Research on Remote Sensing Quantitative Inversion of Oil Spills and Emulsions Using Fusion of Optical and Thermal Characteristics by Zongchen Jiang, Jie Zhang, Yi Ma, Xingpeng Mao

“…By employing the oil–water brightness temperature difference polar coordinate thermal model, the absolute thickness of the oil-in-water emulsions was inverted with an average relative error below 12.7%. When applied to airborne and satellite remote sensing images of actual oil spill incidents, the OQIM model exhibited significant inversion potential and generalization capabilities in practical applications, offering crucial methodological support for emergency responses to marine oil spills.…”
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Study and Verification of a Physical Simulation System for Formation Pressure Testing while Drilling by Tianshou Ma, Nian Peng, Ping Chen, Chunhe Yang, Xingming Wang, Xiong Han

“…In addition, this physical simulation system has important applications to verify the interpretation model, to analyze pressure response recorded by FPTWD tools, to test the capability and design of FPTWD tools, and to calibrate the formation pressure, formation parameters, and instrument factors.…”
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A Deep Learning Approach for Extracting Cyanobacterial Blooms in Eutrophic Lakes From Satellite Imagery by Nan Wang, Zhenyu Tan, Chen Yang, Jinge Ma, Hongtao Duan

“…These results underscore MBAUNet's significant potential and broad applicability for CyanoHAB monitoring.…”
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Artificial Neural Network Modeling of NixMnxOx based Thermistor for Predicative Synthesis and Characterization by T.D. Dongale, K.G. Kharade, N.B. Mullani, G.M. Naik, R.K. Kamat

“…We measure the performance of the ANN model with regard to mean square error (MSE) and the correlation coefficient between expected output and output provided by the network. …”
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A novel fusion of Sentinel-1 and Sentinel-2 with climate data for crop phenology estimation using Machine Learning by Shahab Aldin Shojaeezadeh, Abdelrazek Elnashar, Tobias Karl David Weber

“…At national scale, predicted phenology resulted in a reasonable precision of R2 > 0.43 and a low Mean Absolute Error of 6 days, averaged over all phenological stages and crops. …”
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System Performance Optimization of Frequency-Swept Pump-Based Rectangular Brillouin Optical Filter by M. Shi, L. Yi, W. Wei, G. Pu, W. Hu

“…The experimental results show that the optimal frequency sweep pump period is always around 1/120 of the signal propagation time in the fiber for different transmission length, providing a guideline on the design of the frequency-swept pump based SBS gain filter and its applications.…”
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Attention-Module-Guided Time-Lapse Leakage Plume Imaging Driven by LeakInv-CUNet GPR Inversion Framework by Honghua Wang, Shan Wang, Fei Zhou, Yi Lei, Bin Zhang

“…With a mean absolute percentage error (MAPE) below 0.707%, structural similarity (SSIM) exceeding 0.924, and peak signal-to-noise ratio (PSNR) above 45.416, the attention-guided leakage imaging framework exhibits high efficiency and accuracy, showcasing its potential applications in early leakage warning and pipeline time-lapse monitoring.…”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…Findings offer a promising direction for a clinically applicable tool, personalized prevention strategies, and calls for prospective validation.…”
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Enhanced power sharing and voltage regulation for islanded nano-satellite DC microgrids in spinning flight scenarios by Khalil Louassaa, Josep M. Guerrero, Baseem Khan, Muhammad Zain Yousaf, Mohamed Ali Zdiri, Liu Zhang, Rajkumar Sivanraju

“…The proposed framework offers a practical solution for nano-satellite power management, directly addressing the unique constraints of space applications while maintaining system reliability and efficiency under dynamic operational conditions.…”
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DGL-STFA: Predicting lithium-ion battery health with dynamic graph learning and spatial–temporal fusion attention by Zheng Chen, Quan Qian

“…These results highlight the capability of DGL-STFA to accurately predict SOH, addressing critical challenges in advancing battery health monitoring for energy storage applications.…”
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Development of lesion and organ negative cast modelling technique for quality assurance and optimization of nuclear medicine images by Roberto Fedrigo, Robin J. N. Coope, Guillaume Chaussé, Ingrid Bloise, Claire Gowdy, François Bénard, Arman Rahmim, Carlos F. Uribe

“…Results Mean absolute error (MAE) for tumour volume between the original template and casted models is 13.8%, indicating that the method is reasonably accurate. …”
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Low Complexity Unquantized Forward Stack Decoding Algorithm for Spinal Codes in Measurement While Drilling Communication by Xiaoyang Yu, Lei Liang, Ke Jiang, Tianwei Chen

“…In simulated MWD environment, the proposed system achieved an average bit error rate (BER) of <inline-formula> <tex-math notation="LaTeX">$5.58\times 10^{-5}$ </tex-math></inline-formula>, with BER consistently below 0.1% across all intervals. …”
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A preliminary attempt to harmonize using physics-constrained deep neural networks for multisite and multiscanner MRI datasets (PhyCHarm) by Gawon Lee, Dong Hye Ye, Se-Hong Oh

“…As an initial step toward developing advanced harmonization techniques, we investigated the applicability of physics-based constraints within a supervised training strategy. …”
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Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT by Emanuele Trucco, Joanna M Wardlaw, Wenwen Li, Grant Mair, Amos Storkey, Alessandro Fontanella, Antreas Antoniou, Eleanor Platt, Paul Armitage

“…Ultimately, this should lead to more robust and widely applicable methods.…”
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Near-infrared spectroscopy analysis to predict urinary allantoin in dairy cows by Leonardo A.C. Ribeiro, Guilherme L. Menezes, Tiago Bresolin, Sebastian I. Arriola Apelo, Joao R.R. Dórea

“…The partial least squares regression model achieved an R2 of 0.55, a concordance correlation coefficient of 0.73, and a root mean squared error of prediction (RMSEP) of 3.63 mmol/L to predict allantoin concentration from the spectra data set without preprocessing. …”
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Predicting carbohydrate quality in a global database of packaged foods by Eric Antoine Scuccimarra, Alexandre Arnaud, Marie Tassy, Marie Tassy, Kim-Anne Lê, Fabio Mainardi

“…The overall mean absolute error on the test set was 0.96 g/100 g of product. …”
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Vertical Stratification Increases the Capacity of Morphological Traits to Predict Trophic Position in Neotropical Ants by Jésica Vieira, Karen C. Neves, Lino A. Zuanon, Heloise Gibb, Alan N. Andersen, Heraldo L. Vasconcelos

“…We believe that our approach to assessing the predictive capacity of morphological traits, through the use of multiple traits and consideration of different microhabitats, has wide applicability to functional studies not just of ants but to fauna more generally.…”
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Mean limiting pressure factors determination in contiguous pile walls using RAFELA and nonlinear regression models in spatially random soil by Divesh Ranjan Kumar, Sittha Kaorapapong, Warit Wipulanusat, Suraparb Keawsawasvong

“…The models were evaluated using several statistical performance parameters, scatter plots, residual error curves, and eight statistical performance metrics to ensure predictive accuracy and reliability. …”
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Transformer-Based Fast Mole Fraction of CO2 Retrievals from Satellite-Measured Spectra by Wei Chen, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang

“…Through periodic fine-tuning with minimal new data (<10% of all available data), the model maintains even higher accuracy (RMSE ∼ 1.2 ppm), demonstrating its applicability for ongoing missions up to the most recent measurements (2024 April 1). …”
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Why Do People Gather? A Study on Factors Affecting Emotion and Participation in Group Chats by Lu Yan, Kenta Ono, Makoto Watanabe, Weijia Wang

“…Using data from 546 users in China, a relevant demographic given the dominance of platforms like WeChat in both social and professional settings, we uncover insights that are particularly applicable to highly connected digital environments. …”
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