Physics of Life Reviews最新文献_第3页

The circuit of cognition: Operational closure and the interpenetration of views. Comment on “The affective grounds of the mind. The affective pertinentization (APER) model” by Salvatore et al. 认知回路：操作封闭与观点的相互渗透。评论 "心灵的情感基础。情感相关化（APER）模型 "的评论。

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-11-08 DOI: 10.1016/j.plrev.2024.11.003

Gordon Sammut, Rebekah Mifsud, Noellie Brockdorff

引用次数: 0

What are the psychic forces present within a psychopathological state? Comment on “Nature heals: An informational entropy account of self-organization and change in field psychotherapy” by Pietro Sarasso, Wolfgang Tschacher, Felix Schoeller, Gianni Francesetti, Jan Roubal, Michela Gecele, Katiuscia Sacco, Irene Ronga 精神病理状态中存在哪些精神力量？评论 "自然治愈：Pietro Sarasso、Wolfgang Tschacher、Felix Schoeller、Gianni Francesetti、Jan Roubal、Michela Gecele、Katiuscia Sacco、Irene Ronga 对 "自然治愈：场心理疗法中自我组织和变化的信息熵解释 "的评论。

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-11-08 DOI: 10.1016/j.plrev.2024.11.001

G. de Felice

引用次数: 0

Affective dynamics in unionization and solidarity: Comment on “The affective grounds of the mind. The Affective Pertinentization (APER) model” by Salvatore et al. 工会和团结中的情感动力：对 Salvatore 等人所著 "心灵的情感基础。Salvatore 等人的 "情感化模式（APER）"一文的评论。

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-11-07 DOI: 10.1016/j.plrev.2024.11.002

Kevin R. Carriere , Michael Richardson

引用次数: 0

A theory of affect for social intervention? Comment on “The Affective Grounds of the Mind: The Affective Pertinentization (APER) Model” by Sergio Salvatore, Arianna Palmieri, Raffaele De Luca Picione, Vincenzo Bochicchio, Matteo Reho, Maria Rita Serio, Giampaolo Salvatore 社会干预的情感理论？评论 "心灵的情感基础：Sergio Salvatore、Arianna Palmieri、Raffaele De Luca Picione、Vincenzo Bochicchio、Matteo Reho、Maria Rita Serio、Giampaolo Salvatore 著："心灵的情感基础：情感渗透（APER）模型

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-11-01 DOI: 10.1016/j.plrev.2024.10.014

T. Mannarini

引用次数: 0

LLMs and generative agent-based models for complex systems research 用于复杂系统研究的 LLM 和基于生成代理的模型

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-10-28 DOI: 10.1016/j.plrev.2024.10.013

Yikang Lu , Alberto Aleta , Chunpeng Du , Lei Shi , Yamir Moreno

{"title":"LLMs and generative agent-based models for complex systems research","authors":"Yikang Lu , Alberto Aleta , Chunpeng Du , Lei Shi , Yamir Moreno","doi":"10.1016/j.plrev.2024.10.013","DOIUrl":"10.1016/j.plrev.2024.10.013","url":null,"abstract":"<div><div>The advent of Large Language Models (LLMs) offers to transform research across natural and social sciences, offering new paradigms for understanding complex systems. In particular, Generative Agent-Based Models (GABMs), which integrate LLMs to simulate human behavior, have attracted increasing public attention due to their potential to model complex interactions in a wide range of artificial environments. This paper briefly reviews the disruptive role LLMs are playing in fields such as network science, evolutionary game theory, social dynamics, and epidemic modeling. We assess recent advancements, including the use of LLMs for predicting social behavior, enhancing cooperation in game theory, and modeling disease propagation. The findings demonstrate that LLMs can reproduce human-like behaviors, such as fairness, cooperation, and social norm adherence, while also introducing unique advantages such as cost efficiency, scalability, and ethical simplification. However, the results reveal inconsistencies in their behavior tied to prompt sensitivity, hallucinations and even the model characteristics, pointing to challenges in controlling these AI-driven agents. Despite their potential, the effective integration of LLMs into decision-making processes —whether in government, societal, or individual contexts— requires addressing biases, prompt design challenges, and understanding the dynamics of human-machine interactions. Future research must refine these models, standardize methodologies, and explore the emergence of new cooperative behaviors as LLMs increasingly interact with humans and each other, potentially transforming how decisions are made across various systems.</div></div>","PeriodicalId":403,"journal":{"name":"Physics of Life Reviews","volume":"51 ","pages":"Pages 283-293"},"PeriodicalIF":13.7,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Causal inference from high-dimensional static data in soil microbiota networks 从土壤微生物群网络的高维静态数据中进行因果推断：对 Gong 等人的《全球变暖下土壤微生物群网络拓扑变化对森林恢复力的影响》的评论

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-10-28 DOI: 10.1016/j.plrev.2024.10.012

Arthur Berg

引用次数: 0

Invited Review for 20th Anniversary Special Issue of PLRev “AI for Mechanomedicine” PLRev 20 周年特刊 "AI for Mechanomedicine "特邀评论。

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-10-24 DOI: 10.1016/j.plrev.2024.10.010

Ning Xie , Jin Tian , Zedong Li , Nianyuan Shi , Bin Li , Bo Cheng , Ye Li , Moxiao Li , Feng Xu

{"title":"Invited Review for 20th Anniversary Special Issue of PLRev “AI for Mechanomedicine”","authors":"Ning Xie , Jin Tian , Zedong Li , Nianyuan Shi , Bin Li , Bo Cheng , Ye Li , Moxiao Li , Feng Xu","doi":"10.1016/j.plrev.2024.10.010","DOIUrl":"10.1016/j.plrev.2024.10.010","url":null,"abstract":"<div><div>Mechanomedicine is an interdisciplinary field that combines different areas including biomechanics, mechanobiology, and clinical applications like mechanodiagnosis and mechanotherapy. The emergence of artificial intelligence (AI) has revolutionized mechanomedicine, providing advanced tools to analyze the complex interactions between mechanics and biology. This review explores how AI impacts mechanomedicine across four key aspects, <em>i.e.</em>, biomechanics, mechanobiology, mechanodiagnosis, and mechanotherapy. AI improves the accuracy of biomechanical characterizations and models, deepens the understanding of cellular mechanotransduction pathways, and enables early disease detection through mechanodiagnosis. In addition, AI optimizes mechanotherapy that targets biomechanical features and mechanobiological markers by personalizing treatment strategies based on real-time patient data. Even with these advancements, challenges still exist, particularly in data quality and the ethical integration into AI in clinical practice. The integration of AI with mechanomedicine offers transformative potential, enabling more accurate diagnostics and personalized treatments, and discovering novel mechanobiological pathways.</div></div>","PeriodicalId":403,"journal":{"name":"Physics of Life Reviews","volume":"51 ","pages":"Pages 328-342"},"PeriodicalIF":13.7,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142566774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating and forecasting infectious disease dynamics using epidemiological and molecular surveillance data 利用流行病学和分子监测数据调查和预测传染病动态。

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-10-24 DOI: 10.1016/j.plrev.2024.10.011

Gerardo Chowell , Pavel Skums

{"title":"Investigating and forecasting infectious disease dynamics using epidemiological and molecular surveillance data","authors":"Gerardo Chowell , Pavel Skums","doi":"10.1016/j.plrev.2024.10.011","DOIUrl":"10.1016/j.plrev.2024.10.011","url":null,"abstract":"<div><div>The integration of viral genomic data into public health surveillance has revolutionized our ability to track and forecast infectious disease dynamics. This review addresses two critical aspects of infectious disease forecasting and monitoring: the methodological workflow for epidemic forecasting and the transformative role of molecular surveillance. We first present a detailed approach for validating epidemic models, emphasizing an iterative workflow that utilizes ordinary differential equation (ODE)-based models to investigate and forecast disease dynamics. We recommend a more structured approach to model validation, systematically addressing key stages such as model calibration, assessment of structural and practical parameter identifiability, and effective uncertainty propagation in forecasts. Furthermore, we underscore the importance of incorporating multiple data streams by applying both simulated and real epidemiological data from the COVID-19 pandemic to produce more reliable forecasts with quantified uncertainty. Additionally, we emphasize the pivotal role of viral genomic data in tracking transmission dynamics and pathogen evolution. By leveraging advanced computational tools such as Bayesian phylogenetics and phylodynamics, researchers can more accurately estimate transmission clusters and reconstruct outbreak histories, thereby improving data-driven modeling and forecasting and informing targeted public health interventions. Finally, we discuss the transformative potential of integrating molecular epidemiology with mathematical modeling to complement and enhance epidemic forecasting and optimize public health strategies.</div></div>","PeriodicalId":403,"journal":{"name":"Physics of Life Reviews","volume":"51 ","pages":"Pages 294-327"},"PeriodicalIF":13.7,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142563954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The second law of thermodynamics, life and Earth‘s planetary machinery revisited 热力学第二定律、生命与地球行星机械的再认识

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-10-22 DOI: 10.1016/j.plrev.2024.10.009

Axel Kleidon

{"title":"The second law of thermodynamics, life and Earth‘s planetary machinery revisited","authors":"Axel Kleidon","doi":"10.1016/j.plrev.2024.10.009","DOIUrl":"10.1016/j.plrev.2024.10.009","url":null,"abstract":"<div><div>Life is a planetary feature that depends on its environment, but it has also strongly shaped the physical conditions on Earth, having created conditions highly suitable for a productive biosphere. Clearly, the second law of thermodynamics must apply to these dynamics as well, but how? What insights can we gain by placing life and its effects on planetary functioning in the context of the second law? In Kleidon (2010), I described a thermodynamic Earth system perspective by placing the functioning of the Earth system in terms of the second law. The Earth system is represented by a planetary hierarchy of energy transformations that are driven predominantly by incoming solar radiation, these transformations are constrained by the second law, but they are also modified by the feedbacks from various dissipative activities. It was then hypothesised that life evolves its dissipative activity to the limits imposed by this hierarchy and evolves feedbacks aimed at pushing these limits to higher levels of dissipative activity. Here I provide an update of this perspective. I first review applications to climate and global climate change to demonstrate its success in predicting magnitudes of physical processes, particularly regarding temperatures, heat redistribution and hydrological cycling. I then focus on the limits to dissipative activity of the biosphere. It would seem that the limitations by thermodynamics act indirectly by imposing limitations associated with transport and material exchange. I substantiate this interpretation and discuss the broader implications for habitability, the emergence and evolution of life, and the contemporary biosphere.</div></div>","PeriodicalId":403,"journal":{"name":"Physics of Life Reviews","volume":"51 ","pages":"Pages 382-389"},"PeriodicalIF":13.7,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A brigde toward mathematics theory in living systems: the thermostatted kinetic theory method for crowd dynamics 迈向生命系统数学理论的第一步：人群动力学的恒温动力学理论方法：对 Carlo Bianca 的评论文章 "复杂活性物质生命系统的恒温动力学理论模型十年 "的评论。

IF 13.7 1区生物学

Physics of Life Reviews Pub Date : 2024-10-21 DOI: 10.1016/j.plrev.2024.10.007

Christian Dogbe

引用次数: 0