The Technical Development of a Prototype Lower-Limb Therapy Device for Bed-Resting Users by Juan Fang, Adrien Cerrito, Simón Gamero Schertenleib, Patrick von Raumer, Kai-Uwe Schmitt

“…Using automatic position and force control algorithms, the device produced leg flexion/extension with synchronised ankle plantarflexion/dorsiflexion as well as leg pressing with adjustable resistive loading. …”
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Detection Technology for Catenary Stagger Value Based on Acceleration Signals by CHEN Hongming, ZHOU Ning, LU Wenwei, YANG Zixian, CHENG Yao, WANG Dong, ZHANG Weihua

“…［Result & Conclusion］ The proposed method accurately detects catenary stagger values across various operating speeds, achieving a root mean square error as low as 5.84, outperforming other existing algorithms. …”
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Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes by ZHANG Zihang, XING Bo, MA Zhongqing, HU Yanjun, ZHANG Zhixiao, YUAN Shizhen, LU Rufei, CHEN Yingquan, WANG Shurong*

“…Subsequently, the random forest (RF), gradient boosting decision tree (GBDT), and extreme gradient boosting (XGBoost) algorithms were utilized to predict the high heating value (HHV) of organic solid waste, the distribution of fast pyrolysis products, and the thermogravimetric curves under various atmospheres. …”
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Research on Reservoir Identification of Gas Hydrates with Well Logging Data Based on Machine Learning in Marine Areas: A Case Study from IODP Expedition 311 by Xudong Hu, Wangfeng Leng, Kun Xiao, Guo Song, Yiming Wei, Changchun Zou

“…Among them, RF has the highest accuracy, precision, recall, and harmonic mean of precision and recall (F1 score), all of which are above 0.90. …”
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LIMITATIONS ON PRIMARY PERCUTANEOUS CORONARY INTERVENTION FOR ST-SEGMENT ELEVATION ACUTE MYOCARDIAL INFARCTION IN THE CLINICAL PRACTICE by V. V. Kashtalap, A. M. Kochergina, S. A. Makarov, V. Yu. Kheraskov, O. L. Barbarash

“…Therefore, the development of algorithms is particularly important as they can reduce the time delay in the pre-hospital period, as well as active patient selection for coronary angiography during the in-hospital period.…”
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Fused Multi-Domains and Adaptive Variational Mode Decomposition ECG Feature Extraction for Lightweight Bio-Inspired Key Generation and Encryption by Israel Edem Agbehadji, Richard C. Millham, Emmanuel Freeman, Wanqing Wu, Xianbin Zhang

“…In this research, fusing multiple domains ECG feature and adaptive Variational Mode Decomposition approaches are utilized to mitigate the challenge of losing the intra-leading correlations of mode decompositions, which might reduce the robustness of encryption algorithms. The features extracted using the reconstructed signal have a mean (0.0004), standard deviation (0.0391), skewness (0.1562), and kurtosis (1.2205). …”
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Intelligent Photolithography Corrections Using Dimensionality Reductions by Parag Parashar, Chandni Akbar, Tejender S. Rawat, Sparsh Pratik, Rajat Butola, Shih H. Chen, Yung-Sung Chang, Sirapop Nuannimnoi, Albert S. Lin

“…In this work, we use dimensionality reduction (DR) algorithms to reduce the computation time of complex OPC/EPC problems while the prediction accuracy is maintained. …”
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Evaluation and prediction of the physical properties and quality of Jatobá-do-Cerrado seeds processed and stored in different conditions using machine learning models by Daniel Fernando Figueiredo Spengler, Paulo Carteri Coradi, Dágila Melo Rodrigues, Izabela Cristina de Oliveira, Dalmo Paim de Oliveira, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro

“…The combination of processing, temperature, and packaging variables for Artificial Neural Networks, RepTree, Random Forest, and M5P algorithms outperformed linear regression, providing higher accuracy rates. …”
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Evaluation of machine learning methods for forecasting turbidity in river networks using Sentinel-2 remote sensing data by Victor Oliveira Santos, Paulo Alexandre Costa Rocha, Jesse Van Griensven Thé, Bahram Gharabaghi

“…Results show that considering the individual monitoring stations, the ML algorithms for turbidity modeling were satisfactory at locations with a larger range and standard deviation of turbidity values, achieving a mean R2 value of 59.5 %. …”
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Subtypes of tic disorders in children and adolescents: based on clinical characteristics by Kai Yang, Wenyan Zhang, Ying Li, Xianbin Wang, Zhongliang Jiang, Shujin Hu, JinHyun Jun, Qinghao Yang, Jingyi Li, Xu Hong, Yonghua Cui, Tianyuan Lei

“…Methods We assessed 139 children and adolescents aged 6–18 years using 14 scales covering 43 dimensions. The k-means clustering algorithm was used to identify distinct TD subtypes. …”
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Remote Sensing of Particle Absorption Coefficient of Pigments Using a Two-Stage Framework Integrating Optical Classification and Machine Learning by Xietian Xia, Shaohua Lei, Hui Lu, Zenghui Xu, Xiang Li, Xing Chen, Niancheng Hong, Jie Xu, Kun Shi, Jiacong Huang

“…This new scientific approach and powerful tool provide a means for monitoring and interpreting the pigment particle absorption characteristics in water bodies using remote sensing technology.…”
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Reinforcement learning energy management control strategy of electric tractor based on condition identification by Liqiao Li, Jiangchun Chen, Jing Nie, Zongyu Gao

“…lithium-titanate battery(LTB) and supercapacitor(SC) hybrid power drive electric tractors (ET) are one of the necessary means to achieve truly green agriculture. However, low traction efficiency, short battery life, and high energy consumption are the main reasons hindering the industrialization of ET. …”
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Research on Concrete Crack and Depression Detection Method Based on Multi-Level Defect Fusion Segmentation Network by Zhaochen Yao, Yanjuan Li, Hao Fu, Jun Tian, Yang Zhou, Chee-Loong Chin, Chau-Khun Ma

“…Cracks and dents in concrete structures are core defects that threaten building safety, but the existing YOLO series algorithms face a huge bottleneck in complex engineering scenarios. …”
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The colours of the ocean: using multispectral satellite imagery to estimate sea surface temperature and salinity on global coastal areas, the Gulf of Mexico and the UK by Solomon White, Tiago Silva, Laurent O. Amoudry, Evangelos Spyrakos, Adrien Martin, Adrien Martin, Encarni Medina-Lopez

“…This study presents a methodology for extracting SST and SSS using machine learning algorithms trained with in-situ and multispectral satellite data. …”
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Accurate and rapid single nucleotide variation detection in PCSK9 gene using nanopore sequencing by Ilaria Massaiu, Vincenza Valerio, Valentina Rusconi, Valentina Rusconi, Francesca Bertolini, Donato De Giorgi, Veronika A. Myasoedova, Paolo Poggio, Paolo Poggio

“…Twelve subjects were analyzed using different sequencing flow cells, basecalling models, and SNV calling algorithms. Sanger sequencing served as the reference for performance validation. …”
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Adult Hope Scale: validation in older adults by Kate Labrosciano, Jillian Dorrian, Braam Lowies, Roslyn Russell, Kurt Lushington

“…Dimensionality was tested by (i) bifactor modelling (one-factor, two-factor and a bifactor model with a general factor, Hope, and two specific factors, Agency and Pathways) and (ii) exploratory graph analysis (which uses community detection algorithms to cluster variables into factors). Cross-gender invariance was also tested. …”
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Data-driven fault detection and positioning of eccentric rolls in roll-to-roll systems using wrap angle and sensor proximity by Yoonjae Lee, Minjae Kim, Jaehyun Noh, Gyoujin Cho, Changwoo Lee

“…Classification algorithms were used to compare the performance of models employing these optimized FCM-based features against traditional models utilizing a full suite of 40 statistical features. …”
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Artificial intelligence survival models for identifying relevant risk factors for incident diabetes in Azar cohort population by Neda Gilani, Mohammadhossein Somi, Farzaneh Hamidi, Pasqualina Santaguida, Elnaz Faramarzi, Reza Arabi Belaghi

“…Conclusion: RF machine learning algorithms and LASSO-Cox regression analyses consistently identified WC, hypertension, and MCHC as the main risk factors for developing diabetes. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…However, satellite-derived AOD datasets frequently suffer from missing values due to factors such as cloud cover, algorithmic limitations, and various atmospheric conditions. …”
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Improving ecosystem respiration estimates for CO2 flux partitioning by discriminating water and temperature controls on above- and below-ground sources by Shuai Wang, Shujing Qin, Lei Cheng, Kaijie Zou, Chenhao Fu, Pan Liu, Lu Zhang

“…Our findings highlight the critical need for partitioning ER models into dual-source for developing CO2 flux partitioning algorithms and support the approach as an effective means to enhance the understanding of global carbon cycles with changing climate.…”
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