A Novel Multi-Scale Joint Approach for Estimating Lithium-ion Battery Model Parameters and SOC Considering Hysteresis Effect and Temperature by Xinhui Zhang, Wenyuan Bai, Shuyu Xie, Jiatong Wang, Danny Sutanto, Kashem M. Muttaqi

“…Experimental validation under DST, US06, and FUDS conditions demonstrates the effectiveness of the proposed method, achieving a maximum voltage prediction error of 0.0650 and a maximum SOC estimation error of 0.0092 across the full temperature range.…”
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Lantern-Explorer: A Collision-Avoidance Autonomous Exploration Drone System Based on Laser SLAM with Optimized Hardware and Software by L. Zhu, L. Zhu, R. Zhong, R. Zhong, D. Xie, D. Xie, X. Yuan, X. Yuan

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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…This framework is underpinned by a sophisticated model integrating advanced monitoring systems with a Hybrid Simulated Annealing Genetic Algorithm (H-SAGA), further enhanced by neural network-driven real-time predictions. …”
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Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…Furthermore, AI is being utilized to develop personalized treatment plans by analyzing large datasets to predict individual responses to therapies, thus optimizing patient outcomes and reducing healthcare costs. …”
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Rural Renewable Energy Resources Assessment and Electricity Development Scenario Simulation Based on the LEAP Model by Hai Jiang, Haoshuai Jia, Yong Qiao, Wenzhi Liu, Yijun Miao, Wuhao Wen, Ruonan Li, Chang Wen

“…The energy trends under different demand growth rates were predicted through the LEAP model, revealing that in the clean coal scenario of carbon capture (WSBC-CCS), clean coal power and renewable energy will dominate by 2030. …”
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Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…The integration of artificial intelligence (AI) with nanotechnology marks a new frontier in personalised care. AI algorithms can analyse individual patient data to adjust insulin doses and predict glucose fluctuations, paving the way for more responsive, customised treatment plans. …”
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Multi-Frequency Microwave Sensing System with Frequency Selection Method for Pulverized Coal Concentration by Haoyu Tian, Feng Gao, Yuwei Meng, Xiaoyan Jia, Rongdong Yu, Zhan Wang, Zicheng Liu

“…These results indicate that the system could quantitatively predict PCC and promptly detect PCC fluctuations, highlighting its immediacy and reliability.…”
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Development of Quantitative Structure–Anti-Inflammatory Relationships of Alkaloids by Cristian Rojas, Doménica Muñoz, Ivanna Cordero, Belén Tenesaca, Davide Ballabio

“…Because they can be labelled as active or inactive compounds against the inflammatory biological response, the aim of this work was to calibrate quantitative structure-activity relationships (QSARs) using machine learning classifiers to predict anti-inflammatory activity based on the molecular structures of alkaloids. …”
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The GAN Spatiotemporal Fusion Model Based on Multiscale Convolution and Attention Mechanism for Remote Sensing Images by Youping Xie, Jun Hu, Kang He, Li Cao, Kaijun Yang, Luo Chen

“…Different attention weights are assigned based on their contributions to the final output, resulting in more accurate predicted images. MSCAM-GAN was tested on the Coleambally irrigated area and lower Gwydir catchment datasets and compared with classic spatiotemporal fusion algorithms. …”
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Global sorghum production dataset for temperate to subtropical regions at subnational scale over 2000–2020Zendo by Mohsen Davoudkhani, Nicolas Guilpart, David Makowski, Nicolas Viovy, Philippe Ciais, Ronny Lauerwald

“…The dataset can be used to develop crop models, machine learning algorithms, and statistical models for predicting sorghum yields under different climate scenarios. …”
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Artificial Neural Network Modelling of Photodegradation in Suspension of Manganese Doped Zinc Oxide Nanoparticles under Visible-Light Irradiation by Yadollah Abdollahi, Azmi Zakaria, Nor Asrina Sairi, Khamirul Amin Matori, Hamid Reza Fard Masoumi, Amir Reza Sadrolhosseini, Hossein Jahangirian

“…Moreover, the model predicted the relative importance of the variables which showed none of them was neglectable in this work.…”
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A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides by Nitin Kumar Chauhan, Krishna Singh, Amit Kumar, Ashutosh Mishra, Sachin Kumar Gupta, Shubham Mahajan, Seifedine Kadry, Jungeun Kim

“…Furthermore, two ML methods, Support Vector Machine (SVM) and Random Forest (RF) models, are trained on this reduced feature set, and their predictions are integrated using a majority voting approach for evaluating the final classification results, thereby enhancing overall accuracy and reliability. …”
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Machine learning identifies PYGM as a macrophage polarization–linked metabolic biomarker in rectal cancer prognosis by Chengyuan Xu, Chengyuan Xu, Siqi Zhang, Bin Sun, Zicheng Yu, Hailong Liu

“…Functional analyses, single-cell RNA sequencing, immunohistochemistry of clinical specimens, and in vitro cellular assays were employed to investigate the role of the MPGS hub gene, PYGM, in tumor biology and immune modulation.ResultsThe MPGS exhibited robust prognostic capability and effectively predicted responses to immunotherapy and various chemotherapeutic agents. …”
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Ferroptosis-disulfidptosis-related CHMP6 is a clinico-immune target in colorectal cancer by Yifei Zhu, Huixia Huang, Jiayu Chen, Keji Chen, Yanxi Yao, Yaxian Wang, Yuxue Li, Zhibing Qiu, Dawei Li, Ping Wei

“…Conclusions The FDRG score is a robust tool for predicting CRC prognosis, tumor microenvironment dynamics, and response to immunotherapy. …”
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Simulation of energy consumption processes at the metallurgical enterprises in the energy-saving projects implementation by Kiyko S. G., Druzhinin E. A., Prokhorov O. V., Haidabrus B. V.

“…With this software package’s help, a comparison of the permissible values and the adjusting of the predicted consumption of active power by a metallurgical enterprise for each fixed point in time are carried out. …”
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Matching of Observation Footprints in the FY-3G MWRI-RM Using BGI by Ke Chen, Bowen Cai, Wei Han, Zihao Suo

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Machine Learning G-Code Optimization by Héctor Lasluisa-Naranjo, David Rivas-Lalaleo, Joaquín Vaquero-López, Christian Cruz-Moposita

“…This research applies the K-means machine learning clustering algorithm to optimize G-code parameters such as extruder and heated bed temperature, deposition speed, and flow control. …”
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The class project of cyber-driver by P. S. Sorokoumov

“…Educational robotic platform YARP-3 allows easy modification of constructing arms and grippers encouraging students’ creativity. …”
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Global Methane Retrieval, Monitoring, and Quantification in Hotspot Regions Based on AHSI/ZY-1 Satellite by Tong Lu, Zhengqiang Li, Cheng Fan, Zhuo He, Xinran Jiang, Ying Zhang, Yuanyuan Gao, Yundong Xuan, Gerrit de Leeuw

“…The results show that the improved MF algorithm effectively suppresses noise in retrieval results over both land and ocean surfaces, enhancing algorithm robustness. …”
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