Sentinel-3 Altimetry Thematic Products for Hydrology, Sea Ice and Land Ice by Jérémie Aublanc, Julien Renou, Fanny Piras, Karina Nielsen, Stine K. Rose, Sebastian B. Simonsen, Sara Fleury, Stefan Hendricks, Nicolas Taburet, Giovanni D’Apice, Anouk Chamayou, Pierre Féménias, Filomena Catapano, Marco Restano

“…In this paper, the new architecture of the ground segment processing is presented, along with the major algorithmic developments. The main data content of the Thematic Products is also described, to indicate the key product variables for the end users. …”
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Practicality of training a quantum-classical machine in the noisy intermediate-scale quantum era by Tarun Dutta, Alex Jin, Clarence Liu Huihong, José Ignacio Latorre, Manas Mukherjee

“…It addresses the challenges of coupling ion-trap systems with classical processors and highlights the effectiveness of genetic algorithms for NISQ devices and complex binary classification tasks with many local minima. …”
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Identification and quantification of transposable element transcripts using Long-Read RNA-seq in Drosophila germline tissues by Rebollo, Rita, Gerenton, Pierre, Cumunel, Eric, Mary, Arnaud, Sabot, François, Burlet, Nelly, Gillet, Benjamin, Hughes, Sandrine, S. Oliveira, Daniel, Goubert, Clément, Fablet, Marie, Vieira, Cristina, Lacroix, Vincent

“…TE transcription is therefore not only necessary for TE transposition per se but can also be associated with TE-gene fusion transcripts, and in some cases, be the product of pervasive transcription. …”
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Characterization of defective coffee beans and blends differentiation based on 1H qNMR technique by Gui-Lin Hu, Chen-Xi Quan, Hao-Peng Dai, Ming-Hua Qiu

“…In summary, current research will not only help to reveal the material basis of DCB and their impact on coffee flavor, but also provide feasible strategies for the identification of DCB.…”
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Automatic Generation of Medical Case-Based Multiple-Choice Questions (MCQs): A Review of Methodologies, Applications, Evaluation, and Future Directions by Somaiya Al Shuraiqi, Abdulrahman Aal Abdulsalam, Ken Masters, Hamza Zidoum, Adhari AlZaabi

“…In this review, we explore various algorithms and techniques that have been developed for generating MCQs from medical case studies. …”
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The relative efficiency of time‐to‐progression and continuous measures of cognition in presymptomatic Alzheimer's disease by Dan Li, Samuel Iddi, Paul S. Aisen, Wesley K. Thompson, Michael C. Donohue, Alzheimer's Disease Neuroimaging Initiative

“…Simulated progression events are algorithmically derived from the continuous assessments using a random forest model fit to the same data. …”
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Hate Speech Detection Using Large Language Models: A Comprehensive Review by Aish Albladi, Minarul Islam, Amit Das, Maryam Bigonah, Zheng Zhang, Fatemeh Jamshidi, Mostafa Rahgouy, Nilanjana Raychawdhary, Daniela Marghitu, Cheryl Seals

“…The widespread use of social media and other online platforms has facilitated unprecedented communication and information exchange. However, it has also led to the spread of hate speech and poses serious challenges to societal harmony as well as individual well-being. …”
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A Review of Intelligent Orchard Sprayer Technologies: Perception, Control, and System Integration by Minmin Wu, Siyuan Liu, Ziyu Li, Mingxiong Ou, Shiqun Dai, Xiang Dong, Xiaowen Wang, Li Jiang, Weidong Jia

“…It also discusses existing technical bottlenecks and obstacles to large-scale adoption. …”
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Developing Computer Vision Models for Classifying Grain Shapes of Crushed Stone by Alexey N. Beskopylny, Evgenii M. Shcherban’, Sergey A. Stel’makh, Alexandr A. Shilov, Irina Razveeva, Diana Elshaeva, Andrei Chernil’nik, Gleb Onore

“…The accuracy quality metric achieved during the training of both models was 0.86. Using intelligent algorithms, along with grain analysis methods via manual selection, sieve analysis, or using special equipment, will reduce manual labor and can also serve as an additional source for verifying the quality of building materials at various stages of construction.…”
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Exploring ischemic stroke based on the ferroptosis perspective: ECH1 may serve as a new biomarker and therapeutic target by Rendong Qu, Yiyan Zhang, Haojia Zhang, Ke Li, Boning Zhang, Hongxuan Tong, Tao Lu

“…Hub genes were screened using differential expression analysis and machine learning algorithms. Subsequently, genes were further filtered by mendelian randomization and also validated using transient middle cerebral artery occlusion (tMCAO) model.ResultsFerroptosis-related genes in the IS group showed higher expression compared with the healthy control group. …”
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Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review by Masoud Tafavvoghi, Lars Ailo Bongo, Nikita Shvetsov, Lill-Tove Rasmussen Busund, Kajsa Møllersen

“…This dataset has a considerable selection bias that can impact the robustness and generalizability of the trained algorithms. There is also a lack of consistent metadata reporting of breast WSI datasets that can be an issue in developing accurate deep learning models, indicating the necessity of establishing explicit guidelines for documenting breast WSI dataset characteristics and metadata.…”
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Application of High-Resolution Core Curve Construction in Logging Lithology Identification by YOU Ting, ZHU Tianyi, XU Pengye, WANG Shuhua, HE Xing, YU Lijun

“…Input the curve as one of the features into different models for lithology identification in the study of logging lithology identification based on machine learning algorithms. The results show that the fitted high-resolution core gamma curve can not only improve the accuracy of lithology identification as one of the new features, but also replace the measured core gamma curve features with maintaining a slightly higher or similar lithology identification accuracy in multiple machine learning models. …”
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Sensor-Generated In Situ Data Management for Smart Grids: Dynamic Optimization Driven by Double Deep Q-Network with Prioritized Experience Replay by Peiying Zhang, Siyi Li, Dandan Li, Qingyang Ding, Lei Shi

“…Simulation experiments show that the proposed method reduces waiting latency and response latency by an average of 67.69% and 68.77%, respectively, compared to traditional algorithms and other reinforcement learning algorithms, verifying its effectiveness in in situ data management. …”
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Machine Learning for Predicting Bank Stability: The Role of Income Diversification in European Banking by Karim Farag, Loubna Ali, Noah Cheruiyot Mutai, Rabia Luqman, Ahmed Mahmoud, Nol Krasniqi

“…Conversely, the results also show that the machine-learning algorithms used play a crucial role in enhancing the predictive performance of bank stability.…”
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Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer by Peng Zhang, Meizhong Qin, Fen Li, Kunpeng Hu, He Huang, Cuicui Li

“…Most existing models rely on single-omics data and limited algorithms, reducing robustness and clinical value. …”
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PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning by Boris I. Evstatiev, Dimitar T. Trifonov, Katerina G. Gabrovska-Evstatieva, Nikolay P. Valov, Nicola P. Mihailov

“…In this study, visible spectrum data and machine learning algorithms were used for the identification of soiling. …”
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Prediction of Reservoir Flow Capacity in Sandstone Formations: A Comparative Analysis of Machine Learning Models by Micheal Ayodeji Ogundero, Taiwo Adelakin, Kehinde Orolu, Isaac Femi Johnson, Theophilus Akinfenwa Fashanu, Kingsley Abhulimen

“…With the following supervised machine learning algorithms: Random Forest, Artificial Neural Network (ANN) and Support Vector Regression (SVR); the study modeled RFC. …”
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Energetic Transients Joint Analysis System for Multi-INstrument (ETJASMIN) for GECAM. II. Search, Verification, and Classification of Bursts by Ce Cai, Yan-Qiu Zhang, Shao-Lin Xiong, Jin-Peng Zhang, Ping Wang, Shi-Jie Zheng, Shuo Xiao, Qi-Bin Yi, Yi Zhao, Hao-Xuan Guo, Sheng-Lun Xie, Wang-Chen Xue, Chao Zheng, Jia-Cong Liu, Chen-Wei Wang, Wen-Jun Tan, Yue Wang, Pei-Yi Feng, Zheng-Hang Yu, Peng Zhang, Yan-Ting Zhang, Wen-Long Zhang, Xiao-Yun Zhao, Zhen Zhang, Xiang Ma, Yue Huang, Xiao-Bo Li, Cheng-Kui Li, Ming-Yu Ge, Shu-Xu Yi, Hai-Sheng Zhao, Jin Wang, Bing Li, Li-Ming Song, Lian Tao, Shu Zhang, Shuang-Nan Zhang

“…For this pipeline, we implement a coherent algorithm to search for simultaneous signals in the light curves of multiple instruments, conduct a series of Monte Carlo simulations, and validate the pipeline performance with in-flight observation data. …”
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Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector by A. Gavrikov, V. Cerrone, A. Serafini, R. Brugnera, A. Garfagnini, M. Grassi, B. Jelmini, L. Lastrucci, S. Aiello, G. Andronico, V. Antonelli, A. Barresi, D. Basilico, M. Beretta, A. Bergnoli, M. Borghesi, A. Brigatti, R. Bruno, A. Budano, B. Caccianiga, A. Cammi, R. Caruso, D. Chiesa, C. Clementi, S. Dusini, A. Fabbri, G. Felici, F. Ferraro, M.G. Giammarchi, N. Giudice, R.M. Guizzetti, N. Guardone, C. Landini, I. Lippi, S. Loffredo, L. Loi, P. Lombardi, C. Lombardo, F. Mantovani, S.M. Mari, A. Martini, L. Miramonti, M. Montuschi, M. Nastasi, D. Orestano, F. Ortica, A. Paoloni, E. Percalli, F. Petrucci, E. Previtali, G. Ranucci, A.C. Re, M. Redchuck, B. Ricci, A. Romani, P. Saggese, G. Sava, C. Sirignano, M. Sisti, L. Stanco, E. Stanescu Farilla, V. Strati, M.D.C. Torri, A. Triossi, C. Tuvè, C. Venettacci, G. Verde, L. Votano

“…However, given the low cross-section of antineutrino interactions, the development of a powerful event selection algorithm becomes imperative to achieve effective discrimination between signal and backgrounds. …”
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MolNexTR: a generalized deep learning model for molecular image recognition by Yufan Chen, Ching Ting Leung, Yong Huang, Jianwei Sun, Hao Chen, Hanyu Gao

“…In addition, it employs a series of novel augmentation algorithms to significantly enhance the robustness and performance of the model.…”
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