Dynamic propagation will affect the change of network structure. Different networks are affected by the iterative propagation of information to different degrees. The iterative propagation of information in the network changes the connection strength of the chain edge between nodes. Most studies on temporal networks build networks based on time characteristics, and the iterative propagation of information in the network can also reflect the time characteristics of network evolution. The change of network structure is a macromanifestation of time characteristics, whereas the dynamics in the network is a micromanifestation of time characteristics. How to concretely visualize the change of network structure influenced by the characteristics of propagation dynamics has become the focus of this article. The appearance of chain edge is the micro change of network structure, and the division of community is the macro change of network structure. Based on this, the node participation is proposed to quantify the influence of different users on the information propagation in the network, and it is simulated in different types of networks. By analyzing the iterative propagation of information, the weighted network of different networks based on the iterative propagation of information is constructed. Finally, the chain edge and community division in the network are analyzed to achieve the purpose of quantifying the influence of network propagation on complex network structure.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1089/big.2023.0016 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Multi-class Classification of Retinal Eye Diseases from Ophthalmoscopy Images Using Transfer Learning-Based Vision Transformers.
J Imaging Inform Med
January 2025
College of Engineering, Department of Computer Engineering, Koç University, Rumelifeneri Yolu, 34450, Sarıyer, Istanbul, Turkey.
This study explores a transfer learning approach with vision transformers (ViTs) and convolutional neural networks (CNNs) for classifying retinal diseases, specifically diabetic retinopathy, glaucoma, and cataracts, from ophthalmoscopy images. Using a balanced subset of 4217 images and ophthalmology-specific pretrained ViT backbones, this method demonstrates significant improvements in classification accuracy, offering potential for broader applications in medical imaging. Glaucoma, diabetic retinopathy, and cataracts are common eye diseases that can cause vision loss if not treated.
View Article and Find Full Text PDFThe impact of bleaching using 15% carbamide peroxide on surface properties of CAD-CAM composite structures.
Sci Rep
January 2025
Division of Dentistry, School of Medical Sciences, The University of Manchester, Manchester, M13 9PL, UK.
This study aims to evaluate the effects of the home bleaching method on the surface microhardness and surface roughness of both polished and unpolished CAD-CAM resin composite materials. A polymer-infiltrated ceramic network (PICN) block, Enamic (VE), along with four resin composite blocks (RCB) (Grandio [GN], Lava™ Ultimate [LV], BRILLIANT Crios [B], and Cerasmart [CS]), were prepared to dimensions of 14 mm × 12 mm × 2 mm and were categorized into unpolished and polished groups (n = 4). Microhardness measurements were conducted using a Vickers microhardness tester (300 gf load for 20 s) at various time points: before home bleaching, after home bleaching with 15% Opalescence for 8 h and for 56 h, 24 h after bleaching, and one month after bleaching.
View Article and Find Full Text PDFOptimizing photovoltaic power plant forecasting with dynamic neural network structure refinement.
Sci Rep
January 2025
Instituto de Ingeniería Energética, Universitat Politècnica de València, Valencia, Spain.
Reliable prediction of photovoltaic power generation is key to the efficient management of energy systems in response to the inherent uncertainty of renewable energy sources. Despite advances in weather forecasting, photovoltaic power prediction accuracy remains a challenge. This study presents a novel approach that combines genetic algorithms and dynamic neural network structure refinement to optimize photovoltaic prediction.
View Article and Find Full Text PDFMulti scale multi attention network for blood vessel segmentation in fundus images.
Sci Rep
January 2025
Department of Data Science and Artificial Intelligence, Sunway University, 47500, Petaling Jaya, Selangor Darul Ehsan, Malaysia.
Precise segmentation of retinal vasculature is crucial for the early detection, diagnosis, and treatment of vision-threatening ailments. However, this task is challenging due to limited contextual information, variations in vessel thicknesses, the complexity of vessel structures, and the potential for confusion with lesions. In this paper, we introduce a novel approach, the MSMA Net model, which overcomes these challenges by replacing traditional convolution blocks and skip connections with an improved multi-scale squeeze and excitation block (MSSE Block) and Bottleneck residual paths (B-Res paths) with spatial attention blocks (SAB).
View Article and Find Full Text PDFStrengthening advanced therapy for sickle cell disease in Africa: experience from sickle cell disease centre in Dar es Salaam, Tanzania.
BMJ Glob Health
January 2025
Sickle Cell Programme, Department of Haematology and Blood Transfusion, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.
Despite progress in healthcare services for individuals living with sickle cell disease (SCD) in Africa, substantial gaps remain in advanced treatments for SCD. To help address this burden, Tanzania has established one of the largest single-centre SCD programmes in the world and developed an advanced therapy programme for SCD focused on patient engagement and advocacy, clinical activities involving exchange blood transfusion (ExBT) and haematopoietic stem cell transplant (HSCT), gene therapy (GT) preparedness, and enabling partnerships. This report describes the programme's genesis, structure and progress achieved.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!