Transdimensional Inference for Gravitational-wave Astronomy with Bilby by Hui Tong, Nir Guttman, Teagan A. Clarke, Paul D. Lasky, Eric Thrane, Ethan Payne, Rowina Nathan, Ben Farr, Maya Fishbach, Gregory Ashton, Valentina Di Marco

“…The tBilby package allows users to set up transdimensional inference calculations using the existing Bilby architecture with off-the-shelf nested samplers and/or Markov Chain Monte Carlo algorithms. Transdimensional models are particularly helpful when seeking to test theoretically uncertain predictions described by phenomenological models. …”
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A Self-Supervised Feature Point Detection Method for ISAR Images of Space Targets by Shengteng Jiang, Xiaoyuan Ren, Canyu Wang, Libing Jiang, Zhuang Wang

“…The experiments demonstrate that SFPD has better performance in feature point detection and feature point matching than usual algorithms.…”
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Application of a Hybrid Model for Data Analysis in Hydroponic Systems by Kuanysh Bakirov, Jamalbek Tussupov, Akhmet Tussupov, Ibraheem Shayea, Aruzhan Shoman

“…Experimental evaluation demonstrated superior predictive performance by using XGBoost, achieving an accuracy and F1-score of 97.88%, ROC-AUC of 99.99%, and computational efficiency (training completed in 2.3 s), outperforming RandomForest and GradientBoosting algorithms. …”
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A Review of Abnormal Crowd Behavior Recognition Technology Based on Computer Vision by Rongyong Zhao, Feng Hua, Bingyu Wei, Cuiling Li, Yulong Ma, Eric S. W. Wong, Fengnian Liu

“…Secondly, typical abnormal behavior datasets at home and abroad are sorted out, and the characteristics of these datasets are compared in detail from multiple perspectives such as scale, characteristics, and uses, and the performance indicators of different algorithms on the datasets are compared and analyzed. …”
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An FPGA-accelerated multi-level AI-integrated simulation framework for multi-time domain power systems with high penetration of power converters by Chen Liu, Peng Su, Hao Bai, Xizheng Guo, Alber Filbà Martínez, Jose Luis Dominguez Garcia

“…The framework structures systems hierarchically using energy transmission functions and unified energy information flow-based surrogate models with defined ports, ensuring compatibility with artificial intelligence algorithms. By integrating AI techniques, such as back propagation neural networks, the framework predicts variables with high computational complexity, improving accuracy and simulation efficiency. …”
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Distributed hybrid consensus–based square-root cubature quadrature information filter and its application to maneuvering target tracking by Jun Liu, Yu Liu, Kai Dong, Ziran Ding, You He, Qichao Li

“…The simulation results show that the proposed hybrid consensus–based square-root cubature quadrature information filter outperforms the existing algorithms at the expense of a slight increase in computational cost.…”
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The relationship between epigenetic biomarkers and the risk of diabetes and cancer: a machine learning modeling approach by Shiqi Zhang, Shiqi Zhang, Jianan Jin, Benfeng Xu, Qi Zheng, Haibo Mou

“…Nine machine learning algorithms were used to build models: AdaBoost, GBM, KNN, lightGBM, MLP, RF, SVM, XGBoost, and logistics. …”
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Matrix Metalloproteinase-9 is associated with tumor microenvironment remodeling of bladder cancer by Fang Fang, Tiange Wu, Mengxue Wang, Wenchao Li, Zonghao You, Ming Chen, Han Guan

“…Matrix Metalloproteinase-9 (MMP9) was identified as a predictive biomarker related to immune microenvironment. …”
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TPE-LCE-SHAP: A Hybrid Framework for Assessing Vehicle-Related PM2.5 Concentrations by Hamad Almujibah, Abdulrazak H. Almaliki, Caroline Mongina Matara, Adil Abdallah Mohammed Elhassan, Khalaf Alla Adam Mohamed, Mudthir Bakri, Afaq Khattak

“…This hybrid framework delivers robust predictive accuracy and actionable insights, making it a valuable tool for effective environmental management and policy making.…”
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Implications of artificial intelligence in periodontal treatment maintenance: a scoping review by Raafat Musief Sarakbi, Sudhir Rama Varma, Sudhir Rama Varma, Lovely Muthiah Annamma, Vinay Sivaswamy, Vinay Sivaswamy

“…Additionally, AI facilitated predictive analytics for disease progression and personalized treatment strategies. …”
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Numerical analysis of geometrical configuration effects on near-field shockwave propagation in CL-20 based underwater explosives by Ji-ping Chen, Jun Wang, Xian-pi Zhang, Yan-jie Zhao, Xing-xing Wu, Fang-zhou Zhu, Jun Yu

“…The numerical methodology employs an advanced compressible multiphase flow simulation framework incorporating high-order weighted essentially non-oscillatory schemes, complemented by rigorous validation procedures involving comparative analyses against benchmark experimental data and analytical predictions from gas dynamics theory. The computational framework implements algorithmic initiation modeling for detonation processes, coupled with a front-tracking methodology employing the modified ghost fluid method to resolve discontinuities at immiscible phase boundaries. …”
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Software Supporting the Visualization of Hazardous Substance Emission Zones During a Fire at an Industrial Enterprise by Yuri Matveev, Fares Abu-Abed, Olga Zhironkina, Sergey Zhironkin

“…The objective of this study is to develop algorithms for the development of a mathematical model of a hazardous zone during an explosion and fire at an enterprise. …”
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Prominent events in the development of a simultaneous multidiagnostic system with synthetic peptides by Oscar Noya, Henry Bermúdez, Diana Pachón, Belkisyolé Alarcón de Noya, Diana Ortiz-Princz, Flor Helene Pujol, Sandra Losada

“…Years of work have been required for this complex process, with the recent incorporation of new immunoinformatic predictive tools, methodologies, and cost advantages. …”
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Deep learning in microbiome analysis: a comprehensive review of neural network models by Piotr Przymus, Krzysztof Rykaczewski, Adrián Martín-Segura, Jaak Truu, Enrique Carrillo De Santa Pau, Mikhail Kolev, Mikhail Kolev, Irina Naskinova, Aleksandra Gruca, Alexia Sampri, Alexia Sampri, Marcus Frohme, Alina Nechyporenko, Alina Nechyporenko

“…These computational techniques have become essential for addressing the inherent complexity and high-dimensionality of microbiome data, which consist of different types of omics datasets. Deep learning algorithms have shown remarkable capabilities in pattern recognition, feature extraction, and predictive modeling, enabling researchers to uncover hidden relationships within microbial ecosystems. …”
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A CART-Based Model for Analyzing the Shear Behaviors of Frozen–Thawed Silty Clay and Structure Interface by Fengpan Zhu, Bo Wang, Zhiqiang Liu

“…This study employs integrated machine learning algorithms to model the shear behavior of frozen–thawed silty clay and the structure interface. …”
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Engineering Synthetic Microbial Communities: Diversity and Applications in Soil for Plant Resilience by Arneeb Tariq, Shengzhi Guo, Fozia Farhat, Xihui Shen

“…Artificial intelligence-driven models can predict complex microbial interactions, while machine learning algorithms can analyze vast datasets to identify key microbial taxa and their functions. …”
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Application of Machine Learning and Multi-Dimensional Perception in Urban Spatial Quality Evaluation: A Case Study of Shanghai Underground Pedestrian Street by Tianning Yao, Yao Xu, Liang Sun, Pan Liao, Jin Wang

“…The study proposes a comprehensive and applicable spatial quality evaluation model integrating spatial quantification methods, machine learning algorithms, and multidimensional perception measurements. …”
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Older people and the smart city – Developing inclusive practices to protect and serve a vulnerable population by Aaro Tupasela, Juanita Devis Clavijo, Marjut Salokannel, Christoph Fink

“…In this article, we report on the main challenges encountered during the implementation of the URBANAGE project, and the development of the components for big data analytics, visualisations, predictive algorithms and simulation. Using examples from three European locations – Helsinki, Flanders and Santander – we describe and discuss how we can gather personal data related to the daily lives of older people in terms of the existing privacy and data protection laws in the EU. …”
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A Numerical Laboratory for Simulation of Flanged Reinforced Concrete Shear Walls by Alireza Khaloo, Mohammad Tabiee, Hatef Abdoos

“…Drawing on ABAQUS, FlashLab employs shell elements with longitudinal and transverse reinforcements to accurately and rapidly model the cyclic behavior of flanged RC shear walls. The FlashLab algorithms are on the basis of the Python programming language and can examine flanged RC shear walls, with a general cross-section, which make it possible to parametrically investigate various variables. …”
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Graph Split Federated Learning for Distributed Large-Scale AIoT in Smart Cities by Hanyue Xu, Kah Phooi Seng, Li-Minn Ang, Wei Wang, Jeremy Smith

“…A key element of this transformation is the widespread deployment of IoT devices for data collection, which feeds into machine learning algorithms to improve city services. However, the centralization of sensitive IoT data for ML raises privacy and efficiency concerns. …”
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