GLIHamba: global–local context image harmonization based on Mamba by Jinsheng SUN, Jiao PAN, Yu GUO, Chao YAO

“…In recent years, harmonization methods based on deep learning have achieved significant progress. …”
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In-Season Mapping of Sugarcane Planting Based on Sentinel-2 Imagery by Hui Li, Liping Di, Chen Zhang, Li Lin, Liying Guo, Ruopu Li, Haoteng Zhao

“…Moreover, the LCR-OCSVM method was confirmed to have superior transfer learning capability for sugarcane classification across different regions and periods compared to the Harmonic-OCSVM method.…”
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Predicting brain amyloid load with digital and blood-based biomarkers by Weineng Chen, Yu Liao, Xinchong Shi, Fengjuan Su, Haifan Kong, Yingying Fang, Yifan Zheng, Jiayi Zhou, Ganqiang Liu, Xianbo Zhou, Xiaoli Yao, Curtis B. Ashford, Feng Li, Long Yang, Michael F. Bergeron, J. Wesson Ashford, Xiangsong Zhang, Zhong Pei

“…Abstract Background With the recent approval of anti-β-amyloid (Aβ) treatment for Alzheimer’s disease (AD), a demand has emerged for scalable, convenient and accurate estimations of brain Aβ burden for the detection of AD that would enable timely, accurate and reliable diagnosis in one’s primary care physician’s (PCPs) office as called for recently by World Health Organization (WHO). Methods MemTrax, a 2-minute online memory test, was selected as the digital biomarker of cognitive impairment, and blood-based biomarkers (BBMs) including Aβ42, Aβ40, P-tau181, GFAP and NfL were used to estimate AD-related metrics in different groups of elderly individuals (n = 349) for comparison with Aβ PET scans of brain Aβ burden. …”
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A Rice-Mapping Method with Integrated Automatic Generation of Training Samples and Random Forest Classification Using Google Earth Engine by Yuqing Fan, Debao Yuan, Liuya Zhang, Maochen Zhao, Renxu Yang

“…The proposed LR method initially generated rice distribution maps based on phenology, and 300 sample points were selected for meta-identification of rice images via an enhanced pixel-based phenological feature composite method (Eppf-CM) utilizing high-resolution imagery. …”
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Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning by Chao Lin, Yue Wan, Yong Xu, Qingsong Zou, Xiaoxiao Li

“…High-dimensional weighted gene co-expression network analysis (hdWGCNA) identified 352 module genes linked to OA-macrophages. Machine learning developed a four-gene-based OAMGS score that accurately identifies OA-macrophages, with an AUC of 1 in the discovery cohort and 0.990 in an external cohort. …”
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Emerging techniques for the trace elemental analysis of plants and food-based extracts: A comprehensive review by Hemant Rawat, Shahnawaz Ahmad Bhat, Daljeet Singh Dhanjal, Rajesh Singh, Yashika Gandhi, Sujeet K. Mishra, Vijay Kumar, Santosh K. Shakya, Ch Venkata Narasimhaji, Arjun Singh, Ravindra Singh, Rabinarayan Acharya

“…According to the WHO, herbal plants and medicine from varied soil compositions serve as crucial therapeutic agents for 70–80 % of the world's population. …”
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Relational Knowledge Prediction via Dynamic Bi-Mode Embedding by Yang Fang, Xiang Zhao, Zhen Tan, Weidong Xiao

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Double-diffusive magnetoconvection in a tilted porous parallelogrammic domain with discrete heated-cooled segments: Leveraging machine learning and CFD approach by P. Ravindra, M. Sankar, Suresh Rasappan, Wardah Abdullah Al Majrafi, Pugalarasu Rajan, S. Sanal Kumar

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Identification of key factors for malnutrition diagnosis in chronic gastrointestinal diseases using machine learning underscores the importance of GLIM criteria as well as addition... by Karen Rischmüller, Vanessa Caton, Markus Wolfien, Markus Wolfien, Markus Wolfien, Luise Ehlers, Matti van Welzen, David Brauer, Lea F. Sautter, Fatuma Meyer, Luzia Valentini, Mats L. Wiese, Ali A. Aghdassi, Robert Jaster, Olaf Wolkenhauer, Olaf Wolkenhauer, Georg Lamprecht, Saptarshi Bej, Saptarshi Bej

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Development and Validation of a Machine Learning Prediction Model for Textbook Outcome in Liver Surgery: Results From a Multicenter, International Cohort by Jane Wang, MD, Amir Ashraf Ganjouei, MD, MPH, Taizo Hibi, MD, PhD, Nuria Lluis, MD, PhD, Camilla Gomes, MD, Fernanda Romero-Hernandez, MD, Han Yin, BA, Lucia Calthorpe, MD, Yukiyasu Okamura, MD, PhD, Yuta Abe, MD, PhD, Shogo Tanaka, MD, PhD, Minoru Tanabe, MD, PhD, Zeniche Morise, MD, PhD, Horacio Asbun, MD, PhD, David Geller, MD, Mohammed Abu Hilal, MD, PhD, Mohamed Adam, MD, Adnan Alseidi, MD, EdM, International Hepatectomy Study Group, Alison Baskin, Annie Wong-On-Wing, Annie Yang, Devesh Sharma, Taisuke Imamura, Masanori Nakamura, Yuya Miura, Koki Hayashi, Masatsugu Ishii, Keita Shimata, Kazuya Hirukawa, Hiroki Ueda, June S. Peng, Lucas Thornblade, Kenzo Hirose, Kimberly Kirkwood, Eric Nakakura, Carlos Corvera, Ajay Maker

“…Recently, an expert panel of surgeons proposed a Delphi consensus-based definition of TOLS. Methods:. Adult patients who underwent hepatectomies were identified from a multicenter, international cohort (2010–2022). …”
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Lithology Identification of Buried Hill Reservoirs Based on Support Vector Machine by GAO Yongde, WU Jinbo, SUN Dianqiang

“…As an unconventional reservoir, the potential mountain bedrock reservoir presents significant challenges for lithology identification compared to traditional clastic reservoirs due to its complex bedrock structure, tectonic features, chemical composition and mineralogy. Conventional logging data and traditional evaluation methods are limited in their effectiveness for identifying lithology in such reservoirs, making it difficult to distinguish between different lithology types. …”
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Growth Stages Discrimination of Multi-Cultivar Navel Oranges Using the Fusion of Near-Infrared Hyperspectral Imaging and Machine Vision with Deep Learning by Chunyan Zhao, Zhong Ren, Yue Li, Jia Zhang, Weinan Shi

“…To validate the availability of the proposed method, various machine-learning and deep-learning models are compared for single-modal and multi-modal data. …”
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Development and Evaluation of Machine Learning Models for Air-to-Land Temperature Conversion Using the Newly Established Kunlun Mountain Gradient Observation System by Yongkang Li, Qing He, Yongqiang Liu, Amina Maituerdi, Yang Yan, Jiao Tan

“…Additionally, this study analyzed the spatiotemporal distribution characteristics of cloud cover in the Kunlun Mountain region using the MOD11A1 product and assessed the uncertainties introduced by the 8-day average compositing method of the MOD11A2 product. The results revealed significant discrepancies between the monthly average LST derived from polar-orbiting satellites and the hourly composite monthly LST measured on-site or under ideal cloud-free conditions. …”
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Exploring the Influence of Pottery Jar Formula Variables on Flavor Substances Through Feature Ranking and Machine Learning: Case Study of Maotai-Flavored Baijiu by Haili Yang, Xinjun Hu, Jianpin Tian, Liangliang Xie, Manjiao Chen, Dan Huang

“…It was found that changes in the content of Fe and Zn metals, as well as pore parameters in the jars, significantly affected the content of AL, Mg, K, Na, and Ca ions in Baijiu. Based on three feature ranking methods and three machine learning models, a feature selection method related to flavor substances was established, identifying the key features (i.e., key metal ions) for each flavor group. …”
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AI-Driven predicting and optimizing lignocellulosic sisal fiber-reinforced lightweight foamed concrete: A machine learning and metaheuristic approach for sustainable construction by Mohamed Sahraoui, Aissa Laouissi, Yacine Karmi, Abderazek Hammoudi, Mostefa Hani, Yazid Chetbani, Ahmed Belaadi, Ibrahim M.H. Alshaikh, Djamel Ghernaout

“…The optimized composition achieved a tensile strength of 4.16 MPa, representing a 9.5 % enhancement compared to conventional experimental methods, which yielded 3.8 MPa. …”
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Integrating Drone-Based LiDAR and Multispectral Data for Tree Monitoring by Beatrice Savinelli, Giulia Tagliabue, Luigi Vignali, Roberto Garzonio, Rodolfo Gentili, Cinzia Panigada, Micol Rossini

“…Forests are critical for providing ecosystem services and contributing to human well-being, but their health and extent are threatened by climate change, requiring effective monitoring systems. Traditional field-based methods are often labour-intensive, costly, and logistically challenging, limiting their use for large-scale applications. …”
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Machine learning-assisted analysis of serum metabolomics and network pharmacology reveals the effective compound from herbal formula against alcoholic liver injury by Jiamu Ma, Peng Wei, Xiao Xu, Ruijuan Dong, Xixi Deng, Feng Zhang, Mengyu Sun, Mingxia Li, Wei Liu, Jianling Yao, Yu Cao, Letian Ying, Yuqing Yang, Yongqi Yang, Xiaopeng Wu, Gaimei She

“…Nevertheless, the effective compound is challenging to identify due to its intricate composition and multiple targets. Methods An integration machine learning-assisted approach was established, whereby the particular action mechanism and direct target were obtained through the correlation of compounds, targets, and metabolites. …”
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When from Technology Comes Beauty: A Glass-Gem Case Study to Promote Inclusive and High-Quality Learning Paths in Heritage Science by Daniela Di Martino, Maya Musa, Elisabetta Gagetti, Quentin Lemasson, Giulia Marcucci, Marta Novello, Annalisa De Franzoni, Giacomo Zatti, Francesca Sgarbi, Claudia Rabaioli, Laura Cristina, Martina Veneriano, Monica Zanon, Maria Pia Riccardi

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Evaluation of a novel simulation-based training for urgent laryngectomy care by Freya Sparks, Nicky Gilbody, Katerina Hilari

“…Conclusions Simulation-based training is a feasible method of clinical skill acquisition for urgent laryngectomy care. …”
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Advances in intelligent design of single crystal superalloys and protective coatings by XING Yifeng, YIN Aobo, GENG Lilun, YANG Fan, RU Yi, ZHAO Wenyue, PEI Yanling, LI Shusuo, GONG Shengkai

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