Data-Driven Dynamic Graph Convolution Transformer Network Model for EEG Emotion Recognition Under IoMT Environment by Xing Jin, Fa Zhu, Yu Shen, Gwanggil Jeon, David Camacho

“…To overcome these limitations, this paper proposes a new data-driven dynamic graph-embedded Transformer network (DGETN) that has emerged in different tasks of graph data mining for emotion analysis of EEG signals in the scene of IoMT. …”
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Incremental and transformational climate change adaptation factors in agriculture worldwide: A comparative analysis using natural language processing. by Sofia Gil-Clavel, Thorid Wagenblast, Tatiana Filatova

“…We use the derived data as input for generalized linear models to analyze whether reported factors behind farmers' decisions differ by type of adaptation (incremental vs. transformational) and across different global regions. …”
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Spatial transformation mechanism of city networks in the middle and lower Ganga Plain in modern times: a perspective on cultural routes by Xihui Wang, Wei Dong, Yicun Pang, Hang Yin

“…Second, the spatial‒statistical data translation (S-SDT) method is adopted to construct a gravity model on the basis of a quality evaluation system for historical towns, and the social network analysis (SNA) method is used to analyse the structure of city networks in different historical periods at both the overall and subnet levels. …”
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Minimum PV curtailment for distribution networks based on moment difference analysis theory by Yi Wang, Junyong Wu

“…This theory transforms the integration challenge of DPV into a problem of balancing the moment difference (MD) equations for power restoration and maintenance. …”
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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

“…The aim of this study is to uncover the genotype and the underlying characteristics of different spatial layouts by using the space syntax method. …”
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Global Dynamics of a Rational Difference Equation and Its Solutions to Several Conjectures by Shaoxia Jin, Xianyi Li, Bo Sun

“…Ladas and colleagues. The methods involve transforming the higher-order equation into a first-order difference equation and analyzing the properties of the resulting function, particularly its Schwarzian derivative. …”
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PECULIARITIES OF FORMING TOTAL REVENUES OF UNITED TERRITORIAL COMMUNITIES IN UKRAINE UNDER CURRENT CONDITIONS OF TRANSFORMING THE SYSTEM OF PUBLIC FINANCES by V. Melnyk, N. Kriuchkova, R. Shchur

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GCT-GF: A generative CNN-transformer for multi-modal multi-temporal gap-filling of surface water probability by Yanjiao Song, Linyi Li, Yun Chen, Junjie Li, Zhe Wang, Zhen Zhang, Xi Wang, Wen Zhang, Lingkui Meng

“…However, discontinuous pixel values inherent to conventional water maps hinder the application of deep learning methods, which are effective and popular for relevant studies. …”
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Addressing Sensor Data Heterogeneity and Sample Imbalance: A Transformer-Based Approach for Battery Degradation Prediction in Electric Vehicles by Bi Wu, Shi Qiu, Wenhe Liu

“…This study presents a novel approach based on Transformer architecture to specifically address these issues. …”
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An Integrated Fault Identification Approach for Rolling Bearings Based on Dual-Tree Complex Wavelet Packet Transform and Generalized Composite Multiscale Amplitude-Aware Permutatio... by Wuqiang Liu, Xiaoqiang Yang, Shen Jinxing

“…Besides, this solution can judge the different faults more accurately compared with other ordinary methods.…”
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CBCT-to-CT synthesis using a hybrid U-Net diffusion model based on transformers and information bottleneck theory by Can Hu, Ning Cao, Xiuhan Li, Yang He, Han Zhou

“…In this study, we propose a hybrid U-Net diffusion model (HUDiff) based on Vision Transformer (ViT) and the information bottleneck theory to improve CBCT image quality. …”
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MugenNet: A Novel Combined Convolution Neural Network and Transformer Network with Application in Colonic Polyp Image Segmentation by Chen Peng, Zhiqin Qian, Kunyu Wang, Lanzhu Zhang, Qi Luo, Zhuming Bi, Wenjun Zhang

“…Transformer is another method that can be adapted to the automatic segmentation method by employing a self-attention mechanism, which essentially assigns different importance weights to each piece of information, thus achieving high computational efficiency during segmentation. …”
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ViViT-Prob: A Radar Echo Extrapolation Model Based on Video Vision Transformer and Spatiotemporal Sparse Attention by Yunan Qiu, Bingjian Lu, Wenrui Xiong, Zhenyu Lu, Le Sun, Yingjie Cui

“…To address the limitations of existing deep learning methods in radar echo extrapolation, this paper proposes a radar echo extrapolation model based on video vision transformer and spatiotemporal sparse attention (ViViT-Prob). …”
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Some growth factors in neoplastic tissues of brain tumors of different histological structure by O. I. Kit, E. M. Frantsiyants, E. E. Rostorguev, I. V. Balyazin-Parfenov, N. D. Cheryarina, L. S. Kozlova, Yu. A. Pogorelova

“…Vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF), transforming growth factor alpha and beta (which are also known as “triggers” of angiogenesis), and other factors (Gacche, Meshram, 2013; Nijaguna et al., 2015) play a special role in its development. …”
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Applying auxiliary supervised depth-assisted transformer and cross modal attention fusion in monocular 3D object detection by Zhijian Wang, Jie Liu, Yixiao Sun, Xiang Zhou, Boyan Sun, Dehong Kong, Jay Xu, Xiaoping Yue, Wenyu Zhang

“…Furthermore, Depth-DETR employs cross modal attention mechanisms to effectively fuse three different features. A parallel structure of two cross modal transformer is applied to fuse two depth features with visual features. …”
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HSD²Former: Hybrid-Scale Dual-Domain Transformer with Crisscrossed Interaction for Hyperspectral Image Classification by Binxin Luo, Meihui Li, Yuxing Wei, Haorui Zuo, Jianlin Zhang, Dongxu Liu

“…However, Transformer-based methods still encounter two main challenges. …”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…Recently, with the rise of AI, many data-driven methods are proposed. However, most of them take no consideration of natural physical laws that may cause issues of physical inconsistency among different variables. …”
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Ischemic cerebral infarction with hemorrhagic transformation: peculiarities of perifocal tissue changes depending on the disease phase and background and concomitant pathology by Y.O. Pospishil, R.I. Falion, O.R. Malyk, Y.I. Beketova, R.S. Pshyk, I.S. Dronyk

“…Background. Hemorrhagic transformation of brain tissue with necrosis is a common complication of ischemic stroke. …”
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Advancements in regulatory agility, regional collaboration, and digital transformation: insights from the Asia Partnership Conference of Pharmaceutical Associations (APAC) by Sannie Siaw Foong Chong, Stephanie Hui Min Ong, Siew Mei Long, Masaaki Kanno, Usanee Harnpramukkul, Kum Cheun Wong, Asawari Sathaye, Mamta Singh, Manish Paliwal, Huyen Do, Helene Sou, Richard Simon R. Binos

“…Abstract Purpose The Asia Partnership Conference of Pharmaceutical Associations (APAC) examines recent developments in regulatory practices across Asia, focusing on regulatory agility, regional collaboration, and digital transformation. The paper identifies key improvements made by national regulatory authorities (NRAs) in adopting regulatory agilities over a two-year span. …”
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Improved Agrobacterium-mediated transformation protocol for VgDGAT1a gene based on shoot tip culture of cotton by WANG Anke, HE Qiuling, PAN Jingjing, SUN Yingchao, ZHU Shuijin, CHEN Jinhong

“…In addition, reduplicated selections improved accuracy.In conclusion, this study describes an optimized transformation protocol for shoot tip of ‘Zhongmiansuo 49’with an A. tumefaciens strain EHA105 harboring DGAT1 gene, and proves that it is an efficient and economical method to obtain transgenic plants based on the results of different and important parameters influencing the transformation efficiency.…”
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