检索结果-内蒙古大学图书馆

39th International Symposium on Lattice Field Theory, LATTICE 2022

作者： Yamamoto, Shuhei Bacchio, Simone Finkenrath, Jacob Computation-based Science and Technology Research Center The Cyprus Institute Cyprus

Lyncs-API is a Python API for Lattice QCD applications. It is designed as a Python toolkit that allows the user to use and run various lattice QCD libraries while programming in Python. The goal is to provide the user an easy programming experience without scarifying performance across multiple platforms, by preparing a common framework for various softwares for lattice QCD calculations. As such, it contains interfaces to, e.g., c-lime, DDalphaAMG, tmLQCD, and QUDA. In this proceeding, we focus on a Lyncs interface to QUDA, named Lyncs-QUDA, and present a small tutorial on how to use this Python interface to perform a HMC simulation using QUDA. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-based Phylogenetic Analysis of Influenza Protein Sequences: A Siamese Neural Network Approach

Deep Learning-based Phylogenetic Analysis of Influenza Prote...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Chrysostomou, Charalambos The Cyprus Institute Computation-Based Science and Technology Research Center Nicosia Cyprus

ISBN: (纸本)9798350337488

Influenza, a highly mutable virus that can infect multiple species, has been a persistent global health challenge. The virus's ability to recombine and evolve necessitates robust and efficient tools for phylogenetic analysis. Traditional methods, however, often rely on sequence alignment, which can be computationally intensive and less effective when dealing with large-scale sequence data. This paper introduces a new approach to phylogenetic analysis based on Siamese Neural Network (SNN). Trained on the influenza virus's Neuraminidase (NA) protein, the proposed SNN model can accurately classify the primary host species - human, avian, and swine - and construct phylogenetic trees without requiring sequence alignment. The empirical results demonstrate the model's robustness, achieving an accuracy of 95.2% in host species classification. © 2023 IEEE.

关键词： Alignment Bioinformatics Classification Deep Learning Influenza Machine Learning Neuraminidase Phylogenetic Analysis Protein Sequences Siamese Neural Network Viruses

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Assisted Classification of Allergenic Proteins: An Exploration of Amino Acid Indices

Deep Learning-Assisted Classification of Allergenic Proteins...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Chrysostomou, Charalambos The Cyprus Institute Computation-Based Science and Technology Research Center Nicosia Cyprus

ISBN: (纸本)9798350337488

The allergenicity prediction is a pivotal yet challenging in bioinformatics, with no universally accepted methodology. Existing strategies primarily hinge on comparing novel protein sequences with known allergenic sequences, using sequence identity thresholds as a benchmark. However, these approaches often overlook other influential factors such as physicochemical properties, protein stability, post-translational modifications, and cleavage sites, all of which may contribute to allergenicity. While bioinformatics methodologies have been devised to analyse and classify allergenic protein sequences, their efficacy in accurately predicting low homology allergenic proteins still needs to be investigated. This study introduces a novel approach to allergenicity prediction, leveraging the capabilities of deep learning techniques, specifically Convolutional Neural Networks (CNNs). We investigate the utility of various amino acid indices for encoding protein sequences into numerical data and evaluate their impact on classification accuracy. Our research is underpinned by a comprehensive dataset, encompassing 3,260 allergenic and 191,001 non-allergenic proteins, collated from diverse online databases. The results of our study underscore the potential of our proposed method in advancing bioinformatics methodologies for allergenicity prediction, thereby contributing to the broader scientific discourse on allergenic proteins. © 2023 IEEE.

关键词： Allergenicity Bioinformatics Convolutional Neural Networks Deep Learning Machine Learning Protein Allergens Protein Sequences Sequence Homology

来源：评论

学校读者我要写书评

暂无评论

Lyncs-API: A Python API for Lattice QCD applications 38

Lyncs-API: A Python API for Lattice QCD applications

引用

38th International Symposium on Lattice Field Theory, LATTICE 2021

作者： Bacchio, Simone Finkenrath, Jacob Stylianou, Christodoulos Computation-based Science and Technology Research Center The Cyprus Institute Cyprus

We present Lyncs-API, a Python API for Lattice QCD applications currently under development. Lyncs aims to bring several widely used libraries for Lattice QCD under a common framework. Lyncs flexibly links to libraries for CPUs and GPUs in a way that can accommodate additional computing architectures as these arise, achieving performance-portability for the calculations while maintaining the same high-level workflow. Lyncs distributes calculations using Dask and mpi4py, with bindings to the libraries automatically generated by cppyy. While Lyncs is designed to allow linking to multiple libraries, we focus on a set of targeted packages that include DDalphaAMG, tmLQCD, QUDA and c-lime. More libraries will be added in the future. We also develop generic-purpose tools for facilitating the usage of Python in Lattice QCD and HPC in general. The project is open-source, community-oriented and available on Github. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

关键词： Libraries

来源：评论

学校读者我要写书评

暂无评论

Confining strings, axions and glueballs in the planar limit 20

Confining strings, axions and glueballs in the planar limit

引用

20th Hellenic School and Workshops on Elementary Particle Physics and Gravity, CORFU 2021

作者： Athenodorou, Andreas Computation-based Science and Technology Research Center The Cyprus Institute Cyprus

We present recent results on the spectrum of a confining flux tube that is closed around a spatial torus as a function of its length as well as the spectrum of glueballs. The extraction of the spectra has been realized by simulating four dimensional SU(N) gauge theories and performing measurements using lattice techniques. Regarding flux-tubes, we have performed calculations for N = 3, 5, 6 and for various values of spin, parity and longitudinal momentum. Long flux-tubes can be thought of as infinitesimally thin strings;hence their spectrum is expected to be described by an effective string theory. Furthermore, the flux-tube's internal structure makes possible the existence of massive states in addition to string modes. Our calculations demonstrate that although most states exhibit a spectrum which can be approximated adequately by Nambu-Goto there is strong evidence for the existence of a massive axion on the world-sheet of the QCD flux-tube as well as a bound state of two such axions. Regarding glueballs, we extracted spectra from N = 2 to N = 12 which enables us to extrapolate to N = ∞. Our main aim was to calculate the lightest glueball masses for all different configurations of the quantum numbers of spin, parity and charge conjugation. This provides a major update on the spectrum of glueballs in the planar limit. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

关键词： String theory

来源：评论

学校读者我要写书评

暂无评论

Mixed-decomposed convolutional network:A lightweight yet efficient convolutional neural network for ocular disease recognition

引用

CAAI Transactions on Intelligence technology 2024年第2期9卷 319-332页

作者： Xiaoqing Zhang Xiao Wu Zunjie Xiao Lingxi Hu Zhongxi Qiu Qingyang Sun Risa Higashita Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhenChina Tomey Corporation NagoyaJapan Guangdong Provincial Key Laboratory of Brain‐inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhenChina Singapore Eye Research Institute SingaporeSingapore

Eye health has become a global health concern and attracted broad *** the years,researchers have proposed many state-of-the-art convolutional neural networks(CNNs)to assist ophthalmologists in diagnosing ocular diseases efficiently and ***,most existing methods were dedicated to constructing sophisticated CNNs,inevitably ignoring the trade-off between performance and model *** alleviate this paradox,this paper proposes a lightweight yet efficient network architecture,mixeddecomposed convolutional network(MDNet),to recognise ocular *** MDNet,we introduce a novel mixed-decomposed depthwise convolution method,which takes advantage of depthwise convolution and depthwise dilated convolution operations to capture low-resolution and high-resolution patterns by using fewer computations and fewer *** conduct extensive experiments on the clinical anterior segment optical coherence tomography(AS-OCT),LAG,University of California San Diego,and CIFAR-100 *** results show our MDNet achieves a better trade-off between the performance and model complexity than efficient CNNs including MobileNets and ***,our MDNet outperforms MobileNets by 2.5%of accuracy by using 22%fewer parameters and 30%fewer computations on the AS-OCT dataset.

关键词： artificial intelligence deep learning deep neural networks image analysis image classification medical applications medical image processing

来源：评论

学校读者我要写书评

暂无评论

Implementation of Simultaneous Inversion of a Multi-shifted Dirac Matrix for Twisted-Mass Fermions within DDαAMG 38

Implementation of Simultaneous Inversion of a Multi-shifted ...

引用

38th International Symposium on Lattice Field Theory, LATTICE 2021

作者： Yamamoto, Shuhei Bacchio, Simone Finkenrath, Jacob Computation-based Science and Technology Research Center The Cyprus Institute Aglantzia Nicosia Cyprus

At physical light quark masses, efficient linear solvers are crucial for carrying out the millions of inversions of the Dirac matrix required for obtaining high statistics in quark correlation functions. Adaptive algebraic multi-grid methods have proven to be very efficient in such cases, exhibiting mild critical slowing down towards very light quark masses and outperforming traditional solver methods, such as the conjugate gradient method, at the physical point. We will discuss our implementations of simultaneous inversion of a (degenerate) Dirac matrix for twisted-mass fermions for multiple right-hand-sides (rhs) with multi-shifts and block-Krylov solvers. The implementation is carried out within the community library DDαAMG, which implements aggregation-based Domain Decomposition adaptive algebraic multi-grid methods. The block-Krylov solvers are provided via the Fast Accurate Block Linear krylOv Solver (Fabulous) library and can be used at coarser levels. Our code inverts Dirac matrices with different twisted-mass terms and for multiple rhs simultaneously and is thus also suitable for components within a typical lattice QCD simulation workflow, such as the rational approximation. We show preliminary results on scalability and compare the performance of our implementation when using different Block-Krylov solver techniques. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

Learning continuous network emerging dynamics from scarce observations via data-adaptive stochastic processes

引用

science China(Information sciences) 2024年第12期67卷 240-255页

作者： Jiaxu CUI Qipeng WANG Bingyi SUN Jiming LIU Bo YANG College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Public Computer Education and Research Center Jilin University Department of Computer Science Hong Kong Baptist University

Learning network dynamics from the empirical structure and spatio-temporal observation data is crucial to revealing the interaction mechanisms of complex networks in a wide range of domains. However,most existing methods only aim at learning network dynamic behaviors generated by a specific ordinary differential equation instance, resulting in ineffectiveness for new ones, and generally require dense *** observed data, especially from network emerging dynamics, are usually difficult to obtain, which brings trouble to model learning. Therefore, learning accurate network dynamics with sparse, irregularly-sampled,partial, and noisy observations remains a fundamental challenge. We introduce a new concept of the stochastic skeleton and its neural implementation, i.e., neural ODE processes for network dynamics(NDP4ND), a new class of stochastic processes governed by stochastic data-adaptive network dynamics, to overcome the challenge and learn continuous network dynamics from scarce observations. Intensive experiments conducted on various network dynamics in ecological population evolution, phototaxis movement, brain activity, epidemic spreading, and real-world empirical systems, demonstrate that the proposed method has excellent data adaptability and computational efficiency, and can adapt to unseen network emerging dynamics, producing accurate interpolation and extrapolation with reducing the ratio of required observation data to only about 6% and improving the learning speed for new dynamics by three orders of magnitude.

关键词： complex networks network dynamics emerging spatio-temporal dynamics neural processes

来源：评论

学校读者我要写书评

暂无评论

Effect of Al(OH)_(3) prepared from fly ash on the structural and catalytic properties of g-C_(3)N_(4)-based materials

引用

Chinese Journal of Chemical Engineering 2024年第10期74卷 44-51页

作者： Qingbo Yu Xianhua Li Qingping Wang The First Affiliated Hospital of Anhui University of Science and Technology(Huainan First People's Hospital) Anhui University of Science and TechnologyHuainan 232001China Anhui Industrial Generic Technology Research Center for New Materials from Coal-based Solid Wastes Huainan 232001China School of Materials Science and Engineering Anhui University of Science and TechnologyHuainan 232001China

In order to find the optimal combination method of secondary utilization of fly ash and graphite-phase carbon nitride(g-C_(3)N_(4))modification,an efficient composite photocatalyst of γ-Al_(2)O_(3)/g-C_(3)N_(4)was obtained by calcining the composite precursors of Al(OH)3/dicyandiamide(DCDA).The introduction of Al(OH)_(3)prepared by combining fly ash into the precursors causes hydrogen-bonding interactions between Al(OH)_(3)and DCDA,which facilitate the removal of N atoms from the edges of the CN framework of g-C_(3)N_(4)during condensation,and the composites prepared possess more cyano *** addition,γ-Al_(2)O_(3)and g-C_(3)N_(4)form a chemical bond at the interface,and this chemical bonding causes the density of the electron cloud in the vicinity of the N atoms to *** them,the strongest chemical bonding between Al_(2)O_(3)and g-C_(3)N_(4)was observed in ACN-1,whereas the most cyanine defects were formed in ACN-1,which made ACN-1 exhibit the best photocatalytic degradation of methylene blue,which is 2.48 times higher than that of the pristine g-C_(3)N_(4).

关键词： Precursors g-C_(3)N_(4) Waste treatment Catalyst Synthesis

来源：评论

学校读者我要写书评

暂无评论

Enhancement of densification and mechanical property of(Hf_(0.2)Zr_(0.2)Ti_(0.2)Nb_(0.2)Ta_(0.2))N high-entropy bulk ceramic via silicon carbide addition

引用

Journal of Advanced Ceramics 2025年第1期14卷 59-70页

作者： Wuyang Song Youjun Lu Lutong Yang Maohui Li Xiao Zhang Bo Ma Chuyun Wang Yanmin Wang Jinfeng Li Xiang Liu School of Materials Science and Engineering North Minzu UniversityYinchuan 750021China National and Local Joint Engineering Research Center of Advanced Carbon-Based Ceramics Preparation Technology Yinchuan 750021China College of Materials Science and Engineering South China University of TechnologyGuangzhou 510641China

In this work,high-entropy composite bulk ceramic of(Hf_(0.2)Zr_(0.2)Ti_(0.2)Nb_(0.2)Ta_(0.2))N/silicon carbide(HEN–SiC)was fabricated via spark plasma sintering(SPS)at 2100℃with submicron-sized single-phase(Hf_(0.2)Zr_(0.2)Ti_(0.2)Nb_(0.2)Ta_(0.2))N(HEN)powder as a raw material and SiC particles as a sintering *** crystal structure,phase composition,and grain size/morphology of the composite were characterized by X-ray diffraction,scanning electron microscopy,transmission electron microscopy,and energy dispersive *** relative density and mechanical properties(i.e.,bending strength,Vickers hardness,and fracture toughness)of the composite bulk ceramics were *** results show that the relative density of the composite bulk ceramics with increasing SiC particle content from 0 to 10.0 wt%increases from 93.08%±0.13%to 99.12%±0.12%.The high-entropy composite bulk ceramic with SiC particle content of 10.0 wt%exhibits the optimum mechanical properties(i.e.,Vickers hardness of 23.34±0.67 GPa,fracture toughness of 4.35±0.13 MPa·m^(1/2),and bending strength of 409±11 MPa)compared with the ceramic without SiC particles(i.e.,Vickers hardness of 19.16±0.56 GPa,fracture toughness of 3.78±0.09 MPa·m^(1/2),and bending strength of 335±11 MPa).These results indicate that SiC particles can be distributed and fill the HEN grain boundaries in the ceramic matrix,promoting composite densification via pinning grain boundaries and inhibiting grain *** enhanced fracture toughness can be due mainly to fine-grain toughening in addition to lamellar/chain structure *** use of SiC as a sintering aid can promote the densification and fracture toughness of high-entropy nitride bulk ceramics,providing a promising approach for the preparation of high-density,high-performance high-entropy nitride bulk ceramics.

关键词： high-entropy nitride ceramic composite ceramic fine-grain toughening mechanical properties

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：