arXiv - QuanBio - Populations and Evolution最新文献_第4页

Simple measures to capture the robustness and the plasticity of soil microbial communities 捕捉土壤微生物群落稳健性和可塑性的简单方法

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-05 DOI: arxiv-2409.03372

Takashi Shimada, Kazumori Mise, Kai Morino, Shigeto Otsuka

引用次数: 0

Homoclinic Chaos Unveiling Quorum Sensing Dynamics 同线性混沌揭示法定人数感应动力学

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-04 DOI: arxiv-2409.02764

Mariana Harris, Pablo Aguirre, Víctor F. Breña-Medina

引用次数: 0

Regulatory Functions from Cells to Society 从细胞到社会的调节功能

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-04 DOI: arxiv-2409.02884

Vicky Chuqiao Yang, Christopher P. Kempes, S. Redner, Geoffrey B. West, Hyejin Youn

{"title":"Regulatory Functions from Cells to Society","authors":"Vicky Chuqiao Yang, Christopher P. Kempes, S. Redner, Geoffrey B. West, Hyejin Youn","doi":"arxiv-2409.02884","DOIUrl":"https://doi.org/arxiv-2409.02884","url":null,"abstract":"Regulatory functions are essential in both socioeconomic and biological\u0000systems, from corporate managers to regulatory genes in genomes. Regulatory\u0000functions come with substantial costs, but are often taken for granted. Here,\u0000we empirically examine regulatory costs across diverse systems -- biological\u0000organisms (bacteria and eukaryotic genomes), human organizations (companies,\u0000federal agencies, universities), and decentralized entities (Wikipedia, cities)\u0000-- using scaling analysis. We guide the empirical analysis with a conceptual\u0000model, which anticipates the scaling of regulatory costs to shift with the\u0000system's internal interaction structure -- well-mixed or modular. We find\u0000diverse systems exhibit consistent scaling patterns -- well-mixed systems\u0000exhibit superlinear scaling, while modular ones show sublinear or linear\u0000scaling. Further, we find that the socioeconomic systems containing more\u0000diverse occupational functions tend to have more regulatory costs than expected\u0000from their size, confirming the type of interactions also plays a role in\u0000regulatory costs. While many socioeconomic systems exhibit efficiencies of\u0000scale, regulatory costs in many social systems have grown disproportionally\u0000over time. Our finding suggests that the increasing complexity of functions may\u0000contribute to this trend. This cross-system comparison offers a framework for\u0000understanding regulatory costs and could guide future efforts to identify and\u0000mitigate regulatory inefficiencies.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical Study of Interaction Network Structures in Competitive Ecosystems 竞争性生态系统中互动网络结构的数值研究

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-03 DOI: arxiv-2409.01894

David A. Kessler, Nadav M. Shnerb

引用次数: 0

Compartment model of strategy-dependent time delays in replicator dynamics 复制器动态中与策略有关的时间延迟的区室模型

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-02 DOI: arxiv-2409.01116

Małgorzata Fic, Frank Bastian, Jacek Miękisz, Chaitanya S. Gokhale

{"title":"Compartment model of strategy-dependent time delays in replicator dynamics","authors":"Małgorzata Fic, Frank Bastian, Jacek Miękisz, Chaitanya S. Gokhale","doi":"arxiv-2409.01116","DOIUrl":"https://doi.org/arxiv-2409.01116","url":null,"abstract":"Real-world processes often exhibit temporal separation between actions and\u0000reactions - a characteristic frequently ignored in many modelling frameworks.\u0000Adding temporal aspects, like time delays, introduces a higher complexity of\u0000problems and leads to models that are challenging to analyse and\u0000computationally expensive to solve. In this work, we propose an intermediate\u0000solution to resolve the issue in the framework of evolutionary game theory. Our\u0000compartment-based model includes time delays while remaining relatively simple\u0000and straightforward to analyse. We show that this model yields qualitatively\u0000comparable results with models incorporating explicit delays. Particularly, we\u0000focus on the case of delays between parents' interaction and an offspring\u0000joining the population, with the magnitude of the delay depending on the\u0000parents' strategy. We analyse Stag-Hunt, Snowdrift, and the Prisoner's Dilemma\u0000game and show that strategy-dependent delays are detrimental to affected\u0000strategies. Additionally, we present how including delays may change the\u0000effective games played in the population, subsequently emphasising the\u0000importance of considering the studied systems' temporal aspects to model them\u0000accurately.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mathematical model of CAR-T-cell therapy for a B-cell Lymphoma lymph node CAR-T 细胞疗法治疗 B 细胞淋巴瘤淋巴结的数学模型

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-02 DOI: arxiv-2409.01164

Soukaina Sabir, Odelaisy León-Triana, Sergio Serrano, Roberto Barrio, Victor M. Pérez-García

引用次数: 0

Forecasting infectious disease prevalence with associated uncertainty using neural networks 利用神经网络预测具有相关不确定性的传染病流行率

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-02 DOI: arxiv-2409.01154

Michael Morris

{"title":"Forecasting infectious disease prevalence with associated uncertainty using neural networks","authors":"Michael Morris","doi":"arxiv-2409.01154","DOIUrl":"https://doi.org/arxiv-2409.01154","url":null,"abstract":"Infectious diseases pose significant human and economic burdens. Accurately\u0000forecasting disease incidence can enable public health agencies to respond\u0000effectively to existing or emerging diseases. Despite progress in the field,\u0000developing accurate forecasting models remains a significant challenge. This\u0000thesis proposes two methodological frameworks using neural networks (NNs) with\u0000associated uncertainty estimates - a critical component limiting the\u0000application of NNs to epidemic forecasting thus far. We develop our frameworks\u0000by forecasting influenza-like illness (ILI) in the United States. Our first\u0000proposed method uses Web search activity data in conjunction with historical\u0000ILI rates as observations for training NN architectures. Our models incorporate\u0000Bayesian layers to produce uncertainty intervals, positioning themselves as\u0000legitimate alternatives to more conventional approaches. The best performing\u0000architecture: iterative recurrent neural network (IRNN), reduces mean absolute\u0000error by 10.3% and improves Skill by 17.1% on average in forecasting tasks\u0000across four flu seasons compared to the state-of-the-art. We build on this\u0000method by introducing IRNNs, an architecture which changes the sampling\u0000procedure in the IRNN to improve the uncertainty estimation. Our second\u0000framework uses neural ordinary differential equations to bridge the gap between\u0000mechanistic compartmental models and NNs; benefiting from the physical\u0000constraints that compartmental models provide. We evaluate eight neural ODE\u0000models utilising a mixture of ILI rates and Web search activity data to provide\u0000forecasts. These are compared with the IRNN and IRNN0 - the IRNN using only ILI\u0000rates. Models trained without Web search activity data outperform the IRNN0 by\u000016% in terms of Skill. Future work should focus on more effectively using\u0000neural ODEs with Web search data to compete with the best performing IRNN.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling contagious disease spreading 模拟传染病传播

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-02 DOI: arxiv-2409.01103

Dipak Patra

{"title":"Modeling contagious disease spreading","authors":"Dipak Patra","doi":"arxiv-2409.01103","DOIUrl":"https://doi.org/arxiv-2409.01103","url":null,"abstract":"An understanding of the disease spreading phenomenon based on a mathematical\u0000model is extremely needed for the implication of the correct policy measures to\u0000contain the disease propagation. Here, we report a new model namely the\u0000Ising-SIR model describing contagious disease spreading phenomena including\u0000both airborne and direct contact disease transformations. In the airborne case,\u0000a susceptible agent can catch the disease either from the environment or its\u0000infected neighbors whereas in the second case, the agent can be infected only\u0000through close contact with its infected neighbors. We have performed Monte\u0000Carlo simulations on a square lattice using periodic boundary conditions to\u0000investigate the dynamics of disease spread. The simulations demonstrate that\u0000the mechanism of disease spreading plays a significant role in the growth\u0000dynamics and leads to different growth exponent. In the direct contact disease\u0000spreading mechanism, the growth exponent is nearly equal to two for some model\u0000parameters which agrees with earlier empirical observations. In addition, the\u0000model predicts various types of spatiotemporal patterns that can be observed in\u0000nature.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Swarm Systems as a Platform for Open-Ended Evolutionary Dynamics 作为开放式进化动力学平台的蜂群系统

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-02 DOI: arxiv-2409.01469

Hiroki Sayama

引用次数: 0

Analysis of a mathematical model for malaria using data-driven approach 利用数据驱动方法分析疟疾数学模型

arXiv - QuanBio - Populations and Evolution Pub Date : 2024-09-01 DOI: arxiv-2409.00795

Adithya Rajnarayanan, Manoj Kumar

{"title":"Analysis of a mathematical model for malaria using data-driven approach","authors":"Adithya Rajnarayanan, Manoj Kumar","doi":"arxiv-2409.00795","DOIUrl":"https://doi.org/arxiv-2409.00795","url":null,"abstract":"Malaria is one of the deadliest diseases in the world, every year millions of\u0000people become victims of this disease and many even lose their lives. Medical\u0000professionals and the government could take accurate measures to protect the\u0000people only when the disease dynamics are understood clearly. In this work, we\u0000propose a compartmental model to study the dynamics of malaria. We consider the\u0000transmission rate dependent on temperature and altitude. We performed the\u0000steady state analysis on the proposed model and checked the stability of the\u0000disease-free and endemic steady state. An artificial neural network (ANN) is\u0000applied to the formulated model to predict the trajectory of all five\u0000compartments following the mathematical analysis. Three different neural\u0000network architectures namely Artificial neural network (ANN), convolution\u0000neural network (CNN), and Recurrent neural network (RNN) are used to estimate\u0000these parameters from the trajectory of the data. To understand the severity of\u0000a disease, it is essential to calculate the risk associated with the disease.\u0000In this work, the risk is calculated using dynamic mode decomposition(DMD) from\u0000the trajectory of the infected people.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0