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The role of information systems towards the success of the family planning program: a literature review

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Journal of Physics: Conference Series 2020年第1期1524卷

作者： K Yusika M N Widyawati S Suryono Master of Applied Science in Midwifery Poltekkes Kemenkes Semarang Indonesia Postgraduate Applied Science Midwifery Program Poltekkes Kemenkes Semarang Indonesia Department of Physics Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia

Family planning is an arrangement aimed at forming a prosperous family by limiting the number of births by using contraception. Birth control can reduce unwanted pregnancies, high-risk pregnancies, and prevent maternal death. One of the information systems that has been used in the health world is the immunization day reminder and management of hospital activities. The reminder system is effective as a reminder of the immunization schedule. This wireless technology helps health workers quickly and practically in health services. The use of information systems in family planning programs can support the success of family planning, one of which is to reduce the number of family planning failures and the proper use of family planning. This study uses the PRISMA protocol guidelines. The referenced journals come from various sources that have good publishing credibility and can be accounted for. This study discusses how information systems play a role in the success of family planning programs. The method used in this article is a systematic literature review. This study discusses a number of journals by examining in detail in preliminary studies, research objects, performance indicators, variables and methods applied So as to briefly learn the benefits of information systems as a tool for the success of family planning in midwifery services.

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Directing Near-Infrared Photon Transport with Core@Shell Particles

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arXiv 2020年

作者： Conley, Kevin M. Thakore, Vaibhav Seyedheydari, Fahime Karttunen, Mikko Ala-Nissila, Tapio Department of Applied Physics QTF Centre of Excellence Aalto University School of Science P.O. Box 11100 AaltoFI-00076 Finland Department of Applied Mathematics University of Western Ontario LondonONN6A 5B7 Canada Center for Advanced Materials and Biomaterials Research University of Western Ontario LondonONN6A 3K7 Canada Department of Chemistry University of Western Ontario LondonONN6A 5B7 Canada Interdisciplinary Centre for Mathematical Modelling Department of Mathematical Sciences Loughborough University LoughboroughLeicestershireLE11 3TU United Kingdom

Directing the propagation of near-infrared radiation is a major concern in improving the efficiency of solar cells and thermal insulators. A facile approach to scatter light in the near-infrared region without excessive heating is to embed compact layers with semiconductor particles. The directional scattering by semiconductor@oxide (core@shell) spherical particles (containing Si, InP, TiO2, SiO2, or ZrO2) with a total radius varying from 0.1 to 4.0 µm and in an insulating medium at low volume fraction is investigated using Lorenz-Mie theory and multiscale modelling. The optical response of each layers is calculated under irradiation by the sun or a blackbody emitter at 1180 K. Reflectance efficiency factors of up to 83.7% and 63.9% are achieved for near-infrared solar and blackbody radiation in 200 µm thick compact layers with only 1% volume fraction of bare Si particles with a radius of 0.23 µm and 0.50 µm, respectively. The maximum solar and blackbody efficiency factors of layers containing InP particles was slightly less (80.2% and 60.7% for bare particles with a radius of 0.25 µm and 0.60 µm, respectively). The addition of an oxide coating modifies the surrounding dielectric environment, which improves the solar reflectance efficiency factor to over 90% provided it matches the scattering mode energies with the incident spectral density. The layers are spectrally-sensitive and can be applied as a back or front reflector for solar devices, high temperature thermal insulators, and optical filters in Gradient Heat Flux Sensors for fire safety applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Titanium dioxide

The estimation of the effective reproductive number from disease outbreak data

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arXiv 2020年

作者： Cintrón-Arias, Ariel Castillo-Chávez, Carlos Bettencourt, Luís M.A. Lloyd, Alun L. Banks, H.T. Statistical and Applied Mathematical Sciences Institute 19 T. W. Alexander Drive P.O. Box 14006 Research Triangle ParkNC27709-4006 United States Department of Mathematics and Statistics Arizona State University P.O. Box 871804 TempeAZ85287 - 1804 Los Alamos National Laboratory Mail Stop B284 Los AlamosNM87545 United States Biomathematics Graduate Program Department of Mathematics North Carolina State University RaleighNC27695 United States Center for Research in Scientific Computation North Carolina State University P.O. Box 8205 RaleighNC27695

We consider a single outbreak susceptible-infected-recovered (SIR) model and corresponding estimation procedures for the effective reproductive number R(t). We discuss the estimation of the underlying SIR parameters with a generalized least squares (GLS) estimation technique. We do this in the context of appropriate statistical models for the measurement process. We use asymptotic statistical theories to derive the mean and variance of the limiting (Gaussian) sampling distribution and to perform post statistical analysis of the inverse problems. We illustrate the ideas and pitfalls (e.g., large condition numbers on the corresponding Fisher information matrix) with both synthetic and influenza incidence data sets. Copyright © 2020, The Authors. All rights reserved.

关键词： Parameter estimation

A Low-rank solver for the stochastic unsteady navier-stokes problem

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arXiv 2019年

作者： Elman, Howard Su, Tengfei Department of Computer Science Institute for Advanced Computer Studies University of Maryland College ParkMD20742 United States Applied Mathematics & Statistics and Scientific Computation Program University of Maryland College ParkMD20742 United States

We study a low-rank iterative solver for the unsteady Navier–Stokes equations for incompressible flows with a stochastic viscosity. The equations are discretized using the stochastic Galerkin method, and we consider an all-at-once formulation where the algebraic systems at all the time steps are collected and solved simultaneously. The problem is linearized with Picard’s method. To efficiently solve the linear systems at each step, we use low-rank tensor representations within the Krylov subspace method, which leads to significant reductions in storage requirements and computational costs. Combined with effective mean-based preconditioners and the idea of inexact solve, we show that only a small number of linear iterations are needed at each Picard step. The proposed algorithm is tested with a model of flow in a two-dimensional symmetric step domain with different settings to demonstrate the computational efficiency. Copyright © 2019, The Authors. All rights reserved.

关键词： Navier Stokes equations

Probabilistic Theory of Mean Field Games with Applications I 1

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丛书名： Probability Theory and Stochastic Modelling

2018年

作者： René Carmona François Delarue

ISBN: (数字)9783319589206

ISBN: (纸本)9783319564371;9783030132606

Volume I of the book is entirely devoted to the theory of mean field games without a common noise. The first half of the volume provides a self-contained introduction to mean field games, starting from concrete illustrations of games with a finite number of players, and ending with ready-for-use solvability results. Readers are provided with the tools necessary for the solution of forward-backward stochastic differential equations of the McKean-Vlasov type at the core of the probabilistic approach. The second half of this volume focuses on the main principles of analysis on the Wasserstein space. It includes Lions' approach to the Wasserstein differential calculus, and the applications of its results to the analysis of stochastic mean field control problems.

关键词： Probability Theory Calculus of Variations and Optimization Differential Equations Quantitative Economics

Isotope effects in liquid water via deep potential molecular dynamics

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arXiv 2019年

作者： Ko, Hsin-Yu Zhang, Linfeng Santra, Biswajit Wang, Han Weinan, E. DiStasio, Robert A. Cara, Roberto Department of Chemistry Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Physics Temple University PhiladelphiaPA19122 United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China Department of Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry and Chemical Biology Cornell University IthacaNY14853 United States Department of Physics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States

A comprehensive microscopic understanding of ambient liquid water is a major challenge for ab initio simulations as it simultaneously requires an accurate quantum mechanical description of the underlying potential energy surface (PES) as well as extensive sampling of configuration space. Due to the presence of light atoms (e.g., H or D), nuclear quantum fluctuations lead to observable changes in the structural properties of liquid water (e.g., isotope effects), and therefore provide yet another challenge for ab initio approaches. In this work, we demonstrate that the combination of dispersion-inclusive hybrid density functional theory (DFT), the Feynman discretized path-integral (PI) approach, and machine learning (ML) constitutes a versatile ab initio based framework that enables extensive sampling of both thermal and nuclear quantum fluctuations on a quite accurate underlying PES. In particular, we employ the recently developed deep potential molecular dynamics (DPMD) model - a neural-network representation of the ab initio PES - in conjunction with a PI approach based on the generalized Langevin equation (PIGLET) to investigate how isotope effects influence the structural properties of ambient liquid H2O and D2O. Through a detailed analysis of the interference differential cross sections as well as several radial and angular distribution functions, we demonstrate that this approach can furnish a semi-quantitative prediction of these subtle isotope effects. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems 18

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End-to-end symmetry preserving inter-atomic potential energy...

Proceedings of the 32nd International Conference on Neural Information Processing Systems

作者： Linfeng Zhang Jiequn Han Han Wang Wissam A. Saidi Roberto Car E. Weinan Program in Applied and Computational Mathematics Princeton University Institute of Applied Physics and Computational Mathematics China and CAEP Software Center for High Performance Numerical Simulation China Department of Mechanical Engineering and Materials Science University of Pittsburgh Program in Applied and Computational Mathematics Princeton University and Department of Chemistry and Department of Physics Princeton University and Princeton Institute for the Science and Technology of Materials Princeton University Program in Applied and Computational Mathematics Princeton University and Department of Mathematics Princeton University and Beijing Institute of Big Data Research China

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular interest is the inter-atomic potential energy surface (PES). Here we develop Deep Potential - Smooth Edition (DeepPot-SE), an end-to-end machine learning-based PES model, which is able to efficiently represent the PES of a wide variety of systems with the accuracy of ab initio quantum mechanics models. By construction, DeepPot-SE is extensive and continuously differentiable, scales linearly with system size, and preserves all the natural symmetries of the system. Further, we show that DeepPot-SE describes finite and extended systems including organic molecules, metals, semiconductors, and insulators with high fidelity.

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Langevin equations in the small-mass limit: Higher order approximations

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arXiv 2018年

作者： Birrell, Jeremiah Wehr, Jan Department of Mathematics and Statistics University of Massachusetts Amherst AmherstMA01003 United States Department of Mathematics Program in Applied Mathematics University of Arizona TucsonAZ85721 United States

We study the small-mass (overdamped) limit of Langevin equations for a particle in a potential and/or magnetic field with matrix-valued and state-dependent drift and diffusion. The present work generalizes prior derivations of the homogenized equation for the position degrees of freedom in the m → 0 limit. Specifically, we develop a hierarchy of approximate equations for the position degrees of freedom that achieves accuracy of order m/2 over compact time intervals for any ∈ Z+. The results cover bounded forces, for which we prove convergence in Lp norms, and unbounded forces, in which case we prove convergence in probability. Copyright © 2018, The Authors. All rights reserved.

关键词： Differential equations

Many-body contacts in fractal polymer chains and fractional Brownian trajectories

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Physical Review E 2019年第3期99卷 032501-032501页

作者： K. E. Polovnikov S. Nechaev M. V. Tamm Skolkovo Institute of Science and Technology 143026 Skolkovo Russia Faculty of Physics Lomonosov Moscow State University 119992 Moscow Russia Interdisciplinary Scientific Center Poncelet (ISCP) 119002 Moscow Russia Lebedev Physical Institute RAS 119991 Moscow Russia Department of Applied Mathematics MIEM National Research University Higher School of Economics 101000 Moscow Russia

We calculate the probabilities that a trajectory of a fractional Brownian motion with arbitrary fractal dimension df visits the same spot n≥3 times, at given moments t1,...,tn, and obtain a determinant expression for these probabilities in terms of a displacement-displacement covariance matrix. Except for the standard Brownian trajectories with df=2, the resulting many-body contact probabilities cannot be factorized into a product of single-loop contributions. Within a Gaussian network model of a self-interacting polymer chain, which we suggested recently [K. Polovnikov et al., Soft Matter 14, 6561 (2018)], the probabilities we calculate here can be interpreted as probabilities of multibody contacts in a fractal polymer conformation with the same fractal dimension df. This Gaussian approach, which implies a mapping from fractional Brownian motion trajectories to polymer conformations, can be used as a semiquantitative model of polymer chains in topologically stabilized conformations, e.g., in melts of unconcatenated rings or in the chromatin fiber, which is the material medium containing genetic information. The model presented here can be used, therefore, as a benchmark for interpretation of the data of many-body contacts in genomes, which we expect to be available soon in, e.g., Hi-C experiments.

关键词： Anomalous diffusion Polymer conformation & topology Polymer conformation changes Polymer folding