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An efficient fully Lagrangian solver for modeling wave interaction with oscillating wave energy converter

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arXiv 2020年

作者： Zhang, Chi Wei, Yanji Dias, Frederic Hu, Xiangyu Y. Department of Mechanical Engineering Technical University of Munich Garching85748 Germany Aktis Hydraulics BV Zwolle JM8017 Netherlands School of Mathematics and Statistics University College Dublin Belfield Dublin 4 Ireland

In this paper, we present an efficient, accurate and fully Lagrangian numerical solver for modeling wave interaction with oscillating wave energy converter (OWSC). The key idea is to couple SPHinXsys, an open-source multi-physics library in unified smoothed particle hydrodynamic (SPH) framework, with Simbody which presents an object-oriented Application programming Interface (API) for multi-body dynamics. More precisely, the wave dynamics and its interaction with OWSC is resolved by Riemann-based weakly-compressible SPH method using SPHinXsys, and the solid-body kinematics is computed by Simbody library. Numerical experiments demonstrate that the proposed solver can accurately predict the wave elevations, flap rotation and wave loading on the flap in comparison with laboratory experiment. In particularly, the new solver shows optimized computational performance through CPU cost analysis and comparison with commercial software package ANSYS FLUENT and other SPH-based solvers in literature. Furthermore, a linear damper is applied for imitating the power take-off (PTO) system to study its effects on the hydrodynamics properties of OWSC and efficiency of energy harvesting. In addition, the present solver is used to model extreme wave condition using the focused wave approach to investigate the extreme loads and motions of OWSC under such extreme wave conditions. It worth noting that though the model validation used herein is a bottom hinged oscillating Wave Energy Converter (WEC), the obtained numerical results show promising potential of the proposed solver to future applications in the design of high-performance WECs. Copyright © 2020, The Authors. All rights reserved.

关键词： Hydrodynamics

Hausdorff compactifications

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arXiv 2020年

作者： Insall, Matt Loeb, Peter A. Marciniak, Malgorzata Aneta Department of Mathematics and Statistics Missouri University of Science and Technology 400 W. 12th St. RollaMO65409-0020 United States Department of Mathematics University of Illinois 1409 West Green St. UrbanaIll61801 United States Department of Mathematics Engineering and Computer Science LaGuardia Community College of the City University of New York 31-10 Thomson Avenue Long Island CityNY United States

Previously, the authors used the insights of Robinson’s nonstandard analysis as a powerful tool to extend and simplify the construction of some compactifications of regular spaces. They now show that any Hausdorff compactification is obtainable with their *** Codes 03H05, 54D35 (Primary), 54J05 (Secondary) Copyright © 2020, The Authors. All rights reserved.

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CellBiAge: Improved single-cell age classification using data binarization

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Cell Reports 2023年第12期42卷 113500页

作者： Yu, Doudou Li, Manlin Linghu, Guanjie Hu, Yihuan Hajdarovic, Kaitlyn H. Wang, An Singh, Ritambhara Webb, Ashley E. Molecular Biology Cell Biology and Biochemistry Graduate Program Brown University Providence 02912 RI United States Data Science Institute Brown University Providence 02912 RI United States Neuroscience Graduate Program Brown University Providence 02912 RI United States Department of Applied Mathematics & Statistics Johns Hopkins University Baltimore 21218 MD United States Department of Computer Science Brown University Providence 02912 RI United States Center for Computational Molecular Biology Brown University Providence 02912 RI United States Department of Molecular Biology Cell Biology and Biochemistry Brown University Providence 02912 RI United States Center on the Biology of Aging Brown University Providence 02912 RI United States Carney Institute for Brain Science Brown University Providence 02912 RI United States Center for Translational Neuroscience Brown University Providence 02912 RI United States

Aging is a major risk factor for many diseases. Accurate methods for predicting age in specific cell types are essential to understand the heterogeneity of aging and to assess rejuvenation strategies. However, classifying organismal age at single-cell resolution using transcriptomics is challenging due to sparsity and noise. Here, we developed CellBiAge, a robust and easy-to-implement machine learning pipeline, to classify the age of single cells in the mouse brain using single-cell transcriptomics. We show that binarization of gene expression values for the top highly variable genes significantly improved test performance across different models, techniques, sexes, and brain regions, with potential age-related genes identified for model prediction. Additionally, we demonstrate CellBiAge's ability to capture exercise-induced rejuvenation in neural stem cells. This study provides a broadly applicable approach for robust classification of organismal age of single cells in the mouse brain, which may aid in understanding the aging process and evaluating rejuvenation methods. © 2023 The Authors

关键词： aging brain CP: Cell biology hypothalamus machine learning single-cell RNA-seq

Tsunami evacution building model (TEBM) in Teluk Palu (Palu Bay) area

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IOP Conference Series: Materials Science and engineering 2022年第1期1212卷

作者： M Bakri R Awalia S Mulyati F Zubaidi M Rusydi A A Kasim R Prawita Department of Architecture Faculty of Engineering Tadulako University PaluIndonesia Department of Physics Faculty of Mathematics and Natural Sciences Tadulako University Palu Indonesia Department of Informatics Faculty of Engineering Tadulako University Palu Indonesia Study Program of Architecture Faculty of Engineering Tadulako University Palu Indonesia

The research was conducted in the coastal area of Palu Bay, Lere Village. Data were collected using observation, interviews, and literature study techniques. The data were analyzed using qualitative descriptive methods and focused on the concept of the design of the tsunami evacuation building on the coast of Palu Bay. Data analysis was carried out to obtain an overview of the problems that occurred at the planning location which was analyzed with the concept of architectural design by considering the existing conditions of the site and the surrounding environment, as well as utilizing the potential of the site so that it has the potential for building functions. The conclusion obtained is based on the results of data analysis, it is necessary to have a building that can function as an evacuation container for the community when a disaster occurs in the coastal area of Palu Bay, thereby reducing the number of casualties. The benefit of this research is that it is a solution for local people to save themselves when the tsunami disaster.

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Twisted Trilayer Graphene: A Precisely Tunable Platform for Correlated Electrons

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Physical Review Letters 2020年第11期125卷 116404-116404页

作者： Ziyan Zhu Stephen Carr Daniel Massatt Mitchell Luskin Efthimios Kaxiras Department of Physics Harvard University Cambridge Massachusetts 02138 USA Department of Statistics The University of Chicago Chicago Illinois 60637 USA School of Mathematics University of Minnesota—Twin Cities Minneapolis Minnesota 55455 USA John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts 02138 USA

We introduce twisted trilayer graphene (tTLG) with two independent twist angles as an ideal system for the precise tuning of the electronic interlayer coupling to maximize the effect of correlated behaviors. As established by experiment and theory in the related twisted bilayer graphene system, van Hove singularities (VHS) in the density of states can be used as a proxy of the tendency for correlated behaviors. To explore the evolution of VHS in the twist-angle phase space of tTLG, we present a general low-energy electronic structure model for any pair of twist angles. We show that the basis of the model has infinite dimensions even at a finite energy cutoff and that no Brillouin zone exists even in the continuum limit. Using this model, we demonstrate that the tTLG system exhibits a wide range of magic angles at which VHS merge and that the density of states has a sharp peak at the charge-neutrality point through two distinct mechanisms: the incommensurate perturbation of twisted bilayer graphene’s flatbands or the equal hybridization between two bilayer moiré superlattices.

关键词： Density of states Electronic structure van Hove singularity Graphene

Method of moments for 3-D single particle ab initio modeling with non-uniform distribution of viewing angles

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arXiv 2019年

作者： Sharon, Nir Kileel, Joe Khoo, Yuehaw Landa, Boris Singer, Amit School of Mathematical Sciences Tel Aviv University Israel Program in Applied and Computational Mathematics Princeton University United States Department of Statistics and the College University of Chicago United States Applied Mathematics Program Yale University United States Program in Applied and Computational Mathematics Department of Mathematics Princeton University United States

Single-particle reconstruction in cryo-electron microscopy (cryo-EM) is an increasingly popular technique for determining the 3-D structure of a molecule from several noisy 2-D projections images taken at unknown viewing angles. Most reconstruction algorithms require a low-resolution initialization for the 3-D structure, which is the goal of ab initio modeling. Suggested by Zvi Kam in 1980, the method of moments (MoM) offers one approach, wherein low-order statistics of the 2-D images are computed and a 3-D structure is estimated by solving a system of polynomial equations. Unfortunately, Kam’s method suffers from restrictive assumptions, most notably that viewing angles should be distributed uniformly. Often unrealistic, uniformity entails the computation of higher-order correlations, as in this case first and second moments fail to determine the 3-D structure. In the present paper, we remove this hypothesis, by permitting an unknown, non-uniform distribution of viewing angles in MoM. Perhaps surprisingly, we show that this case is statistically easier than the uniform case, as now first and second moments generically suffice to determine low-resolution expansions of the molecule. In the idealized setting of a known, non-uniform distribution, we find an efficient provable algorithm inverting first and second moments. For unknown, non-uniform distributions, we use non-convex optimization methods to solve for both the molecule and distribution. Copyright © 2019, The Authors. All rights reserved.

关键词： Method of moments

The algebraic structure of additive conjucyclic codes over Fq2

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arXiv 2020年

作者： Lv, Jingjie Li, Ruihu Li, Juan Graduate School at Shenzhen Tsinghua University Shenzhen518055 China Department of Basic Sciences Air Force Engineering University Xi’an710051 China School of Mathematics and Statistics Linyi University Linyi276000 China

Conjucyclic codes are an important and special family of classical error-correcting codes, which have been used to construct binary quantum error-correcting codes (QECCs) [7]. However, at present, the research on the conjucyclic codes is extremely insufficient. This paper will explore the algebraic structure of additive conjucyclic codes over Fq2 for the first time. Mainly via the trace function from Fq2 down Fq, we will firstly build an isomorphic mapping between q2-ary additive conjucyclic codes and q-ary linear cyclic codes. Since the mapping preserves the weight and orthogonality, then the dual structure of these codes with respect to the alternating inner product will be described. Then a new construction of QECCs from conjucyclic codes can be obtained. Finally, the enumeration of q2-ary additive conjucyclic codes of length n and the explicit forms of their generator and parity-check matrices will be determined. © 2020, CC BY.

关键词： Additives

Critical mass effect in evolutionary games triggered by zealots

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Physical Review Research 2020年第2期2卷 023305-023305页

作者： Alessio Cardillo Naoki Masuda Department of Engineering Mathematics University of Bristol Bristol BS8 1UB United Kingdom Department of Computer Science and Mathematics University Rovira i Virgili E-43007 Tarragona Spain GOTHAM Lab – Institute for Biocomputation and Physics of Complex Systems (BIFI) University of Zaragoza E-50018 Zaragoza Spain Department of Mathematics State University of New York at Buffalo Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo New York 14260-5030 USA

Tiny perturbations may trigger large responses in systems near criticality, shifting them across equilibria. Committed minorities are suggested to be responsible for the emergence of collective behaviors in many physical, social, and biological systems. Using evolutionary game theory, we address the question whether a finite fraction of zealots can drive the system to large-scale coordination. We find that a tipping point exists in coordination games, whereas the same phenomenon depends on the selection pressure, update rule, and network structure in other types of games. Our study paves the way to understand social systems driven by the individuals' benefit in the presence of zealots, such as human vaccination behavior or cooperative transports in animal groups.

关键词： Patterns in complex systems Social systems

Nuclei grading of clear cell renal cell carcinoma in histopathological image by composite high-resolution network

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arXiv 2021年

作者： Gao, Zeyu Shi, Jiangbo Zhang, Xianli Li, Yang Zhang, Haichuan Wu, Jialun Wang, Chunbao Meng, Deyu Li, Chen School of Computer Science and Technology Xi'an Jiaotong University Shaanxi Xi'an710049 China National Engineering Lab for Big Data Analytics Xi'an Jiaotong University Shaanxi Xi'an710049 China Department of Pathology The First Affiliated Hospital of Xi'an Jiaotong University Xi'an710061 China School of Mathematics and Statistics Xi'an Jiaotong University Shaanxi Xi'an710049 China

The grade of clear cell renal cell carcinoma (ccRCC) is a critical prognostic factor, making ccRCC nuclei grading a crucial task in RCC pathology analysis. Computer-aided nuclei grading aims to improve pathologists' work efficiency while reducing their misdiagnosis rate by automatically identifying the grades of tumor nuclei within histopathological images. Such a task requires precisely segment and accurately classify the nuclei. However, most of the existing nuclei segmentation and classification methods can not handle the inter-class similarity property of nuclei grading, thus can not be directly applied to the ccRCC grading task. In this paper, we propose a Composite High-Resolution Network for ccRCC nuclei grading. Specifically, we propose a segmentation network called W-Net that can separate the clustered nuclei. Then, we recast the fine-grained classification of nuclei to two cross-category classification tasks, based on two high-resolution feature extractors (HRFEs) which are proposed for learning these two tasks. The two HRFEs share the same backbone encoder with W-Net by a composite connection so that meaningful features for the segmentation task can be inherited for the classification task. Last, a head-fusion block is applied to generate the predicted label of each nucleus. Furthermore, we introduce a dataset for ccRCC nuclei grading, containing 1000 image patches with 70945 annotated nuclei. We demonstrate that our proposed method achieves state-of-the-art performance compared to existing methods on this large ccRCC grading dataset. © 2021, CC BY.

关键词： Grading