Statistical Investigation of the 2020–2023 Micro-Seismicity in Enguri Area (Georgia) by Luciano Telesca, Nino Tsereteli, Nazi Tugushi, Tamaz Chelidze

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Winter Wheat Yield Prediction and Influencing Factors Analysis Based on FourierGNN–Random Forest Combined Modeling by Jianqin Ma, Yijian Chen, Bifeng Cui, Yu Ding, Xiuping Hao, Yan Zhao, Junsheng Li, Xianrui Su

“…In order to investigate the changes in winter wheat yield and the factors influencing it, five meteorological factors—such as rainfall and soil moisture—collected from the experimental area between 2010 and 2022 were used as characteristic features. …”
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Predicting photodegradation rate constants of water pollutants on TiO2 using graph neural network and combined experimental-graph features by Mahia V. Solout, Jahan B. Ghasemi

“…The efficiency of photocatalytic reactions in degrading pollutants is influenced by several factors, making parameter optimization time-consuming. …”
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Psychosocial factors influencing dietary management in patients with type 2 diabetes and healthy adults: an ecological momentary assessment approach by Junichi Saito, Hiroaki Kumano, Hiroaki Kumano

“…In both type 2 diabetes patients and healthy adults, eating-out situations were linked to dietary lapse.ConclusionThe results suggest differences in psychosocial factors influencing dietary lapse between patients with type 2 diabetes and healthy adults. …”
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Interpretation of chemical reaction yields with graph neural additive network by Youngchun Kwon, Yongsik Jung, Youn-Suk Choi, Seokho Kang

“…Prediction of chemical yields is crucial for exploring untapped chemical reactions and optimizing synthetic pathways for targeted compounds. Recently, graph neural networks have proven successful in achieving high predictive accuracy. …”
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Dynamic spatiotemporal graph network for traffic accident risk prediction by Pengcheng Zhang, Wen Yi, Yongze Song, Penggao Yan, Peng Wu, Ammar Shemery, Keith Hampson, Albert P. C. Chan

“…However, predicting traffic accident risks is challenging due to the relationships among factors such as weather, traffic conditions, and road characteristics, along with capturing spatial correlations of traffic accidents across different time scales. …”
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Factors influencing the prevalence and death rate of COPD: a pan-database ecological study covering 201 countries and regions from 1990 to 2021Research in context by Zihui Wang, Wenhan Cao, Zhixuan You, Shaoqiang Li, Mingshan Xue, Haiyang Li, Junfeng Lin, Guannan Cai, Yuqi Chen, Zhiman Liang, Chengtao Zhou, Xiaofang Wu, Guanghui Dong, Nanshan Zhong, Baoqing Sun, Zhangkai J. Cheng

“…Summary: Background: Chronic obstructive pulmonary disease (COPD) is a common, heterogeneous disease and may be influenced by diverse factors. However, gaps remain in previous studies regarding the exploration of potential influencing factors. …”
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Inventory of Galilean Transformation of uniform linear motion in position-time graphs by E. B. Merki, S. I. Hofer, A. Vaterlaus, A. Lichtenberger

“…In its current form, the IGT serves as a new instrument for assessing students’ ability to interpret position-time graphs under the influence of the Galilean transformation, making it suitable for formative or summative assessment in advanced upper secondary education.…”
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Graph-Aware Multimodal Deep Learning for Classification of Diabetic Retinopathy Images by Amina Zedadra, Ouarda Zedadra, Mahmoud Yassine Salah-Salah, Antonio Guerrieri

“…DRdiag integrates multiple modalities: the Fundus images and the duration of disease evolution which is an important factor in the diagnosis of DR as the duration of the disease directly influences the onset and progression of retinal lesions, leveraging two distinct models: a Convolutional Neural Network (CNN) based on DenseNet121 for image feature extraction and a Graph Neural Network (GNN) for capturing complex relationships between patient features. …”
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CGRS: Collaborative Knowledge Propagation Graph Attention Network for Recipes Recommendation by Suzhi Zhang, Xiang Lin, Zijian Bai, Pu Li, Haidi Fan

“…This method designs collaborative information propagation to make full use of user interaction and recipe attribute information to meet the needs of multiple influencing factors. Use the graph attention feature learning network to obtain the high-order feature information of the entity to meet the demand for fine-grained representation. …”
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Using the Space Syntax Analysis to Examine the Spatial Configuration of Houses Layouts and Its Transformation over Time in Biskra City by Rihane Barkat, Yassine Bada, Yasemin İnce Güney, Hafnaoui Hamzaoui

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Factors influencing evidence-based cardiovascular disease prevention programming in rural African American communities: a community-engaged concept mapping study by Amelia DeFosset, Breanna Deutsch-Williams, Mysha Wynn, Katrina Blunt, Scott Rosas, Mary Wolfe McKinley, Brian Ellerby, Shirley McFarlin, Veena Reddy, Giselle Corbie, Gaurav Dave

“…Absolute pattern matches comparing ratings of the relative importance and feasibility of each factor were generated and depicted via ladder graphs. …”
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Talking Wikidata: Communication Patterns and Their Impact on Community Engagement in Collaborative Knowledge Graphs by Koutsiana, Elisavet, Reklos, Ioannis, Alghamdi, Kholoud Saad, Jain, Nitisha, Meroño-Peñuela, Albert, Simperl, Elena

“…We analysed all the discussions on Wikidata using a mixed methods approach, including statistical tests, network analysis, and text and graph embedding representations. Our findings reveal that the interactions between Wikidata editors form a small world network, resilient to dropouts and inclusive, where both the network topology and discussion content influence the continuity of conversations. …”
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Graph neural networks and transfer entropy enhance forecasting of mesozooplankton community dynamics by Minhyuk Jeung, Min-Chul Jang, Kyoungsoon Shin, Seung Won Jung, Sang-Soo Baek

“…These findings will provide insights into the influential factors affecting mesozooplankton species and emphasize the importance of constructing appropriate graphs for forecasting these species.…”
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Question-matching approach based on gradual machine learning by Xuejian HE, Anqi CHEN, Zhiqiang GUO, Zhiru WANG, Qun CHEN

“…We model keyword features as unary factors in a factor graph, which define their influence on the matching status of the two questions. …”
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Research on network attack analysis method based on attack graph of absorbing Markov chain by Haiyan KANG, Molan LONG

“…Existing intrusion path studies based on attack graph lack consideration of factors other than basic network environment information when calculating the state transition probability.In order to analyze the security of target network comprehensively and reasonably, a network attack analysis method based on attack graph of absorbing Markov chain was proposed.Firstly, a state transition probability normalization algorithm based on vulnerability life cycle was proposed based on attack graph.Secondly, the attack graph was mapped to the absorbing Markov chain and the state transition probability matrix was given.Finally, the state transition probability matrix was calculated to comprehensively analyze the node threat degree, attack path length and expected impact of the target network.The results show that the proposed method can effectively analyze the expected influence of node threat degree, attack path length and vulnerability life cycle on the whole network, which is helpful for security research personnel to better understand the security state of the network.…”
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m-Polar Quadripartitioned Neutrosophic Graphs with Applications in Decision-Making for Mobile Network Selection by Basavaraj V Hiremath, Durga Nagarajan, Satham Hussain S, Hossein Rashmanlou, Farshid Mofidnakhaei

“…This study introduces m-polar Quadripartitioned neutrosophic sets and graphs, along with key results and operations, such as the composition and Cartesian product of m-polar quadripartitoned neutrosophic graphs, supported by illustrative examples to clarify the proposed concepts. …”
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Using Geographical Weighting and Knowledge Graph Centrality to Identify Key Management Areas for Shared Bikes by Yu Deng, Zechun Huang

“…Therefore, a new method for identifying key management areas for shared bikes using geographical weighting and knowledge graph centrality is proposed. In this study, a multiscale geographically weighted Poisson regression (MGWPR) model was initially used to explore the influencing factors of shared-bike usage and their degrees of influence. …”
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Uncovering Systemic Risk in ASEAN Corporations: A Framework Based on Graph Theory and Hidden Models by Marc Cortés Rufé, Jordi Martí Pidelaserra, Cecilia Kindelán Amorrich

“…The research focuses on identifying critical nodes within the corporate network, evaluating their contagion potential—both in terms of reinforcing resilience and amplifying vulnerabilities—and analyzing the influence of external factors on the network’s structure and behavior. …”
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Modeling ESG-driven industrial value chain dynamics using directed graph neural networks by Zhizhong Tan, Siyang Liu, Qiang Liu, Min Hu, Xiang Zhang, Wenyong Wang, Bin Liu

“…Abstract This study explores the dynamics of industrial value chains from the perspective of directed graph neural networks (DGNNs). This study focuses on the effects of environmental, social, and governance (ESG) factors on industrial value extension. …”
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