Article
Physics, Multidisciplinary
Yuan-Hao Xu, Hao-Jie Wang, Zhong-Wen Lu, Mao-Bin Hu
Summary: This paper presents a coupled epidemic-awareness-mobility model on multiplex networks, incorporating the dissemination of awareness through information links and the spread of epidemics through human mobility. The results show that information dissemination greatly affects the epidemic threshold and the final recovery density. The study also highlights the role of hub nodes and the impact of information transmission rate and mobility rate on epidemic containment.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Physics, Applied
Yue-Xia Zhang, Lie Zou
Summary: The study introduces a susceptible-exposed-adopted-recovered (SEAR) information dissemination model that considers the reinforcement effect of nonredundant information memory. Simulation results show a significant impact of nonredundant information memory's reinforcement effect on information dissemination, with theoretical predictions being largely consistent with the simulations.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2021)
Article
Computer Science, Information Systems
Qian Li, Hui Chen, Wen Li, Yunpeng Xiao
Summary: This paper proposes a group behavior dissemination model based on data enhancement and data representation. It introduces Generative Adversarial Networks (GAN) to generate homomorphic data, designs HP2vec method to convert the feature space to a low rank and dense vector, and proposes a dynamic dissemination method based on CNN. The experiments show that this model has high accuracy and can effectively predict group behavior in hotspots.
INFORMATION SCIENCES
(2022)
Article
Urban Studies
Ye Wei, Jiaoe Wang, Wei Song, Chunliang Xiu, Li Ma, Tao Pei
Summary: This study constructed a city-based epidemic and mobility model to simulate the spatiotemporal spread of COVID-19, emphasizing the role of intercity population mobility. Results showed high precision in simulating the inter-city spread of COVID-19 in China. Scenario simulations quantitatively evaluated the effect of control measures such as city lockdown and decreasing population mobility on containing the spatial spread of the COVID-19 epidemic.
Article
Computer Science, Information Systems
Vishrant Tripathi, Rajat Talak, Eytan Modiano
Summary: In this study, we investigate the timely exchange of updates between a central station and a set of ground terminals. We design a trajectory for a mobile agent to minimize the average-peak and average age of information. Through analysis, we demonstrate the optimal performance of randomized trajectories for both information gathering and dissemination problems, and propose an age-based trajectory strategy.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Yun-Chao Gong, Min Wang, Wei Liang, Feng Hu, Zi-Ke Zhang
Summary: With the expansion of online social networks, the diversity of users and community characteristics has become more prominent. This paper proposes a hypernetwork-based information dissemination model (UHIR model) to simulate and analyze the dynamic process of information dissemination in different network structures. The model takes into account user influence, confidence, interest value, and information timeliness. Simulation results demonstrate that the model accurately describes the information dissemination trend and process in real online social networks. This work extends the research direction of information dissemination in hypernetworks and contributes to the study of complex information dissemination mechanisms.
INFORMATION SCIENCES
(2023)
Article
Physics, Multidisciplinary
F. E. Cornes, G. A. Frank, C. O. Dorso
Summary: This study presents an epidemiological model that examines the impact of human mobility on the dynamics of the COVID-19 outbreak, proposing global confinement, partial restriction to mobility, and localized confinement as strategies to mitigate disease spread. It was observed that localized isolation policies based on the health status of each block were effective in containing and reducing the outbreak in specific regions of the city.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Mathematical & Computational Biology
Liang'an Huo, Shiguang Meng
Summary: Disease dissemination poses serious problems in the economy and livelihood. It is crucial to study the patterns of disease dissemination from multiple perspectives. The quality of disease prevention information has a significant impact on its dissemination, as only genuine information can inhibit the spread of disease. The decay of information quantity and quality can influence individuals' attitudes and behaviors towards disease.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2023)
Article
Physics, Multidisciplinary
Maojie Ran, Jiancu Chen
Summary: This study introduces a new information dissemination model, the PaNSEIR model, which simulates the spread of information in social networks by incorporating an information interference function and combining complex network theory and propagation dynamics theory. The results show that external information interference promotes the dissemination of original information, and the model can better reflect the characteristics of information dissemination in social networks.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Review
Agronomy
Helio R. Sousa Filho, Raildo M. de Jesus, Marcos A. Bezerra, Gregorio M. Santana, Romario O. de Santana
Summary: The world demand for cocoa beans has increased, but the spread of witches' broom disease poses a significant obstacle to cocoa production. Various strategies such as genetic control, cultural management, and chemical and biological control have been attempted in the field to combat the disease, but economic and technical difficulties remain to be overcome. Although the disease is currently restricted to Central and South America, measures need to be taken to prevent its spread to other regions to avoid a global crisis in cocoa production.
Article
Engineering, Civil
Yingjie Xia, Xuejiao Liu, Jing Ou, Oubo Ma
Summary: In this paper, a reinforcement learning-based information dissemination policy generation scheme in VANETs, named RLID-V, is proposed. It combines multiple attribute-based access control policies to resolve conflicts and uses a decision tree to construct a manual feedback policy. Reinforcement learning is employed to dynamically update confidence weights of different policy sources. Experimental results show that RLID-V outperforms three existing schemes in accuracy and effectiveness of information dissemination in traffic guidance and accident warning scenarios. Additionally, RLID-V exhibits robustness, with a negligible cost of less than 1% of overall delay overhead for policy generation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Physics, Multidisciplinary
Felipe Araujo, Lucas Bastos, Iago Medeiros, Osvaldo A. Rosso, Andre L. L. Aquino, Denis Rosario, Eduardo Cerqueira
Summary: Location-aware services provide valuable information for understanding human mobility patterns. Analyzing the mobility dynamics, such as transportation means and speeds, can lead to better solutions by identifying different patterns. Information Theory measures, such as Complex-Entropy Causality Plane and Fisher-Shannon Causality Plane, have shown advancements in distinguishing time series dynamics, making them promising tools for improving human mobility-based services. This study characterizes users' transportation means based on their speed time series, using Information Theory quantifiers and colored noises mapped onto causal planes to differentiate motorized and non-motorized transportation.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Kashif Naseer Qureshi, Awais Ahmad, Francesco Piccialli, Giampaolo Casolla, Gwanggil Jeon
Summary: The relentless growth of population and urbanization has intensified the pressure on traditional systems to address issues related to citizen lifestyle, environment, economics, and good governance. New communication technologies are crucial in transforming traditional urbanization into a smarter and more comfortable environment, but smart cities face various challenges related to technology, system control and management, scalability, and security. New concepts of nature-inspired solutions have been implemented to address smart cities' challenges through optimization and performance-oriented methods.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Jing Chen, Jincheng Huang, Chen Xin, Mingxin Liu
Summary: This paper proposes a heat transfer (HT) information dissemination model based on the idea of heat transfer, which simulates the dissemination process of information in online social networks. By introducing the temperature value attribute of nodes and defining dissemination nodes and observer nodes, the model accurately predicts dissemination trends and node variations.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Management
Yossi Aviv, Noam Shamir
Summary: This study examines the impact of financial cross-ownership on operational decisions in a supply chain with competing retailers. The results show that holding stocks in a rival reduces competition during the production stage and increases the incentive for information acquisition. This information benefits retailers and consumers alike.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2021)
Article
Biochemical Research Methods
Valeria d'Andrea, Riccardo Gallotti, Nicola Castaldo, Manlio De Domenico
Summary: The perception of epidemic risk by individuals plays a crucial role in determining compliance with control measures. A mathematical model is developed to study the impact of non-compliant individuals on epidemic dynamics, taking into account different social contact structures. The study finds a one-to-one relationship between perceived risk and compliance with mitigation rules, and shows that epidemic spreading is hindered when the population fraction of risk-denier individuals decreases. The findings highlight the importance of risk awareness and social contact patterns in managing disease outbreaks.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Alina L. Machidon, Veljko Pejovic
Summary: This paper investigates the integration of CS and DL in the ubiquitous computing domain, identifies key ideas and trends, and provides guidelines for the future development of CS-DL.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Information Systems
Octavian Machidon, Jani Asprov, Tine Fajfar, Veljko Pejovic
Summary: This study investigates how a user's physical activity, the spatial/temporal properties of the video, and the user's personality traits interact and jointly influence the minimal acceptable playback resolution. The findings show that the minimal acceptable resolution varies across different contextual factors. The predictive models and power consumption measurements suggest an opportunity for energy saving through context-adaptable approximate computing.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Mathematics, Interdisciplinary Applications
Pier Luigi Sacco, Alex Arenas, Manlio De Domenico
Summary: The governance of the political and economic world order relies on international treaties at various geographical scales. Assessing the stability of this architecture is crucial, considering the potential unilateral defection of countries and treaty breakdowns. Our analysis reveals that small and micro countries pose the highest disruption potential, while political stability depends on overseas territories and emerging economies. Economic stability relies on medium-sized European and African countries. Surprisingly, single global treaties have limited disruptive potential, apart from the WTO. Our findings suggest that the fragility of the world order is closely linked to global inequality and fiscal injustice, highlighting the continued influence of the colonial world order.
Article
Computer Science, Information Systems
Christoph Anderson, Judith Simone Heinisch, Shohreh Deldari, Flora Salim, Sandra Ohly, Klaus David, Veljko Pejovic
Summary: Pervasive and ubiquitous computing provides immediate access to information, which can enhance daily routines but may be disruptive if not aligned with users' interruptibility preferences. Attention management systems use machine learning to identify opportune moments for information delivery and reduce interruptions. Our comprehensive approach combines on-device sensing, machine learning, and theories from social science to create a personalized two-stage classification model based on social role-based attention and interruptibility management.
IEEE PERVASIVE COMPUTING
(2023)
Article
Multidisciplinary Sciences
Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi
Summary: We address the issue of goal-directed graph construction, aiming to find a set of edges that maximally improve a global objective function in a given starting graph. This problem is prevalent in transportation and infrastructure networks that are critical to society. By formulating it as a deterministic Markov decision process, we propose improvements over the standard UCT algorithm to solve this problem efficiently and enhance attack resilience in networks. Our approach achieves significant advancements in efficiency and scalability compared to previous reinforcement learning methods.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Giorgio Franceschelli, Mirco Musolesi
Summary: This paper explores the possibility of using generative learning techniques to measure machine creativity. A new measure called DeepCreativity, based on Margaret Boden's definition of creativity, is introduced. The effectiveness and expressiveness of the proposed methodology is evaluated through a case study on 19th century American poetry.
INTELLIGENZA ARTIFICIALE
(2022)
Article
Mathematics, Interdisciplinary Applications
Pier Luigi Sacco, Alex Arenas, Manlio De Domenico
Summary: The leak of documents from Mossack Fonseca revealed a complex offshore business network involving individuals and companies engaging in offshore activities and transactions with multiple tax havens. This network forms an effective global infrastructure for tax evasion, with a strongly connected core consisting of well-known tax havens and major global powers. These findings provide insights into the interconnection between tax evaders in a globalized economy and its potential impact on social dynamics and political polarization.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Computer Science, Theory & Methods
Alessandro Staffolani, Victor-Alexandru Darvariu, Paolo Bellavista, Mirco Musolesi
Summary: Distributed workload queues are widely used due to their advantages in decoupling, resilience, and scaling. However, existing task allocation strategies may result in high execution times and costs when task information is unavailable and worker node capabilities are not homogeneous. In this work, we propose RLQ, a reinforcement learning-based task allocation solution, which achieves significant improvements in execution cost, time, and waiting time compared to traditional solutions.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Article
Physics, Multidisciplinary
Sebastiano Bontorin, Manlio De Domenico
Summary: Understanding information flow in networks is crucial for predicting the behavior of various systems, such as cellular regulatory dynamics and epidemic spreading in social networks. In this study, we propose a multi-pathways temporal distance that encodes the collective behavior of paths in propagating perturbations and predicts the latent geometry induced by the dynamics. Our framework outperforms existing approaches in predicting arrival times and shows remarkable accuracy in predicting the timing of infections in empirical social systems. It has broad applications in fields ranging from cellular dynamics to epidemic spreading.
COMMUNICATIONS PHYSICS
(2023)
Review
Physics, Multidisciplinary
Manlio De Domenico
Summary: The constituents of complex systems exhibit non-trivial connectivity patterns and dynamical processes, which can be well captured by network models. However, most systems are coupled with each other through interdependencies or multiplexity. Multilayer networks provide the framework to capture the complexity of systems of systems, enabling the analysis of various networks from an integrated perspective. This Review covers recent theoretical developments in multilayer network analysis, discussing phenomena that cannot be observed from isolated subsystems or their aggregation, and exploring applications in various spatial scales.
Article
Multidisciplinary Sciences
Pascal P. Klamser, Valeria d'Andrea, Francesco Di Lauro, Adrian Zachariae, Sebastiano Bontorin, Antonello Di Nardo, Matthew Hall, Benjamin F. Maier, Luca Ferretti, Dirk Brockmann, Manlio De Domenico
Summary: As the coronavirus disease 2019 spread globally, emerging variants like B.1.1.529 quickly became dominant worldwide. Sustained community transmission and cross-national mobility flows led to consecutive cases surge. Integrating data from national genomic surveillance and global human mobility with epidemic modeling allows quantifying the pandemic potential of emerging variants and provides indicators for policy interventions. This scalable integrated approach enhances global preparedness to counter the pandemic of respiratory pathogens.
Article
Physics, Fluids & Plasmas
Arsham Ghavasieh, Manlio De Domenico
Summary: The network density matrix formalism is limited to diffusion dynamics on undirected networks. To overcome this limitation, we propose an approach based on dynamical systems and information theory to derive density matrices, which can encapsulate a wider range of linear and nonlinear dynamics as well as richer classes of structure. Our findings demonstrate that topological complexity does not necessarily lead to functional diversity, and instead, functional diversity is a genuine emergent property that cannot be deduced from the knowledge of topological features.
Article
Physics, Multidisciplinary
Arsham Ghavasieh, Giulia Bertagnolli, Manlio De Domenico
Summary: Microscopic structural damage, such as lesions in neural systems or disruptions in urban transportation networks, can impair the dynamics crucial for systems' functionality, such as electrochemical signals or human flows, or any other type of information exchange, respectively, at larger topological scales. Yet, this approach fails to capture how damage hinders the propagation of information across scales, since system function can be degraded even in absence of fragmentation-e.g., pathological yet structurally integrated human brain. Using a damaging protocol explicitly accounting for flow dynamics, we analyze synthetic and empirical systems, from biological to infrastructural ones, and show that it is possible to drive the system towards functional fragmentation before full structural disintegration.
PHYSICAL REVIEW RESEARCH
(2023)
Article
Psychology, Multidisciplinary
Amadej Jankovic, Tine Kolenik, Veljko Pejovic
Summary: This paper presents a preliminary investigation on the persuasiveness of mobile notifications within a real-world behavior change intervention mobile app. The results indicate that customized messages may work for some individuals while working poorly for others. The study also highlights a nuanced relationship between personalization and persuasiveness, calling for further exploration.
BEHAVIORAL SCIENCES
(2022)