Investigation of the impact of token embeddings in Transformer-based models on short-term tropical cyclone track and intensity predictions by Yuan-Jiang Zeng, Yi-Qing Ni, Zheng-Wei Chen, Guang-Zhi Zeng, Jia-Yao Wang, Pak-Wai Chan

“…Comparative analysis with four recurrent neural network (RNN) models demonstrates the superiority of the refined Transformer models over RNNs: iTransformer reduces mean absolute error (MAE) and root mean square error (RMSE) by 29.55% and 25.80% (latitude), 50.31% and 46.18% (longitude), 8.71% and 9.98% (pressure), and 8.68% and 9.45% (wind speed), while TVFormer achieves MAE and RMSE reductions of 13.98% and 13.84% (latitude), 39.11% and 38.02% (longitude), 13.69% and 14.02% (pressure), and 12.84% and 12.94% (wind speed) on average. …”
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A random-forest-derived 35-year snow phenology record reveals climate trends in the Yukon River Basin by C. G. Pan, K. Lasko, S. P. Griffin, J. S. Kimball, J. Du, T. G. Meehan, P. B. Kirchner

“…Model evaluation against station observations yielded a mean absolute error (MAE) of 10.5 d and a root mean square error (RMSE) of 13.7 d for snowmelt onset. …”
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Mathematical Modelling and Optimization Methods in Geomechanically Informed Blast Design: A Systematic Literature Review by Fabian Leon, Luis Rojas, Alvaro Peña, Paola Moraga, Pedro Robles, Blanca Gana, Jose García

“…Conclusions: Persisting challenges in scalable uncertainty quantification, coupled discrete–continuous fracture solvers, and rigorous fusion of physics-informed and data-driven models position blast design as a fertile test bed for advances in applied mathematics, numerical analysis, and machine-learning theory.…”
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Iterative refinement and goal articulation to optimize large language models for clinical information extraction by David Hein, Alana Christie, Michael Holcomb, Bingqing Xie, AJ Jain, Joseph Vento, Neil Rakheja, Ameer Hamza Shakur, Scott Christley, Lindsay G. Cowell, James Brugarolas, Andrew R. Jamieson, Payal Kapur

“…Our innovation combines flexible prompt templates, the direct production of analysis-ready tabular data, and a rigorous, human-in-the-loop iterative refinement process guided by a comprehensive error ontology. …”
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Predicting depression and unravelling its heterogeneous influences in middle-aged and older people populations: a machine learning approach by Ling Zhang, Ruigang Wei, Jingwen Zhou, Lin Tan, Xiaolong Che, Minqinag Zhang, Xiaoyue Ning, Zhiliang Zhong

“…Existing studies primarily rely on statistical methods such as logistic regression for small-scale data analysis, while research on the application of machine learning in large-scale data remains limited. …”
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A hierarchical simulation framework incorporating full-link physical response for short-range infrared detection by Mingze Gao, Lixin Xu, Shiyuan Hu, Xiaolong Shi, Jiaming Gao, Yanjiang Wu, Huimin Chen

“…The proposed simulation framework can provide pixel-level signal output and is verified by the measured data. The evaluation results of the root mean square error (RMSE) and the Pearson correlation coefficient (PCC) show that the simulated data and the measured data achieve good consistency, and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals. …”
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Decentralized EEG-based detection of major depressive disorder via transformer architectures and split learning by Muhammad Umair, Jawad Ahmad, Nada Alasbali, Oumaima Saidani, Muhammad Hanif, Aizaz Ahmad Khattak, Muhammad Shahbaz Khan

“…Traditional approaches to diagnosing MDD often rely on manual Electroencephalography (EEG) analysis to identify potential disorders. However, the inherent complexity of EEG signals along with the human error in interpreting these readings requires the need for more reliable, automated methods of detection.MethodsThis study utilizes EEG signals to classify MDD and healthy individuals through a combination of machine learning, deep learning, and split learning approaches. …”
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A Robust Digital Elevation Model-Based Registration Method for Mini-RF/Mini-SAR Images by Zihan Xu, Fei Zhao, Pingping Lu, Yao Gao, Tingyu Meng, Yanan Dang, Mofei Li, Robert Wang

“…SAR data from the lunar spaceborne Reconnaissance Orbiter’s (LRO) Mini-RF and Chandrayaan-1’s Mini-SAR provide valuable insights into the properties of the lunar surface. …”
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Benchmarking farm-level cotton water productivity using on-farm irrigation measurements and remotely sensed yields by Zitian Gao, Danlu Guo, Dongryeol Ryu, Andrew W. Western

“…We also examined: 1) if the yield model is transferable to unseen years and 2) if sub-field-scale yield data from a harvester over a small number of fields are effective for training ML models, in case field-scale yield data are insufficient. …”
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The structure and predictive value of intrinsic capacity in a longitudinal study of ageing by John R Beard, A T Jotheeswaran, Matteo Cesari, Islene Araujo de Carvalho

“…Objectives To assess the validity of the WHO concept of intrinsic capacity in a longitudinal study of ageing; to identify whether this overall measure disaggregated into biologically plausible and clinically useful subdomains; and to assess whether total capacity predicted subsequent care dependence.Design Structural equation modelling of biomarkers and self-reported measures in the English Longitudinal Study of Ageing including exploratory factor analysis, exploratory bi-factor analysis and confirmatory factor analysis. …”
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Psychometric testing of the Persian version of the nurse caring behavior scale by Mojtaba Jafari, Reza Ghanei Gheshlagh, Abbas Ebadi, Asra Nassehi, Alessandro Sili, Michela Piredda

“…Cronbach’s alpha and McDonald’s omega coefficients were used to evaluate internal consistency. Data analysis was performed using Mplus version 8.1.8 and Jamovi version 2.4.14. …”
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Rare Earth Element Contents and Occurrence Forms in Weathering Crust Ion Adsorption Rare Earth Ore by Xilian XIAO, Min GUO, Xin SHAO, Juanjuan TAN, Lei WANG, Xiaofei QIU

“…The RD of ∑REEs determination values was between 0.62% to 21.00%, and the relative error (RE) was less than 40%. In contrast, the BCR method has a simpler pre-processing flow, but the partitioned forms are not as intuitive and specific as the Tessier method, which cannot be used to obtain more detailed data on each form. …”
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A nomogram for predicting early bacterial infection after liver transplantation: a retrospective study by Jie Yu, Jie Yu, Jichang Jiang, Jichang Jiang, Caili Fan, Caili Fan, Jinlong Huo, Jinlong Huo, Tingting Luo, Tingting Luo, Lijin Zhao, Lijin Zhao

“…Therefore, this study investigated the risk factors of early bacterial infections after liver transplantation and used them to establish a nomogram.MethodsWe retrospectively collected the clinical data of 232 patients who underwent liver transplantation. …”
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Automatic characterization of stride parameters in canines with a single wearable inertial sensor. by Gregory J Jenkins, Chady H Hakim, N Nora Yang, Gang Yao, Dongsheng Duan

“…<h4>Background and objective</h4>Gait analysis is valuable for studying neuromuscular and skeletal diseases. …”
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A comprehensive IoT cloud-based wind station ready for real-time measurements and artificial intelligence integration by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…Internet of Things communication via Hypertext Transfer Protocol enables efficient data transmission between the Automated Weather Station and the cloud server, which processes and stores the data for future analysis. …”
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Evaluating the slope behavior for geophysical flow prediction with advanced machine learning combinations by Kennedy C. Onyelowe, Ahmed M. Ebid, Shadi Hanandeh, Viroon Kamchoom

“…This has been successfully done through literature search, data curation and data sorting. A total of three hundred and forty-nine (349) data entries on the FOS of slopes were collected from literature and sorted to remove odd values and unlogic results, which had been used together in a previous research work. …”
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Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study by Daniel Sumsion, Elijah Davis, Marta Fernandes, Ruoqi Wei, Rebecca Milde, Jet Malou Veltink, Wan-Yee Kong, Yiwen Xiong, Samvrit Rao, Tara Westover, Lydia Petersen, Niels Turley, Arjun Singh, Stephanie Buss, Shibani Mukerji, Sahar Zafar, Sudeshna Das, Valdery Moura Junior, Manohar Ghanta, Aditya Gupta, Jennifer Kim, Katie Stone, Emmanuel Mignot, Dennis Hwang, Lynn Marie Trotti, Gari D Clifford, Umakanth Katwa, Robert Thomas, M Brandon Westover, Haoqi Sun

“…These models were also externally validated by training the data on one hospital sample and testing on the other, and an overall estimated error was calculated using a completely random sample from both hospitals. …”
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A GPR-Based Test Study on the Influencing Factors of the Dielectric Constant of Cement-Stabilized Macadam Bases by Xue Han, Shifei Cao, Hanhui He

“…The relationship between the dielectric constant of CSMB and the influencing factors such as the compaction degree, moisture content, percent residues of aggregate on the sieve of maximum particle size and curing age, and the relationship between the dielectric constant and the unconfined compressive strength were investigated based on several test data and theoretical analysis. The major findings are as follows. …”
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Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions by Wu Kerui

“…This comprehensive review analyzes principle innovations and industrial applications of non-invasive glucose monitoring technologies, employing technical evolution pathway analysis and clinical data benchmarking to evaluate seven methodological paradigms - including spectroscopy, electrochemistry, and microwave sensing - along with their translational achievements in wearable devices and healthcare systems. …”
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Blind source separation and unmanned aerial vehicle classification using CNN with hybrid cross-channel and spatial attention module by Jiangong Ni, Zhigang Zhou

“…Aiming to effectively separate mixed signals from unmanned aerial vehicles (UAVs), an improved Fast Independent Component Analysis (FastICA) algorithm is proposed. By enhancing the whitening process during the data preprocessing step, the blind source separation process becomes more stable and reliable. …”
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