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R. Mantegna15/09/2025, 09:30
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G. Caldarelli15/09/2025, 10:00
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M. Osella15/09/2025, 10:30
Many complex systems exhibit a modular structure: genomes are composed of genes, books consist of words, and technological systems like LEGO sets can be broken down into elementary building blocks. Representing these as component systems—collections of discrete elements—reveals a range of quantitative regularities, often shared across domains. Among these, Zipf’s law is perhaps the most...
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S. Meloni15/09/2025, 10:50
The emergence of biodiversity in ecological communities remains a major open question in theoretical ecology, leading to a fundamental inquiry: what mechanisms support the stability and coexistence of species within these ecosystems? Traditional ecological models have largely been based on the assumption that species primarily engage in pairwise interactions. However, interactions in...
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E. Omodei15/09/2025, 11:40
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D. Remondini15/09/2025, 12:10
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D. Zanchetta15/09/2025, 12:40
Pathogen mutations are widely understood to play a significant role in the long-term outcome of epidemics [1,2]. At the same time, the heterogeneous nature of social and mobility networks [3,4] can affect the evolution of pathogens by boosting or restraining availability of diverse hosts over different time scales. We report the results of our study on the interaction between these two...
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S. Suweis15/09/2025, 13:00
Diatoms (Bacillariophyta) are key contributors to marine ecosystems and global biogeochemical cycles. Using data from the TARA Oceans project, we analyzed the environmental responses of a diatom subspecies across diverse oceanic regions. Community detection on metatranscriptomic datasets identified three distinct clusters corresponding to regions with varying temperature profiles. These...
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F. Castellana15/09/2025, 14:30
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A. Fania15/09/2025, 15:00
West Nile Virus (WNV) is a mosquito-borne zoonotic disease increasingly recognized as a public health concern across Europe, particularly due to its complex transmission dynamics influenced by climatic, environmental, and anthropogenic factors. In this study, we implemented a predictive machine learning framework integrating Random Forest classifiers and explainable artificial intelligence...
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M. Caruso15/09/2025, 15:50
Antimicrobial resistance (AMR) is one of the most urgent and cross-cutting challenges to public health, society and the environment, due to the increasing ability of pathogens to develop resistance to drugs. This world-spread resistance is making infections harder to treat, raising the risk of higher and higher mortality.
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The One Health framework, which acknowledges the interconnectedness of... -
J. Aguilar15/09/2025, 16:10
Species interactions—ranging from direct predator-prey relationships to indirect effects shaped by
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environmental factors—are fundamental to maintaining ecosystem balance and biodiversity.
Although various empirical measures of these interactions have been proposed, their
interpretability, informativeness, and limitations in ecosystem analysis remain challenging. In this
study, we focus on... -
A. Gabrielli16/09/2025, 09:30
Heterogeneous and complex networks represent the intertwined
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interactions between real-world elements or agents. Determining the
multi-scale mesoscopic organization of clusters and intertwined
structures is still a fundamental and open problem of complex network
theory. By taking advantage of the recent Laplacian Renormalization
Group [1-4] approach , we scrutinize information diffusion... -
M. Caselle16/09/2025, 10:00
Topic models are a set of algorithms originally developed to extract latent variables from texts corpora. The most popular of these algorithms is the so-called Latent Dirichlet Allocation (LDA) which has been successfully applied in these last years not only in texts analysis but also in bioinformatics. In fact algorithms which try to identify the ``topic'' of a given document from the word...
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M. Seppi16/09/2025, 10:30
Shotgun metagenomics enables the quantitative profiling of microbial communities in biological samples, providing a rich, high-dimensional description of microbiota composition. These microbial profiles are increasingly used to investigate associations with host health. However, the high dimensionality of such data—thousands of microbial or functional features per sample—and the heterogeneity...
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S. Grassia16/09/2025, 10:50
The human brain is a complex system of 100 billion neurons, each one connected on average to 10,000 other neurons to exchange
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electrochemical information. It is possible to coarse-grain this system by considering the average activity of large neuronal aggregates
into Regions of Interest (ROIs), acting as fundamental areas in functional Magnetic Resonance Imaging (fMRI), and their... -
C. Testa16/09/2025, 11:40
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C. Malvaso16/09/2025, 12:10
Magnetoencephalography (MEG) is a neuroimaging technique that captures the magnetic fields generated by neuronal activity, offering millisecond-scale temporal resolution and fine-grained spatial information, making it ideal for exploring the complex dynamics of the human brain. In cognitive neuroscience, event-related experimental designs are commonly used to investigate how the brain...
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A. Nitti16/09/2025, 12:30
The capacity of groups to accomplish complicated tasks that exceed individual skills is acknowledged in natural and human environments [1]. Animals that live in groups demonstrate complex collective behaviours that allows to fulfil fundamental biologic functionalities, such as foraging or defence from predators. In this connection, the collective intelligence of animal swarms can by mimicked...
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R. Burioni16/09/2025, 14:00
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M. De Domenico16/09/2025, 14:30
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A. Lacalamita16/09/2025, 15:00
The information-theoretic framework provides valuable insights into the dynamics of correlated groups within networks. Although established methodologies exist for measuring new information, storage, and transmission, accurately quantifying changes in information remains challenging. Information change in networks pertains to redundancy and synergy among systems that collectively contain...
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N. Pedreschi16/09/2025, 15:20
Gentrification, “the rapid increase in cost and standard of living in a disadvantaged neighbourhood”, causes the relocation of lower-income inhabitants in favor of wealthier citizens[1]. Relocation is caused by socio-economic inequalities and may be influenced by the presence of amenities and infrastructures. In this work, we focus on relocation trajectories and develop an agent-based...
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E. Calò16/09/2025, 16:20
Ecosystems face intensifying threats from climate change, overexploitation, and other human pressures, emphasizing the urgent need to identify keystone species and vulnerable ones. While established network-based measures often rely on a single metric to quantify a species’ relevance, they overlook how organisms can be both carbon providers and consumers, thus playing a dual role in food webs....
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T. Bertola16/09/2025, 16:40
We present an analysis of the complex network structure of some microblogging platforms, comparing their internal organizations and, for the case of BlueSky, its growth during a period of massive migration from X/Twitter. Topological differences are the result of platforms’ functionalities and of individuals’ behaviors. At the same time, the sudden increase of users in BlueSky acts as a large...
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A. Veronese16/09/2025, 17:00
Understanding the brain’s response to transcranial magnetic stimulation (TMS) is crucial for advanc-
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ing both basic and clinical neuroscience. This study applies neural mass modelling to analyze TMS-
evoked potentials (TEPs) through electroencephalography (EEG). Building on Momi et al. (2023)
[1], who used source-localized TMS-EEG analyses to disentangle local from network dynamics, we
aim... -
R. M. Di Mauro16/09/2025, 17:20
Diagnosing mental disorders remains one of the most intricate challenges in
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neuroscience and clinical practice. Unlike many physical illnesses, mental health
conditions often lack well-defined biological markers or clear-cut diagnostic thresh-
olds. Instead, diagnoses are typically informed by subjective assessments, be-
havioral evaluations, and social indicators, making the process... -
A. Rapisarda17/09/2025, 09:30
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A. Pluchino17/09/2025, 10:00
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T. Scagliarini17/09/2025, 10:30
In this work we address the problem of assessing the network robustness of transportation networks due to external stressors, such as natural events. Here we focus on US power grid, but the same framework can be applied in a system where there is a physical quantity flowing through the nodes, as current in the power lines. As a stressor, we consider daily wind gust data at 10 meters above...
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V. D'Andrea17/09/2025, 11:20
Brain network reconstruction from neuroimaging data is subject to sources of systematic bias. One can arise from the arbitrariness introduced by thresholding procedures used in typical structural and functional network reconstruction techniques. The produced connectivity matrices exhibit variable density, which has been shown to impact the evaluation of many graph metrics [1]. Additionally,...
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N. Kheirkhahan17/09/2025, 11:40
This research applies complex network theory to investigate the resilience of provincial road networks, focusing on Foggia Province in southern Italy. Foggia was selected due to its critical role in regional logistics and its vulnerability to disruptions caused by environmental hazards such as earthquakes. Road infrastructure resilience is essential for sustaining economic and social systems,...
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A. Lo Sasso17/09/2025, 12:00
In recent years, network science predictive methods leveraging artificial intelligence have gained particular prominence in big data analysis. Among the various implementations of these tools, they have proven particularly useful for monitoring and predicting socioeconomic and health-related phenomena, uncovering intriguing and non-intuitive patterns [1]. In this way, a consensus began to...
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L. Taffarello17/09/2025, 12:20
The collective dynamics of complex systems such as neural circuits are shaped by how their units interact. Theoretical models of recurrent neural networks (RNNs) with random interactions have been investigated by dynamical mean field theory (DMFT) to derive fundamental properties of their dynamics such as the onset of chaos. However, the fully-interacting systems considered in previous studies...
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