Signature of pre-pregnancy microbiome in infertile women undergoing frozen embryo transfer with gestational diabetes mellitus by Wenzheng Guan, Tian Zhou, Jiao Jiao, Liwen Xiao, Zhen Wang, Siyuan Liu, Fujie Yan, Fangqing Zhao, Xiuxia Wang

“…The microbial community in the HCs group remained relatively stable throughout the pregnancy, while the microbial structure alteration occurred in the GDM group during T2. …”
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Blind Remote Sensing Image Deblurring Based on Local Maximum High-Frequency Coefficient Prior and Graph Regularization by Zhidan Cai, Ming Fang, Zhe Li, Jinyi Ming, Huimin Wang

“…This approach aims to produce a skeleton image that retains sharp edge details while eliminating harmful structures, thereby enabling accurate estimation of the fuzzy kernel. …”
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Quality prediction of semi-solid die casting of aluminum alloy in terms of machine learning by Zhiyuan Wang, Xiaogang Hu, Gan Li, Zhen Xu, Hongxing Lu, Qiang Zhu

“…In this study, a machine learning (ML) model has been developed to identify defective products through the detection of injection pressure, thereby providing a foundation for monitoring and further optimizing the manufacturing process. Among various ML algorithms, the Multilayer Perceptron (MLP) is the most effective for overall quality prediction. …”
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Computational study of fluid forces over a cylinder attached with elastic beam: A finite element-based simulations by Yasir Arif, Rashid Mahmood, Mehdi Tlija, Afraz Hussain Majeed, Kamran Usman, Ehab Seif Ghith

“…In this paper, we describe numerical algorithms that can be used to solve the coupled fluid–structure interaction with incompressible viscous fluid. …”
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Towards a greener future: The role of sustainable methodologies in metabolomics research by Chiara Spaggiari, Kgalaletso Othibeng, Fidele Tugizimana, Gabriele Rocchetti, Laura Righetti

“…By integrating innovative green methodologies across all stages of metabolomic workflows, researchers can significantly reduce environmental footprints while maintaining analytical rigor.…”
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Congestion forecast framework based on probabilistic power flow and machine learning for smart distribution grids by Alejandro Hernandez-Matheus, Kjersti Berg, Vinicius Gadelha, Mònica Aragüés-Peñalba, Eduard Bullich-Massagué, Samuel Galceran-Arellano

“…A congestion forecast framework is proposed by combining probabilistic power flows and machine learning algorithms to support DSOs in their daily decision-making. …”
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A deep neural network for tactile perception in open scenes by Huirong Fang, Qianhui Yang, Kunhong Liu, Xiangyi Huang, Yu Xie

“…Summary: Tactile perception is important for the robots to understand their working environment. While in real-world applications, robots usually must face unexpected changes in external conditions, such as the re-installation of the robot end effector or the change of the installation location. …”
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Advanced 5G Channel Estimation in mmWave MIMO Systems: Leveraging Compressive Sensing for Enhanced Performance by Zaid Albataineh, Mohammad Al Bataineh, Khaled Farouq Hayajneh, Raed Al Athamneh

“…In this paper, we propose an enhanced adaptive channel estimation technique that leverages compressive sensing (CS) principles to effectively mitigate pilot overhead while maintaining high estimation accuracy. The proposed approach combines compressive sampling matching pursuit (CoSaMP) and sparsity adaptive matching pursuit (SAMP) algorithms, augmented by a novel iterative reweighting strategy and adaptive thresholding mechanism. …”
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HammingVis: A visual analytics approach for understanding erroneous outcomes of quantum computing in hamming space by Jieyi Chen, Zhen Wen, Li Zheng, Jiaying Lu, Hui Lu, Yiwen Ren, Wei Chen

“…One highlights the overall structure of errors, while the other focuses on the impact of errors within important subspaces. …”
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Improving triage performance in emergency departments using machine learning and natural language processing: a systematic review by Bruno Matos Porto

“…Results Sixty studies covering 57 ML algorithms were included. Logistic Regression (LR) was the most used model, while eXtreme Gradient Boosting (XGBoost), decision tree-based algorithms with Gradient Boosting (GB), and Deep Neural Networks (DNNs) showed superior performance. …”
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Reinforcement Learning With Selective Exploration for Interference Management in mmWave Networks by Son Dinh-van, van-Linh Nguyen, Berna Bulut Cebecioglu, Antonino Masaracchia, Matthew D. Higgins

“…Numerical results demonstrate that selective exploration improves per-user spectral efficiency by up to 22.5% compared to scenarios without it. Additionally, our algorithms significantly outperform existing methods by 50% in terms of per-user spectral effciency and achieve 90% of the per-user spectral efficiency of the exhaustive search approach while requiring only 0.1% of its computational runtime.…”
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Refining CT image analysis: Exploring adaptive fusion in U-nets for enhanced brain tissue segmentation. by Bang-Chuan Chen, Chung-Yi Shen, Jyh-Wen Chai, Ren-Hung Hwang, Wei-Chuan Chiang, Chi-Hsiang Chou, Wei-Min Liu

“…However, Deep-Learning (DL) algorithms often generate false alarms (FA) beyond the cerebral region.…”
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A Comprehensive Survey on Machine and Deep Learning for Optical Communications by Mohammad Ali Amirabadi, S. Alireza Nezamalhosseini, Mohammad Hossein Kahaei, Lawrence R. Chen

“…Many algorithms have yet to be fully deployed in practical settings, underscoring the emerging nature of this research area. …”
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AI-powered blockchain technology in industry 4.0, a review by Mohsen Soori, Roza Dastres, Behrooz Arezoo

“…Artificial Intelligence (AI) algorithms can be employed to enhance the security of the blockchain networks in the era of industry 4.0. …”
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Building trust for traffic flow forecasting components in intelligent transportation systems via interpretable ensemble learning by Jishun Ou, Jingyuan Li, Chen Wang, Yun Wang, Qinghui Nie

“…However, most existing studies have concentrated on developing advanced algorithms or models to attain state-of-the-art forecasting accuracy. …”
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Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…Their effectiveness is limited by the attacks being controlled by the center, the limited data transmission capacity and also the viruses' ability to operate under-the-roof while using the mobile nodes which helps them move covertly. …”
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Automated Detection of Recent Mud Extrusions Using UAV Imagery and Deep Learning: A Comparative Analysis of Traditional and CNN-Based Approaches by M. Guastella, M. Guastella, A. Pisciotta, R. Martorana, A. D’Alessandro

“…Traditional algorithms rely on handcrafted features, while CNNs learn hierarchical representations directly from raw data. …”
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Discovering User Sentiment Patterns in Libraries with a Hybrid Machine Learning and Lexicon-Based Approach by Dini Nurmalasari, Dini Hidayatul Qudsi, Nessa Chairani, Heri R Yuliantoro

“…The high accuracy and effectiveness of the employed algorithms highlight the potential of this methodology for libraries. …”
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A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts. by Matheus Viana da Silva, Natália de Carvalho Santos, Julie Ouellette, Baptiste Lacoste, Cesar H Comin

“…Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for blood vessel segmentation since one or more specialists are usually required for image annotation, and creating ground truth labels for just a single image can take up to several hours. …”
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Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review by Jade Basem, Racheed Mani, Scott Sun, Kevin Gilotra, Neda Dianati-Maleki, Reza Dashti

“…In the focus of cryptogenic strokes, there is promising research elucidating likely underlying cardiac causes and thus, improved treatment options and secondary stroke prevention. While many algorithms still require a larger knowledge base or manual algorithmic training, AI/ML in neurocardiology has the potential to provide more comprehensive healthcare treatment, increase access to equitable healthcare, and improve patient outcomes. …”
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