<?xml version="1.0" encoding="utf-8"?>
    <rss version="2.0">
      <channel xmlns:content="http://purl.org/rss/1.0/modules/content/">
        <title>Frontiers in Complex Systems | Multi- and Cross-Disciplinary Complexity section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/complex-systems/sections/multi--and-cross-disciplinary-complexity</link>
        <description>RSS Feed for Multi- and Cross-Disciplinary Complexity section in the Frontiers in Complex Systems journal | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-08-17T20:34:25.586+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1812652</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1812652</link>
        <title><![CDATA[Towards community-scale resilience via repurposable computing continuum infrastructures]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Nikil Dutt</author><author>Julio A. de Oliveira Filho</author><author>Francesca Palumbo</author><author>Francesco Regazzoni</author><author>Nalini Venkatasubramanian</author>
        <description><![CDATA[Smart cities rely on Cyber Physical Human Systems (CPHS) for efficiently delivering critical services (water, electricity, weather, traffic, etc.) to the community. These community-scale CHPS typically rely on an edge-fog-cloud computing continuum spanning multiple abstraction levels, and are typically purpose-built to deliver these services. This article makes the case that these siloed CPHS can be repurposed to deliver additional services in the face of disasters and unexpected events, raising the overall resilience of these community-scale infrastructures. We use two motivating CPHS case studies–information exchange for healthcare resilience (NSF project CAREDEX) and community-scale urban mobility through end-to-end orchestration (EU project MYRTUS) – as exemplars to tease out the opportunities and challenges faced in repurposing these CHPS in extreme events such as disasters. We highlight some of the key technologies required to facilitate repurposing, summarize their current status, and discuss ongoing efforts and future challenges for achieving community-scale CPHS resilience.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1919371</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1919371</link>
        <title><![CDATA[Correction: Decentralized coordination of autonomous agents in the Compute Continuum using consensus]]></title>
        <pubdate>2026-08-10T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Xavier Casas-Moreno</author><author>Komal Thareja</author><author>Pablo de Juan Vela</author><author>Rajiv Mayani</author><author>Josep Fanals-i-Batllori</author><author>Anirban Mandal</author><author>Ewa Deelman</author><author>Rosa M. Badia</author><author>Francesc Lordan</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1856624</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1856624</link>
        <title><![CDATA[Winter workshop on complex systems: more than a decade of self-organised community building in complexity research]]></title>
        <pubdate>2026-07-21T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Natalia Briñas-Pascual</author><author>Pablo Rosillo-Rodes</author>
        <description><![CDATA[Every winter for the past 11 years, young researchers from across disciplines and around the world have gathered to explore complexity science and to collaborate intensively on self-organised projects. What began in 2015 as a gathering of colleagues who had first met at a previous workshop at the Santa Fe Institute has since consolidated into a self-organised, resilient workshop for early-career scientists in the complexity community. The Winter Workshop on Complex Systems is characterised by its format: participants form interdisciplinary teams and spend a week developing projects of their own design. By maintaining an economical model that serves as a low-cost alternative to expensive traditional conferences, the workshop prioritises inclusion, ensuring that financial constraints do not prevent talented early-career researchers from participating. This approach not only promotes collaboration and the exchange of ideas but also helps to build a strong, supportive community of young researchers. Many of these collaborations have endured well beyond the workshop, leading to successful publications and long-term partnerships and friendships.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1838587</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1838587</link>
        <title><![CDATA[Time as event: bridging explicit and emergent temporal representations in computer-based social simulations ]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Juan A. Barceló</author><author>Joaquim Fort</author><author>Albert García Piquer</author><author>Olga Palacios</author><author>Ramón Buxó</author><author>Jaume Noguera</author>
        <description><![CDATA[Time is a fundamental yet conceptually undertheorized dimension in computational simulations of historical processes. This paper addresses the problem of temporal representation in these social models by distinguishing two types of temporal information—explicit and emergent—and suggests a formal definition of the temporal event as the primary unit of analysis in a unifying framework for both. In explicit-time models—such as reaction-diffusion systems calibrated against georeferenced calendar dates—time enters as an independent variable governed by differential equations, enabling rigorous testing of temporal sequences that in some circumstances may be consistent with causal hypotheses about the rate, direction, and intensity of social change. In emergent-time models—typically agent-based simulations governed by iterative cycles—temporality arises endogenously from local interactions, adaptive feedback, and cumulative system transformations, revealing how processes may have unfolded mechanistically without imposing predetermined chronological constraints. Our main point is that this difference has profound implications for determining what counts as an assumption and what counts as a result. It also determines the ability to compare computational models of social dynamics with historical empirical evidence. All along the paper, we use the origins of early farming communities in the Prehistoric Mediterranean as a case study for a comparative analysis to reveal critical differences in the way time and space are used as parameters or as emergent dynamics, and their methodological and epistemological consequences.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800335</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800335</link>
        <title><![CDATA[Kiso: a foundation for complex, agentic, and reproducible experiments]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Rajiv Mayani</author><author>Karan Vahi</author><author>Mats Rynge</author><author>Komal Thareja</author><author>Xavier Casas-Moreno</author><author>Hongwei Jin</author><author>Anirban Mandal</author><author>Francesc Lordan</author><author>Krishnan Raghavan</author><author>Rosa M. Badia</author><author>Ewa Deelman</author>
        <description><![CDATA[Experimentation on distributed, heterogeneous computing environments—from edge devices to large-scale cloud platforms—demands orchestration technologies that are both flexible and extensible. Kiso is an open-source framework designed to provision resources and manage complex scientific workflows across the edge-to-cloud continuum. Its architecture unifies infrastructure provisioning, experiment configuration, and reproducible execution, enabling researchers to compose and monitor experiments that span geographically dispersed sites and variable network conditions. Although Kiso was conceived for workflow management—coordinating data-intensive tasks and ensuring reproducibility across dynamic infrastructures—its modular design makes it equally promising for providing reproducible environments for deploying and studying emerging agentic frameworks, where autonomous AI agents require consistent resource provisioning, cross-site communication, and result collection. We describe Kiso’s core capabilities for resource orchestration, experiment lifecycle management, and integration with containerized services, and we outline how these capabilities can support distributed multi-agent systems. In particular, we discuss how its declarative provisioning, extensible task abstractions, and built-in monitoring and output collection provide a natural foundation for experiments in which reasoning agents plan, negotiate, and adapt in real time. This study situates Kiso at the intersection of scientific workflow management and complex, agent-based computing, highlighting its potential to accelerate research on adaptive, self-organizing cyber-physical systems—an emerging frontier in complex systems science.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1801157</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1801157</link>
        <title><![CDATA[SWEET: serving workload-balanced end-to-end efficient and tailored edge inference via quantization and partitioning]]></title>
        <pubdate>2026-06-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xiangchen Li</author><author>Saeid Ghafouri</author><author>Hans Vandierendonck</author><author>Deepu John</author><author>Dimitrios S. Nikolopoulos</author>
        <description><![CDATA[We present SWEET, an end-to-end, accuracy-aware inference serving system that tailors execution to heterogeneous edge devices under diverse hardware constraints. Rather than deploying a single fixed pre-trained model for all future queries, serving workload-balanced end-to-end efficient and tailored edge inference (SWEET) plans a request-specific inference pattern by co-optimizing the model configuration and the device–server workload split according to the device’s compute capacity, accuracy requirements, and time constraints. At its core, SWEET integrates joint model quantization and inference partitioning: upon receiving an inference request, the server dynamically provides a quantized model and adaptively shares computation with the edge device, while the system determines the partition point and quantization settings based on the available device computation, channel capacity, and target accuracy. To enable principled decision making, we introduce a unified optimization framework that jointly selects layer-wise quantization bitwidths and partition points to minimize overall time and cost while explicitly accounting for task-dependent accuracy requirements through an accuracy degradation metric in the optimization model. To our knowledge, SWEET is the first inference serving system to optimize layer-wise quantization bitwidth using a theoretical measurement of accuracy degradation. Simulation results demonstrate substantial reductions in end-to-end time and power consumption, achieving a greater than 80% reduction in communication payload while keeping accuracy degradation below 1%.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1808634</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1808634</link>
        <title><![CDATA[Complex systems vs. complex adaptive systems: why the difference matters]]></title>
        <pubdate>2026-05-15T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Shade T. Shutters</author><author>Kelle Dhein</author>
        <description><![CDATA[Terms such as “complexity,” “complex systems,” and “complex adaptive systems” have moved rapidly from specialist research into the vocabularies of policy, sustainability practice, business, and health. Governments now speak of complex adaptive policy systems, funders call for complexity science, and consultants market “complexity thinking” as a way to make sense of polycrises and interlocking risks. Yet underlying this welcome diffusion is a persistent ambiguity. In the research literature, complex systems (CS) and complex adaptive systems (CAS) are related but distinct concepts: all CAS are complex systems, but not all complex systems are adaptive. Outside of academia, however, these terms are often used interchangeably. In this Perspective we clarify the difference between CS and CAS for audiences who are adopting complexity ideas in their own work. We define complex systems as many-component systems with nonlinear interactions and emergent behavior, and complex adaptive systems as the subset in which agents or institutions adapt or learn from experience. We then show how this conceptual distinction maps onto typical examples (weather vs. cities) and onto modeling approaches, such as system dynamics versus agent-based modeling. A concise table summarizes the main contrasts. Finally, we argue that being explicit about CS versus CAS can improve model selection, literature synthesis, and the design of interventions in policy, sustainability, and governance. Rather than proposing new theory, our goal is practical: to help researchers and practitioners understand what they are actually adopting when they invoke “complexity thinking,” and what its limits are in different settings.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1749741</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1749741</link>
        <title><![CDATA[Deliberative project design for understanding and working within complexity in agricultural systems]]></title>
        <pubdate>2026-04-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hanabeth Luke</author><author>Catherine Allan</author><author>Penny Cooke</author><author>Sarina Kilham</author><author>Alison Ollerenshaw</author><author>Nathan Craig</author><author>Naomi Scholz</author><author>Diana Fear</author><author>Simon Kruger</author><author>Joshua Telfer</author><author>Mathew Alexanderson</author><author>David Davenport</author><author>Yvonne Haigh</author><author>Shae Brown</author><author>Kelly Angel</author>
        <description><![CDATA[New innovations have the potential to improve agricultural resilience, profitability, sustainability and regenerative potential. However, new technologies and approaches emerge in a complex sociocultural context, with farmer decisions based on a range of interacting social, economic and environmental factors. Traditional approaches to research and development within agri-food systems often assume continuity and/or linearity in change processes, which is rarely the case in practice. There are calls for approaches and methods to research and development that can apply deliberative and participatory processes to enable social learning and innovation while embracing inherent complexities. Through a reflection process relating to two multi-stakeholder, collaborative, soils-focused agri-food research projects in Australia, this paper explores how agricultural research projects can navigate and work with complexity. The first project is a national Rural Landholder Social Benchmarking Study, aimed at collecting and drawing together complex data on farmer decision-making around adoption of innovations; and the second is a Knowledge-Sharing Project aimed at improving farmer engagement in new technologies and innovation across Australian farming regions. Our reflective analysis, based on exploring how complexity principles are enacted in these two projects, illustrates how projects can be developed along self-organising principles, developing team capacity to continually learn together and respond to the unexpected. Considering the complex elements of these projects, and how they have operated, opens a pathway for deliberative design that embraces complexity, which may assist the agricultural sector in the development of future research and project management.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800101</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800101</link>
        <title><![CDATA[Decentralized coordination of autonomous agents in the Compute Continuum using consensus]]></title>
        <pubdate>2026-04-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xavier Casas-Moreno</author><author>Komal Thareja</author><author>Pablo de Juan Vela</author><author>Rajiv Mayani</author><author>Josep Fanals-i-Batllori</author><author>Anirban Mandal</author><author>Ewa Deelman</author><author>Rosa M. Badia</author><author>Francesc Lordan</author>
        <description><![CDATA[The Compute Continuum—spanning IoT, Edge, Cloud, and HPC resources—is reshaping how hyper-distributed applications are designed and orchestrated. Traditional service orchestrators and workload management systems rely on centralized runtimes; however, the emerging paradigm requires decentralized coordination, where autonomous agents cooperate to achieve common goals and dynamically distribute workloads. Consensus algorithms play a crucial role in multi-agent systems (MAS), as they enable agents to reach agreement on how to coordinate and execute functionalities in a cooperative manner. While consensus has previously been applied to distributed job selection, here we extend its use to swarm environments. In this setting, agents autonomously decide which service functionalities (i.e., roles) to execute based on their capabilities and the real-time quality of service (QoS). Functionalities can be elastically activated or terminated as application needs evolve. To support this model, we leverage the COLMENA framework, a programming environment for defining and managing such dynamic services. We apply a greedy consensus-based approach to modern power systems, which are increasingly decentralized due to the large-scale integration of renewable energy sources. Centralized power plants are giving way to distributed, intermittent resources that require decentralized control paradigms. To demonstrate this, we simulate the Northeastern Power Coordinating Council’s (NPCC) 140-bus grid using the ANDES simulator in conjunction with the COLMENA middleware. We deploy this use case across six different sites in the FABRIC testbed, using up to 60 different nodes. Our results show that, under contingency scenarios such as load and generator disconnections, agents self-organize, elect local leaders, and execute optimization algorithms to stabilize grid frequency. Detection and organization times remain below 10s across all experiments, even as the number of agents per area scales from 3 to 10. Stability is restored within approximately 27s and 40s for the respective cases. Resource overhead is minimal, with CPU and memory usage remaining below 7.5% and 2%, respectively. Experiment automation and reproducibility are ensured through Kiso. These findings indicate that role-based programming models complement traditional workflows and that consensus-driven coordination can effectively decentralize decision-making in swarm environments. This approach represents a step toward enabling resilient, decentralized power systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1724679</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1724679</link>
        <title><![CDATA[Deployment of transatlantic computational testbeds via the infrastructure manager]]></title>
        <pubdate>2026-02-17T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Germán Moltó</author><author>Miguel Caballer</author><author>Estíbaliz Parcero</author><author>Vicente Rodríguez</author>
        <description><![CDATA[Transatlantic scientific collaborations require computational testbeds that can be provisioned on demand and reconfigured rapidly while spanning institutions in different regulatory and operational domains. During the DISCOVER-US exchange program, we integrated the Infrastructure Manager (IM), a TOSCA-based orchestrator for the computing continuum, with the Chameleon cloud infrastructure. The workflow combined federated identity management, delegated project administration, and an IM plugin that targets Chameleon’s OpenStack endpoints through application credentials. We validated the approach by deploying single virtual machines, a production-ready Galaxy environment, distributed OSCAR-based serverless clusters that offload an AI-based fish detection pipeline, a workflow for flood impact modeling, and a hybrid SLURM cluster. Transatlantic computational testbeds included dynamically provisioned computational resources from EGI Federated Cloud and Chameleon. The study also documents operational constraints encountered with lease automation, bare-metal introspection, and the exposure of Kubernetes services across wide-area networks. The resulting blueprint demonstrates a reproducible path to deploy secure, elastic, and scientifically useful transatlantic computational testbeds.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1794474</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1794474</link>
        <title><![CDATA[Editorial: Game theory and evolutionary dynamics: unraveling complex systems]]></title>
        <pubdate>2026-02-13T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Chengyi Tu</author><author>Hongzhong Deng</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1666594</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1666594</link>
        <title><![CDATA[Modified training drills in improving the dribbling agility of futsal athletes]]></title>
        <pubdate>2025-09-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ma. Jan Donna G. Marcojos</author><author>Mylene P. Labastida</author><author>Jade Rona S. Soriano</author><author>Jennifer Degracia</author><author>Marinila T. Urboda</author><author>Louie P. Gula</author>
        <description><![CDATA[IntroductionFutsal has become increasingly popular over the years; hence, studies focusing on the integration of drills to improve the performance of athletes are relevant. This study investigates the impact of modified training drills in improving the dribbling agility of futsal athletes.MethodsA total of 13 athletes participated in the research. Their dribbling agility was classified based on the Test of Agility in Dribbling before and after the training duration. The training program, which follows the FITT principle, consisted of three sessions per week (following a TThS schedule) for 2 weeks, adapting their normal training days. Descriptive statistics (frequency counts, percentages, mean, and standard deviation) summarized the demographic characteristics and agility levels. A Wilcoxon signed-rank test was utilized to determine the significant difference between the pre-test and post-test results, as the participants were not randomly sampled. A Spearman's rank correlation test was used to test the association of demographic profiles with the levels of dribbling agility.ResultsDemographic analysis revealed that most participants were 14 years old, with a majority having a height between 140-149 cm and a weight of 40-49 kg. Descriptive statistics showed a significant improvement in agility performance, as the average agility time decreased from 24.51 s in the pre-test to 20.50 s in the post-test. After training, the participants’ dribbling agility levels shifted from predominantly ‘poor’ classifications to ‘average’, ‘good’, and ‘excellent’. Statistical analysis confirmed that this difference was statistically significant (p < 0.05). Further analysis revealed that weight has a significant association with agility performance, while age and height did not.DiscussionThe results support the hypothesis that modified training drills positively impact agility. The findings suggest that weight can be considered an important factor in evaluating the impact of agility training.ConclusionThe modified agility training program effectively enhanced dribbling agility among futsal athletes. The study suggests that future researchers may extend the training duration and control external factors. It is also recommended that weight be considered in planning and evaluating agility training programs.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1609467</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1609467</link>
        <title><![CDATA[Fragility in human progress. A perspective on governance, technology and societal resilience]]></title>
        <pubdate>2025-09-10T00:00:00Z</pubdate>
        <category>Opinion</category>
        <author>G.-Fivos Sargentis</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1617092</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1617092</link>
        <title><![CDATA[Unsettling the settled: simple musings on the complex climatic system]]></title>
        <pubdate>2025-08-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Demetris Koutsoyiannis</author><author>George Tsakalias</author>
        <description><![CDATA[Our revisit of fundamental issues of climate challenges the notion and term of the “greenhouse effect”, and attempts a scientific reevaluation using minimal assumptions, such as Newton’s laws, maximum entropy and gas spectroscopy. It replaces terms like “greenhouse gas” with “radiatively active gas” (RAG) and “greenhouse effect” with “atmospheric radiative effect” (ARE). While ARE exists in several planets’ atmospheres, on Earth it is primarily driven by water vapor and clouds, with CO2 playing a minor role (especially anthropogenic CO2 which represents 4% of total emissions). Equilibrium thermodynamics, via entropy maximization or molecular collision simulation, leads to an isothermal atmosphere at about 250 K (the average temperature of the troposphere and stratosphere) irrespective of RAG presence or not. It is the troposphere’s 6.5 K/km temperature gradient (lapse rate), partly shaped by moist adiabatic processes, that drives the atmosphere away from this equilibrium and warms the surface to about 288 K on average, with ARE (mainly water vapor and clouds) contributing to the warming, but only when this gradient exists. The temperature gradient varies spatially and temporally and, since 1950, has weakened in the tropics and grown in the polar areas, resulting in a decrease of the surface equator-to-pole gradient, as expected in global warming conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1612998</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1612998</link>
        <title><![CDATA[Traces of tricritical dynamics beyond SSB in finite-size systems undergoing second-order phase transition: the case of the 3D Ising model]]></title>
        <pubdate>2025-08-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yiannis Contoyiannis</author><author>Stelios M. Potirakis</author><author>Stavros G. Stavrinides</author><author>Michael P. Hanias</author><author>Pericles Papadopoulos</author><author>Niki-Lina Matiadou</author>
        <description><![CDATA[In finite-size thermal systems that exhibit second-order phase transition, the fluctuations of the order parameter ϕn obey type I intermittent dynamics at their pseudocritical temperature Tpc. Moreover, as recently demonstrated, spontaneous symmetry breaking (SSB) is gradually completed as temperature is reduced until reaching an SSB completion temperature, TSSB. Within this temperature zone, ϕn obey the dynamics of critical intermittency. This behavior has also been observed in pre-seismic fracture-induced electromagnetic emissions (FEME) of the MHz band—a real-world finite-size system undergoing a second-order phase transition. Interestingly, MHz FEME has recently been found to consistently present indications of tricritical dynamics after the SSB. We examine here whether this could also be true for a finite-size thermal system. We conduct a numerical experiment for the 3D Ising model at different temperatures by gradually reducing temperature beyond SSB and analyze order parameter fluctuations using the method of critical fluctuations (MCF) and a recently introduced wavelet-based method for detecting scaling behavior in noisy experimental data. Our results reveal that power-laws still exist within a very narrow zone of temperatures right after SSB completion for the 3D Ising model. These power-laws are shown to be compatible with another form of intermittency that determines the dynamics of the order parameter fluctuations close to the Griffiths tricritical point. As a possible interpretation of this finding, we suggest that our results imply that 3D Ising presents, just below TSSB, an imprint approaching the Griffiths tricritical point from the second-order phase transition line.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1563687</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1563687</link>
        <title><![CDATA[On cyclostationary linear inverse models: a mathematical insight and implication]]></title>
        <pubdate>2025-04-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Justin Lien</author><author>Yan-Ning Kuo</author><author>Hiroyasu Ando</author><author>Shoichiro Kido</author>
        <description><![CDATA[Cyclostationary linear inverse models (CS-LIMs) are advanced data-driven techniques for extracting first-order time-dependent dynamics and random forcing information from cyclostationary observational data. This study focuses on the mathematical perspective of CS-LIMs and presents two variants, namely, e-CS-LIM and l-CS-LIM. The e-CS-LIM, improved from the original CS-LIM, constructs the first-order dynamics through the interval-wise application of the stationary LIM (ST-LIM), capturing the integrated effect of each interval where similar cyclostationary dependencies are present. This approach provides robustness against noise but is affected by the Nyquist issue, similar to the ST-LIM. The l-CS-LIM, on the other hand, estimates the time-dependent Jacobian of the underlying system. Although more sensitive to noise, this method is free from the Nyquist issue. Numerical experiments demonstrate that both CS-LIM variants effectively capture the temporal structure of the underlying system using synthetic observational data. Moreover, when applied to real-world ENSO data, CS-LIMs yield consistent results that align well with the observations and current El Niño–Southern Oscillation (ENSO) understanding.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1569364</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1569364</link>
        <title><![CDATA[Conflict and cooperation: a systematic exploration]]></title>
        <pubdate>2025-04-16T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Leonardo Castro-Gonzalez</author><author>Rodrigo Leal-Cervantes</author><author>Ekkehard Ernst</author>
        <description><![CDATA[Economic cooperation is inherently dynamic, with agents adjusting the frequency, mechanisms, and intensity of their interactions over time. When scaling this behaviour to a large number of agents, we obtain a complex cooperation network where interaction dynamics influence the system’s macro-state. This study looks into how network topologies impact the survival of economic cooperation. Specifically, we explore the effect of topologies in sustaining cooperation through the survival of a “saving trait”, a feature that promotes cooperative interactions among agents. In our model, similar to a Stag Hunt (SH) game with memory, agents adapt their saving traits based on the profitability of past interactions with others. We simulate the game on seven distinct network structures sourced from the public repository Netzschleuder and analyse the robustness of the saving trait under topological shocks. From the seven studied networks, we recover the two equilibria dynamics from the SH game for four of them. For the remaining three, we obtain stable mixed states. These findings show that network topology affects the survival of the saving trait and its vulnerability to widespread topological shocks (over 25% of edges shifted or added). This work contributes to the interdisciplinary effort to understand economic cooperation by integrating insights from network science, game theory, and the social sciences.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1565736</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1565736</link>
        <title><![CDATA[Insight into employees' perceptions on reform initiatives in public service organizations using fractional order derivatives with optimal control strategies]]></title>
        <pubdate>2025-03-28T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Gizachew Kefelew Hailu</author><author>Shewafera Wondimagegnhu Teklu</author><author>Yohannes Fissha Abebaw</author><author>Dejen Ketema Mamo</author>
        <description><![CDATA[This study presents a compartmental model that classifies employees into three categories: “indifferent,” “resistant,” and “adaptive,” to explore their transitions based on adaptation to workplace reform initiatives. The researchers rigorously assessed the model for well-posedness and stability of its steady states. Utilizing Pontryagin’s maximum principle alongside numerical simulations, the researchers identified effective strategies aimed at reducing the number of resistant employees, thereby cultivating a more supportive atmosphere for reform efforts. The findings indicate that such an environment encourages employees to remain indifferent or adaptive, fostering a positive outlook toward change. The optimal strategies identified include providing training sessions to enhance employees' skills for adapting to new processes and technologies, as well as ensuring clear communication regarding the rationale, benefits, and impacts of the reforms. Furthermore, the study examined memory effects by transforming the integer order model into a fractional order model, with graphical representations highlighting the significance of fractional derivatives in illustrating the evolution of employees' perceptions over time. This research contributes valuable insights into managing employee adaptation during organizational change.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1534330</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1534330</link>
        <title><![CDATA[Carbon storage of seagrass ecosystems may experience tipping points in response to anthropogenic stress - a modeling perspective]]></title>
        <pubdate>2025-03-18T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Vasilis Dakos</author><author>Antoine Le Vilain</author><author>Elisa Thebault</author><author>Teresa Alcoverro</author><author>Jordi Boada</author><author>Eduardo Infantes</author><author>Dorte Krause-Jensen</author><author>Núria Marbà</author><author>Oscar Serrano</author><author>Salvatrice Vizzini</author><author>Eugenia T. Apostolaki</author>
        <description><![CDATA[Coastal Blue Carbon ecosystems like seagrass meadows are foundation habitats with a capacity to sequester and store organic carbon in their sediments, and their protection and restoration may thereby support climate change mitigation while also supporting biodiversity and many other ecosystem functions. However, seagrass ecosystems are being lost due to human activities, disease and, in some regions, climate change, which may trigger the release of stored carbon into the atmosphere. Yet, we do not fully understand how global change-induced seagrass loss influences sedimentary carbon dynamics. What is even less clear is whether seagrass loss may also result in tipping points, i.e., abrupt and difficult-to-reverse shifts, in carbon flux dynamics turning seagrass ecosystems from net carbon sinks to net carbon sources. Here, we propose that conceptual mechanistic models of coupled ecological and biogeochemical dynamics can help to study the effects of major stressors on seagrass meadows and associated carbon fluxes. We then illustrate one case of such a conceptual model that focuses on anthropogenic induced mortality by physical stress as an example. Our perspective highlights how a modeling approach for understanding the response of carbon fluxes in seagrass ecosystems to global change stressors may be useful in informing coastal seagrass management towards climate change mitigation actions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1544420</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1544420</link>
        <title><![CDATA[Diversity is key: fantasy football dream teams under budget constraints]]></title>
        <pubdate>2025-02-25T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Josef Gullholm</author><author>Jil Klünder</author><author>Julie Rowlett</author><author>Jonathan Stålberg</author>
        <description><![CDATA[Given a fixed budget for player salaries, what is the distribution of salaries of the top scoring teams? We investigated this question using the wealth of data available from fantasy premier league football (soccer). Using the players’ data from past seasons, for several seasons and several different budget constraints, we identified the highest scoring fantasy team for each season subject to each budget constraint. We then investigated quantifiable characteristics of these teams. Interestingly, across nearly every variable that is significant to the game of football and the budget, these top teams display diversity across these variables. Furthermore, randomly assembled teams would statistically not display such diversity across these variables. Our results indicate that diversity across these variables, including salaries, is a general feature of top performing teams. Moreover, in the process of obtaining these results we developed a data cleaning (or data reduction) algorithm that drastically reduced the amount of data to be analyzed.]]></description>
      </item>
      </channel>
    </rss>