Complexity最新文献

{"title":"Exploring Ecological Dynamics and Bifurcation Structure of a Prey–Predator Model","authors":"M. D. Mutakabbir Khan,&nbsp;M. D. Jasim Uddin,&nbsp;Mainul Haque","doi":"10.1155/cplx/5317438","DOIUrl":"https://doi.org/10.1155/cplx/5317438","url":null,"abstract":"<p>The present work examines the dynamical features of a discrete-time Rosenzweig–MacArthur predator–prey system in which the predation rate is modulated by prey density. Through a combination of theoretical derivations and computational experiments, we establish the occurrence of period-doubling (PD) and Neimark–Sacker (NS) bifurcations, both of which culminate in chaotic regimes. The Lyapunov exponent spectrum corroborates this picture: Positive values mark the onset of chaos and reveal a pronounced dependence of the trajectories on parameter perturbations. Numerical simulations further reveal chaotic attractors and invariant closed trajectories. The Ott–Grebogi–Yorke (OGY) method is employed to stabilise unstable orbits to control chaos. When extending the analysis to a coupled network, we show that chaos appears beyond a certain critical coupling threshold. These insights advance understanding of predator–prey dynamics and chaos control in ecological systems.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/5317438","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dengue in Vulnerable Populations: A Mathematical Modeling Study Assessing the Impact on Pregnant Women and Comorbid Individuals","authors":"Sujana Azmi Polin,&nbsp;Amit Kumar Saha","doi":"10.1155/cplx/4398097","DOIUrl":"https://doi.org/10.1155/cplx/4398097","url":null,"abstract":"<p>Dengue continues to be a major global health concern, disproportionately affecting vulnerable populations such as pregnant women and individuals with comorbidities. In this study, we propose a deterministic compartmental model that stratifies the human population into nine classes, including those with comorbid conditions and pregnancy, to capture the heterogeneities in disease transmission, progression, and outcomes. The model incorporates behavior-related exposure modifiers and hospitalization dynamics to reflect real-world complexities. We perform a thorough mathematical analysis of the model, including positivity, boundedness, and equilibrium analysis. Using a series of numerical experiments, we explore how variations in transmission rates, recovery rates, exposure risks, and hospitalization influence epidemic outcomes across subpopulations. The simulations reveal that comorbid individuals and pregnant women significantly alter the course and severity of dengue outbreaks, both directly and indirectly. Our findings underscore the importance of targeted interventions and subgroup-specific prevention strategies, offering novel insights to inform public health policy and dengue control programs.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4398097","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Frequency Thunderstorm Prediction via Seasonally Decomposed Hybrid Models: Toward Data-Driven Early Warning and Climate Risk Mitigation","authors":"Mahabuba Akter Mimi,&nbsp;Mohammad Mahboob Hussain Khan,&nbsp;Amrin Binte Ahmed,&nbsp;Rumana Rois","doi":"10.1155/cplx/9285052","DOIUrl":"https://doi.org/10.1155/cplx/9285052","url":null,"abstract":"<p>Thunderstorms are frequent and destructive mesoscale phenomena in tropical and subtropical regions, posing major hazards through intense rainfall, lightning, strong winds, hail, and occasional tornadoes. In Bangladesh, premonsoon Kalbaishakhi (Nor’westers) are particularly damaging and remain difficult to forecast at local scales using computationally intensive numerical weather prediction approaches. This study aimed to develop and comparatively evaluate high-frequency data-driven forecasting frameworks for daily thunderstorm occurrence in Mymensingh, a thunderstorm-prone district in north-central Bangladesh and to assess their applicability for operational early warning. Daily thunderstorm frequency observations obtained from the Bangladesh Meteorological Department covering January 1, 1981, to December 31, 2024, were analyzed using a chronological training–testing split (80%–20%). Classical statistical models (ARIMA, ETS, TBATS, and GARCH), machine learning models (SVR, ANN, random forest, and Prophet), deep learning models (LSTMs), and sequential hybrid frameworks were evaluated using MAE, RMSE, MASE, and MAPE. Seasonal-Trend Decomposition using Loess (STL) was applied to address strong seasonality and intermittent zero-inflated behavior prior to hybrid modeling. Exploratory analyses revealed pronounced annual seasonality, minimal winter thunderstorm activity, and peak occurrences during April–June with substantial interannual variability. Among the nonseasonally adjusted models, ETS and ARIMA demonstrated comparatively reliable performance, while hybrid models generally improved forecasting accuracy. STL decomposition substantially enhanced predictive performance, with STL–LSTM achieving the lowest MAPE (2.25%) among individual models, whereas the STL–ARIMA–SVR hybrid model demonstrated the most balanced overall forecasting performance (MAE = 0.0274, RMSE = 0.4830, MASE = 0.2071, MAPE = 3.52%). For operational early warning assessment, STL–ARIMA–SVR achieved a probability of detection (POD) of 0.8435 and a critical success index (CSI) of 0.4157, indicating strong thunderstorm-event-detection capability under intermittent conditions. The findings demonstrate that seasonally decomposed hybrid forecasting frameworks can substantially improve localized thunderstorm prediction and support climate risk mitigation and operational early warning systems in Bangladesh. Future studies should incorporate multistation observations, atmospheric predictor variables, and real-time deployment evaluation to further improve forecasting robustness and operational applicability.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9285052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and Simulation of Cyber Epidemics Using a Delayed Variable-Order Fractional Framework","authors":"Mohamed Khalil,&nbsp;Anas Arafa,&nbsp;Ahmad Almutlg,&nbsp;Amaal Sayed","doi":"10.1155/cplx/3346036","DOIUrl":"https://doi.org/10.1155/cplx/3346036","url":null,"abstract":"<p>In today’s digital era, cyber epidemics are evolving rapidly. They pose a growing global threat. A cyber epidemic involves malware that spreads across connected networks. In this paper, we propose a delayed variable-order fractional model to study the spread of malware. The model incorporates time-varying memory effects through Caputo’s variable-order fractional derivative. It also accounts for delayed antivirus response via a time-delay term. The system is solved numerically using a predictor–corrector scheme. To the best of our knowledge, this work presents the first delayed variable-order fractional cyber epidemic model that integrates both time-dependent memory and time-delay effects. The results indicate that as the fractional order decreases, the system dynamics become slower and more stable, with lower infection levels. In addition, the variable-order model provides a more flexible description of evolving memory effects in cyber epidemic systems.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/3346036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equity Pledge and Corporate Green Transformation: Nonlinear Regime Transitions and Threshold Dynamics in a Financial–Environmental System","authors":"Enmin Zhang,&nbsp;Jianmin Wang,&nbsp;Juanjuan Chen,&nbsp;Jichao Geng","doi":"10.1155/cplx/5815910","DOIUrl":"https://doi.org/10.1155/cplx/5815910","url":null,"abstract":"<p>The transition toward carbon neutrality constitutes a complex adaptive process in which firms must continuously balance long-term environmental objectives against short-term financing constraints. While corporate green transformation is widely recognized as essential for sustainable development, the internal financial mechanisms shaping firms’ environmental strategies remain insufficiently understood. This study explores how controlling shareholders’ (CSs) equity pledge—a prevalent liquidity mechanism in emerging capital markets—generate nonlinear and threshold-dependent effects on corporate green transformation. We develop a constrained optimization model that embeds financing constraints and control-transfer risks into shareholders’ decision-making. The model formalizes a resource–risk trade-off and predicts a nonmonotonic relationship: Equity pledge initially facilitates green investment by easing liquidity constraints, but beyond a critical threshold, escalating control risk induces short-termism and crowds out substantive sustainability efforts. Using a balanced panel of Chinese A-share listed firms from 2014 to 2023, we empirically confirm a robust inverted U-shaped relationship between equity pledge intensity and green transformation. Further mechanism analyses reveal that financing constraints and digital transformation act as key transmission channels through which this nonlinear effect materializes. Heterogeneity tests indicate that the trade-off is most pronounced among non–state-owned firms, high-pollution industries, and firms with weak external governance. Extending the analysis, we show that although green transformation generally enhances firm value, excessive equity pledge undermines this benefit by amplifying governance risks. By integrating formal modeling with large-sample empirical evidence, this study demonstrates that corporate green transformation emerges from a complex interaction between liquidity incentive and risk constraint. The findings highlight equity pledge regulation as a critical leverage point for stabilizing the financial–environmental nexus in the transition toward low-carbon development.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/5815910","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"QualityNet: Complexity-Aware Temporal–Spatial Air Quality Categorization via Deep Tabular Attention Networks on Multisensor Urban Data","authors":"Kishor Kumar Reddy C.,&nbsp;Hafsa Ihteshamuddin Ahmed,&nbsp;Anisha P. R.,&nbsp;Surbhi B. Khan,&nbsp;Asma Alshuhail,&nbsp;Amina Salhi","doi":"10.1155/cplx/9155881","DOIUrl":"https://doi.org/10.1155/cplx/9155881","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Air pollution is a serious threat to public health and urban sustainability, posing a threat to our planet’s ecological balance and human well-being. Prolonged exposure to air pollution is linked to cardiovascular and respiratory diseases, cancers, and premature deaths. Urban locations, in particular, serve as a central hub for pollutant emissions from transportation vehicles, industrial units, and household operations, along with various meteorological factors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This research proposes temporal–spatial (implicit) air quality categorization based on deep tabular attention networks, the QualityNet model, on multisensor urban air pollution data from the UCI Air Quality dataset, which contains continuous pollutant concentrations. These are later mapped into discrete air quality categories to facilitate a classification structure that has the capability to detect subtle nonlinearities in relationships between environmental variables and multiple gas sensor readings. This research addresses constraints such as class imbalance through weighted loss functions, feature scaling, and solid train–test splits to ensure model generalizability.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Experimental results prove that the QualityNet classifier learns effective representative features from high-dimensional sensor data with an accuracy of 95.78%, precision of 95.8%, recall of 95.78%, F1-score of 95.78%, Cohen kappa score of 94.18%, and an AUC-ROC score of 99.46%. The attentive mechanisms of the model are useful for revealing the most impactful sensor inputs, making environmental monitoring explainable and interpretable.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This paper emphasizes the capability of deep tabular learning architectures for robust, dynamic, and interpretable air quality classification in urban monitoring systems. It efficiently classifies air quality levels into multiple categories, achieving high evaluation metrics such as accuracy: 95.78% and AUC-ROC: 0.9946. This provides a benchmark for future work in environmental and urban health monitoring.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9155881","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148616984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Translating Complexity Through Embodied Systems Awareness in Higher Education","authors":"Lucy Allen-Kelley,&nbsp;Alex Baumber,&nbsp;Jarnae Leslie,&nbsp;Susanne Pratt,&nbsp;Jacqueline Melvold,&nbsp;Monique Potts,&nbsp;Barbara Doran,&nbsp;Bem Le Hunte","doi":"10.1155/cplx/7012783","DOIUrl":"https://doi.org/10.1155/cplx/7012783","url":null,"abstract":"<p>Increasing international complexity and uncertainty challenges us to consider the future world state we create. The platform of higher education provides a space to equip the next generation of thinkers with perspectives, methods and approaches to navigate uncertain times through complexity theory. Despite the explicit focus on complexity within transdisciplinary approaches and the established link between embodied learning to enhanced student outcomes, research to date on how and why educators utilise embodied learning to enhance understanding of complexity within transdisciplinary higher education is still an emerging domain of scholarship. Therefore, the aim of this paper was to share how and why transdisciplinary educators from the UTS Transdisciplinary School approach the design, delivery and impact of embodied learning to support educating for complexity in a transdisciplinary co-joint degree. Six key insights are presented in this paper: (1) influences for implementation, (2) perceived student benefits, (3) perceived educator benefits, (4) implementation across a programme curriculum, (5) creating enabling conditions and (6) reflexive adaption across contexts. Through collaborative autoethnographic inquiry, this research surfaces embodied systems awareness as central to how we educate for complexity in transdisciplinary higher education. We demonstrate how embodied learning approaches support dynamic engagement with complex challenges, principles and characteristics and why this proves valuable in transdisciplinary higher education.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/7012783","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148616853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Power and Control in Complex Networks: A Taxonomy and Critical Review","authors":"A. Abeltino,&nbsp;T. Bacaloni,&nbsp;A. Bernardini,&nbsp;A. Pannone,&nbsp;F. Giancaterini","doi":"10.1155/cplx/6901600","DOIUrl":"https://doi.org/10.1155/cplx/6901600","url":null,"abstract":"<p>This paper reviews the main network analysis methodologies used to measure structural power, understood as the ability of actors to shape outcomes through their position and influence within a network. These approaches have been widely applied to the study of corporate control, global value chains, financial systems, and technology supply networks. Despite substantial methodological advances, the literature remains fragmented, with different measures often capturing distinct dimensions of structural power without a common conceptual framework. To address this gap, the paper develops a taxonomy that classifies existing methodologies by the dominant mechanism they use to conceptualize and measure power. Six methodological families are identified: centrality-based approaches, game-theoretic models, concentration measures, flow-based methods, optimization frameworks, and hybrid approaches. By clarifying the assumptions, analytical focus, and limitations of each family, the taxonomy provides a coherent framework for comparing alternative measures of structural power and understanding the dimensions of influence they capture. The paper concludes by outlining future research directions to refine hybrid models linking decision-making and network flows.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/6901600","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148616245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing the Italian and Danish Music Industries With Network Analysis","authors":"Lisandro Marco Benetti,&nbsp;Daniel Fejerskov-Quist,&nbsp;Michele Coscia","doi":"10.1155/cplx/4108905","DOIUrl":"https://doi.org/10.1155/cplx/4108905","url":null,"abstract":"<p>Making music is a collaborative effort, and understanding artistic endeavors with a network science lens has been a prolific field of study. Recently, a new approach produced a novel database of Italian music and analyzed it with innovative network analysis techniques to find music eras, a data-driven genre classification and a specialization index based on how bands share artists to publish records. In this work, we expand the previous work by adding data from Denmark and recording music labels’ information. We are interested in investigating whether the music eras and genre classifications found in previous work were universal, or whether they are driven by context-specific dynamics in a country. We find that only the most superficial structural statistics are preserved between Denmark and Italy. However, music eras, genre classifications, and artist specialization are actually different between the two countries. This shows how, to get a more complete picture of contemporary music production, the view from a single country is not enough.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4108905","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On Nonlinear Poverty–Hunger Model for Sustainability and Basic Needs: Awareness Feedback, Threshold Dynamics, and Attention-Enhanced Reservoir Computing","authors":"Amr Elsonbaty,&nbsp;Shaima Elnazer,&nbsp;Rajagopalan Ramaswamy,&nbsp;S. Padmaja,&nbsp;Waleed Adel","doi":"10.1155/cplx/6681986","DOIUrl":"https://doi.org/10.1155/cplx/6681986","url":null,"abstract":"<p>Eradicating poverty and hunger (SDG 1 and SDG 2) is central to sustainable development and environmental stability. This study proposes a nonlinear dynamical model describing the coupled evolution of poverty and hunger under awareness-driven mitigation strategies. The population is divided into socio-economically secure, poor, food-insecure, and co-burdened groups, together with a dynamic awareness variable that reduces transitions into adverse states. The model incorporates bidirectional coupling, endogenous reinforcement, partial recovery, and exogenous socio-economic shocks linked to climate variability and policy disruptions. Qualitative analysis establishes positivity, boundedness, and invariant regions. A poverty–hunger reproduction number derived via the next-generation matrix determines the local stability of the poverty–hunger-free equilibrium. A high-order numerical framework combining quasilinearization with shifted Legendre spectral collocation and domain decomposition is developed to simulate the model dynamics; this approach enables spectrally accurate, stable long-horizon simulations and provides a globally smooth solution approximation that supports the subsequent data-driven forecasting stage. Attention-enhanced reservoir computing is further employed to investigate the forecasting capability of data-driven models for reproducing the temporal dynamics generated by the proposed system. The framework supports evidence-based policies toward sustainable livelihoods and basic-needs security.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/6681986","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}