Journal of Physics: Complexity最新文献

{"title":"Polarization Dynamics: A Study of Individuals Shifting Between Political Communities on Social Media","authors":"Federico Albanese, Esteban Feuerstein, P. Balenzuela","doi":"10.1088/2632-072x/ad679d","DOIUrl":"https://doi.org/10.1088/2632-072x/ad679d","url":null,"abstract":"\u0000 Individuals engaging on social media often tend to establish online communities where interactions predominantly occur among like-minded peers. While considerable efforts have been devoted to studying and delineating these communities, there has been limited attention directed towards individuals who diverge from these patterns. In this study, we examine the community structure of re-post networks within the context of a polarized political environment at two different times. We specifically identify individuals who consistently switch between opposing communities and analyze the key features that distinguish them. Our investigation focuses on two crucial aspects of these users: the topological properties of their interactions and the political bias in the content of their posts. Our analysis is based on a dataset comprising 2 million tweets related to US President Donald Trump, coupled with data from over 100,000 individual user accounts spanning the 2020 US presidential election year. Our findings indicate that individuals who switch communities exhibit disparities compared to those who remain within the same communities, both in terms of the topological aspects of their interaction patterns (pagerank, degree, betweenness centrality.) and in the sentiment bias of their content towards Donald Trump.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"34 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141804398","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}

{"title":"Coarse-graining model reveals universal exponential scaling in axonal length distributions","authors":"Máté Józsa, Mária Ercsey-Ravasz, Z. Lázár","doi":"10.1088/2632-072x/ad66a6","DOIUrl":"https://doi.org/10.1088/2632-072x/ad66a6","url":null,"abstract":"\u0000 The Exponential Distance Rule (EDR) is a well-documented phenomenon suggesting that the distribution of axonal lengths in the brain follows an exponential decay pattern. Nevertheless, individual-level axon data supporting this assertion is limited to Drosophila and mice, while inter-region connectome data is also accessible for macaques, marmosets, and humans. Although axon-level data in Drosophila and mice support the generality of the EDR, region-level data can significantly deviate from the exponential curve. In this study, we establish that the axon number-weighted length distribution of region-level connections converges onto a universal curve when rescaled to the mean axonal length, demonstrating similarities across different species. To explain these observations, we present a simple mathematical model that attributes the observed deviations from the EDR in the weighted length distribution of inter-regional connectomes to the inherent coarse-graining effect of translating from neuron-level to region-level connectomics. We demonstrate that the qualitative predictions of the model are robust with respect to various aspects of brain region-geometry, including dimensionality, resolution, and curvature. On the other hand, the performance of the model exhibits a monotonous dependence on the amount of region-geometry related detail incorporated into the model. The findings validate the universality of the EDR rule across various species, paving the way for further in-depth exploration of this remarkably simple principle.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"139 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810805","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}

{"title":"From Malthusian Stagnation to Modern Economic Growth: A swarm-intelligence perspective","authors":"Yong Tao","doi":"10.1088/2632-072x/ad5822","DOIUrl":"https://doi.org/10.1088/2632-072x/ad5822","url":null,"abstract":"\u0000 The correlation between decentralized decision-making and swarm intelligence has emerged as a significant subject within self-organization phenomena. Here, we demonstrate that, if an exponential probability distribution of income emerges in a decentralized economic system, then the total income of all agents can be represented by an aggregate production function, in which the technology factor precisely aligns with the information content inherent in the event of decentralized decision-making by all agents. In particular, for sufficiently large population sizes, the emergence of this technology factor enables the income per capita to increase with the population size, akin to a manifestation of swarm intelligence. More importantly, we find that an exponential probability distribution of income can be generated within a peer-to-peer economy governed by specific game rules, characterizing a decentralized-decision economic system. Building upon this discovery, we propose a swarm-intelligence explanation to elucidate the transition from thousands of years of Malthusian stagnation to modern economic growth.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141346742","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}

{"title":"Alternative cliques of coexisting species in complex ecosystems","authors":"Guim Aguadé-Gorgorió, Sonia Kefi","doi":"10.1088/2632-072x/ad506a","DOIUrl":"https://doi.org/10.1088/2632-072x/ad506a","url":null,"abstract":"\u0000 The possibility that some ecosystems can exist in alternative stable states has profound implications for ecosystem conservation and restoration. Current ecological theory on multistability mostly relies on few-species dynamical models, in which alternative states are intrinsically related to specific non-linear dynamics. Recent theoretical advances, however, have shown that multiple stable ‘cliques’ – small subsets of coexisting species– can be present in species-rich models even under linear interactions. Yet, the mechanisms governing the appearence and characteristics of these cliques remain largely unexplored. In the present work, we investigate cliques in the generalized Lotka-Volterra model with mathematical and computational techniques. Our findings reveal that simple probabilistic and dynamical constraints can explain the appearence, properties and stability of cliques. Our work contributes to the understanding of alternative stable states in complex ecological communities.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"1 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141098903","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}

{"title":"DDoS Attack Detection in Edge-IIoT Network Using Ensemble Learning","authors":"Fariba Laiq, F. Al-Obeidat, Adnan Amin, Fernando Moreira","doi":"10.1088/2632-072x/ad506b","DOIUrl":"https://doi.org/10.1088/2632-072x/ad506b","url":null,"abstract":"\u0000 As the number of IoT devices increases daily due to the rapid growth in technology, every device and network is vulnerable to attacks because it is exposed to the internet. Denial of Service (DoS) is a prevalent type of intrusion on the Internet of Things (IoT) network in which the server becomes down due to flooding requests. Distributed Denial of Service (DDoS) is a special type of DoS attack where the network of malicious computers called botnet consumes the target’s system resources by flooding the requests. Edge computing is closely related to Industrial Internet of Things (IIoT), and industry 4.0. Both of them are relatively emerging technologies so security is a crucial part of them. By incorporating our contributions to the current and innovative dataset Edge-IIoT, the proposed study presents a novel approach to detect DDoS attacks in an IIoT network in the domain of edge computing, whether the traffic is normal or malicious (DDoS traffic). This study explores various Ensemble Learning (EL) techniques to predict normal and malicious DDoS traffic along with the type of DDoS attack. The study applies various preprocessing techniques like Synthetic Minority Over Sampling Technique (SMOTE), label encoding, etc. to enhance the model’s performance and reveals how EL techniques performs better in terms of accuracy than the individual classifiers. Further, the performance of all EL techniques has been investigated in terms of all evaluation measures, including the elapsed time. This important addition not only broadens the focus of study in this area but also offers insightful comparisons of the efficiency and precision of various ensemble approaches as well as individual classifiers. The study achieved a maximum of 99.99% in all evaluation measures.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"8 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141099864","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}

{"title":"Interconnectivity disrupted by fading globalization: A network approach to recent international trade developments","authors":"T. C. Silva, P. V. B. Wilhelm, D. R. Amancio","doi":"10.1088/2632-072x/ad4dfc","DOIUrl":"https://doi.org/10.1088/2632-072x/ad4dfc","url":null,"abstract":"\u0000 The post-World War II decades experienced rapid growth in international trade, but recently a trend of weakening globalization has been consolidating. We construct an International Trade Network (ITN) using bilateral trade (2010 to 2022) to assess how interconnectedness has evolved in the face of recent developments. Our analysis reveals that while network connectivity initially improved, there was a shift towards a negative trend from 2018, coinciding with an increasingly unfavorable environment for international trade. We also document significant changes in the roles of countries within the ITN. While the USA remains the primary hub and China solidifies its second position, key countries like Germany, France, Great Britain, and Japan have notably lost relevance, whereas nations like India and the Republic of Korea are gaining prominence. Finally, employing an econometric model, we show that countries with large economies, significant manufacturing sector, lower inward foreign direct investment stock, and economic and geopolitical stability tend to occupy more central positions in the ITN.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"26 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119240","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}

{"title":"Growth and addition in a herding model with fractional orders of derivatives","authors":"Y. J. Yap, Mohamad Rafi Segi Rahmat, Pak Ming Hui","doi":"10.1088/2632-072x/ad4d4a","DOIUrl":"https://doi.org/10.1088/2632-072x/ad4d4a","url":null,"abstract":"\u0000 This work involves an investigation of the mechanics of the herding behaviour using a non-linear timescale, with the aim to generalize the herding model which helps to explain frequently occurring complex behaviour in the real world, such as the financial markets. A herding model with fractional order of derivatives was developed. This model involves the use of derivatives of order α where 0<α ≤1. We have found the generalized result that the number of groups of agents with size k increases linearly with time as nk={p(2p-1)(2-α)/[p(1-α)+1]}Γ(α+(2-α)/(1-p){Γ(k)/[Γ(k-1+α+(2-α)/(1-p))}t for α ∈ (0,1], where p is a growth parameter. The result reduces to that in a previous herding model with derivative order of 1 for α=1. The results corresponding to various values of α and p are presented. The group size distribution at long time is found to decay as a generalized power law, with an exponent depending on both α and p, thereby demonstrating that the scale invariance property of a complex system holds regardless of the order of the derivatives. The physical interpretation of fractional differentiation and fractional integration is also explored based on the results of this work.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"72 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140964362","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}

{"title":"Optimization of investment portfolios of Chinese commodity futures market based on complex networks","authors":"Ke Huang, LiFei Ke, Zuo-Ming Zhang, Qiumei Li, Jifeng Sun","doi":"10.1088/2632-072x/ad49fe","DOIUrl":"https://doi.org/10.1088/2632-072x/ad49fe","url":null,"abstract":"\u0000 China commodity futures market network is constructed. Commodity is the node of the network, and the network link is defined by the price correlation matrix. We analyze the relationship between the centrality of each commodity in the commodity futures market network and the optimal weight of the commodity portfolio, empirically examine the market system factors and commodity personalized factors that affect the centrality of commodity, and evaluate the effect of network structure on the optimization of commodity portfolio selection under the mean-variance framework. It is found that the commodities with high network centrality are often related to industrial products and have high volatility. Commodities with higher centrality have lower portfolio weights. We put forward a kind of commodity futures investment strategy based on network, according to the network centricity grouping the commodities, the network centricity lower edge of the commodity structure of the portfolio, cumulative yield is better than that of centricity higher core product portfolio, the whole market portfolio yield, but due to large maximum retracement, lead to the stability and ability to resist risk compared with the other two groups of goods combination. The main contribution of this paper is to optimize portfolio selection by establishing the relationship between portfolio weight and commodity centrality by using commodity futures market network as a tool.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140992556","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}

{"title":"Next-Day Largest Earthquake Magnitude Forecasting with the Aid of Moon Tidal Force and Sunspot Data","authors":"Matheus Henrique Junqueira Saldanha, Yoshito Hirata","doi":"10.1088/2632-072x/ad4a18","DOIUrl":"https://doi.org/10.1088/2632-072x/ad4a18","url":null,"abstract":"\u0000 Seismicity is a complex phenomenon with a multitude of components involved. In order to perform forecasting, which has yet to be done sufficiently well, it is paramount to be in possession of information of all these components, and use this information effectively in a prediction model. In the literature, the influence of the Sun and the Moon in seismic activity on Earth has been discussed numerous times. In this paper we contribute to such discussion, giving continuity to a previous work. Most importantly, we instrument four earthquake catalogs from different regions, calculating the Moon tidal force at the region and time of each earthquake, which allows us to analyze the relation between the tidal forces and the earthquake magnitudes. At first, we find that the dynamical system governing Moon motion is unidirectionally coupled with seismic activity, indicating that the position of the Moon drives, to some extent, the earthquake generating process. Furthermore, we present an analysis that demonstrates a clear positive correlation between tidal force and earthquake magnitude. Finally, it is shown that the use of Moon tidal force data and sunspot number data can be used to improve next-day maximum magnitude forecasting, with the highest accuracy being achieved when using both kinds of data. We hope that our results encourage researchers to include data from Moon tidal forces and Sun activity in their earthquake forecasting models.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140992281","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}

{"title":"Sensitivity to network perturbations in the Randomized Shortest Paths framework: theory and applications in ecological connectivity","authors":"Ilkka Kivimäki, B. van Moorter, M. Saerens","doi":"10.1088/2632-072x/ad4841","DOIUrl":"https://doi.org/10.1088/2632-072x/ad4841","url":null,"abstract":"\u0000 The Randomized Shortest Paths (RSP) framework, developed for network analysis, extends traditional proximity and distance measures between two nodes, such as shortest path distance and commute cost distance (related to resistance distance). Consequently, the RSP framework has gained popularity in studies on landscape connectivity within ecology and conservation, where the behavior of animals is neither random nor optimal. In this work, we study how local perturbations in a network affect proximity and distance measures derived from the RSP framework. For this sensitivity analysis, we develop computable expressions for derivatives with respect to weights on the edges or nodes of the network. Interestingly, the sensitivity of expected cost to edge or node features provides a new signed network centrality measure, the negative covariance between edge/node visits and path cost, that can be used for pinpointing strong and weak parts of a network. It is also shown that this quantity can be interpreted as minus the endured expected detour (in terms of cost) when constraining the walk to pass through the node or the edge. Our demonstration of this framework focuses on a migration corridor for wild reindeer (Rangifer rangifer) in Southern Norway. By examining the sensitivity of the expected cost of movement between winter and calving ranges to perturbations in local areas, we have identified priority areas crucial for the conservation of this migration corridor. This innovative approach not only holds great promise for conservation and restoration of migration corridors, but also more generally for connectivity corridors between important areas for biodiversity (e.g. protected areas) and climate adaptation. Furthermore, the derivations and computational methods introduced in this work present fundamental features of the RSP framework. These contributions are expected to be of interest to practitioners applying the framework across various disciplines, ranging from ecology, transport and communication networks to machine learning.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141002744","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}