Machine Learning-Assisted Sustainable Mix Design of Waste Glass Powder Concrete with Strength–Cost–CO₂ Emissions Trade-Offs by Yuzhuo Zhang, Jiale Peng, Zi Wang, Meng Xi, Jinlong Liu, Lei Xu

“…To address this gap, this study proposes an AI-assisted framework integrating machine learning (ML) and Multi-Objective Optimization (MOO) to achieve a sustainable GPC design. …”
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Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm – a 10-year multicenter retrospective study by Yuan Liu, Songyun Zhao, Wenyi Du, Wei Shen, Ning Zhou

“…Additionally, calibration curves, decision curve analysis (DCA), and external validation were integrated to provide a comprehensive evaluation of the model’s clinical applicability and utility.ResultsAmong the four predictive models, the XGBoost algorithm demonstrated superior performance. …”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…To address the above problems, we proposed a typing evaluation method for KASP primers by integrating deep learning and traditional machine learning algorithms, called TAL-SRX. …”
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Energy Storage Regulation Method of Base Stations in 5G Integrated Distribution Network Based on Energy Sharing and Trading Coordination by Yanru WANG, Xiyang YIN, Qinghai OU, Wenjie MA, Hui LIU, Zhigang DU

“…Then, with the optimization objectives of promoting energy sharing of 5G base stations, improving operation efficiency of base stations, and participating in peak shaving and valley filling, the optimization problem of energy storage regulation of base stations in a 5G integrated distribution network is constructed, and an energy storage regulation algorithm of 5G base stations based on energy sharing and trading coordination is proposed. …”
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Parametric Architectural Design for a New City Identity: Materials, Environments and New Applications by Inès Sahtout Gaha

“… In contemporary architectural Design, we speak of a parametric structural design. A design that integrates new functionalities crossed with the spatial geometry of objects. …”
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Parametric Architectural Design for a New City Identity: Materials, Environments and New Applications by Inès Sahtout Gaha

“… In contemporary architectural Design, we speak of a parametric structural design. A design that integrates new functionalities crossed with the spatial geometry of objects. …”
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Energy-Efficient Route and Velocity Planning for Electric Vehicles: A Hierarchical Eco-Driving Framework Integrating Traffic and Road Information by Dong Xie, Jianhua Guo, Yu Jiang, Zhuoran Hou, Jintao Deng

“…Then, an energy-efficient route is efficiently planned using the proposed multi-heuristic A* algorithm. Finally, based on the route information from the upper level, along with traffic, kinematic, and road information, a convex optimization algorithm is employed to achieve accurate and efficient velocity planning. …”
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Research on Underground Track Tracking of a New Type Shaft Boring Machine by Jinyu Sun, Xinming Chen, Huazhe Jiao, Qi Wang, Diantao Zheng, Yulong Han, Ziyang Liu

“…The PID (proportional–integral–derivative control) algorithm can complete complex trajectory tracking tasks and promote the development of unmanned construction technology.…”
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Building domain lexicon oriented to behavioral features in depression by ZHOU Ruotong, ZHU Guangli, LI Shuyu, DUAN Wenjie, LI Jiawei

“…In addition, the candidate word set was acquired by calculating the similarity between the seed word set of behavioral and depression texts In addition,based on the similarity between words, the semantic graph was constructed to obtain the word set of behavioral features by label propagation algorithm. …”
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A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

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Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus erythematosus by Junjie Wang, Qingao Deng, Lu Qi

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Physics-informed modeling of splitting tensile strength of recycled aggregate concrete using advanced machine learning by Kennedy C. Onyelowe, Viroon Kamchoom, Shadi Hanandeh, S. Anandha Kumar, Rolando Fabián Zabala Vizuete, Rodney Orlando Santillán Murillo, Susana Monserrat Zurita Polo, Rolando Marcel Torres Castillo, Ahmed M. Ebid, Paul Awoyera, Krishna Prakash Arunachalam

“…By harnessing the synergies between physics-based principles and data-driven algorithms, PIM-ML not only streamlines the design process but also enhances the reliability and sustainability of concrete structures. …”
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TensorTrack: Tensor Decomposition for Video Object Tracking by Yuntao Gu, Pengfei Zhao, Lan Cheng, Yuanjun Guo, Haikuan Wang, Wenjun Ding, Yu Liu

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An Encrypted Speech Integrity Authentication Method: Focus on Fine-Grained Tampering Detection and Tampering Recovery Under High Tamper Ratios by Fujiu Xu, Jianqiang Li, Xi Xu

“…This method constructs the model based on the correlation between tampered sampling points and their surrounding sampling points and refines the scenarios of the model according to the tampering situation of the sampling points, with experimental results showing that the recovered speech exhibits improved auditory quality and intelligibility. (3) A scrambling encryption algorithm based on the Lorenz mapping is proposed as the speech encryption method. …”
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Integrative analysis of bulk and single-cell transcriptomic data reveals novel insights into lipid metabolism and prognostic factors in hepatocellular carcinoma by Feiyu Qi, Guiming Zha, Yanfang Zhang, Sihua Liu, Yuhang Yang, Wanliang Sun, Dongdong Wang, Zhong Liu, Zheng Lu, Dengyong Zhang

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A hybrid ultra-short-term photovoltaic power prediction framework integrating ant colony optimization for clustering with Bi-GRU by Xinyi Liu, Zitao Wang, Yang Wang, Shanke Liu, Lijun Yu

“…To address the challenges posed to stable power grid operation by the intermittency and volatility of photovoltaic (PV) power generation, this paper proposes an ultra-short-term hybrid PV power prediction model based on a logical framework integrating a scenario-based prediction strategy. This hybrid framework employs an improved Ant Colony Optimization algorithm fused with K-Means pre-clustering (K-MACO) to perform unsupervised learning on samples within the physical feature space of radiation patterns, humidity, and temperature dynamics, classifying weather scenarios into sunny, cloudy, and rainy types. …”
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Integrating weighted gene co-expression network analysis and machine learning to elucidate neural characteristics in a mouse model of depression by Jinli Gao, Qinglang Wang, Jie Liu, Siqian Zheng, Jiahong Liu, Zhiyong Gao, Cheng Zhu

“…IntroductionAn AI-assisted deep learning strategy was applied to analyze the neurobiological characteristics of depression in mouse models. Integration of weighted gene co-expression network analysis (WGCNA) with the random forest algorithm enabled the identification of critical genes strongly associated with depression onset, offering theoretical support and potential biomarkers for early diagnosis and precision treatment.MethodsGene expression data from depression-related mouse models were obtained from public GEO datasets (e.g., GSE102556) and normalized using Z-score transformation. …”
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Integrated analysis of single-cell and bulk transcriptomic data reveals altered cellular composition and predictive cell types in ectopic endometriosis by Meihong Chen, Meihong Chen, Liqun Wang, Yuanting Chen, Ting Wang, Guanqun Jiang, Qi Chen, Qi Chen

“…A random forest model was constructed to predict the diagnosis of endometriosis. …”
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Integrated single-cell and bulk RNA dequencing to identify and validate prognostic genes related to T Cell senescence in acute myeloid leukemia by Mengyao Sha, Jun Chen, Haifeng Hou, Huaihui Dou, Yan Zhang

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Development of a numerical method for solving optimization problems approximation of the function given approximately and its derivatives based on the variational approach by Igor Naats, Victoria Igorevna Naats, Elena Yartseva

“…A numerical method for solving optimization problems of function approximation from approximate data is developed. The construction of the corresponding computational algorithm is carried out. …”
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