Ensemble Techniques for Robust Fake News Detection: Integrating Transformers, Natural Language Processing, and Machine Learning by Mohammed Al-alshaqi, Danda B. Rawat, Chunmei Liu

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THE INFLUENCE OF PROPIONATE ON THE SPECTRUM OF LONG-CHAIN FATTY ACIDS IN CERVICAL CELLS DURING DIS- AND NEOPLASTIC TRANSFORMATION by E. V. Kayukova, T. E. Belokrinitskaya, P. P. Tereshkov

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Towards a more secure reconstruction-based anomaly detection model for power transformer differential protection by Martiya Zare Jahromi, Mohsen Khalaf, Mohsen Khalaf, Marthe Kassouf, Deepa Kundur

“…We then review and compare the effect of adversarial training on the performance of four different model architectures. To demonstrate the efficacy of our proposed approach for improved security and performance in PTDP scenarios, the IEEE PSRC D6 benchmark test system is tested in an OPAL-RT environment.ResultsSimulation results show the effectiveness of the proposed method for improved detection of cyberattacks.…”
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LCC-Net: Swin transformer-CNN hybrid for enhanced land cover classification in natural disaster monitoring by P. Shailaja, Pala Mahesh Kumar, Nalla Nikhitha, Kunta Neeraj Kumar Reddy, Enthala Mukesh Reddy, Goli Ganesh Reddy, Vadde Indu

“…Statistics reveal that accurate disaster classification from satellite data can enhance response times by up to 30 % and improve prediction accuracy by approximately 25 %. However, existing methods need more accuracy due to varying image resolutions and difficulty distinguishing between similar land cover types under different disaster conditions. …”
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Some transformations in a series of 4-amino-1,2,4-triazole-3-thion derivatives by O. A. Bihdan, V. V. Parchenko, B. V. Gutyj

“…The continuous improvement of synthesis methods enables the optimization of the process for developing and obtaining target products of chemical transformation. …”
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Application of three Transformer neural networks for short-term photovoltaic power prediction: A case study by Jiahao Wu, Yongkai Zhao, Ruihan Zhang, Xin Li, Yuxin Wu

“…The results of some configurations meet the industry-recommended metric requirements, and the overall performance of the vanilla Transformer is better than Informer and Autoformer. …”
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Brazil’s Agribusiness Economic Miracle: Exploring Food Supply Chain Transformations for Promoting Win–Win Investments by José Elenilson Cruz, Gabriel da Silva Medina, João Ricardo de Oliveira Júnior

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Integrating encryption and watermarking for enhanced information transmission security by Hadi Nazari, Mahmoud Mahlouji Bidgoli, Hossein Ghasvari

“…This watermarking process involves a clever two-step transformation. First, the color image is converted into a different color space using the Triangle Vertex Transform (TVT). …”
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FEM Simulation of FDS Response in Oil-Impregnated Paper Insulation of Current Transformers with Axial Aging Variation by Lujia Wang, Yutong Zhang, Ling Yang, Xiaoyu Hu, Sien Xu, Weimin Huang, Longzhen Wang

“…However, traditional aging models typically ignored significant aging differences between the transformer OIP head and straight sections caused by the axial temperature gradient. …”
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Scale, state and the city: Transformation of Diyarbakır, Suriçi region through the framework of spatial morphology and urban resilience by Berfin Eren, Mehmet Emin Şalgamcıoğlu

“…It evaluates how these modified layouts reflect social, cultural, and political realities, and how they differ from the originally designed houses in spatial terms. …”
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Plot-scale peanut yield estimation using a phenotyping robot and transformer-based image analysis by Zhengkun Li, Rui Xu, Nino Brown, Barry L. Tillman, Changying Li

“…In a case study of a total of 68 plots across 19 genotypes in a peanut breeding yield trial, the result presented a correlation (R2=0.47) between the yield and predicted pod count, better than the structure-from-motion (SfM) method. The yield ranking among different genotypes using image prediction achieved an average consistency of 84.8% with manual measurement. …”
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Frequency-Aware Diffusion Model for Multi-Modal MRI Image Synthesis by Mingfeng Jiang, Peihang Jia, Xin Huang, Zihan Yuan, Dongsheng Ruan, Feng Liu, Ling Xia

“…Multi-modal MRI, which combines images from different modalities, enhances diagnostic accuracy by offering comprehensive tissue characterization. …”
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DepthFormer: Depth‐Enhanced Transformer Network for Semantic Segmentation of the Martian Surface From Rover Images by Yuan Ma, Zhaojin Li, Bo Wu, Ran Duan

“…Advanced deep learning techniques, particularly Transformers, can enhance semantic segmentation and image interpretation, deepening our understanding of Martian surface features. …”
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Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data by Yihang Zhou, Ruige Kong, Zhengsen Xu, Linlin Xu, Sibo Cheng

“…Through detailed quantitative comparison analysis, we discovered that Transformer‐based Swin‐UNet and UNet generally outperform Autoencoder and ResNet, particularly due to the advanced attention mechanisms in Transformer‐based Swin‐UNet and the efficient use of skip connections in both UNet and Transformer‐based Swin‐UNet, which contribute to superior predictive accuracy and model interpretability. …”
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The power of leadership transforming nurses’ professional attitudes through the balance theory: a cross-sectional study by Siai Zhang, Chennong Liu, Cuiwei Lai, Bingyan Zhao, Chunmei Zhang, Yajun Zhang, Zhengtao Zhang, Jiajia Li, Sina Zhang, Tiane Fa

“…Aim To investigate the relationship between nurses’ professional attitudes and nursing managers’ authentic, destructive, and transformational leadership styles, based on the Balance theory. …”
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Spatial–Spectral Hierarchical Multiscale Transformer-Based Masked Autoencoder for Hyperspectral Image Classification by Haipeng Liu, Zhen Ye, Wen-Shuai Hu, Zhan Cao, Wei Li

“…Due to the excellent feature extraction capabilities, deep learning has become the mainstream method for hyperspectral image (HSI) classification. …”
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DTASUnet: a local and global dual transformer with the attention supervision U-network for brain tumor segmentation by Bo Ma, Qian Sun, Ze Ma, Baosheng Li, Qiang Cao, Yungang Wang, Gang Yu

“…First, we built a pyramid hierarchical encoder based on 3D shift local and global transformers to effectively extract the features and relationships of different tumor regions. …”
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A Real-Time Vision Transformers-Based System for Enhanced Driver Drowsiness Detection and Vehicle Safety by Anwar Jarndal, Hissam Tawfik, Ali I. Siam, Imad Alsyouf, Ali Cheaitou

“…We demonstrate that the proposed Vision Transformers-based Driver Drowsiness Detection (ViT-DDD) system surpasses existing state-of-the-art methods, particularly in challenging scenarios such as drivers wearing glasses or sunglasses, or in different lighting conditions. …”
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Remaining Useful Life Prediction for Rolling Bearings Based on TCN–Transformer Networks Using Vibration Signals by Xiaochao Jin, Yaping Ji, Shiteng Li, Kailang Lv, Jianzheng Xu, Haonan Jiang, Shengnan Fu

“…In addition, a new RUL prediction method, TCN–Transformer, is developed which can efficiently learn and integrate local and global features of vibration signals, addressing the long time series prediction problem in RUL prediction. …”
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Microbial transformation of sewage sludge to biolipid-based fuel using potential oleaginous bacteria Streptomyces sp. by Sana Akbar, Muzammil Anjum, Samia Qadeer, Rab Nawaz, Zepeng Rao, Zepeng Rao, Habib Ullah, Abdulaziz Alamri, Mohamed A. El-Tayeb

“…IntroductionThe high proportion of sludge generation worldwide has sparked interest in utilizing it for alternative purposes. Among different potential applications, using sludge as a substrate for oleaginous bacteria is a relatively novel approach. …”
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