Research on the synergistic prediction of the suitable distribution and chemical components of Panax Notoginseng under the background of climate warming by Peiyuan Li, Zhitian Zuo, Yuanzhong Wang

“…In the context of global warming, it is far from adequate to merely predict the suitability distribution of P. notoginseng under future climate, as it remains unclear whether the Highly suitable habitats in the results are also the high content areas. We used machine learning for the first time to predict the changes in chemical components under future climate scenarios and found that it was more scientific than the Biomod2 based on environmental variables. …”
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A Weighted-Transfer Domain-Adaptation Network Applied to Unmanned Aerial Vehicle Fault Diagnosis by Jian Yang, Hairong Chu, Lihong Guo, Xinhong Ge

“…The method is based on unsupervised transfer learning, which can transfer the knowledge learnt from existing datasets to solve problems in the target domain. …”
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Fundamental and Application of Co-assembly of Peptides and Proteins: Experiment and Computation by Newton A. Ihoeghian, Qing Shao

“…Integrating experimental and computational methods would provide crucial insights for understanding and designing robust functional co-assemblies with precisely controlled compositions and properties. …”
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Psychotherapist remarks’ ML classifier: insights from LLM and topic modeling application by Alexander Vanin, Vadim Bolshev, Anastasia Panfilova

“…Understanding recurring language patterns in therapist communication can enhance clinical practice, supervision, and training, yet systematic approaches to topic analysis remain limited.MethodsThe study applies BERTopic, an ML-based topic modeling technique, to unstructured dialogues from two distinct groups of therapists: classical (founders of therapeutic schools such as Carl Rogers, Fritz Perls, and Albert Ellis) and modern practitioners representing diverse psychotherapeutic approaches. …”
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Super Resolution Reconstruction of Mars Thermal Infrared Remote Sensing Images Integrating Multi-Source Data by Chenyan Lu, Cheng Su

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Nonlinear association between visceral fat metabolism score and heart failure: insights from LightGBM modeling and SHAP-Driven feature interpretation in NHANES by Ningyi Cheng, Yukun Chen, Lei Jin, Liangwan Chen

“…Conclusion METS-VF is independently and nonlinearly associated with HF prevalence, particularly in obese individuals. Machine learning enhances predictive accuracy by capturing complex interactions, while SHAP-based interpretability establishes METS-VF as a key biomarker integrating metabolic-adipose abnormalities, offering a novel target for personalized HF prevention.…”
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Quantitatively Detecting Camellia Oil Products Adulterated by Rice Bran Oil and Corn Oil Using Raman Spectroscopy: A Comparative Study Between Models Utilizing Machine Learning Alg... by Henan Liu, Sijia Ma, Ni Liang, Xin Wang

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Framework for Groove Rating in Exercise-Enhancing Music Based on a CNN–TCN Architecture with Integrated Entropy Regularization and Pooling by Jiangang Chen, Junbo Han, Pei Su, Gaoquan Zhou

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Protocol for the OPTIMSE-1 randomised clinical trial to test specialist-led identification and management of cardio-renal-metabolic-pulmonary disease in machine learning algorithm-... by Chris P Gale, Jianhua Wu, Ramesh Nadarajah, Catherine Reynolds, Chris Hayward, Ali Wahab, Mohammad Haris, Tobin Joseph, Sheena Bennett, Adam B Smith

“…The OPTIMISE-1 randomised controlled trial aims to test the effect of community-based specialist-led identification and management of cardio-renal-metabolic-pulmonary (CRMP) disease and risk factors compared with usual care on the use of therapeutic interventions over a follow-up of 6 months among high FIND-AF risk community-dwelling individuals.Methods and analysis OPTIMISE-1 is a multicentre, pragmatic, prospective, randomised, open-label, blinded-endpoint strategy trial that will recruit 138 participants aged 30 years or older, with a high FIND-AF risk score and previously enrolled in the FIND-AF pilot study (NCT05898165), to be randomised 1:1 to a specialist-led care intervention or usual care. …”
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Predicting mechanical properties of low-alloy steels using features extracted from Electron Backscatter Diffraction characterization by Yu Li, Jingxiao Zhao, Xiucheng Li, Zhao Xing, Qiqiang Duan, Xiaojun Liang, Xuemin Wang

“…Machine learning (ML) approaches have recently been increasingly employed to establish quantitative relationships between material composition, processing, microstructure, and properties. …”
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Advancements in Viral Genomics: Gated Recurrent Unit Modeling of SARS-CoV-2, SARS, MERS, and Ebola viruses by Abhishak Raj Devaraj, Victor Jose Marianthiran

“…Advanced genomic sequencing techniques and a Gated Recurrent Unit-based deep learning model were used to examine the intricate genetic makeup of these viruses. …”
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Classification of Chicken Carcass Breast Blood-Related Defects Using Hyperspectral Imaging Combined with Convolutional Neural Networks by Liukui Duan, Juanfang Bao, Hao Yang, Liuqian Gao, Xu Zhang, Shengjie Li, Huihui Wang

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Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model by Tapanee Treeratanaporn, Thongchai Phairoh

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A Fast Prediction Model of Supercritical Airfoils Based on Deep Operator Network and Variational Autoencoder Considering Physical Constraints by Mengxin Liu, Yunjia Yang, Chenyu Wu, Yufei Zhang

“…In this study, a composite model based on deep learning is proposed for flow field prediction. …”
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BiEHFFNet: A Water Body Detection Network for SAR Images Based on Bi-Encoder and Hybrid Feature Fusion by Bin Han, Xin Huang, Feng Xue

“…Finally, a composite loss function combining Dice loss and Active Contour loss is used to provide stronger boundary supervision. …”
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Artificial intelligence techniques by Ahmad Gholizadeh, Ali Shabani

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Machine vision approach for monitoring and quantifying fish school migration by Feng Lin, Jicheng Zhu, Aiju You, Lei Hua

“…Ultimately, these machine learning methods holds promising prospects for ecological applications.…”
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Subtle changes on electrocardiogram in severe patients with COVID-19 may be predictors of treatment outcome by Illya Chaikovsky, Illya Chaikovsky, Dmytro Dziuba, Olga Kryvova, Katerina Marushko, Julia Vakulenko, Kyrylo Malakhov, Оleg Loskutov, Оleg Loskutov

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A Neural Network Constitutive Model and Automatic Stiffness Evaluation for Multiscale Finite Elements by Aliki D. Mouratidou, Georgios E. Stavroulakis

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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…The primary AI approaches were machine learning, neural networks, and chatbot development. …”
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