The Application of Deep Learning for Lymph Node Segmentation: A Systematic Review by Jingguo Qu, Xinyang Han, Man-Lik Chui, Yao Pu, Simon Takadiyi Gunda, Ziman Chen, Jing Qin, Ann Dorothy King, Winnie Chiu-Wing Chu, Jing Cai, Michael Tin-Cheung Ying

“…Despite the advancements, it still confronts challenges like the shape diversity of lymph nodes, the scarcity of accurately labeled datasets, and the inadequate development of methods that are robust and generalizable across different imaging modalities. …”
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Multistep photovoltaic power forecasting based on multi-timescale fluctuation aggregation attention mechanism and contrastive learning by Liang Yuan, Xiangting Wang, Yao Sun, Xubin Liu, Zhao Yang Dong

“…Despite the superior performance of Transformer-based time series methods, their application to PV power prediction remains suboptimal. …”
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MtAD-Net: Multi-Threshold Adaptive Decision Net for Unsupervised Synthetic Aperture Radar Ship Instance Segmentation by Junfan Xue, Junjun Yin, Jian Yang

“…Therefore, exploring the use of unsupervised instance segmentation methods to convert BBox-level annotations into pixel-level GT holds great significance in the SAR field. …”
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Adoption of business intelligence in Jordanian hospitals: Examining moderating effects of support, readiness, compatibility, and user satisfaction by Mohammad Mahmoud Saleem Alzubi

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DB-Net: A Dual-Branch Hybrid Network for Stroke Lesion Segmentation on Non-Contrast CT Images by Xiao Jia, He Dong, Jiashu Xu, Yanhong Zhang, Yihua Lan

“…To address these challenges, this study proposes a two-branch hybrid network combining a convolutional neural network (CNN) with a Transformer framework. The proposed architecture features the aforementioned dual-branch encoder, as well as a spatial channel difference learning module and parallel attention module. …”
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ADVERTISEMENT AS A MEANS OF COMMUNICATION: THE CONTENT AND PECULIARITIES OF TRANSLATION by Inna M. Anataichuk, Olena V. Rutz, Viktoriya S. Sazonova

“…Therefore, after the analysis of the abovementioned methods of translating English advertising texts, we can conclude that the translator has a large variety of translation transformations. …”
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Academentia, management and satire: ‘The good, the bad and the ugly’ by Keyan G. Tomaselli

“…Research design, approach and method: The general methodology derives from both literary and business principles read through critical management studies and cultural studies. …”
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Semantic Tokenization-Based Mamba for Hyperspectral Image Classification by Ri Ming, Na Chen, Jiangtao Peng, Weiwei Sun, Zhijing Ye

“…Recently, the Mamba-based methods have shown even stronger spatial context modeling ability than Transformer for HSIC. …”
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Hierarchical Multi-Scale Decomposition and Deep Learning Ensemble Framework for Enhanced Carbon Emission Prediction by Yinuo Sun, Zhaoen Qu, Zhuodong Liu, Xiangyu Li

“…Experiments on four real-world datasets (133,225 observations) demonstrate that our CEEMDAN–CNN–Transformer framework outperforms 12 state-of-the-art methods, achieving a 13.3% reduction in root mean square error (RMSE) to 0.117, 12.7% improvement in mean absolute error (MAE) to 0.088, and 13.0% improvement in continuous ranked probability score (CRPS) to 0.060. …”
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Anesthesia depth prediction from drug infusion history using hybrid AI by Liang Wang, Yiqi Weng, Wenli Yu

“…Methods The proposed model combines multiple deep learning techniques to address different aspects of anesthesia prediction. …”
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Prior-FOVNet: A Multimodal Deep Learning Framework for Megavoltage Computed Tomography Truncation Artifact Correction and Field-of-View Extension by Long Tang, Mengxun Zheng, Peiwen Liang, Zifeng Li, Yongqi Zhu, Hua Zhang

“…Specifically, to address the intensity discrepancies between different imaging modalities, we employ a contrastive learning-based GAN, named TransNet, to transform KVCT images into synthesized MVCT (sMVCT) images. …”
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Resource state adaptive collaboration mechanism based on resource modeling and multi-agent system by Zhengzuo Li, Chengxi Piao, Dianhui Chu, Zhiying Tu, Xin Hu, Deqiong Ding

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Dagestan national clothes as an attribute of rural everyday life. 1920–1960s by Madina Magomedovna Amirkhanova

“…In national clothes, the values of the time, consonant with the era, are objectively fixed.The national costume is comprehensively considered in the context of socio-historical processes, using the principle of historicism and interdisciplinary, comparative, historical, logical, problem-chronological methods. The purpose of the research is to show the spatial and temporal processes of distribution, development of traditional clothes of Dagestan, general and special in cut, the way of wearing clothes among different nationalities, to analyze the transformation of the national costume in the specified chronological framework. …”
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Robust Prediction of Wildfire Spread in Australia by Michael Palk, Katharina Knappmann, Stefan Voss, Raka Jovanovic

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Arabic Cyberbullying Detection: A Comprehensive Review of Datasets and Methodologies by Huda Aljalaoud, Kia Dashtipour, Ahmed Y. Al-Dubai

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Investments in Renewable Energy in Rural Communes: An Analysis of Regional Disparities in Poland by Agnieszka Kozera, Aldona Standar, Joanna Stanisławska, Anna Rosa

“…Therefore, this study extends the existing literature resources with a view to bridging that gap by assessing rural communes’ investment activity in the context of the Polish energy transformation, with particular emphasis on regional differences in RES investments financed with Union funds. …”
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Linguistic-stylistic analysis of the language of leadership in the political arena and the business world by Oremire J. Ehibor, Joy Eyisi, Jonathan A. Odukoya, Charles U. Ogbulogo, C. U. C. Ugorji, Onyekachi Odo, Lily Chimuanya, Eugenia Abiodun-Eniayekan, Edith Awogu-Maduagwu, Rebecca U. Adesiyan

“…By analysing speeches through qualitative and quantitative methods, the study highlights how linguistic styles and choices vary distinctively between the two sectors, influenced by their specific contexts and communication strategies. …”
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Evaluating large language models and agents in healthcare: key challenges in clinical applications by Xiaolan Chen, Jiayang Xiang, Shanfu Lu, Yexin Liu, Mingguang He, Danli Shi

“…Second, we analyzed key medical task scenarios: closed-ended tasks, open-ended tasks, image processing tasks, and real-world multitask scenarios involving LLM agents, thereby offering guidance for further research across different medical applications. Third, we compared evaluation methods and dimensions, covering both automated metrics and human expert assessments, while addressing traditional accuracy measures alongside agent-specific dimensions, such as tool usage and reasoning capabilities. …”
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Stability of tenogenic secretomes optical density, colour, weight, TGF-b concentration and bacterial growth after 30-day storage under room or refrigerator temperature by Aziz Mukhlis, Soesilawati Pratiwi, Lestari Pudji, Suroto Heri

“…The parameters used in this study were physical (optical density (OD); weight differences (D weight) and colour changes); chemical (transforming growth factor beta (TGF-b) concentration); and biological (bacterial growth) stability. …”
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Prediction on rock strength by mineral composition from machine learning of ECS logs by Dongwen Li, Xinlong Li, Li Liu, Wenhao He, Yongxin Li, Shuowen Li, Huaizhong Shi, Gaojian Fan

“…Its training time is only one three hundredth of the latter and its prediction time is just one tenth of the later, making it highly suitable for well-logging interpretation. Although the Transformer model was less computationally efficient, it exhibited strengths in predicting subsurface strength parameters, particularly in capturing spatial variations and forecasting these parameters across different spatial locations. …”
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