检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Fudolig, Mikaela Irene Alshaabi, Thayer Cramer, Kathryn Danforth, Christopher M. Dodds, Peter Sheridan Computational Story Lab Vermont Complex Systems Center MassMutual Center of Excellence for Complex Systems and Data Science Vermont Advanced Computing Core University of Vermont BurlingtonVT United States Advanced Bioimaging Center UC Berkeley BerkeleyCA United States Department of Mathematics & Statistics University of Vermont BurlingtonVT United States Department of Computer Science University of Vermont BurlingtonVT United States

While quantitative methods have been used to examine changes in word usage in books, studies have focused on overall trends, such as the shapes of narratives, which are independent of book length. We instead look at how words change over the course of a book as a function of the number of words, rather than the fraction of the book, completed at any given point;we define this measure as "cumulative word-time". Using ousiometrics, a reinterpretation of the valence-arousal-dominance framework of meaning obtained from semantic differentials, we convert text into time series of power and danger scores, with time corresponding to cumulative word-time. Each time series is then decomposed using empirical mode decomposition into a sum of constituent oscillatory modes and a non-oscillatory trend. By comparing the decomposition of the original power and danger time series with those derived from shuffled text, we find that shorter books exhibit only a general trend, while longer books have fluctuations in addition to the general trend. These fluctuations typically have a period of a few thousand words regardless of the book length or library classification code, but vary depending on the content and structure of the book. Our findings suggest that, in the ousiometric sense, longer books are not expanded versions of shorter books, but rather are more similar in structure to a concatenation of shorter texts. Further, they are consistent with editorial practices that require longer texts to be broken down into sections, such as chapters. Our method also provides a data-driven denoising approach that works for texts of various lengths, in contrast to the more traditional approach of using large window sizes that may inadvertently smooth out relevant information, especially for shorter texts. All together, these results open up avenues for future work in computational literary analysis, particularly the possibility of measuring a basic unit of narrative. Copyright © 2022, The Auth

关键词： Empirical mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Insights into elastic properties of coarse-grained DNA models: q-stiffness of cgDNA vs. cgDNA+

arXiv

引用

arXiv 2024年

作者： Laeremans, Wout Segers, Midas Voorspoels, Aderik Carlon, Enrico Hooyberghs, Jef Soft Matter and Biological Physics Department of Applied Physics Institute for Complex Molecular Systems Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Soft Matter and Biophysics Unit KU Leuven Celestijnenlaan 200D Leuven3001 Belgium UHasselt Faculty of Sciences Data Science Institute Theory Lab Agoralaan Diepenbeek3590 Belgium

Coarse-grained models have emerged as valuable tools to simulate long DNA molecules while maintaining computational efficiency. These models aim at preserving interactions among coarse-grained variables in a manner that mirrors the underlying atomistic description. We explore here a method for testing coarse-grained vs. all-atom models using stiffness matrices in Fourier space (q-stiffnesses), which are particularly suited to probe DNA elasticity at different length scales. We focus on a class of coarse-grained rigid base DNA models known as cgDNA and its most recent version cgDNA+. Our analysis shows that while cgDNA+ follows closely the q-stiffnesses of the all-atom model, the original cgDNA shows some deviations for twist and bending variables which are rather strong in the q → 0 (long length scale) limit. The consequence is that while both cgDNA and cgDNA+ give a suitable description of local elastic behavior, the former misses some effects which manifest themselves at longer length scales. In particular, cgDNA performs poorly on the twist stiffness with a value much lower than expected for long DNA molecules. Conversely, the all-atom and cgDNA+ twist is strongly length scale dependent: DNA is torsionally soft at a few base pair distances, but becomes more rigid at distances of a few dozens base pairs. Our analysis shows that the bending persistence length in all-atom and cgDNA+ is somewhat overestimated. © 2024, CC BY.

关键词： Stiffness

来源：评论

学校读者我要写书评

暂无评论

Biphasic amplitude oscillator characterized by distinct dynamics of trough and crest

引用

Physical Review E 2023年第6期108卷 064412-064412页

作者： Jun Jin Fei Xu Zhilong Liu Hong Qi Chenggui Yao Jianwei Shuai Xiang Li Department of Physics Xiamen University Xiamen Fujian 361005 China Department of Physics Anhui Normal University Wuhu Anhui 241002 China Complex Systems Research Center Shanxi University Taiyuan Shanxi 030006 China College of Data Science Jiaxing University Jiaxing Zhejiang 314000 China Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine Vision and Brain Health) and Wenzhou Institute University of Chinese Academy of Sciences Wenzhou Zhejiang 325001 China

Biphasic amplitude dynamics (BAD) of oscillation have been observed in many biological systems. However, the specific topology structure and regulatory mechanisms underlying these biphasic amplitude dynamics remain elusive. Here, we searched all possible two-node circuit topologies and identified the core oscillator that enables robust oscillation. This core oscillator consists of a negative feedback loop between two nodes and a self-positive feedback loop of the input node, which result in the fast and slow dynamics of the two nodes, thereby achieving relaxation oscillation. Landscape theory was employed to study the stochastic dynamics and global stability of the system, allowing us to quantitatively describe the diverse positions and sizes of the Mexican hat. With increasing input strength, the size of the Mexican hat exhibits a gradual increase followed by a subsequent decrease. The self-activation of input node and the negative feedback on input node, which dominate the fast dynamics of the input node, were observed to regulate BAD in a bell-shaped manner. Both deterministic and statistical analysis results reveal that BAD is characterized by the linear and nonlinear dependence of the oscillation trough and crest on the input strength. In addition, combining with computational and theoretical analysis, we addressed that the linear response of trough to input is predominantly governed by the negative feedback, while the nonlinear response of crest is jointly regulated by the negative feedback loop and the self-positive feedback loop within the oscillator. Overall, this study provides a natural and physical basis for comprehending the occurrence of BAD in oscillatory systems, yielding guidance for the design of BAD in synthetic biology applications.

关键词： Cell signaling Biological networks Dynamical systems Stochastic dynamical systems

来源：评论

学校读者我要写书评

暂无评论

Polymer dynamics under tension: Mean first passage time for looping

arXiv

引用

arXiv 2024年

作者： Laeremans, Wout den Ouden, Anne Floor Hooyberghs, Jef Ellenbroek, Wouter G. Soft Matter and Biological Physics Department of Applied Physics and Science Education Institute for Complex Molecular Systems Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Laboratory of Physical Chemistry Department of Chemical Engineering and Chemistry Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands UHasselt Faculty of Sciences Data Science Institute Theory Lab Agoralaan Diepenbeek3590 Belgium

This study deals with polymer looping, an important process in many chemical and biological systems. We investigate basic questions on the looping dynamics of a polymer under tension using the freely-jointed chain (FJC) model. Previous theoretical approaches to polymer looping under tension have relied on barrier escape methods, which assume local equilibrium, an assumption that may not always hold. As a starting point we use an analytical expression for the equilibrium looping probability as a function of the number of monomers and applied force, predicting an inverse relationship between looping time and looping probability. Using molecular dynamics simulations the predictions of this theoretical approach are validated within the numerical precision achieved. We compare our predictions to those of the barrier escape approach, by way of a calculation of the mean first passage time (MFPT) for the ends of a polymer to cross. For this purpose, we derive the exact free energy landscape, but resulting temporal predictions do not agree with the observed inverse scaling. We conclude that the traditional barrier escape approach does not provide satisfactory predictions for polymer looping dynamics and that the inverse scaling with looping probability offers a more reliable alternative. Copyright © 2024, The Authors. All rights reserved.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

An unsupervised sampling approach for image-sentence matching using document-level structural information

arXiv

引用

arXiv 2021年

作者： Li, Zejun Wei, Zhongyu Fan, Zhihao Shan, Haijun Huang, Xuanjing School of Data Science Fudan University China Zhejiang Lab China School of Computer Science Fudan University China Research Institute of Intelligent and Complex Systems Fudan University China

In this paper, we focus on the problem of unsupervised image-sentence matching. Existing research explores to utilize document-level structural information to sample positive and negative instances for model training. Although the approach achieves positive results, it introduces a sampling bias and fails to distinguish instances with high semantic similarity. To alleviate the bias, we propose a new sampling strategy to select additional intra-document image-sentence pairs as positive or negative samples. Furthermore, to recognize the complex pattern in intra-document samples, we propose a Transformer based model to capture fine-grained features and implicitly construct a graph for each document, where concepts in a document are introduced to bridge the representation learning of images and sentences in the context of a document. Experimental results show the effectiveness of our approach to alleviate the bias and learn well-aligned multimodal representations. Copyright © 2021, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Community Detection with the Map Equation and Infomap: Theory and Applications

arXiv

引用

arXiv 2023年

作者： Smiljanić, Jelena Blöcker, Christopher Holmgren, Anton Edler, Daniel Neuman, Magnus Rosvall, Martin Integrated Science Lab Department of Physics Umeå University UmeåSE-901 87 Sweden Scientific Computing Laboratory Center for the Study of Complex Systems Institute of Physics Belgrade University of Belgrade Pregrevica 118 Belgrade11080 Serbia Center for Artificial Intelligence and Data Science University of Würzburg WürzburgDE-97070 Germany Data Analytics Group Department of Informatics University of Zürich ZürichCH-8006 Switzerland Gothenburg Global Biodiversity Centre University of Gothenburg Gothenburg Sweden

Real-world networks have a complex topology comprising many elements often structured into communities. Revealing these communities helps researchers uncover the organizational and functional structure of the system that the network represents. However, detecting community structures in complex networks requires selecting a community detection method among a multitude of alternatives with different network representations, community interpretations, and underlying mechanisms. This review and tutorial focuses on a popular community detection method called the map equation and its search algorithm Infomap. The map equation framework for community detection describes communities by analyzing dynamic processes on the network. Thanks to its flexibility, the map equation provides extensions that can incorporate various assumptions about network structure and dynamics. To help decide if the map equation is a suitable community detection method for a given complex system and problem at hand - and which variant to choose - we review the map equation's theoretical framework and guide users in applying the map equation to various research problems. © 2023, CC BY-NC-ND.

关键词： Information theory

来源：评论

学校读者我要写书评

暂无评论

Noncooperative dynamics in election interference

引用

Physical Review E 2020年第2期101卷 022307-022307页

作者： David Rushing Dewhurst Christopher M. Danforth Peter Sheridan Dodds MassMutual Center of Excellence in Complex Systems and Data Science Computational Story Lab Vermont Complex Systems Center and Department of Mathematics and Statistics University of Vermont Burlington Vermont 05405 USA.

Foreign power interference in domestic elections is an existential threat to societies. Manifested through myriad methods from war to words, such interference is a timely example of strategic interaction between economic and political agents. We model this interaction between rational game players as a continuous-time differential game, constructing an analytical model of this competition with a variety of payoff structures. All-or-nothing attitudes by only one player regarding the outcome of the game lead to an arms race in which both countries spend increasing amounts on interference and counterinterference operations. We then confront our model with data pertaining to the Russian interference in the 2016 United States presidential election contest. We introduce and estimate a Bayesian structural time-series model of election polls and social media posts by Russian Twitter troll accounts. Our analytical model, while purposefully abstract and simple, adequately captures many temporal characteristics of the election and social media activity. We close with a discussion of our model's shortcomings and suggestions for future research.

关键词： Econophysics Brownian dynamics data analysis Fokker–Planck equation Monte Carlo methods

来源：评论

学校读者我要写书评

暂无评论

Keep it Consistent: Topic-Aware Storytelling from an Image Stream via Iterative Multi-agent Communication 28

Keep it Consistent: Topic-Aware Storytelling from an Image S...

引用

28th International Conference on Computational Linguistics, COLING 2020

作者： Wang, Ruize Wei, Zhongyu Cheng, Ying Li, Piji Shan, Haijun Zhang, Ji Zhang, Qi Huang, Xuanjing Academy for Engineering and Technology Fudan University China School of Data Science Fudan University China Research Institute of Intelligent and Complex Systems Fudan University China Tencent AI Lab. China Zhejiang Lab. China School of Computer Science Fudan University China

ISBN: (纸本)9781952148279

Visual storytelling aims to generate a narrative paragraph from a sequence of images automatically. Existing approaches construct text description independently for each image and roughly concatenate them as a story, which leads to the problem of generating semantically incoherent content. In this paper, we propose a new way for visual storytelling by introducing a topic description task to detect the global semantic context of an image stream. A story is then constructed with the guidance of the topic description. In order to combine the two generation tasks, we propose a multi-agent communication framework that regards the topic description generator and the story generator as two agents and learn them simultaneously via iterative updating mechanism. We validate our approach on VIST dataset, where quantitative results, ablations, and human evaluation demonstrate our method’s good ability in generating stories with higher quality compared to state-of-the-art methods. © 2020 COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference. All rights reserved.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Administrative Health Records: A Systematic Review of Techniques and Applications

arXiv

引用

arXiv 2023年

作者： Caruana, Adrian Bandara, Madhushi Musial, Katarzyna Catchpoole, Daniel Kennedy, Paul J. Australian Artificial Intelligence Institute Faculty of Engineering and IT University of Technology Sydney Australia Complex Adaptive Systems Lab Data Science Institute Faculty of Engineering and IT University of Technology Sydney Australia Biospecimen Research Services The Children's Cancer Research Unit The Children's Hospital Westmead Australia Joint Research Centre in AI for Health and Wellness University of Technology Sydney Australia Ontario Tech University Canada

Machine learning provides many powerful and effective techniques for analysing heterogeneous electronic health records (EHR). Administrative Health Records (AHR) are a subset of EHR collected for administrative purposes, and the use of machine learning on AHRs is a growing subfield of EHR analytics. Existing reviews of EHR analytics emphasise that the data-modality of the EHR limits the breadth of suitable machine learning techniques, and pursuable healthcare applications. Despite emphasising the importance of data modality, the literature fails to analyse which techniques and applications are relevant to AHRs. AHRs contain uniquely well-structured, categorically encoded records which are distinct from other data-modalities captured by EHRs, and they can provide valuable information pertaining to how patients interact with the healthcare system. This paper systematically reviews AHR-based research, analysing 70 relevant studies and spanning multiple databases. We identify and analyse which machine learning techniques are applied to AHRs and which health informatics applications are pursued in AHR-based research. We also analyse how these techniques are applied in pursuit of each application, and identify the limitations of these approaches. We find that while AHR-based studies are disconnected from each other, the use of AHRs in health informatics research is substantial and accelerating. Our synthesis of these studies highlights the utility of AHRs for pursuing increasingly complex and diverse research objectives despite a number of pervading data- and technique-based limitations. Finally, through our findings, we propose a set of future research directions that can enhance the utility of AHR data and machine learning techniques for health informatics research. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Inferring Actual Treatment Pathways from Patient Records

arXiv

引用

arXiv 2023年

作者： Wilkins-Caruana, Adrian Bandara, Madhushi Musial, Katarzyna Catchpoole, Daniel Kennedy, Paul J. Australian Artificial Intelligence Institute Faculty of Engineering and IT University of Technology Sydney Australia Complex Adaptive Systems Lab Data Science Institute Faculty of Engineering and IT University of Technology Sydney Australia Biospecimen Research Services The Children's Cancer Research Unit The Children's Hospital Westmead Australia Joint Research Centre in AI for Health and Wellness University of Technology Sydney Australia Ontario Tech University Canada

Objective: Treatment pathways are step-by-step plans outlining the recommended medical care for specific diseases;they get revised when different treatments are found to improve patient outcomes. Examining health records is an important part of this revision process, but inferring patients' actual treatments from health data is challenging due to complex event-coding schemes and the absence of pathway-related annotations. The objective of this study is to develop a method for inferring actual treatment steps for a particular patient group from administrative health records - a common form of tabular healthcare data - and address several technique- and methodology-based gaps in treatment pathway-inference research. Methods: We introduce Defrag, a method for examining health records to infer the real-world treatment steps for a particular patient group. Defrag learns the semantic and temporal meaning of healthcare event sequences, allowing it to reliably infer treatment steps from complex healthcare data. To our knowledge, Defrag is the first pathway-inference method to utilise a neural network (NN), an approach made possible by a novel, self-supervised learning objective. We also developed a testing and validation framework for pathway inference, which we use to characterise and evaluate Defrag's pathway inference ability, establish benchmarks, and compare against baselines. Results: We demonstrate Defrag's effectiveness by identifying best-practice pathway fragments for breast cancer, lung cancer, and melanoma in public healthcare records. Additionally, we use synthetic data experiments to demonstrate the characteristics of the Defrag inference method, and to compare Defrag to several baselines, where it significantly outperforms non-NN-based methods. Conclusions: Defrag offers an innovative and effective approach for inferring treatment pathways from complex health data. Defrag significantly outperforms several existing pathway-inference methods, but computationall

关键词： Semantics

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：