Article
Computer Science, Artificial Intelligence
Zhenyue Qin, Tom Gedeon, R. I. McKay
Summary: Discrete gene regulatory networks (GRNs) are important in the study of robustness and modularity. Evaluating the robustness of GRNs has often involved sampling random gene activation patterns, introducing stochasticity and making reproducibility difficult. In this study, a deterministic distributional fitness evaluation method is proposed to address these issues, allowing for repeatability and theoretical bounds on fitness. The effects of problem domain and noisy fitness evaluation are differentiated, leading to a deeper understanding of the nature of the problem domain.
Article
Cell Biology
Xin Xue, Jia-Jia Wu, Bei-Bei Huo, Xiang-Xin Xing, Jie Ma, Yu-Lin Li, Mou-Xiong Zheng, Xu-Yun Hua, Jian-Guang Xu
Summary: Using animal models to study the mechanisms of aging in the brain is crucial for developing interventions for aging-related brain disorders. In this study, young and aged rats were examined using positron emission tomography to build brain metabolic networks. It was found that aged rats showed similar aging-related alterations in brain metabolism as humans, making them a suitable model for studying aging and potential therapies.
Article
Multidisciplinary Sciences
Gaoyang Li, Li Liu, Wei Du, Huansheng Cao
Summary: The authors develop a method called Decrem, which integrates locally coupled reactions and global transcriptional regulation of metabolism, to reconstruct genome-scale metabolic networks. Decrem achieves accurate predictions of phenotypes and has broad applications in bioengineering, synthetic biology, and microbial pathology.
NATURE COMMUNICATIONS
(2023)
Article
Engineering, Industrial
Shuliang Wang, Wenzhuo Lv, Jianhua Zhang, Shengyang Luan, Chen Chen, Xifeng Gu
Summary: A novel framework is proposed in this paper to evaluate network robustness from different perspectives, considering typical complex network models and power characteristics. The study case of IEEE 118 bus test case was used to analyze the features of the power network based on topology theory and electrical science. It is found that critical nodes identification from different perspectives can lead to different results, highlighting the importance of integrating information from multiple angles. The study also suggests methods to improve power network robustness and discusses network recovery strategies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Physics, Multidisciplinary
Marco Tomassini
Summary: This study demonstrates that the robustness of real-world complex networks against deliberate attacks can be improved using network modification techniques. Two methods, edge rewiring and edge addition, are compared and both are found to be useful in reducing vulnerability of infrastructure networks. Edge rewiring leads to less vulnerable networks, but it is difficult to implement in real-world networks due to engineering and cost reasons. Edge addition, on the other hand, is easier to apply and effective against random edge failures and attacks targeting bridge edges.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Biology
U. Hernandez, L. Posadas-Vidales, C. Espinosa-Soto
Summary: Biological adaptations depend on natural selection eliminating individuals unfit to their environment, as well as the presence of phenotypic variation in populations. The properties of developmental mechanisms, such as modularity and robustness, impact phenotypic variability, which plays a role in the widespread occurrence of modularity and robustness in biological systems.
Article
Ecology
Kate P. Maia, Flavia M. D. Marquitti, Ian P. Vaughan, Jane Memmott, Rafael L. G. Raimundo
Summary: Understanding the processes driving ecological resilience in plant-insect assemblages is a central challenge for ecologists. The mechanisms affecting community response to perturbations depend on natural history attributes and interaction structure, and interaction rewiring plays a key role in determining resilience. Network structure and the level of generalisation also interact to affect the resilience of dynamic ecological networks.
JOURNAL OF ANIMAL ECOLOGY
(2021)
Article
Behavioral Sciences
Anjalika Nande, Veronika Dubinkina, Riccardo Ravasio, Grace H. Zhang, Gordon J. Berman
Summary: This study investigates the impact of information bottleneck in neural networks, demonstrating that a modular structure enhances network efficiency and robustness, at the expense of increased state-dependent effects. Despite its simplicity, the model provides insight into the trade-offs faced by nervous systems under information processing constraints and offers predictions for future experiments.
FRONTIERS IN BEHAVIORAL NEUROSCIENCE
(2022)
Article
Automation & Control Systems
Mohamed Sayah, Djillali Guebli, Zeina Al Masry, Noureddine Zerhouni
Summary: This paper proposes a framework to test the robustness of deep LSTM architecture for RUL prediction, and validates its resilience through the use of stress functions. The comparison between mutant fuzzed Deep LSTM networks and the original model indicates the quality of the RUL prediction model. The use of phi-stress operators demonstrates the ability to build stable and data-independent Deep LSTM models for RUL prediction.
Article
Neurosciences
Qi Huang, Shuhua Ren, Tianhao Zhang, Junpeng Li, Donglang Jiang, Jianfei Xiao, Fengchun Hua, Fang Xie, Yihui Guan
Summary: Using metabolic brain network, this study revealed the reorganization of brain modular architecture during aging. The modular architecture was slightly reorganized from young to old ages, with regions related to sensorimotor function more converged. The number of connector nodes was reduced, with most connector nodes localized in the temporo-occipital regions. The major gender difference was that the metabolic brain network was split into four modules in the old female group, with the sensorimotor functions divided into two modules.
BRAIN CONNECTIVITY
(2022)
Article
Physics, Multidisciplinary
Mohammad Nabizadeh, Abhinendra Singh, Safa Jamali
Summary: This study compares force network formation in continuous and discontinuous shear thickening dense suspensions, revealing notable differences in their characteristics and impact on system behavior.
PHYSICAL REVIEW LETTERS
(2022)
Review
Automation & Control Systems
Petter Ogren, Christopher Sprague
Summary: This article provides a control-theoretic perspective on behavior trees in robotics, discussing the use of modularity, hierarchies, and feedback in handling the complexity of versatile robot control systems.
ANNUAL REVIEW OF CONTROL ROBOTICS AND AUTONOMOUS SYSTEMS
(2022)
Article
Biochemical Research Methods
Peilin Jia, Astrid M. Manuel, Brisa S. Fernandes, Yulin Dai, Zhongming Zhao
Summary: The study investigates the temporal network modularity using brain tissue transcriptomics to explore different brain disorders and traits at various developmental stages. The analysis reveals that most psychiatric disorders and traits have a fetal origin, while neurological diseases and anthropometric traits show increased co-expression activities in postnatal brains. Additionally, enriched cell types and functional features in specific brain disorders were identified, supporting previous knowledge in the field.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biotechnology & Applied Microbiology
Maciek R. Antoniewicz
Summary: Metabolic engineering aims to improve biological production by designing and optimizing metabolic pathways, quantifying metabolic fluxes, and analyzing metabolic network models; essential concepts include metabolic network models and metabolic fluxes; in recent years, advancements in technology and methods have allowed for a deeper understanding of the capabilities of biological systems.
METABOLIC ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Kun Sun, Haixia Xu, Liming Yuan, Xianbin Wen
Summary: CapsInfor is a novel tiny deep capsule architecture that achieves satisfactory performance with fewer parameters compared to CapsNet. By utilizing fast tensor capsule layers and a novel routing process, CapsInfor demonstrates competitive results on various datasets and shows robustness in certain tests.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Review
Physics, Multidisciplinary
Marko Jusup, Petter Holme, Kiyoshi Kanazawa, Misako Takayasu, Ivan Romic, Zhen Wang, Suncana Gecek, Tomislav Lipic, Boris Podobnik, Lin Wang, Wei Luo, Tin Klanjscek, Jingfang Fan, Stefano Boccaletti, Matjaz Perc
Summary: In recent years, physics methods have been widely used to study societal phenomena. Social physics examines topics at the core of modern human societies and explores potential threats to society. The future of this field looks promising, with physicists playing an important role in studying social phenomena.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2022)
Article
Multidisciplinary Sciences
Boris Podobnik, Marko Jusup, Dean Korosak, Petter Holme, Tomislav Lipic
Summary: This article empirically documents a tipping point in the relationship between democratic norms and corruption suppression, and demonstrates how such a tipping point emerges from a micro-scale mechanistic model. The research suggests that under weak democratic norms, corruption is difficult to suppress, while strong democratic norms can effectively suppress corruption.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2022)
Article
Public, Environmental & Occupational Health
Fan Fang, Tong Wang, Suoyi Tan, Saran Chen, Tao Zhou, Wei Zhang, Qiang Guo, Jianguo Liu, Petter Holme, Xin Lu
Summary: The study found that during the COVID-19 pandemic, social media networks experienced an increase in size and frequency of interactions. The number of unique recipients, average degree, and transitivity also increased during the severe stage of the outbreak. The similarity of topics discussed on Weibo increased during the local peak of the epidemic, and the number of communities focused on COVID-19 increased significantly. Furthermore, there was a statistically significant rebound effect in the emotional content of users' posts.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Engineering, Multidisciplinary
Marcin Waniek, Petter Holme, Talal Rahwan
Summary: Social network analysis tools can infer various attributes by examining connections. Previous studies on hiding personal importance in static networks have overlooked the more general case of temporal networks. This research investigates the concealment of personal importance in temporal networks with changing edges. The study shows that finding the optimal hiding strategy is usually computationally infeasible, but manipulating contacts can increase privacy. Temporal networks provide more strategies for manipulation compared to static networks, making hiding easier.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Physics, Multidisciplinary
Francesco Picciolo, Franco Ruzzenenti, Petter Holme, Rossana Mastrandrea
Summary: Network theory has proven to be a useful paradigm for understanding the organization and functioning of complex systems in the real world. This study proposes a novel methodology for analyzing weighted motifs and applies it to various real networks. The identified similarities enable the classification of systems based on specific configurations associated with functioning mechanisms.
NEW JOURNAL OF PHYSICS
(2022)
Editorial Material
Multidisciplinary Sciences
Petter Holme
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Marcin Waniek, Petter Holme, Manuel Cebrian, Talal Rahwan
Summary: Influence through social networks is fundamental, but identifying the diffusion source is challenging as sources can strategically modify network structure. Efforts should focus on exposing concealed ties rather than planted entities to improve detection.
Article
Multidisciplinary Sciences
Zhizheng Wang, Xiao Fan Liu, Zhanwei Du, Lin Wang, Ye Wu, Petter Holme, Michael Lachmann, Hongfei Lin, Zoie S. Y. Wong, Xiao-Ke Xu, Yuanyuan Sun
Summary: This paper proposes a computational framework that can automatically extract epidemiological information from open-access COVID-19 case reports, and provides an open-access online platform to implement the algorithm.
Article
Multidisciplinary Sciences
Marcin Waniek, Petter Holme, Katayoun Farrahi, Remi Emonet, Manuel Cebrian, Talal Rahwan
Summary: This study shows that increasing the budget for contact tracing improves the identification of infected individuals, but has diminishing returns in terms of source detection. Disease variants with higher infectivity make it easier to find the source, but harder to identify infected individuals. There is a trade-off between using contact tracing to identify patient zero or detect infected individuals.
SCIENTIFIC REPORTS
(2022)
Article
Psychology, Biological
Fengyuan Liu, Petter Holme, Matteo Chiesa, Bedoor AlShebli, Talal Rahwan
Summary: Using algorithmic tools, researchers found pervasive gender inequalities among academic editors, with only 8% of editors-in-chief being women. Men editors were more likely to self-publish in the journal they edit. Career length explains the gender gap among editors, but not editors-in-chief.
NATURE HUMAN BEHAVIOUR
(2023)
Article
Public, Environmental & Occupational Health
Zhanwei Du, Qi Tan, Yuan Bai, Lin Wang, Benjamin J. Cowling, Petter Holme
Summary: The ease of COVID-19 non-pharmacological interventions and the increased susceptibility during the past COVID-19 pandemic may lead to a severe outbreak of influenza in the winter of 2022 and future seasons. The availability of Electronic Health Records (EHR) data in public health systems offers new opportunities to monitor individuals and mitigate outbreaks.
Article
Public, Environmental & Occupational Health
Yuan Bai, Mingda Xu, Caifen Liu, Mingwang Shen, Lin Wang, Linwei Tian, Suoyi Tan, Lei Zhang, Petter Holme, Xin Lu, Eric H. Y. Lau, Benjamin J. Cowling, Zhanwei Du
Summary: This study estimates the importation and exportation risks between Chinese cities using a stochastic metapopulation model based on the epidemic characteristics of COVID-19. It reveals the existence of high exportation risks in certain regions, emphasizing the importance of preparedness and control measures for COVID-19.
Article
Multidisciplinary Sciences
Shupeng Gao, Lili Chang, Ivan Romic, Zhen Wang, Marko Jusup, Petter Holme
Summary: This article presents a solution to the problem of controlling Turing patterns in networks, utilizing an analytical framework and numerical algorithm. The authors demonstrate the effectiveness of their method and discuss factors that impact its performance. They also pave the way for multidisciplinary applications of their framework beyond reaction-diffusion models.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Multidisciplinary Sciences
Zhanwei Du, Yuan Bai, Lin Wang, Jose L. Herrera-Diestra, Zhilu Yuan, Renzhong Guo, Benjamin J. Cowling, Lauren A. Meyers, Petter Holme
Summary: This article proposes a data-driven COVID-19 surveillance strategy using Electronic Health Record (EHR) data to identify vulnerable individuals who are at high risk of early infection. The simulations demonstrate that this strategy performs as well as the most-connected strategy and can detect early warning signals and peak timings earlier than random acquaintance surveillance.
Article
Social Sciences, Mathematical Methods
Luis E. C. Rocha, Petter Holme, Claudio D. G. Linhares
Summary: This study examines the international migration patterns of sex-workers using network methods. The results reveal that the migration network of sex-workers has different structural patterns compared to the general population. Europe is divided into various network communities with specific connections to non-European countries. Moreover, there are asymmetrical relations between countries, with some predominantly offering services while others attract workers. The financial gains of migration are related to the GDP per capita of the country of origin.
JOURNAL OF COMPUTATIONAL SOCIAL SCIENCE
(2022)
