Shinichiro; Sato, Tadashi; Kodashima, Shinya; Okada, Hiroyuki; Mannami, Tomohiko; Yamamoto, Shojiro; Niwa, Yasumasa; Yashima, Kazuo; Tanabe, Satoshi; Satoh, Hiro; Sasaki, Fumisato; Yamazato, Tetsuro; Ikeda, Yoshiou; Nishisaki, Hogara; Nakagawa, Masahiro; Matsuda, Akio; Tamura, Fumio; Nishiyama, Hitoshi; Arita, Keiko; Kawasaki, Keisuke; Hoppo, Kazushige; Oka, Masashi; Ishihara, Shinichi; Mukasa, Michita; Minamino, Hiroaki; Yao, Kenshi

2017-10-01

Background and study aim  Magnifying narrow-band imaging (M-NBI) is useful for the accurate diagnosis of early gastric cancer (EGC). However, acquiring skill at M-NBI diagnosis takes substantial effort. An Internet-based e-learning system to teach endoscopic diagnosis of EGC using M-NBI has been developed. This study evaluated its effectiveness. Participants and methods  This study was designed as a multicenter randomized controlled trial. We recruited endoscopists as participants from all over Japan. After completing Test 1, which consisted of M-NBI images of 40 gastric lesions, participants were randomly assigned to the e-learning or non-e-learning groups. Only the e-learning group was allowed to access the e-learning system. After the e-learning period, both groups received Test 2. The analysis set was participants who scored < 80 % accuracy on Test 1. The primary end point was the difference in accuracy between Test 1 and Test 2 for the two groups. Results  A total of 395 participants from 77 institutions completed Test 1 (198 in the e-learning group and 197 in the non-e-learning group). After the e-learning period, all 395 completed Test 2. The analysis sets were e-learning group: n = 184; and non-e-learning group: n = 184. The mean Test 1 score was 59.9 % for the e-learning group and 61.7 % for the non-e-learning group. The change in accuracy in Test 2 was significantly higher in the e-learning group than in the non-e-learning group (7.4 points vs. 0.14 points, respectively; P  < 0.001). Conclusion This study clearly demonstrated the efficacy of the e-learning system in improving practitioners' capabilities to diagnose EGC using M-NBI.Trial registered at University Hospital Medical Information Network Clinical Trials Registry (UMIN000008569). © Georg Thieme Verlag KG Stuttgart · New York.

Modeling cometary photopolarimetric characteristics with Sh-matrix method

NASA Astrophysics Data System (ADS)

Kolokolova, L.; Petrov, D.

2017-12-01

Cometary dust is dominated by particles of complex shape and structure, which are often considered as fractal aggregates. Rigorous modeling of light scattering by such particles, even using parallelized codes and NASA supercomputer resources, is very computer time and memory consuming. We are presenting a new approach to modeling cometary dust that is based on the Sh-matrix technique (e.g., Petrov et al., JQSRT, 112, 2012). This method is based on the T-matrix technique (e.g., Mishchenko et al., JQSRT, 55, 1996) and was developed after it had been found that the shape-dependent factors could be separated from the size- and refractive-index-dependent factors and presented as a shape matrix, or Sh-matrix. Size and refractive index dependences are incorporated through analytical operations on the Sh-matrix to produce the elements of T-matrix. Sh-matrix method keeps all advantages of the T-matrix method, including analytical averaging over particle orientation. Moreover, the surface integrals describing the Sh-matrix elements themselves can be solvable analytically for particles of any shape. This makes Sh-matrix approach an effective technique to simulate light scattering by particles of complex shape and surface structure. In this paper, we present cometary dust as an ensemble of Gaussian random particles. The shape of these particles is described by a log-normal distribution of their radius length and direction (Muinonen, EMP, 72, 1996). Changing one of the parameters of this distribution, the correlation angle, from 0 to 90 deg., we can model a variety of particles from spheres to particles of a random complex shape. We survey the angular and spectral dependencies of intensity and polarization resulted from light scattering by such particles, studying how they depend on the particle shape, size, and composition (including porous particles to simulate aggregates) to find the best fit to the cometary observations.

Does a Preschool Social and Emotional Learning Intervention Pay Off for Classroom Instruction and Children's Behavior and Academic Skills? Evidence from the Foundations of Learning Project

ERIC Educational Resources Information Center

Morris, Pamela; Millenky, Megan; Raver, C. Cybele; Jones, Stephanie M.

2013-01-01

This article tests the hypothesis that children's learning environment will improve through a social and emotional learning (SEL) intervention that provides preschool teachers with new skills to manage children's disruptive behavior by reporting results from the Foundations of Learning (FOL) Demonstration, a place-randomized, experimental…

Online Learning from Input versus Offline Memory Evolution in Adult Word Learning: Effects of Neighborhood Density and Phonologically Related Practice

ERIC Educational Resources Information Center

Storkel, Holly L.; Bontempo, Daniel E.; Pak, Natalie S.

2014-01-01

Purpose: In this study, the authors investigated adult word learning to determine how neighborhood density and practice across phonologically related training sets influence online learning from input during training versus offline memory evolution during no-training gaps. Method: Sixty-one adults were randomly assigned to learn low- or…

Detection of biological particles by the use of circular dichroism measurements improved by scattering theory

NASA Astrophysics Data System (ADS)

Rosen, David L.; Pendleton, J. David

1995-09-01

Light scattered from optically active spheres was theoretically analyzed for biodetection. The circularly polarized signal of near-forward scattering from circularly dichroic spheres was calculated. Both remote and point biodetection were considered. The analysis included the effect of a circular aperture and beam block at the detector. If the incident light is linearly polarized, a false signal would limit the sensitivity of the biodetector. If the incident light is randomly polarized, shot noise would limit the sensitivity. Suggested improvements to current techniques include a beam block, precise angular measurements, randomly polarized light, index-matching fluid, and larger apertures for large particles.

Coherent Backscattering in the Cross-Polarized Channel

NASA Technical Reports Server (NTRS)

Mischenko, Michael I.; Mackowski, Daniel W.

2011-01-01

We analyze the asymptotic behavior of the cross-polarized enhancement factor in the framework of the standard low-packing-density theory of coherent backscattering by discrete random media composed of spherically symmetric particles. It is shown that if the particles are strongly absorbing or if the smallest optical dimension of the particulate medium (i.e., the optical thickness of a plane-parallel slab or the optical diameter of a spherically symmetric volume) approaches zero, then the cross-polarized enhancement factor tends to its upper-limit value 2. This theoretical prediction is illustrated using direct computer solutions of the Maxwell equations for spherical volumes of discrete random medium.

Coherent Backscattering by Polydisperse Discrete Random Media: Exact T-Matrix Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Dlugach, Janna M.; Mackowski, Daniel W.

2011-01-01

The numerically exact superposition T-matrix method is used to compute, for the first time to our knowledge, electromagnetic scattering by finite spherical volumes composed of polydisperse mixtures of spherical particles with different size parameters or different refractive indices. The backscattering patterns calculated in the far-field zone of the polydisperse multiparticle volumes reveal unequivocally the classical manifestations of the effect of weak localization of electromagnetic waves in discrete random media, thereby corroborating the universal interference nature of coherent backscattering. The polarization opposition effect is shown to be the least robust manifestation of weak localization fading away with increasing particle size parameter.

Trapping and assembling of particles and live cells on large-scale random gold nano-island substrates

PubMed Central

Kang, Zhiwen; Chen, Jiajie; Wu, Shu-Yuen; Chen, Kun; Kong, Siu-Kai; Yong, Ken-Tye; Ho, Ho-Pui

2015-01-01

We experimentally demonstrated the use of random plasmonic nano-islands for optical trapping and assembling of particles and live cells into highly organized pattern with low power density. The observed trapping effect is attributed to the net contribution due to near-field optical trapping force and long-range thermophoretic force, which overcomes the axial convective drag force, while the lateral convection pushes the target objects into the trapping zone. Our work provides a simple platform for on-chip optical manipulation of nano- and micro-sized objects, and may find applications in physical and life sciences. PMID:25928045

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

NASA Astrophysics Data System (ADS)

Sposini, Vittoria; Chechkin, Aleksei V.; Seno, Flavio; Pagnini, Gianni; Metzler, Ralf

2018-04-01

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential (Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time-dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments.

Quantum Optics, Diffraction Theory, and Elementary Particle Physics

ScienceCinema

Glauber, Roy

2018-05-22

Physical optics has expanded greatly in recent years. Though it remains part of the ancestry of elementary particle physics, there are once again lessons to be learned from it. I shall discuss several of these, including some that have emerged at CERN and Brookhaven.

Learning Outcomes and Affective Factors of Blended Learning of English for Library Science

ERIC Educational Resources Information Center

Wentao, Chen; Jinyu, Zhang; Zhonggen, Yu

2016-01-01

English for Library Science is an essential course for students to command comprehensive scope of library knowledge. This study aims to compare the learning outcomes, gender differences and affective factors in the environments of blended and traditional learning. Around one thousand participants from one university were randomly selected to…

Global Connectedness in Higher Education: Student Voices on the Value of Cross-Cultural Learning Dialogue

ERIC Educational Resources Information Center

Lehtomäki, Elina; Moate, Josephine; Posti-Ahokas, Hanna

2016-01-01

The study explores how sense of global connectedness can be enhanced by creating opportunities for cross-cultural dialogue in higher education. Thematic analysis of randomly selected 15 learning journals, students' reflections on their learning during an international seminar was used to identify students' significant learning experiences. The…

How Learning about Scientists' Struggles Influences Students' Interest and Learning in Physics

ERIC Educational Resources Information Center

Hong, Huang-Yao; Lin-Siegler, Xiaodong

2012-01-01

How does learning about scientists' struggles during their scientific knowledge building affect students' science learning? Two hundred and seventy-one high school students were randomly assigned to 1 of 3 conditions: (a) the struggle-oriented background information (n = 90) condition, which presented students with stories about 3 scientists'…

Identifying WIMP dark matter from particle and astroparticle data

NASA Astrophysics Data System (ADS)

Bertone, Gianfranco; Bozorgnia, Nassim; Kim, Jong Soo; Liem, Sebastian; McCabe, Christopher; Otten, Sydney; Ruiz de Austri, Roberto

2018-03-01

One of the most promising strategies to identify the nature of dark matter consists in the search for new particles at accelerators and with so-called direct detection experiments. Working within the framework of simplified models, and making use of machine learning tools to speed up statistical inference, we address the question of what we can learn about dark matter from a detection at the LHC and a forthcoming direct detection experiment. We show that with a combination of accelerator and direct detection data, it is possible to identify newly discovered particles as dark matter, by reconstructing their relic density assuming they are weakly interacting massive particles (WIMPs) thermally produced in the early Universe, and demonstrating that it is consistent with the measured dark matter abundance. An inconsistency between these two quantities would instead point either towards additional physics in the dark sector, or towards a non-standard cosmology, with a thermal history substantially different from that of the standard cosmological model.

Scattering of Gaussian Beams by Disordered Particulate Media

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Dlugach, Janna M.

2016-01-01

A frequently observed characteristic of electromagnetic scattering by a disordered particulate medium is the absence of pronounced speckles in angular patterns of the scattered light. It is known that such diffuse speckle-free scattering patterns can be caused by averaging over randomly changing particle positions and/or over a finite spectral range. To get further insight into the possible physical causes of the absence of speckles, we use the numerically exact superposition T-matrix solver of the Maxwell equations and analyze the scattering of plane-wave and Gaussian beams by representative multi-sphere groups. We show that phase and amplitude variations across an incident Gaussian beam do not serve to extinguish the pronounced speckle pattern typical of plane-wave illumination of a fixed multi-particle group. Averaging over random particle positions and/or over a finite spectral range is still required to generate the classical diffuse speckle-free regime.

Real time visualization of quantum walk

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

Miyazaki, Akihide; Hamada, Shinji; Sekino, Hideo

2014-02-20

Time evolution of quantum particles like electrons is described by time-dependent Schrödinger equation (TDSE). The TDSE is regarded as the diffusion equation of electrons with imaginary diffusion coefficients. And the TDSE is solved by quantum walk (QW) which is regarded as a quantum version of a classical random walk. The diffusion equation is solved in discretized space/time as in the case of classical random walk with additional unitary transformation of internal degree of freedom typical for quantum particles. We call the QW for solution of the TDSE a Schrödinger walk (SW). For observation of one quantum particle evolution under amore » given potential in atto-second scale, we attempt a successive computation and visualization of the SW. Using Pure Data programming, we observe the correct behavior of a probability distribution under the given potential in real time for observers of atto-second scale.« less

Anomalous transport in fluid field with random waiting time depending on the preceding jump length

NASA Astrophysics Data System (ADS)

Zhang, Hong; Li, Guo-Hua

2016-11-01

Anomalous (or non-Fickian) transport behaviors of particles have been widely observed in complex porous media. To capture the energy-dependent characteristics of non-Fickian transport of a particle in flow fields, in the present paper a generalized continuous time random walk model whose waiting time probability distribution depends on the preceding jump length is introduced, and the corresponding master equation in Fourier-Laplace space for the distribution of particles is derived. As examples, two generalized advection-dispersion equations for Gaussian distribution and lévy flight with the probability density function of waiting time being quadratic dependent on the preceding jump length are obtained by applying the derived master equation. Project supported by the Foundation for Young Key Teachers of Chengdu University of Technology, China (Grant No. KYGG201414) and the Opening Foundation of Geomathematics Key Laboratory of Sichuan Province, China (Grant No. scsxdz2013009).

bicoid mRNA localises to the Drosophila oocyte anterior by random Dynein-mediated transport and anchoring

PubMed Central

Trovisco, Vítor; Belaya, Katsiaryna; Nashchekin, Dmitry; Irion, Uwe; Sirinakis, George; Butler, Richard; Lee, Jack J; Gavis, Elizabeth R; St Johnston, Daniel

2016-01-01

bicoid mRNA localises to the Drosophila oocyte anterior from stage 9 of oogenesis onwards to provide a local source for Bicoid protein for embryonic patterning. Live imaging at stage 9 reveals that bicoid mRNA particles undergo rapid Dynein-dependent movements near the oocyte anterior, but with no directional bias. Furthermore, bicoid mRNA localises normally in shot2A2, which abolishes the polarised microtubule organisation. FRAP and photo-conversion experiments demonstrate that the RNA is stably anchored at the anterior, independently of microtubules. Thus, bicoid mRNA is localised by random active transport and anterior anchoring. Super-resolution imaging reveals that bicoid mRNA forms 110–120 nm particles with variable RNA content, but constant size. These particles appear to be well-defined structures that package the RNA for transport and anchoring. DOI: http://dx.doi.org/10.7554/eLife.17537.001 PMID:27791980

Stochastic transport in the presence of spatial disorder: Fluctuation-induced corrections to homogenization

NASA Astrophysics Data System (ADS)

Russell, Matthew J.; Jensen, Oliver E.; Galla, Tobias

2016-10-01

Motivated by uncertainty quantification in natural transport systems, we investigate an individual-based transport process involving particles undergoing a random walk along a line of point sinks whose strengths are themselves independent random variables. We assume particles are removed from the system via first-order kinetics. We analyze the system using a hierarchy of approaches when the sinks are sparsely distributed, including a stochastic homogenization approximation that yields explicit predictions for the extrinsic disorder in the stationary state due to sink strength fluctuations. The extrinsic noise induces long-range spatial correlations in the particle concentration, unlike fluctuations due to the intrinsic noise alone. Additionally, the mean concentration profile, averaged over both intrinsic and extrinsic noise, is elevated compared with the corresponding profile from a uniform sink distribution, showing that the classical homogenization approximation can be a biased estimator of the true mean.

Atherogenic Lipoprotein Subfractions Determined by Ion Mobility and First Cardiovascular Events After Random Allocation to High-Intensity Statin or Placebo: The Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) Trial.

PubMed

Mora, Samia; Caulfield, Michael P; Wohlgemuth, Jay; Chen, Zhihong; Superko, H Robert; Rowland, Charles M; Glynn, Robert J; Ridker, Paul M; Krauss, Ronald M

2015-12-08

Cardiovascular disease (CVD) can occur in individuals with low low-density lipoprotein (LDL) cholesterol (LDL-C). We investigated whether detailed measures of LDL subfractions and other lipoproteins can be used to assess CVD risk in a population with both low LDL-C and high C-reactive protein who were randomized to high-intensity statin or placebo. In 11 186 Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) participants, we tested whether lipids, apolipoproteins, and ion mobility-measured particle concentrations at baseline and after random allocation to rosuvastatin 20 mg/d or placebo were associated with first CVD events (n=307) or CVD/all-cause death (n=522). In placebo-allocated participants, baseline LDL-C was not associated with CVD (adjusted hazard ratio [HR] per SD, 1.03; 95% confidence interval [CI], 0.88-1.21). In contrast, associations with CVD events were observed for baseline non-high-density lipoprotein (HDL) cholesterol (HR, 1.18; 95% CI, 1.01-1.38), apolipoprotein B (HR, 1.28; 95% CI, 1.11-1.48), and ion mobility-measured non-HDL particles (HR, 1.19; 95% CI, 1.05-1.35) and LDL particles (HR, 1.21; 95% CI, 1.07-1.37). Association with CVD events was also observed for several LDL and very-low-density lipoprotein subfractions but not for ion mobility-measured HDL subfractions. In statin-allocated participants, CVD events were associated with on-treatment LDL-C, non-HDL cholesterol, and apolipoprotein B; these were also associated with CVD/all-cause death, as were several LDL and very-low-density lipoprotein subfractions, albeit with a pattern of association that differed from the baseline risk. In JUPITER, baseline LDL-C was not associated with CVD events, in contrast with significant associations for non-HDL cholesterol and atherogenic particles: apolipoprotein B and ion mobility-measured non-HDL particles, LDL particles, and select subfractions of very-low-density lipoprotein particles and LDL particles. During high-intensity statin therapy, on-treatment levels of LDL-C and atherogenic particles were associated with residual risk of CVD/all-cause death. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681. © 2015 American Heart Association, Inc.

Experimental studies of the effects of buffered particle dampers attached to a multi-degree-of-freedom system under dynamic loads

NASA Astrophysics Data System (ADS)

Lu, Zheng; Lu, Xilin; Lu, Wensheng; Masri, Sami F.

2012-04-01

This paper presents a systematic experimental investigation of the effects of buffered particle dampers attached to a multi-degree-of-freedom (mdof) system under different dynamic loads (free vibration, random excitation as well as real onsite earthquake excitations), and analytical/computational study of such a system. A series of shaking table tests of a three-storey steel frame with the buffered particle damper system are carried out to evaluate the performance and to verify the analysis method. It is shown that buffered particle dampers have good performance in reducing the response of structures under dynamic loads, especially under random excitation case. It can effectively control the fundamental mode of the mdof primary system; however, the control effect for higher modes is variable. It is also shown that, for a specific container geometry, a certain mass ratio leads to more efficient momentum transfer from the primary system to the particles with a better vibration attenuation effect, and that buffered particle dampers have better control effect than the conventional rigid ones. An analytical solution based on the discrete element method is also presented. Comparison between the experimental and computational results shows that reasonably accurate estimates of the response of a primary system can be obtained. Properly designed buffered particle dampers can effectively reduce the response of lightly damped mdof primary system with a small weight penalty, under different dynamic loads.

Respiratory Effects of Fine and Ultrafine Particles from Indoor Sources—A Randomized Sham-Controlled Exposure Study of Healthy Volunteers

PubMed Central

Soppa, Vanessa J.; Schins, Roel P. F.; Hennig, Frauke; Hellack, Bryan; Quass, Ulrich; Kaminski, Heinz; Kuhlbusch, Thomas A. J.; Hoffmann, Barbara; Weinmayr, Gudrun

2014-01-01

Particulate air pollution is linked to impaired respiratory health. We analyzed particle emissions from common indoor sources (candles burning (CB), toasting bread (TB), frying sausages (FS)) and lung function in 55 healthy volunteers (mean age 33.0 years) in a randomized cross-over controlled exposure study. Lung-deposited particle surface area concentration (PSC), size-specific particle number concentration (PNC) up to 10 µm, and particle mass concentration (PMC) of PM1, PM2.5 and PM10 were determined during exposure (2 h). FEV1, FVC and MEF25%–75% was measured before, 4 h and 24 h after exposure. Wilcoxon-rank sum tests (comparing exposure scenarios) and mixed linear regression using particle concentrations and adjusting for personal characteristics, travel time and transportation means before exposure sessions were performed. While no effect was seen comparing the exposure scenarios and in the unadjusted model, inverse associations were found for PMC from CB and FS in relation to FEV1 and MEF25%–75%. with a change in 10 µg/m3 in PM2.5 from CB being associated with a change in FEV1 of −19 mL (95%-confidence interval:−43; 5) after 4 h. PMC from TB and PNC of UFP were not associated with lung function changes, but PSC from CB was. Elevated indoor fine particles from certain sources may be associated with small decreases in lung function in healthy adults. PMID:25000149

Oncology E-Learning for Undergraduate. A Prospective Randomized Controlled Trial.

PubMed

da Costa Vieira, René Aloisio; Lopes, Ana Helena; Sarri, Almir José; Benedetti, Zuleica Caulada; de Oliveira, Cleyton Zanardo

2017-06-01

The e-learning education is a promising method, but there are few prospective randomized publications in oncology. The purpose of this study was to assess the level of retention of information in oncology from undergraduate students of physiotherapy. A prospective, controlled, randomized, crossover study, 72 undergraduate students of physiotherapy, from the second to fourth years, were randomized to perform a course of physiotherapy in oncology (PHO) using traditional classroom or e-learning. Students were offered the same content of the subject. The teacher in the traditional classroom model and the e-learning students used the Articulate® software. The course tackled the main issues related to PHO, and it was divided into six modules, 18 lessons, evaluated by 126 questions. A diagnosis evaluation was performed previous to the course and after every module. The sample consisted of 67 students, allocated in groups A (n = 35) and B (n = 32), and the distribution was homogeneous between the groups. Evaluating the correct answers, we observed a limited score in the pre-test (average grade 44.6 %), which has significant (p < 0.001) improvement in post-test evaluation (average grade 73.9 %). The correct pre-test (p = 0.556) and post-test (p = 0.729) evaluation and the retention of information (p = 0.408) were not different between the two groups. The course in PHO allowed significant acquisition of knowledge to undergraduate students, but the level of information retention was statistically similar between the traditional classroom form and the e-learning, a fact that encourages the use of e-learning in oncology. REBECU1111-1142-1963.

Online neural monitoring of statistical learning

PubMed Central

Batterink, Laura J.; Paller, Ken A.

2017-01-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the RT task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. PMID:28324696

Activated Random Walkers: Facts, Conjectures and Challenges

NASA Astrophysics Data System (ADS)

Dickman, Ronald; Rolla, Leonardo T.; Sidoravicius, Vladas

2010-02-01

We study a particle system with hopping (random walk) dynamics on the integer lattice ℤ d . The particles can exist in two states, active or inactive (sleeping); only the former can hop. The dynamics conserves the number of particles; there is no limit on the number of particles at a given site. Isolated active particles fall asleep at rate λ>0, and then remain asleep until joined by another particle at the same site. The state in which all particles are inactive is absorbing. Whether activity continues at long times depends on the relation between the particle density ζ and the sleeping rate λ. We discuss the general case, and then, for the one-dimensional totally asymmetric case, study the phase transition between an active phase (for sufficiently large particle densities and/or small λ) and an absorbing one. We also present arguments regarding the asymptotic mean hopping velocity in the active phase, the rate of fixation in the absorbing phase, and survival of the infinite system at criticality. Using mean-field theory and Monte Carlo simulation, we locate the phase boundary. The phase transition appears to be continuous in both the symmetric and asymmetric versions of the process, but the critical behavior is very different. The former case is characterized by simple integer or rational values for critical exponents ( β=1, for example), and the phase diagram is in accord with the prediction of mean-field theory. We present evidence that the symmetric version belongs to the universality class of conserved stochastic sandpiles, also known as conserved directed percolation. Simulations also reveal an interesting transient phenomenon of damped oscillations in the activity density.

Modeling sediment transport as a spatio-temporal Markov process.

NASA Astrophysics Data System (ADS)

Heyman, Joris; Ancey, Christophe

2014-05-01

Despite a century of research about sediment transport by bedload occuring in rivers, its constitutive laws remain largely unknown. The proof being that our ability to predict mid-to-long term transported volumes within reasonable confidence interval is almost null. The intrinsic fluctuating nature of bedload transport may be one of the most important reasons why classical approaches fail. Microscopic probabilistic framework has the advantage of taking into account these fluctuations at the particle scale, to understand their effect on the macroscopic variables such as sediment flux. In this framework, bedload transport is seen as the random motion of particles (sand, gravel, pebbles...) over a two-dimensional surface (the river bed). The number of particles in motion, as well as their velocities, are random variables. In this talk, we show how a simple birth-death Markov model governing particle motion on a regular lattice accurately reproduces the spatio-temporal correlations observed at the macroscopic level. Entrainment, deposition and transport of particles by the turbulent fluid (air or water) are supposed to be independent and memoryless processes that modify the number of particles in motion. By means of the Poisson representation, we obtained a Fokker-Planck equation that is exactly equivalent to the master equation and thus valid for all cell sizes. The analysis shows that the number of moving particles evolves locally far from thermodynamic equilibrium. Several analytical results are presented and compared to experimental data. The index of dispersion (or variance over mean ratio) is proved to grow from unity at small scales to larger values at larger scales confirming the non Poisonnian behavior of bedload transport. Also, we study the one and two dimensional K-function, which gives the average number of moving particles located in a ball centered at a particle centroid function of the ball's radius.

Computational investigation of longitudinal diffusion, eddy dispersion, and trans-particle mass transfer in bulk, random packings of core-shell particles with varied shell thickness and shell diffusion coefficient.

PubMed

Daneyko, Anton; Hlushkou, Dzmitry; Baranau, Vasili; Khirevich, Siarhei; Seidel-Morgenstern, Andreas; Tallarek, Ulrich

2015-08-14

In recent years, chromatographic columns packed with core-shell particles have been widely used for efficient and fast separations at comparatively low operating pressure. However, the influence of the porous shell properties on the mass transfer kinetics in core-shell packings is still not fully understood. We report on results obtained with a modeling approach to simulate three-dimensional advective-diffusive transport in bulk random packings of monosized core-shell particles, covering a range of reduced mobile phase flow velocities from 0.5 up to 1000. The impact of the effective diffusivity of analyte molecules in the porous shell and the shell thickness on the resulting plate height was investigated. An extension of Giddings' theory of coupled eddy dispersion to account for retention of analyte molecules due to stagnant regions in porous shells with zero mobile phase flow velocity is presented. The plate height equation involving a modified eddy dispersion term excellently describes simulated data obtained for particle-packings with varied shell thickness and shell diffusion coefficient. It is confirmed that the model of trans-particle mass transfer resistance of core-shell particles by Kaczmarski and Guiochon [42] is applicable up to a constant factor. We analyze individual contributions to the plate height from different mass transfer mechanisms in dependence of the shell parameters. The simulations demonstrate that a reduction of plate height in packings of core-shell relative to fully porous particles arises mainly due to reduced trans-particle mass transfer resistance and transchannel eddy dispersion. Copyright © 2015 Elsevier B.V. All rights reserved.

Making A D-Latch Sensitive To Alpha Particles

NASA Technical Reports Server (NTRS)

Buehler, Martin G.; Blaes, Brent R.; Nixon, Robert H.

1994-01-01

Standard complementary metal oxide/semiconductor (CMOS) D-latch integrated circuit modified to increase susceptibility to single-event upsets (SEU's) (changes in logic state) caused by impacts of energetic alpha particles. Suitable for use in relatively inexpensive bench-scale SEU tests of itself and of related integrated circuits like static random-access memories.

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering

DTIC Science & Technology

2014-08-24

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering Isaac L. Manuel and Adrian N. Bishop Australian National University and...2 20 + vit , (21) where vit is Gaussian white noise with a random variance. We initialised the filters with the state xi0 = 0.1 for all i ∈ V . This

Tested Demonstrations. Brownian Motion: A Classroom Demonstration and Student Experiment.

ERIC Educational Resources Information Center

Kirksey, H. Graden; Jones, Richard F.

1988-01-01

Shows how video recordings of the Brownian motion of tiny particles may be made. Describes a classroom demonstration and cites a reported experiment designed to show the random nature of Brownian motion. Suggests a student experiment to discover the distance a tiny particle travels as a function of time. (MVL)

Pulmonary effects of inhaled concentrated fine particles (PM2.5) in somkers and patients with chronic obstructive lung disease

EPA Science Inventory

Although numerous field and epidemiological studies of particulate matter (PM) have strongly suggested that patients with COPD and smokers may be susceptible to fine particles (PM2.5), very little is known about the health effects on such sub-populations. In a randomized double...

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

Jin, C.; Potts, I.; Reeks, M. W., E-mail: mike.reeks@ncl.ac.uk

We present a simple stochastic quadrant model for calculating the transport and deposition of heavy particles in a fully developed turbulent boundary layer based on the statistics of wall-normal fluid velocity fluctuations obtained from a fully developed channel flow. Individual particles are tracked through the boundary layer via their interactions with a succession of random eddies found in each of the quadrants of the fluid Reynolds shear stress domain in a homogeneous Markov chain process. In this way, we are able to account directly for the influence of ejection and sweeping events as others have done but without resorting tomore » the use of adjustable parameters. Deposition rate predictions for a wide range of heavy particles predicted by the model compare well with benchmark experimental measurements. In addition, deposition rates are compared with those obtained from continuous random walk models and Langevin equation based ejection and sweep models which noticeably give significantly lower deposition rates. Various statistics related to the particle near wall behavior are also presented. Finally, we consider the model limitations in using the model to calculate deposition in more complex flows where the near wall turbulence may be significantly different.« less

Swarming behavior of gradient-responsive Brownian particles in a porous medium.

PubMed

Grančič, Peter; Štěpánek, František

2012-07-01

Active targeting by Brownian particles in a fluid-filled porous environment is investigated by computer simulation. The random motion of the particles is enhanced by diffusiophoresis with respect to concentration gradients of chemical signals released by the particles in the proximity of a target. The mathematical model, based on a combination of the Brownian dynamics method and a diffusion problem is formulated in terms of key parameters that include the particle diffusiophoretic mobility and the signaling threshold (the distance from the target at which the particles release their chemical signals). The results demonstrate that even a relatively simple chemical signaling scheme can lead to a complex collective behavior of the particles and can be a very efficient way of guiding a swarm of Brownian particles towards a target, similarly to the way colonies of living cells communicate via secondary messengers.

A study of active learning methods for named entity recognition in clinical text.

PubMed

Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

2015-12-01

Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random sampling, the best uncertainty based method saved 42% annotations in words. But the best diversity based method reduced only 7% annotation effort. In the simulated setting, AL methods, particularly uncertainty-sampling based approaches, seemed to significantly save annotation cost for the clinical NER task. The actual benefit of active learning in clinical NER should be further evaluated in a real-time setting. Copyright © 2015 Elsevier Inc. All rights reserved.

Shape Universality Classes in the Random Sequential Adsorption of Nonspherical Particles

NASA Astrophysics Data System (ADS)

Baule, Adrian

2017-07-01

Random sequential adsorption (RSA) of particles of a particular shape is used in a large variety of contexts to model particle aggregation and jamming. A key feature of these models is the observed algebraic time dependence of the asymptotic jamming coverage ˜t-ν as t →∞ . However, the exact value of the exponent ν is not known apart from the simplest case of the RSA of monodisperse spheres adsorbed on a line (Renyi's seminal "car parking problem"), where ν =1 can be derived analytically. Empirical simulation studies have conjectured on a case-by-case basis that for general nonspherical particles, ν =1 /(d +d ˜ ), where d denotes the dimension of the domain, and d ˜ the number of orientational degrees of freedom of a particle. Here, we solve this long-standing problem analytically for the d =1 case—the "Paris car parking problem." We prove, in particular, that the scaling exponent depends on the particle shape, contrary to the original conjecture and, remarkably, falls into two universality classes: (i) ν =1 /(1 +d ˜ /2 ) for shapes with a smooth contact distance, e.g., ellipsoids, and (ii) ν =1 /(1 +d ˜ ) for shapes with a singular contact distance, e.g., spherocylinders and polyhedra. The exact solution explains, in particular, why many empirically observed scalings fall in between these two limits.

Meta-analysis inside and outside particle physics: two traditions that should converge?

PubMed

Baker, Rose D; Jackson, Dan

2013-06-01

The use of meta-analysis in medicine and epidemiology really took off in the 1970s. However, in high-energy physics, the Particle Data Group has been carrying out meta-analyses of measurements of particle masses and other properties since 1957. Curiously, there has been virtually no interaction between those working inside and outside particle physics. In this paper, we use statistical models to study two major differences in practice. The first is the usefulness of systematic errors, which physicists are now beginning to quote in addition to statistical errors. The second is whether it is better to treat heterogeneity by scaling up errors as do the Particle Data Group or by adding a random effect as does the rest of the community. Besides fitting models, we derive and use an exact test of the error-scaling hypothesis. We also discuss the other methodological differences between the two streams of meta-analysis. Our conclusion is that systematic errors are not currently very useful and that the conventional random effects model, as routinely used in meta-analysis, has a useful role to play in particle physics. The moral we draw for statisticians is that we should be more willing to explore 'grassroots' areas of statistical application, so that good statistical practice can flow both from and back to the statistical mainstream. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Fluorescence imaging of single-molecule retention trajectories in reversed-phase chromatographic particles.

PubMed

Cooper, Justin T; Peterson, Eric M; Harris, Joel M

2013-10-01

Due to its high specific surface area and chemical stability, porous silica is used as a support structure in numerous applications, including heterogeneous catalysis, biomolecule immobilization, sensors, and liquid chromatography. Reversed-phase liquid chromatography (RPLC), which uses porous silica support particles, has become an indispensable separations tool in quality control, pharmaceutics, and environmental analysis requiring identification of compounds in mixtures. For complex samples, the need for higher resolution separations requires an understanding of the time scale of processes responsible for analyte retention in the stationary phase. In the present work, single-molecule fluorescence imaging is used to observe transport of individual molecules within RPLC porous silica particles. This technique allows direct measurement of intraparticle molecular residence times, intraparticle diffusion rates, and the spatial distribution of molecules within the particle. On the basis of the localization uncertainty and characteristic measured diffusion rates, statistical criteria were developed to resolve the frame-to-frame behavior of molecules into moving and stuck events. The measured diffusion coefficient of moving molecules was used in a Monte Carlo simulation of a random-walk model within the cylindrical geometry of the particle diameter and microscope depth-of-field. The simulated molecular transport is in good agreement with the experimental data, indicating transport of moving molecules in the porous particle is described by a random-walk. Histograms of stuck-molecule event times, locations, and their contributions to intraparticle residence times were also characterized.

New description of charged particle propagation in random magnetic fields

NASA Technical Reports Server (NTRS)

Earl, James A.

1994-01-01

When charged particles spiral along a large constant magnetic field, their trajectories are scattered by random components that are superposed on the guiding field. In the simplest analysis of this situation, scattering causes the particles to diffuse parallel to the guiding field. At the next level of approximation, moving pulses that correspond to a coherent mode of propagation are present, but they are represented by delta-functions whose infinitely narrow width makes no sense physically and is inconsistent with the finite duration of coherent pulses observed in solar energetic particle events. To derive a more realistic description, the transport problem is formulated in terms of 4 x 4 matrices, which derive from a representation of the particle distribution function in terms of eigenfunctions of the scattering operator, and which lead to useful approximations that give explicit predictions of the detailed evolution not only of the coherent pulses, but also of the diffusive wake. More specifically, the new description embodies a simple convolution of a narrow Gaussian with the solutions above that involve delta-functions, but with a slightly reduced coherent velocity. The validity of these approximations, which can easily be calculated on a desktop computer, has been exhaustively confirmed by comparison with results of Monte Carlo simulations which kept track of 50 million particles and which were carried out on the Maspar computer at Goddard Space Flight Center.

CW-SSIM kernel based random forest for image classification

NASA Astrophysics Data System (ADS)

Fan, Guangzhe; Wang, Zhou; Wang, Jiheng

2010-07-01

Complex wavelet structural similarity (CW-SSIM) index has been proposed as a powerful image similarity metric that is robust to translation, scaling and rotation of images, but how to employ it in image classification applications has not been deeply investigated. In this paper, we incorporate CW-SSIM as a kernel function into a random forest learning algorithm. This leads to a novel image classification approach that does not require a feature extraction or dimension reduction stage at the front end. We use hand-written digit recognition as an example to demonstrate our algorithm. We compare the performance of the proposed approach with random forest learning based on other kernels, including the widely adopted Gaussian and the inner product kernels. Empirical evidences show that the proposed method is superior in its classification power. We also compared our proposed approach with the direct random forest method without kernel and the popular kernel-learning method support vector machine. Our test results based on both simulated and realworld data suggest that the proposed approach works superior to traditional methods without the feature selection procedure.

Practicing Field Hockey Skills Along the Contextual Interference Continuum: A Comparison of Five Practice Schedules

PubMed Central

Cheong, Jadeera Phaik Geok; Lay, Brendan; Grove, J. Robert; Medic, Nikola; Razman, Rizal

2012-01-01

To overcome the weakness of the contextual interference (CI) effect within applied settings, Brady, 2008 recommended that the amount of interference be manipulated. This study investigated the effect of five practice schedules on the learning of three field hockey skills. Fifty-five pre-university students performed a total of 90 trials for each skill under blocked, mixed or random practice orders. Results showed a significant time effect with all five practice conditions leading to improvements in acquisition and learning of the skills. No significant differences were found between the groups. The findings of the present study did not support the CI effect and suggest that either blocked, mixed, or random practice schedules can be used effectively when structuring practice for beginners. Key pointsThe contextual interference effect did not surface when using sport skills.There appears to be no difference between blocked and random practice schedules in the learning of field hockey skills.Low (blocked), moderate (mixed) or high (random) interference practice schedules can be used effectively when conducting a multiple skill practice session for beginners. PMID:24149204

Practicing field hockey skills along the contextual interference continuum: a comparison of five practice schedules.

PubMed

Cheong, Jadeera Phaik Geok; Lay, Brendan; Grove, J Robert; Medic, Nikola; Razman, Rizal

2012-01-01

To overcome the weakness of the contextual interference (CI) effect within applied settings, Brady, 2008 recommended that the amount of interference be manipulated. This study investigated the effect of five practice schedules on the learning of three field hockey skills. Fifty-five pre-university students performed a total of 90 trials for each skill under blocked, mixed or random practice orders. Results showed a significant time effect with all five practice conditions leading to improvements in acquisition and learning of the skills. No significant differences were found between the groups. The findings of the present study did not support the CI effect and suggest that either blocked, mixed, or random practice schedules can be used effectively when structuring practice for beginners. Key pointsThe contextual interference effect did not surface when using sport skills.There appears to be no difference between blocked and random practice schedules in the learning of field hockey skills.Low (blocked), moderate (mixed) or high (random) interference practice schedules can be used effectively when conducting a multiple skill practice session for beginners.

Charged Particle Diffusion in Isotropic Random Static Magnetic Fields

NASA Astrophysics Data System (ADS)

Subedi, P.; Sonsrettee, W.; Matthaeus, W. H.; Ruffolo, D. J.; Wan, M.; Montgomery, D.

2013-12-01

Study of the transport and diffusion of charged particles in a turbulent magnetic field remains a subject of considerable interest. Research has most frequently concentrated on determining the diffusion coefficient in the presence of a mean magnetic field. Here we consider Diffusion of charged particles in fully three dimensional statistically isotropic magnetic field turbulence with no mean field which is pertinent to many astrophysical situations. We classify different regions of particle energy depending upon the ratio of Larmor radius of the charged particle to the characteristic outer length scale of turbulence. We propose three different theoretical models to calculate the diffusion coefficient each applicable to a distinct range of particle energies. The theoretical results are compared with those from computer simulations, showing very good agreement.

Effects of Mobile Phone-Based App Learning Compared to Computer-Based Web Learning on Nursing Students: Pilot Randomized Controlled Trial

PubMed Central

2015-01-01

Objectives This study aimed to determine the effect of mobile-based discussion versus computer-based discussion on self-directed learning readiness, academic motivation, learner-interface interaction, and flow state. Methods This randomized controlled trial was conducted at one university. Eighty-six nursing students who were able to use a computer, had home Internet access, and used a mobile phone were recruited. Participants were randomly assigned to either the mobile phone app-based discussion group (n = 45) or a computer web-based discussion group (n = 41). The effect was measured at before and after an online discussion via self-reported surveys that addressed academic motivation, self-directed learning readiness, time distortion, learner-learner interaction, learner-interface interaction, and flow state. Results The change in extrinsic motivation on identified regulation in the academic motivation (p = 0.011) as well as independence and ability to use basic study (p = 0.047) and positive orientation to the future in self-directed learning readiness (p = 0.021) from pre-intervention to post-intervention was significantly more positive in the mobile phone app-based group compared to the computer web-based discussion group. Interaction between learner and interface (p = 0.002), having clear goals (p = 0.012), and giving and receiving unambiguous feedback (p = 0.049) in flow state was significantly higher in the mobile phone app-based discussion group than it was in the computer web-based discussion group at post-test. Conclusions The mobile phone might offer more valuable learning opportunities for discussion teaching and learning methods in terms of self-directed learning readiness, academic motivation, learner-interface interaction, and the flow state of the learning process compared to the computer. PMID:25995965

Driving a Superconductor to Insulator Transition with Random Gauge Fields.

PubMed

Nguyen, H Q; Hollen, S M; Shainline, J; Xu, J M; Valles, J M

2016-11-30

Typically the disorder that alters the interference of particle waves to produce Anderson localization is potential scattering from randomly placed impurities. Here we show that disorder in the form of random gauge fields that act directly on particle phases can also drive localization. We present evidence of a superfluid bose glass to insulator transition at a critical level of this gauge field disorder in a nano-patterned array of amorphous Bi islands. This transition shows signs of metallic transport near the critical point characterized by a resistance , indicative of a quantum phase transition. The critical disorder depends on interisland coupling in agreement with recent Quantum Monte Carlo simulations. We discuss how this disorder tuned SIT differs from the common frustration tuned SIT that also occurs in magnetic fields. Its discovery enables new high fidelity comparisons between theoretical and experimental studies of disorder effects on quantum critical systems.

Geometrical effects on the electron residence time in semiconductor nano-particles

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

Koochi, Hakimeh; Ebrahimi, Fatemeh, E-mail: f-ebrahimi@birjand.ac.ir; Solar Energy Research Group, University of Birjand, Birjand

2014-09-07

We have used random walk (RW) numerical simulations to investigate the influence of the geometry on the statistics of the electron residence time τ{sub r} in a trap-limited diffusion process through semiconductor nano-particles. This is an important parameter in coarse-grained modeling of charge carrier transport in nano-structured semiconductor films. The traps have been distributed randomly on the surface (r{sup 2} model) or through the whole particle (r{sup 3} model) with a specified density. The trap energies have been taken from an exponential distribution and the traps release time is assumed to be a stochastic variable. We have carried out (RW)more » simulations to study the effect of coordination number, the spatial arrangement of the neighbors and the size of nano-particles on the statistics of τ{sub r}. It has been observed that by increasing the coordination number n, the average value of electron residence time, τ{sup ¯}{sub r} rapidly decreases to an asymptotic value. For a fixed coordination number n, the electron's mean residence time does not depend on the neighbors' spatial arrangement. In other words, τ{sup ¯}{sub r} is a porosity-dependence, local parameter which generally varies remarkably from site to site, unless we are dealing with highly ordered structures. We have also examined the effect of nano-particle size d on the statistical behavior of τ{sup ¯}{sub r}. Our simulations indicate that for volume distribution of traps, τ{sup ¯}{sub r} scales as d{sup 2}. For a surface distribution of traps τ{sup ¯}{sub r} increases almost linearly with d. This leads to the prediction of a linear dependence of the diffusion coefficient D on the particle size d in ordered structures or random structures above the critical concentration which is in accordance with experimental observations.« less

News Teaching: The epiSTEMe project: KS3 maths and science improvement Field trip: Pupils learn physics in a stately home Conference: ShowPhysics welcomes fun in Europe Student numbers: Physics numbers increase in UK Tournament: Physics tournament travels to Singapore Particle physics: Hadron Collider sets new record Astronomy: Take your classroom into space Forthcoming Events

NASA Astrophysics Data System (ADS)

2010-05-01

Teaching: The epiSTEMe project: KS3 maths and science improvement Field trip: Pupils learn physics in a stately home Conference: ShowPhysics welcomes fun in Europe Student numbers: Physics numbers increase in UK Tournament: Physics tournament travels to Singapore Particle physics: Hadron Collider sets new record Astronomy: Take your classroom into space Forthcoming Events

Toward Solutions: The Work of the Chemistry Action-Research Group. Learning in Science Project. Working Paper No. 35.

ERIC Educational Resources Information Center

Osborne, Roger; And Others

In the action-research phase of the Learning in Science Project, four groups of people worked on problems identified in the project's second (in-depth) phase. The Chemistry Action-Research Group considered problems related to the teaching and learning of ideas associated with particles and physical/chemical changes. Based on findings during the…

A randomized placebo-controlled pilot study of pravastatin as an adjunctive therapy in schizophrenia patients: effect on inflammation, psychopathology, cognition and lipid metabolism

PubMed Central

Vincenzi, Brenda; Stock, Shannon; Borba, Christina P.C.; Cleary, Sarah M.; Oppenheim, Claire E.; Petruzzi, Liana J.; Fan, Xiaoduo; Copeland, Paul M.; Freudenreich, Oliver; Cather, Corinne; Henderson, David C.

2015-01-01

Objective The aim of this study was to investigate the role of pravastatin, as an adjunctive therapy, on inflammatory markers, lipid and glucose metabolism, psychopathology, and cognition in subjects with schizophrenia and schizoaffective disorder. Methods Schizophrenia or schizoaffective subjects (N=60) were randomized to receive either a 12-week supply of pravastatin 40 mg/day or placebo treatment. Anthropometric measures, lipids and glucose metabolism, inflammatory markers, psychopathology and cognitive performance were assessed at baseline, 6 weeks and 12 weeks. Results Pravastatin use was associated with a significant decrease in total cholesterol, low density lipoprotein (LDL) cholesterol and LDL particle number levels, but was not associated with any significant changes in cognition or psychopathology in the participants, except a significant decrease in the Positive and Negative Syndrome Scale (PANSS) positive symptoms score from baseline to week 6. However, this decrease failed to remain significant at 12 weeks. Interestingly, triglycerides, LDLCholesterol, Total cholesterol, LDL particle number, small LDL particle number, large very low density lipoprotein (VLDL) particle number and c-reactive protein (CRP) followed a similar pattern at 6 and 12 weeks as psychopathology. Conclusions These results suggest that a randomized trial with a larger sample size and a higher dosage of pravastatin, and would be helpful in further evaluating the anti-inflammatory properties of pravastatin, its association with improvements in cognitive symptoms, and its potential to reduce positive and negative symptoms associated with schizophrenia or schizoaffective disorders. PMID:25261882

Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial.

PubMed

Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

2014-01-01

This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001) and in the follow-up test (P<0.01). Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04). Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills.

Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial

PubMed Central

Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

2014-01-01

Background and aims This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Materials and methods Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. Results The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001) and in the follow-up test (P<0.01). Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04). Conclusion Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills. PMID:25152638

Modulating effects in learned helplessness of dyadic dominance-submission relations.

PubMed

Díaz-Berciano, Cristina; de Vicente, Francisco; Fontecha, Elisa

2008-01-01

In this experiment, learned helplessness was studied from an ethological perspective by examining individual differences in social dominance and its influence on the effects of helplessness. Ninety animals were used, 30 randomly selected and 60 selected because of their clear dominance or submission. Each condition (dominant, submissive, and random) was distributed in three subgroups corresponding to the triadic design. The test consisted of an escape/avoidance task. The results showed that the animals in the uncontrollable condition performed worse than those in the controllable and no treatment conditions. Social submission and dominance reduced vulnerability of the subjects against learned helplessness. Submission had a facilitating effect on subsequent learning, independently of whether pretreatment was controllability or uncontrollability. Learned mastery was observed in the submissive condition, because submission benefited the subjects in the controllable condition in comparison with the untreated subjects, and dominance impaired the subjects in the controllable condition. Copyright 2007 Wiley-Liss, Inc.

Enhancing learning using questions, adjunct to science charts

NASA Astrophysics Data System (ADS)

Holliday, William G.; Benson, Garth

This study supported two hypotheses. First, adjunct questions interacted with a science chart so powerfully that content established as difficult to learn in the pilot and in this study's control groups became easier to learn when charted. Second, students familiar with the chart test before instruction (test exposure) were better prepared to take this test after instruction. This adjunct-question study examined the generalizability of selective-attention and academic-studying hypotheses to a modified science chart medium. About 300 high school students were randomly assigned to four conditions each including a vitamin chart (chart only, test exposure, importance of questions emphasized to students by teachers, and combinational conditions - test exposure and question importance) across 16 biology classrooms. Then these same students were again randomly assigned within each classroom to a control and to four question treatments no questions, questions focusing on easy-to-learn charted content, questions focusing on difficult-to-learn charted content, and a combinational treatment.

Enhancing learning using questions adjunct to science charts

NASA Astrophysics Data System (ADS)

Holliday, William G.; Benson, Garth

This study supported two hypotheses. First, adjunct questions interacted with a science chart so powerfully that content established as difficult to learn in the pilot and in this study's control groups became easier to learn when charted. Second, students familiar with the chart test before instruction (test exposure) were better prepared to take this test after instruction. This adjunct-question study examined the generalizability of selective-attention and academic-studying hypotheses to a modified science chart medium. About 300 high school students were randomly assigned to four conditions each including a vitamin chart (chart only, test exposure, importance of questions emphasized to students by teachers, and combinational conditions--test exposure and question importance) across 16 biology classrooms. Then these same students were again randomly assigned within each classroom to a control and to four question treatments (no questions, questions focusing on easy-to-learn charted content, questions focusing on difficult-to-learn charted content, and a combinational treatment).

Computational ghost imaging using deep learning

NASA Astrophysics Data System (ADS)

Shimobaba, Tomoyoshi; Endo, Yutaka; Nishitsuji, Takashi; Takahashi, Takayuki; Nagahama, Yuki; Hasegawa, Satoki; Sano, Marie; Hirayama, Ryuji; Kakue, Takashi; Shiraki, Atsushi; Ito, Tomoyoshi

2018-04-01

Computational ghost imaging (CGI) is a single-pixel imaging technique that exploits the correlation between known random patterns and the measured intensity of light transmitted (or reflected) by an object. Although CGI can obtain two- or three-dimensional images with a single or a few bucket detectors, the quality of the reconstructed images is reduced by noise due to the reconstruction of images from random patterns. In this study, we improve the quality of CGI images using deep learning. A deep neural network is used to automatically learn the features of noise-contaminated CGI images. After training, the network is able to predict low-noise images from new noise-contaminated CGI images.

Collective states in social systems with interacting learning agents

NASA Astrophysics Data System (ADS)

Semeshenko, Viktoriya; Gordon, Mirta B.; Nadal, Jean-Pierre

2008-08-01

We study the implications of social interactions and individual learning features on consumer demand in a simple market model. We consider a social system of interacting heterogeneous agents with learning abilities. Given a fixed price, agents repeatedly decide whether or not to buy a unit of a good, so as to maximize their expected utilities. This model is close to Random Field Ising Models, where the random field corresponds to the idiosyncratic willingness to pay. We show that the equilibrium reached depends on the nature of the information agents use to estimate their expected utilities. It may be different from the systems’ Nash equilibria.

Emotional Design in Multimedia Learning

ERIC Educational Resources Information Center

Um, Eunjoon; Plass, Jan L.; Hayward, Elizabeth O.; Homer, Bruce D.

2012-01-01

Can multimedia learning environments be designed to foster positive emotions that will improve learning and related affective outcomes? College students (N = 118) were randomly assigned to 4 conditions created by 2 factors related to learners' emotion: "external mood induction" (positive vs. neutral emotions) and "emotional design induction"…

Effects of Traditional, Blended and E-Learning on Students' Achievement in Higher Education

ERIC Educational Resources Information Center

Al-Qahtani, Awadh A. Y.; Higgins, S. E.

2013-01-01

The study investigates the effect of e-learning, blended learning and classroom learning on students' achievement. Two experimental groups together with a control group from Umm Al-Qura University in Saudi Arabia were identified randomly. To assess students' achievement in the different groups, pre- and post-achievement tests were used. The…

The Effect of Graphical Representation on the Learner's Learning Interest and Achievement in Multimedia Learning

ERIC Educational Resources Information Center

Park, Sanghoon; Lim, Jung

2004-01-01

The purpose of this paper was to investigate the effects of different types of visual illustrations on learner's learning interest, motivation and achievement, especially in multimedia learning. The participants were drawn from two classes of an "Introduction to Educational Technology" course and randomly assigned to one of the three…

Using Random Parameter Logit in Open and Distance Learning (ODL) Institutions in Malaysia

ERIC Educational Resources Information Center

Chiam, Chooi Chea; Loo, SzeWei

2015-01-01

Attention has been drawn to Open Distance Learning (ODL) as a mode for teaching and learning with the advancement in communication via the Internet. Education today has expanded the role of ICT in learning and knowledge generation, leveraging on Internet technology to transmit education across the country. Due to the advancement of technology and…

An Experimental Investigation into the Efficiency of Cooperative Learning with Consideration of Multiple Grouping Criteria

ERIC Educational Resources Information Center

Hsiung, C. -M.

2010-01-01

The present study conducts an experimental investigation to compare the efficiency of the cooperative learning method with that of the traditional learning method. A total of 42 engineering students are randomly assigned to the two learning conditions and are formed into mixed-ability groups comprising three team members. In addition to the…

Incorporating Meaningful Gamification in a Blended Learning Research Methods Class: Examining Student Learning, Engagement, and Affective Outcomes

ERIC Educational Resources Information Center

Tan, Meng; Hew, Khe Foon

2016-01-01

In this study, we investigated how the use of meaningful gamification affects student learning, engagement, and affective outcomes in a short, 3-day blended learning research methods class using a combination of experimental and qualitative research methods. Twenty-two postgraduates were randomly split into two groups taught by the same…

Does Comparing Solution Methods Facilitate Conceptual and Procedural Knowledge? An Experimental Study on Learning to Solve Equations

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Star, Jon R.

2007-01-01

Encouraging students to share and compare solution methods is a key component of reform efforts in mathematics, and comparison is emerging as a fundamental learning mechanism. To experimentally evaluate the effects of comparison for mathematics learning, the authors randomly assigned 70 seventh-grade students to learn about algebra equation…

RANDOM EVOLUTIONS, MARKOV CHAINS, AND SYSTEMS OF PARTIAL DIFFERENTIAL EQUATIONS

PubMed Central

Griego, R. J.; Hersh, R.

1969-01-01

Several authors have considered Markov processes defined by the motion of a particle on a fixed line with a random velocity1, 6, 8, 10 or a random diffusivity.5, 12 A “random evolution” is a natural but apparently new generalization of this notion. In this note we hope to show that this concept leads to simple and powerful applications of probabilistic tools to initial-value problems of both parabolic and hyperbolic type. We obtain existence theorems, representation theorems, and asymptotic formulas, both old and new. PMID:16578690

Interactive learning in 2×2 normal form games by neural network agents

NASA Astrophysics Data System (ADS)

Spiliopoulos, Leonidas

2012-11-01

This paper models the learning process of populations of randomly rematched tabula rasa neural network (NN) agents playing randomly generated 2×2 normal form games of all strategic classes. This approach has greater external validity than the existing models in the literature, each of which is usually applicable to narrow subsets of classes of games (often a single game) and/or to fixed matching protocols. The learning prowess of NNs with hidden layers was impressive as they learned to play unique pure strategy equilibria with near certainty, adhered to principles of dominance and iterated dominance, and exhibited a preference for risk-dominant equilibria. In contrast, perceptron NNs were found to perform significantly worse than hidden layer NN agents and human subjects in experimental studies.

Calibration of Discrete Random Walk (DRW) Model via G.I Taylor's Dispersion Theory

NASA Astrophysics Data System (ADS)

Javaherchi, Teymour; Aliseda, Alberto

2012-11-01

Prediction of particle dispersion in turbulent flows is still an important challenge with many applications to environmental, as well as industrial, fluid mechanics. Several models of dispersion have been developed to predict particle trajectories and their relative velocities, in combination with a RANS-based simulation of the background flow. The interaction of the particles with the velocity fluctuations at different turbulent scales represents a significant difficulty in generalizing the models to the wide range of flows where they are used. We focus our attention on the Discrete Random Walk (DRW) model applied to flow in a channel, particularly to the selection of eddies lifetimes as realizations of a Poisson distribution with a mean value proportional to κ / ɛ . We present a general method to determine the constant of this proportionality by matching the DRW model dispersion predictions for fluid element and particle dispersion to G.I Taylor's classical dispersion theory. This model parameter is critical to the magnitude of predicted dispersion. A case study of its influence on sedimentation of suspended particles in a tidal channel with an array of Marine Hydrokinetic (MHK) turbines highlights the dependency of results on this time scale parameter. Support from US DOE through the Northwest National Marine Renewable Energy Center, a UW-OSU partnership.

Particle Acceleration at the Sun and in the Heliosphere

NASA Technical Reports Server (NTRS)

Reames, Donald V.

1999-01-01

Energetic particles are accelerated in rich profusion at sites throughout the heliosphere. They come from solar flares in the low corona, from shock waves driven outward by coronal mass ejections (CMEs), from planetary magnetospheres and bow shocks. They come from corotating interaction regions (CIRs) produced by high-speed streams in the solar wind, and from the heliospheric termination shock at the outer edge of the heliospheric cavity. We sample all these populations near Earth, but can distinguish them readily by their element and isotope abundances, ionization states, energy spectra, angular distributions and time behavior. Remote spacecraft have probed the spatial distributions of the particles and examined new sources in situ. Most acceleration sources can be "seen" only by direct observation of the particles; few photons are produced at these sites. Wave-particle interactions are an essential feature in acceleration sources and, for shock acceleration, new evidence of energetic-proton-generated waves has come from abundance variations and from local cross-field scattering. Element abundances often tell us the physics the source plasma itself, prior to acceleration. By comparing different populations, we learn more about the sources, and about the physics of acceleration and transport, than we can possibly learn from one source alone.

The relationship of dynamical heterogeneity to the Adam-Gibbs and random first-order transition theories of glass formation.

PubMed

Starr, Francis W; Douglas, Jack F; Sastry, Srikanth

2013-03-28

We carefully examine common measures of dynamical heterogeneity for a model polymer melt and test how these scales compare with those hypothesized by the Adam and Gibbs (AG) and random first-order transition (RFOT) theories of relaxation in glass-forming liquids. To this end, we first analyze clusters of highly mobile particles, the string-like collective motion of these mobile particles, and clusters of relative low mobility. We show that the time scale of the high-mobility clusters and strings is associated with a diffusive time scale, while the low-mobility particles' time scale relates to a structural relaxation time. The difference of the characteristic times for the high- and low-mobility particles naturally explains the well-known decoupling of diffusion and structural relaxation time scales. Despite the inherent difference of dynamics between high- and low-mobility particles, we find a high degree of similarity in the geometrical structure of these particle clusters. In particular, we show that the fractal dimensions of these clusters are consistent with those of swollen branched polymers or branched polymers with screened excluded-volume interactions, corresponding to lattice animals and percolation clusters, respectively. In contrast, the fractal dimension of the strings crosses over from that of self-avoiding walks for small strings, to simple random walks for longer, more strongly interacting, strings, corresponding to flexible polymers with screened excluded-volume interactions. We examine the appropriateness of identifying the size scales of either mobile particle clusters or strings with the size of cooperatively rearranging regions (CRR) in the AG and RFOT theories. We find that the string size appears to be the most consistent measure of CRR for both the AG and RFOT models. Identifying strings or clusters with the "mosaic" length of the RFOT model relaxes the conventional assumption that the "entropic droplets" are compact. We also confirm the validity of the entropy formulation of the AG theory, constraining the exponent values of the RFOT theory. This constraint, together with the analysis of size scales, enables us to estimate the characteristic exponents of RFOT.

One Hundred Ways to be Non-Fickian - A Rigorous Multi-Variate Statistical Analysis of Pore-Scale Transport

NASA Astrophysics Data System (ADS)

Most, Sebastian; Nowak, Wolfgang; Bijeljic, Branko

2015-04-01

Fickian transport in groundwater flow is the exception rather than the rule. Transport in porous media is frequently simulated via particle methods (i.e. particle tracking random walk (PTRW) or continuous time random walk (CTRW)). These methods formulate transport as a stochastic process of particle position increments. At the pore scale, geometry and micro-heterogeneities prohibit the commonly made assumption of independent and normally distributed increments to represent dispersion. Many recent particle methods seek to loosen this assumption. Hence, it is important to get a better understanding of the processes at pore scale. For our analysis we track the positions of 10.000 particles migrating through the pore space over time. The data we use come from micro CT scans of a homogeneous sandstone and encompass about 10 grain sizes. Based on those images we discretize the pore structure and simulate flow at the pore scale based on the Navier-Stokes equation. This flow field realistically describes flow inside the pore space and we do not need to add artificial dispersion during the transport simulation. Next, we use particle tracking random walk and simulate pore-scale transport. Finally, we use the obtained particle trajectories to do a multivariate statistical analysis of the particle motion at the pore scale. Our analysis is based on copulas. Every multivariate joint distribution is a combination of its univariate marginal distributions. The copula represents the dependence structure of those univariate marginals and is therefore useful to observe correlation and non-Gaussian interactions (i.e. non-Fickian transport). The first goal of this analysis is to better understand the validity regions of commonly made assumptions. We are investigating three different transport distances: 1) The distance where the statistical dependence between particle increments can be modelled as an order-one Markov process. This would be the Markovian distance for the process, where the validity of yet-unexplored non-Gaussian-but-Markovian random walks start. 2) The distance where bivariate statistical dependence simplifies to a multi-Gaussian dependence based on simple linear correlation (validity of correlated PTRW/CTRW). 3) The distance of complete statistical independence (validity of classical PTRW/CTRW). The second objective is to reveal characteristic dependencies influencing transport the most. Those dependencies can be very complex. Copulas are highly capable of representing linear dependence as well as non-linear dependence. With that tool we are able to detect persistent characteristics dominating transport even across different scales. The results derived from our experimental data set suggest that there are many more non-Fickian aspects of pore-scale transport than the univariate statistics of longitudinal displacements. Non-Fickianity can also be found in transverse displacements, and in the relations between increments at different time steps. Also, the found dependence is non-linear (i.e. beyond simple correlation) and persists over long distances. Thus, our results strongly support the further refinement of techniques like correlated PTRW or correlated CTRW towards non-linear statistical relations.

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

Impact of self-assessment questions and learning styles in Web-based learning: a randomized, controlled, crossover trial.

PubMed

Cook, David A; Thompson, Warren G; Thomas, Kris G; Thomas, Matthew R; Pankratz, V Shane

2006-03-01

To determine the effect of self-assessment questions on learners' knowledge and format preference in a Web-based course, and investigate associations between learning styles and outcomes. The authors conducted a randomized, controlled, crossover trial in the continuity clinics of the Mayo-Rochester internal medicine residency program during the 2003-04 academic year. Case-based self-assessment questions were added to Web-based modules covering topics in ambulatory internal medicine. Participants completed two modules with questions and two modules without questions, with sequence randomly assigned. Outcomes included knowledge assessed after each module, format preference, and learning style assessed using the Index of Learning Styles. A total of 121 of 146 residents (83%) consented. Residents had higher test scores when using the question format (mean +/- standard error, 78.9% +/- 1.0) than when using the standard format (76.2% +/- 1.0, p = .006). Residents preferring the question format scored higher (79.7% +/- 1.1) than those preferring standard (69.5% +/- 2.3, p < .001). Learning styles did not affect scores except that visual-verbal "intermediate" learners (80.6% +/- 1.4) and visual learners (77.5% +/- 1.3) did better than verbal learners (70.9% +/- 3.0, p = .003 and p = .033, respectively). Sixty-five of 78 residents (83.3%, 95% CI 73.2-90.8%) preferred the question format. Learning styles were not associated with preference (p > .384). Although the question format took longer than the standard format (60.4 +/- 3.6 versus 44.3 +/- 3.3 minutes, p < .001), 55 of 77 residents (71.4%, 60.0-81.2%) reported that it was more efficient. Instructional methods that actively engage learners improve learning outcomes. These findings hold implications for both Web-based learning and "traditional" educational activities. Future research, in both Web-based learning and other teaching modalities, should focus on further defining the effectiveness of selected instructional methods in specific learning contexts.

Impact of e-learning on nurses' and student nurses knowledge, skills, and satisfaction: a systematic review and meta-analysis.

PubMed

Lahti, Mari; Hätönen, Heli; Välimäki, Maritta

2014-01-01

To review the impact of e-learning on nurses' and nursing student's knowledge, skills and satisfaction related to e-learning. We conducted a systematic review and meta-analysis of randomized controlled trials (RCT) to assess the impact of e-learning on nurses' and nursing student's knowledge, skills and satisfaction. Electronic databases including MEDLINE (1948-2010), CINAHL (1981-2010), Psychinfo (1967-2010) and Eric (1966-2010) were searched in May 2010 and again in December 2010. All RCT studies evaluating the effectiveness of e-learning and differentiating between traditional learning methods among nurses were included. Data was extracted related to the purpose of the trial, sample, measurements used, index test results and reference standard. An extraction tool developed for Cochrane reviews was used. Methodological quality of eligible trials was assessed. 11 trials were eligible for inclusion in the analysis. We identified 11 randomized controlled trials including a total of 2491 nurses and student nurses'. First, the random effect size for four studies showed some improvement associated with e-learning compared to traditional techniques on knowledge. However, the difference was not statistically significant (p=0.39, MD 0.44, 95% CI -0.57 to 1.46). Second, one study reported a slight impact on e-learning on skills, but the difference was not statistically significant, either (p=0.13, MD 0.03, 95% CI -0.09 to 0.69). And third, no results on nurses or student nurses' satisfaction could be reported as the statistical data from three possible studies were not available. Overall, there was no statistical difference between groups in e-learning and traditional learning relating to nurses' or student nurses' knowledge, skills and satisfaction. E-learning can, however, offer an alternative method of education. In future, more studies following the CONSORT and QUOROM statements are needed to evaluate the effects of these interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Remote-online case-based learning: A comparison of remote-online and face-to-face, case-based learning - a randomized controlled trial.

PubMed

Nicklen, Peter; Keating, Jenny L; Paynter, Sophie; Storr, Michael; Maloney, Stephen

2016-01-01

Case-based learning (CBL) is an educational approach where students work in small, collaborative groups to solve problems. Computer assisted learning (CAL) is the implementation of computer technology in education. The purpose of this study was to compare the effects of a remote-online CBL (RO-CBL) with traditional face-to-face CBL on learning the outcomes of undergraduate physiotherapy students. Participants were randomized to either the control (face-to-face CBL) or to the CAL intervention (RO-CBL). The entire 3rd year physiotherapy cohort (n = 41) at Monash University, Victoria, Australia, were invited to participate in the randomized controlled trial. Outcomes included a postintervention multiple-choice test evaluating the knowledge gained from the CBL, a self-assessment of learning based on examinable learning objectives and student satisfaction with the CBL. In addition, a focus group was conducted investigating perceptions and responses to the online format. Thirty-eight students (control n = 19, intervention n = 19) participated in two CBL sessions and completed the outcome assessments. CBL median scores for the postintervention multiple-choice test were comparable (Wilcoxon rank sum P = 0.61) (median/10 [range] intervention group: 9 [8-10] control group: 10 [7-10]). Of the 15 examinable learning objectives, eight were significantly in favor of the control group, suggesting a greater perceived depth of learning. Eighty-four percent of students (16/19) disagreed with the statement "I enjoyed the method of CBL delivery." Key themes identified from the focus group included risks associated with the implementation of, challenges of communicating in, and flexibility offered, by web-based programs. RO-CBL appears to provide students with a comparable learning experience to traditional CBL. Procedural and infrastructure factors need to be addressed in future studies to counter student dissatisfaction and decreased perceived depth of learning.

Preparation of Octadecyltrichlorosilane Nanopatterns Using Particle Lithography: An Atomic Force Microscopy Laboratory

ERIC Educational Resources Information Center

Highland, Zachary L.; Saner, ChaMarra K.; Garno, Jayne C.

2018-01-01

Experiments are described that involve undergraduates learning concepts of nanoscience and chemistry. Students prepare nanopatterns of organosilane films using protocols of particle lithography. A few basic techniques are needed to prepare samples, such as centrifuging, mixing, heating, and drying. Students obtain hands-on skills with nanoscale…

Individual Differences in L2 Acquisition of Japanese Particles "WA" and "GA"

ERIC Educational Resources Information Center

Mori, Sachiho

2008-01-01

Although the L2 acquisition studies of Japanese particles "WA" and "GA" were investigated by many researchers (Sakamoto, 2000), they completely ignored learners' individual differences. Indeed, learners' individualities are important factors for the L2 learning (Lightbrown & Spada, 1999). Thus, this research explored whether learners' individual…

On real statistics of relaxation in gases

NASA Astrophysics Data System (ADS)

Kuzovlev, Yu. E.

2016-02-01

By example of a particle interacting with ideal gas, it is shown that the statistics of collisions in statistical mechanics at any value of the gas rarefaction parameter qualitatively differ from that conjugated with Boltzmann's hypothetical molecular chaos and kinetic equation. In reality, the probability of collisions of the particle in itself is random. Because of that, the relaxation of particle velocity acquires a power-law asymptotic behavior. An estimate of its exponent is suggested on the basis of simple kinematic reasons.

Auditory Magnetoencephalographic Frequency-Tagged Responses Mirror the Ongoing Segmentation Processes Underlying Statistical Learning.

PubMed

Farthouat, Juliane; Franco, Ana; Mary, Alison; Delpouve, Julie; Wens, Vincent; Op de Beeck, Marc; De Tiège, Xavier; Peigneux, Philippe

2017-03-01

Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic frequency-tagged responses to investigate the neural sources and temporal development of the ongoing brain activity that supports the detection of regularities embedded in auditory streams. Participants passively listened to statistical streams in which tones were grouped as triplets, and to random streams in which tones were randomly presented. Results show that during exposure to statistical (vs. random) streams, tritone frequency-related responses reflecting the learning of regularities embedded in the stream increased in the left supplementary motor area and left posterior superior temporal sulcus (pSTS), whereas tone frequency-related responses decreased in the right angular gyrus and right pSTS. Tritone frequency-related responses rapidly developed to reach significance after 3 min of exposure. These results suggest that the incidental extraction of novel regularities is subtended by a gradual shift from rhythmic activity reflecting individual tone succession toward rhythmic activity synchronised with triplet presentation, and that these rhythmic processes are subtended by distinct neural sources.

Effectiveness of applying flipped learning to clinical nursing practicums for nursing students in Korea: A randomized controlled trial.

PubMed

Kim, Hyun Sook; Kim, Mi Young; Cho, Mi-Kyoung; Jang, Sun Joo

2017-10-01

The purpose of this study was to develop flipped learning models for clinical practicums and compare their effectiveness regarding learner motivation toward learning, satisfaction, and confidence in performing core nursing skills among undergraduate nursing students in Korea. This study was a randomized clinical trial designed to compare the effectiveness of 2 flipped learning models. Data were collected for 3 days from October 21 to 23, 2015 before the clinical practicum was implemented and for 2 weeks from October 26 to December 18, 2015 during the practicum period. The confidence of the students in performing core nursing skills was likely to increase after they engaged in the clinical practicum in both study groups. However, while learner confidence and motivation were not affected by the type of flipped learning, learner satisfaction did differ between the 2 groups. The findings indicate that applying flipped learning allows students to conduct individualized learning with a diversity of clinical cases at their own level of understanding and at their own pace before they participate in real-world practicums. © 2017 John Wiley & Sons Australia, Ltd.

Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery.

PubMed

Sigdel, Madhav; Dinç, İmren; Dinç, Semih; Sigdel, Madhu S; Pusey, Marc L; Aygün, Ramazan S

2014-03-01

In this paper, we investigate the performance of two wrapper methods for semi-supervised learning algorithms for classification of protein crystallization images with limited labeled images. Firstly, we evaluate the performance of semi-supervised approach using self-training with naïve Bayesian (NB) and sequential minimum optimization (SMO) as the base classifiers. The confidence values returned by these classifiers are used to select high confident predictions to be used for self-training. Secondly, we analyze the performance of Yet Another Two Stage Idea (YATSI) semi-supervised learning using NB, SMO, multilayer perceptron (MLP), J48 and random forest (RF) classifiers. These results are compared with the basic supervised learning using the same training sets. We perform our experiments on a dataset consisting of 2250 protein crystallization images for different proportions of training and test data. Our results indicate that NB and SMO using both self-training and YATSI semi-supervised approaches improve accuracies with respect to supervised learning. On the other hand, MLP, J48 and RF perform better using basic supervised learning. Overall, random forest classifier yields the best accuracy with supervised learning for our dataset.

Growth performance and total tract nutrient digestion for Holstein heifers limit-fed diets high in distillers grains with different forage particle sizes

USDA-ARS?s Scientific Manuscript database

This study evaluated dairy heifer growth performance and total tract nutrient digestion when fed diets high in dried distillers grains with solubles (DDGS) with different forage particle size. An 8-wk randomized complete block design study was conducted utilizing twenty-two Holstein heifers (123 ±...

Integrating nutrition and early child-development interventions among infants and preschoolers in rural India.

PubMed

Fernandez-Rao, Sylvia; Hurley, Kristen M; Nair, Krishnapillai Madhavan; Balakrishna, Nagalla; Radhakrishna, Kankipati V; Ravinder, Punjal; Tilton, Nicholas; Harding, Kimberly B; Reinhart, Greg A; Black, Maureen M

2014-01-01

This article describes the development, design, and implementation of an integrated randomized double-masked placebo-controlled trial (Project Grow Smart) that examines how home/preschool fortification with multiple micronutrient powder (MNP) combined with an early child-development intervention affects child development, growth, and micronutrient status among infants and preschoolers in rural India. The 1-year trial has an infant phase (enrollment age: 6-12 months) and a preschool phase (enrollment age: 36-48 months). Infants are individually randomized into one of four groups: placebo, placebo plus early learning, MNP alone, and MNP plus early learning (integrated intervention), conducted through home visits. The preschool phase is a cluster-randomized trial conducted in Anganwadi centers (AWCs), government-run preschools sponsored by the Integrated Child Development System of India. AWCs are randomized into MNP or placebo, with the MNP or placebo mixed into the children's food. The evaluation examines whether the effects of the MNP intervention vary by the quality of the early learning opportunities and communication within the AWCs. Study outcomes include child development, growth, and micronutrient status. Lessons learned during the development, design, and implementation of the integrated trial can be used to guide large-scale policy and programs designed to promote the developmental, educational, and economic potential of children in developing countries. © 2013 New York Academy of Sciences.

Stellate ganglion blockade and verbal memory in midlife women: Evidence from a randomized trial.

PubMed

Maki, Pauline M; Rubin, Leah H; Savarese, Antonia; Drogos, Lauren; Shulman, Lee P; Banuvar, Suzanne; Walega, David R

2016-10-01

In a pilot randomized clinical trial of active stellate ganglion blockade (SGB) versus sham control, SGB significantly reduced the frequency of reported moderate to severe vasomotor symptoms (VMS) and the frequency of physiologic VMS measured using ambulatory skin conductance monitors. Here we examine secondary effects of SGB on verbal learning and memory. In a randomized, sham-controlled study, 36 women met eligibility criteria for cognitive assessments, of whom 17 were randomized to receive fluoroscopy-guided SGB and 19 to sham control. At baseline and three months post-treatment, women completed tests of verbal learning and memory (primary outcome) and other cognitive measures and also wore an ambulatory monitor for 24h to measure physiologic VMS and VMS reported in real time. Verbal learning improved following active SGB (p<0.05) but not sham treatment; however, the interaction between group and time was not significant (p values 0.13-0.20). Two secondary cognitive measures improved only in the sham group. Improvements in physiologic VMS correlated significantly with improvements in verbal learning (r=0.51, p<0.05). SGB might confer benefits to memory in relation to the magnitude of improvement in physiologic VMS. Broadly these findings suggest a possible link between physiologic VMS and memory problems in midlife women. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Clogging in constricted suspension flows

NASA Astrophysics Data System (ADS)

Marin, Alvaro; Lhuissier, Henri; Rossi, Massimiliano; Kähler, Christian J.

2018-02-01

The flow of a charged-stabilized suspension through a single constricted channel is studied experimentally by tracking the particles individually. Surprisingly, the behavior is found to be qualitatively similar to that of inertial dry granular systems: For small values of the neck-to-particle size ratio (D /d <3 ), clogs form randomly as arches of the particle span the constriction. The statistics of the clogging events are Poissonian as reported for granular systems and agree for moderate particle volume fraction (ϕ ≈20 % ) with a simple stochastic model for the number of particles at the neck. For larger neck sizes (D /d >3 ), even at the largest ϕ (≈60 %) achievable in the experiments, an uninterrupted particle flow is observed, which resembles that of an hourglass. This particularly small value of D /d (≃3 ) at the transition to a practically uninterrupted flow is attributed to the low effective friction between the particles, achieved by the particle's functionalization and lubrication.

Uncertainty quantification in Eulerian-Lagrangian models for particle-laden flows

NASA Astrophysics Data System (ADS)

Fountoulakis, Vasileios; Jacobs, Gustaaf; Udaykumar, Hs

2017-11-01

A common approach to ameliorate the computational burden in simulations of particle-laden flows is to use a point-particle based Eulerian-Lagrangian model, which traces individual particles in their Lagrangian frame and models particles as mathematical points. The particle motion is determined by Stokes drag law, which is empirically corrected for Reynolds number, Mach number and other parameters. The empirical corrections are subject to uncertainty. Treating them as random variables renders the coupled system of PDEs and ODEs stochastic. An approach to quantify the propagation of this parametric uncertainty to the particle solution variables is proposed. The approach is based on averaging of the governing equations and allows for estimation of the first moments of the quantities of interest. We demonstrate the feasibility of our proposed methodology of uncertainty quantification of particle-laden flows on one-dimensional linear and nonlinear Eulerian-Lagrangian systems. This research is supported by AFOSR under Grant FA9550-16-1-0008.

A study of MRI gradient echo signals from discrete magnetic particles with considerations of several parameters in simulations.

PubMed

Kokeny, Paul; Cheng, Yu-Chung N; Xie, He

2018-05-01

Modeling MRI signal behaviors in the presence of discrete magnetic particles is important, as magnetic particles appear in nanoparticle labeled cells, contrast agents, and other biological forms of iron. Currently, many models that take into account the discrete particle nature in a system have been used to predict magnitude signal decays in the form of R2* or R2' from one single voxel. Little work has been done for predicting phase signals. In addition, most calculations of phase signals rely on the assumption that a system containing discrete particles behaves as a continuous medium. In this work, numerical simulations are used to investigate MRI magnitude and phase signals from discrete particles, without diffusion effects. Factors such as particle size, number density, susceptibility, volume fraction, particle arrangements for their randomness, and field of view have been considered in simulations. The results are compared to either a ground truth model, theoretical work based on continuous mediums, or previous literature. Suitable parameters used to model particles in several voxels that lead to acceptable magnetic field distributions around particle surfaces and accurate MR signals are identified. The phase values as a function of echo time from a central voxel filled by particles can be significantly different from those of a continuous cubic medium. However, a completely random distribution of particles can lead to an R2' value which agrees with the prediction from the static dephasing theory. A sphere with a radius of at least 4 grid points used in simulations is found to be acceptable to generate MR signals equivalent from a larger sphere. Increasing number of particles with a fixed volume fraction in simulations reduces the resulting variance in the phase behavior, and converges to almost the same phase value for different particle numbers at each echo time. The variance of phase values is also reduced when increasing the number of particles in a fixed voxel. These results indicate that MRI signals from voxels containing discrete particles, even with a sufficient number of particles per voxel, cannot be properly modeled by a continuous medium with an equivalent susceptibility value in the voxel. Copyright © 2017 Elsevier Inc. All rights reserved.

Fostering Cooperative Learning in Middle and Secondary Level Classrooms.

ERIC Educational Resources Information Center

Wood, Karen D.

1987-01-01

Provides a brief overview of the research on cooperative learning, and describes several classroom grouping techniques useful for all grade levels and subject areas. Discusses group retellings, associational dialogue, dyadic learning, needs grouping, the buddy system, cybernetic sessions, and research, interest, ability, tutorial, random social,…

Multistrategy Self-Organizing Map Learning for Classification Problems

PubMed Central

Hasan, S.; Shamsuddin, S. M.

2011-01-01

Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test. PMID:21876686

Shape effects in the turbulent tumbling of large particles

NASA Astrophysics Data System (ADS)

Variano, Evan; Oehmke, Theresa; Pujara, Nimish

2017-11-01

We present laboratory results on rotation of finite-sized, neutrally buoyant, anisotropic particles in isotropic turbulence. The isotropic turbulent flow is generated using a randomly-actuated synthetic jet array that minimizes tank scale circulation and measurements are made with stereoscopic particle image velocimetry. By using particles of different shapes, we explore the effects that symmetries have on particle rotation. We add to previous data collected for spheres cylinders and ellipsoids by performing new measurements on cubes, cuboids and cones. The measurement technique and results on mean-square particle rotation will be presented. Preliminary results, at the time of writing this abstract, indicate that symmetry breaking increases the rate of particle rotation. More complete quantitative results will be presented. This work was partially supported by the NSF award ENG-1604026 and by the Army Research Office Biomathematics Program.

Propagation and scattering of optical light beams in free space, in atmosphere and in biological media

NASA Astrophysics Data System (ADS)

Sahin, Serkan

With their first production implemented around 1960's, lasers have afterwards proven to be excellent light sources in building the technology. Subsequently, it has been shown that the extraordinary properties of lasers are related to their coherence properties. Recent developments in optics make it possible to synthesize partially coherent light beams from fully coherent ones. In the last several decades it was seen that using partially coherent light sources may be advantageous, in the areas such as laser surface processing, fiber and free-space optical communications, and medical diagnostics. In this thesis, I study extensively the generation, the propagation in different media, and the scattering of partially coherent light beams with respect to their spectral polarization and coherence states. For instance, I analyze the evolution of recently introduced degree of cross-polarization of light fields in free space; then develop a novel partially coherent light source which acquires and keeps a flat intensity profile around the axis at any distance in the far field; and investigate the interaction of electromagnetic random light with the human eye lens. A part of the thesis treats the effect of atmospheric turbulence on random light beams. Due to random variations in the refractive index, atmospheric turbulence modulates all physical and statistical properties of propagating beams. I have explored the possibility of employing the polarimetric domain of the beam for scintillation reduction, which positively affects the performance of free-space communication systems. I also discuss novel techniques for the sensing of rough targets in the turbulent atmosphere by polarization and coherence properties of light. The other contribution to the thesis is the investigation of light scattering from deterministic or random collections of particles, within the validity of first Born approximation. In the case of a random collection, I introduce and model the new quantity (named pair-structure function) describing correlations among particles, the knowledge of which is necessary for the rigorous predictions of scattered radiation's statistics. Also, by introducing the multi-Gaussian family of functions for scattering potentials, we demonstrate a realistic model for semi-hard edges of particles and bubblelike particles.

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

NASA Astrophysics Data System (ADS)

Ayyad, Yassid; Mittig, Wolfgang; Bazin, Daniel; Beceiro-Novo, Saul; Cortesi, Marco

2018-02-01

The three-dimensional reconstruction of particle tracks in a time projection chamber is a challenging task that requires advanced classification and fitting algorithms. In this work, we have developed and implemented a novel algorithm based on the Random Sample Consensus Model (RANSAC). The RANSAC is used to classify tracks including pile-up, to remove uncorrelated noise hits, as well as to reconstruct the vertex of the reaction. The algorithm, developed within the Active Target Time Projection Chamber (AT-TPC) framework, was tested and validated by analyzing the 4He+4He reaction. Results, performance and quality of the proposed algorithm are presented and discussed in detail.

Steady States, Fluctuation-Dissipation Theorems and Homogenization for Reversible Diffusions in a Random Environment

NASA Astrophysics Data System (ADS)

Mathieu, P.; Piatnitski, A.

2018-04-01

Prolongating our previous paper on the Einstein relation, we study the motion of a particle diffusing in a random reversible environment when subject to a small external forcing. In order to describe the long time behavior of the particle, we introduce the notions of steady state and weak steady state. We establish the continuity of weak steady states for an ergodic and uniformly elliptic environment. When the environment has finite range of dependence, we prove the existence of the steady state and weak steady state and compute its derivative at a vanishing force. Thus we obtain a complete `fluctuation-dissipation Theorem' in this context as well as the continuity of the effective variance.