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arXiv 2020年

作者： Röding, Magnus Ma, Zheng Torquato, Salvatore RISE Research Institutes of Sweden Göteborg41276 Sweden Department of Physics Princeton University PrincetonNJ08544 United States Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Quantitative structure-property relationships are crucial for the understanding and prediction of the physical properties of complex materials. For fluid flow in porous materials, characterizing the geometry of the pore microstructure facilitates prediction of permeability, a key property that has been extensively studied in material science, geophysics and chemical engineering. In this work, we study the predictability of different structural descriptors via both linear regressions and neural networks. A large data set of 30,000 virtual, porous microstructures of different types, including both granular and continuous solid phases, is created for this end. We compute permeabilities of these structures using the lattice Boltzmann method, and characterize the pore space geometry using one-point correlation functions (porosity, specific surface), two-point surface-surface, surface-void, and void-void correlation functions, as well as the geodesic tortuosity as an implicit descriptor. Then, we study the prediction of the permeability using different combinations of these descriptors. We obtain significant improvements of performance when compared to a Kozeny-Carman regression with only lowest-order descriptors (porosity and specific surface). We find that combining all three two-point correlation functions and tortuosity provides the best prediction of permeability, with the void-void correlation function being the most informative individual descriptor. Moreover, the combination of porosity, specific surface, and geodesic tortuosity provides very good predictive performance. This shows that higher-order correlation functions are extremely useful for forming a general model for predicting physical properties of complex materials. Additionally, our results suggest that artificial neural networks are superior to the more conventional regression methods for establishing quantitative structure-property relationships. We make the data and code used publicly available to fac

关键词： Forecasting

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Connecting polymer collapse and the onset of jamming

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Physical Review E 2024年第3期109卷 034406-034406页

作者： Alex T. Grigas Aliza Fisher Mark D. Shattuck Corey S. O'Hern Graduate Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven Connecticut 06520 USA Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA

Previous studies have shown that the interiors of proteins are densely packed, reaching packing fractions that are as large as those found for static packings of individual amino-acid-shaped particles. How can the interiors of proteins take on such high packing fractions given that amino acids are connected by peptide bonds and many amino acids are hydrophobic with attractive interactions? We investigate this question by comparing the structural and mechanical properties of collapsed attractive disk-shaped bead-spring polymers to those of three reference systems: static packings of repulsive disks, of attractive disks, and of repulsive disk-shaped bead-spring polymers. We show that the attractive systems quenched to temperatures below the glass transition T≪Tg and static packings of both repulsive disks and bead-spring polymers possess similar interior packing fractions. Previous studies have shown that static packings of repulsive disks are isostatic at jamming onset, i.e., the number of interparticle contacts Nc matches the number of degrees of freedom, which strongly influences their mechanical properties. We find that repulsive polymer packings are hypostatic at jamming onset (i.e., with fewer contacts than degrees of freedom) but are effectively isostatic when including stabilizing quartic modes, which give rise to quartic scaling of the potential energy with displacements along these modes. While attractive disk and polymer packings are often considered hyperstatic with excess contacts over the isostatic number, we identify a definition for interparticle contacts for which they can also be considered as effectively isostatic. As a result, we show that the mechanical properties (e.g., scaling of the potential energy with excess contact number and low-frequency contribution to the density of vibrational modes) of weakly attractive disk and polymer packings are similar to those of isostatic repulsive disk and polymer packings. Our results demonstrate that static

关键词： Jamming Polymer folding Protein folding Single polymer chains

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Inventory of fungi from termite nests at Gunung Leuser National Park, northern Sumatra 2

Inventory of fungi from termite nests at Gunung Leuser Natio...

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2nd International Conference on Agriculture and Bioindustry, ICAGRI 2020

作者： Hanum, S. Fitri, L. Lisa, O. Samingan, S. Alfizar, A. Sutekad, D. Novita, N. Muarrif, S. Syaukani, S. Master Program in Biological Science Faculty of Mathematic and Natural Sciences Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia Biology Department Faculty of Mathematic and Natural Sciences Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia Faculty of Teacher Training and Education Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia Plant Protection Department Faculty of Agriculture Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia Graduate School of Mathematics and Applied Science Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia

Fungi and termite coexisted each other and have diverse symbiotic relationship in tropical forest. This research aims to determine the fungus found on termite nests in Suaq Balimbing Research Station so it can be used that as initial information in developing environmentally friendly termite control. The method used for collecting samples of fungus is a Standarized Sampling Protocol and for identification used slide culture method. The results showed that 5 of 12 termites nest are invaded by fungi. Based on macroscopic and microscopic observation, fungus species that obtained from termite nests are 2 species, namely: Penicillium sp.1, Trichoderma sp. 1 © Published under licence by IOP Publishing Ltd.

关键词： Fungi

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Bridging preference-based instrumental variable studies and cluster-randomized encouragement experiments: Study design, noncompliance, and average cluster effect ratio

arXiv

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arXiv 2020年

作者： Zhang, Bo Heng, Siyu Mackay, Emily J. Ye, Ting Department of Statistics The Wharton School University of Pennsylvania PhiladelphiaPA United States Graduate Group in Applied Mathematics and Computational Science School of Arts and Sciences University of Pennsylvania PhiladelphiaPA United States Department of Anesthesiology and Critical Care Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States

Instrumental variable methods are widely used in medical and social science research to draw causal conclusions when the treatment and outcome are confounded by unmeasured confounding variables. One important feature of such studies is that the instrumental variable is often applied at the cluster level, e.g., hospitals’ or physicians’ preference for a certain treatment where each hospital or physician naturally defines a cluster. This paper proposes to embed such observational instrumental variable data into a cluster-randomized encouragement experiment using statistical matching. Potential outcomes and causal assumptions underpinning the design are formalized and examined. Testing procedures for two commonly-used estimands, Fisher’s sharp null hypothesis and the pooled effect ratio, are extended to the current setting. We then introduce a novel cluster-heterogeneous proportional treatment effect model and the relevant estimand: the average cluster effect ratio. This new estimand is advantageous over the structural parameter in a constant proportional treatment effect model in that it allows treatment heterogeneity, and is advantageous over the pooled effect ratio estimand in that it is immune to Simpson’s paradox. We develop an asymptotically valid randomization-based testing procedure for this new estimand based on solving a mixed integer quadratically-constrained optimization problem. The proposed design and inferential methods are applied to a study of the effect of using transesophageal echocardiography during CABG surgery on patients’ 30-day mortality rate. Copyright © 2020, The Authors. All rights reserved.

关键词： Hospitals

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

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DeePN2: A deep learning-based non-Newtonian hydrodynamic model

arXiv

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arXiv 2021年

作者： Fang, Lidong Ge, Pei Zhang, Lei Weinan, E. Lei, Huan Department of Computational Mathematics Science and Engineering Michigan State University MI48824 United States School of Mathematical Sciences Institute of Natural Sciences and MOE-LSC Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China Center for Machine Learning Research School of Mathematical Sciences Peking University Beijing100871 China AI for Science Institute Beijing100080 China Department of Mathematics and Program in Applied and Computational Mathematics Princeton University NJ08544 United States Department of Statistics and Probability Michigan State University MI48824 United States

A long standing problem in the modeling of non-Newtonian hydrodynamics of polymeric flows is the availability of reliable and interpretable hydrodynamic models that faithfully encode the underlying micro-scale polymer dynamics. The main complication arises from the long polymer relaxation time, the complex molecular structure and heterogeneous interaction. DeePN2, a deep learning-based non-Newtonian hydrodynamic model, has been proposed and has shown some success in systematically passing the micro-scale structural mechanics information to the macro-scale hydrodynamics for suspensions with simple polymer conformation and bond potential. The model retains a multi-scaled nature by mapping the polymer configurations into a set of symmetry-preserving macro-scale features. The extended constitutive laws for these macro-scale features can be directly learned from the kinetics of their micro-scale counterparts. In this paper, we develop DeePN2 using more complex micro-structural models. We show that DeePN2 can faithfully capture the broadly overlooked viscoelastic differences arising from the specific molecular structural mechanics without human intervention. © 2021, CC BY.

关键词： Non Newtonian flow

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Dynamical charge structure factor of a one-dimensional ionic Hubbard model in the low-energy region

arXiv

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arXiv 2018年

作者： Komaki, Yuhei Iwase, Yuma Yanagimatsu, Shogo Muta, Yoshiyuki Maeshima, Nobuya Hino, Ken-ichi Doctoral Program in Materials Science Graduate School of Pure and Applied Sciences University of Tsukuba Tsukuba Ibaraki305-8573 Japan College of Engineering Sciences University of Tsukuba Tsukuba305-8573 Japan Center for Computational Sciences University of Tsukuba Tsukuba305-8577 Japan Division of Materials Science University of Tsukuba Tsukuba305-8573 Japan

We present a numerical study of the charge dynamical structure factor N(k, ω) of a one-dimensional (1D) ionic Hubbard model in the Mott insulator (MI) phase. We show that the low-energy spectrum of N(k, ω) is expressed in terms of the spin operators for the spin degrees of freedom. Numerical results for the spin degrees of freedom, obtained by the Lanczos diagonalization method, well reproduce the low-energy spectrum of N(k, ω) of the 1D ionic Hubbard model. In addition, we show that these spectral peaks probe the dispersion of the spin-singlet excitations of the system and are observed in the wide parameter region of the MI phase. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical methods

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An unsupervised auditory scene analysis system using incremental low-dimensional embedding

An unsupervised auditory scene analysis system using increme...

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IEEE/SICE International Symposium on System Integration

作者： Kenta Shinzato Ryosuke Kojima Undergraduate School of Informatics and Mathematical Science Undergraduate Course Program of Applied Mathematics and Physics Kyoto University 54 Kawahara-cho Shogoin Sakyo-ku Kyoto Japan Graduate School of Medicine Kyoto University 54 Kawahara-cho Shogoin Sakyo-ku Kyoto Japan

ISBN: (数字)9781728176581

ISBN: (纸本)9781728176598

This paper addresses the low-dimensional embedding of sounds towards unsupervised auditory scene analysis. Summarizing long-time recordings by mapping them into low-dimensional space is an essential task in long-time environmental monitoring. In this paper, we propose a novel low-dimensional embedding system using an incremental embedding algorithm. To analyze long-time recordings, we design an incremental system consisting of recording, feature extraction, low-dimensional embedding, and visualization. Recently, many low-dimensional embedding methods for acoustic scenes have been studied; however, applicability of these methods to the long-time recording is not adequately evaluated. Thus, this paper describes the construction of the scene analysis system and evaluates the performance of this system. In this paper, we especially focus on two important viewpoints in long-time monitoring: incremental methods and effects of noisy data. To realize an incremental system, we use Self-Organizing Nebulous Growths (SONG), which can incrementally construct a low-dimensional embedding space. Also, in our experiments, we apply our system to bird song analysis under noise conditions. By the preliminary experiments using benchmark datasets, we discover noise sensitivity of our system and applicability to environmental monitoring.

关键词： Training Image analysis Feature extraction Birds Real-time systems Environmental monitoring Task analysis

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Minuscule corrections to near-surface solar internal rotation using mode-coupling

arXiv

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arXiv 2023年

作者： Das, Srijan Bharati Kashyap, Samarth G. Oktay, Deniz Hanasoge, Shravan M. Tromp, Jeroen Department of Geosciences Princeton University PrincetonNJ United States Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Mumbai India Department of Computer Science Princeton University PrincetonNJ United States Department of Geosciences and Program in Applied & Computational Mathematics Princeton University PrincetonNJ United States

The observed solar oscillation spectrum is influenced by internal perturbations such as flows and structural asphericities. These features induce splitting of characteristic frequencies and distort the resonant-mode eigenfunctions. Global axisymmertric flow — differential rotation — is a very prominent perturbation. Tightly constrained rotation profiles as a function of latitude and radius are products of established helioseismic pipelines that use observed Dopplergrams to generate frequency-splitting measurements at high precision. However, the inference of rotation using frequency-splittings do not consider the effect of mode-coupling. This approximation worsens for high-angular-degree modes, as they become increasingly proximal in frequency. Since modes with high angular degrees probe the near-surface layers of the Sun, inversions considering coupled modes could potentially lead to more accurate estimates of rotation very close to the surface. In order to investigate if this is indeed the case, we perform inversions for solar differential rotation, considering coupling of modes for angular degrees 160 ≤ ` ≤ 300 in the surface gravity f-branch and first-overtone p modes. In keeping with the character of mode coupling, we carry out a non-linear inversion using an eigenvalue solver. Differences in inverted profiles for frequency splitting measurements from MDI and HMI are compared and discussed. We find that corrections to the near-surface differential rotation profile, when accounting for mode-coupling effects, are smaller than 0.003 nHz and hence are insignificant. These minuscule corrections are found to be correlated with the solar cycle. We also present corrections to even-order splitting coefficients, which could consequently impact inversions for structure and magnetic fields. © 2023, CC BY.

关键词： Rotation

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Domain morphology and mechanics of the H/T′ transition metal dichalcogenide monolayers

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Physical Review Materials 2018年第11期2卷 114002-114002页

作者： Joel Berry Songsong Zhou Jian Han David J. Srolovitz Mikko P. Haataja Department of Materials Science and Engineering University of Pennsylvania Philadelphia Pennsylvania 19104 USA Department of Mechanical and Aerospace Engineering Princeton University Princeton New Jersey 08544 USA Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania Philadelphia Pennsylvania 19104 USA Department of Materials Science and Engineering City University of Hong Kong Hong Kong SAR People's Republic of China Princeton Institute for the Science and Technology of Materials (PRISM) Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics (PACM) Princeton University Princeton New Jersey 08544 USA

The properties of two-dimensional (2D) transition metal dichalcogenide (TMD) monolayers can be dynamically controlled via strain-induced displacive structural transformations between semiconducting (H) and metallic or semimetallic (T′) crystal structures. The shapes, symmetries, and kinetics of crystalline domains generated during these transformations and the mechanical response of transforming monolayers are of fundamental and applied interest in, e.g., phase change memory devices and the study of topologically protected edge states in quantum spin Hall insulating T′ crystals. We quantitatively characterize T′ domain morphologies during H→T′ transformations in both flat and bendable TMD monolayers using a combination of first principles and continuum calculations. Wulff constructions for MoTe2 and MoS2 show that T′ domains within much larger T′ domains are either rhombi of fixed proportions (if nonmisfitting) or rectangles whose aspect ratio AR increases with domain size L0 (if misfitting). Isolated T′ domains within much larger H domains undergo a morphological crossover from compact to elongated shapes at L0≈100–200 nm if the sheet is constrained to be flat or L0≳2μm if the sheet is free to bend. This crossover is driven by a competition between anisotropic interfacial energy and elastic misfit energy, and its position can be tuned via the monolayer-substrate interaction strength. It is shown that the aspect ratio AR obeys a scaling law AR∼L02/3. Stress-strain response characterized as a function of strain orientation reveals extreme anisotropy in the effective elastic modulus through H/T′ coexistence. Ferroelastic multidomain T′−WTe2 monolayers are found to exhibit two to three regimes of reversible mechanical response, and localized buckling in freely suspended T′ monolayers is shown to qualitatively alter T′ domain symmetries.

关键词： Bending Domain walls Mechanical deformation Microstructure Structural phase transition 2-dimensional systems Transition metal dichalcogenides Density functional theory Phase-field modeling

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