Research on Segmentation Experience of Music Signal Improved Based on Maximization of Negative Entropy by Qin Yao, Zhencong Li, Wanzhi Ma

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Adaptive mobile application for the CATS learning system by Y. V. Popova, I. V. Lehchylin

“…The proposed development is implemented in the educational process of the Belarusian National Technical University, covers all the main components of the learning process, including working with electronic educational and methodical complexes, passing tests, downloading the required information. …”
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In silico assessment of biocompatibility and toxicity: molecular docking and dynamics simulation of PMMA-based dental materials for interim prosthetic restorations by Ravinder S. Saini, Rayan Ibrahim H. Binduhayyim, Vishwanath Gurumurthy, Abdulkhaliq Ali F. Alshadidi, Shashit Shetty Bavabeedu, Rajesh Vyas, Doni Dermawan, Punnoth Poonkuzhi Naseef, Seyed Ali Mosaddad, Artak Heboyan

“…Methodology: Molecular docking was employed to predict the binding affinities, energetics, and steric features of MMA and PMMA with selected receptors involved in bone metabolism and tissue development, including RANKL, Fibronectin, BMP9, NOTCH2, and other related receptors. …”
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Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas by Xing Liu, Yiming Li, Zhiyan Sun, Shaowu Li, Kai Wang, Xing Fan, Yuqing Liu, Lei Wang, Yinyan Wang, Tao Jiang

“…Our gene signature helps interpret the occurrence of radiological traits and predict clinical outcomes. Additionally, we found nine prognostic quantitative radiomic features of CE and investigated the underlying biological processes of them.…”
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Multi-modality radiomics diagnosis of breast cancer based on MRI, ultrasound and mammography by Jiao Wu, YongXin Li, Wanqing Gong, Qian Li, Xue Han, Tingting Zhang

“…Conclusions The multi-modality radiomics model based on MRI, ultrasound, and mammography can predict benign and malignant breast lesions.…”
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A Meta-Learning-Based Ensemble Model for Explainable Alzheimer’s Disease Diagnosis by Fatima Hasan Al-bakri, Wan Mohd Yaakob Wan Bejuri, Mohamed Nasser Al-Andoli, Raja Rina Raja Ikram, Hui Min Khor, Zulkifli Tahir, The Alzheimer’s Disease Neuroimaging Initiative

“…The findings demonstrated significant progress in diagnostic transparency, as the algorithm consistently linked predictions to observed structural changes in the dilated lateral ventricles of the brain, which serve as a clinically reliable biomarker for AD and can be easily verified by medical professionals. …”
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Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC by Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf, ALMA Comprehensive High-resolution Extragalactic Molecular Inventory (ALCHEMI) collaboration

“…These inferred CRIRs are consistent within 1 dex with theoretical predictions based on nonthermal emission. Additionally, the high CRIRs estimated in NGC 253's CMZ can be explained by the large number of cosmic-ray-producing sources as well as a potential suppression of cosmic-ray diffusion near their injection sites.…”
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Hot deformation physical mechanisms and a unified constitutive model of a solid solution Ti55511 alloy deformed in the two-phase region by Huijie Zhang, Y.C. Lin, Gang Su, Yongfu Xie, Wei Qiu, Ningfu Zeng, Song Zhang, Guicheng Wu

“…Material constants are determined using a genetic algorithm (GA), and the experimental data align well with the predicted data. …”
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Wood Species Identification Based on Gray Level Co-Occurrence Matrix (GLCM) Features on Macroscopic Images by Muhammad Ghiffaari Ilham Ramadhan, Bambang Sugiarto, Okta Dwi Mulya, Defti Septian Chairulsyah, Adyanto Syahrizal, Gunawan Gunawan, Riffa Haviani Laluma, Rini Nuraini Sukmana, Teguh Wiharko

“…The model achieved a peak accuracy of 0.81 and correctly predicted all test images. This study indicates that the Random Forest model can be an effective classifier for wood species identification.…”
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Optimization of Gas-Liquid Sulfonation in Cross-Shaped Microchannels for α-Olefin Sulfonate Synthesis by Yao Li, Yingxin Mu, Muxuan Qin, Wei Zhang, Wenjin Zhou

“…A high-precision empirical model (coefficient of determination, <i>R</i>² = 0.9882) to predict product content was successfully constructed. …”
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Indoor positioning systems provide insight into emergency department systems enabling proposal of designs to improve workflow by Marius Huguet, Canan Pehlivan, François Ballereau, Antoine Dodane-Loyenet, Franck Fontanili, Thierry Garaix, Youri Yordanov, Vincent Augusto, Karim Tazarourte, Abdesslam Redjaline

“…The random forest classifier predicts job categories with 96% accuracy. Conclusions Indoor tracking systems offer additional perspectives for enhancing the understanding of emergency department systems. …”
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Developing A Digital Twin of a TRUEX Extraction Process that Enables Non-proliferation and Safeguards Monitoring through Optical Spectroscopy and Machine Learning [version 1; peer... by Justin T. Cooper, Ramedy Flores, Addyson Barnes, Eduardo Trevino, Kathrine Jesse, Kolton Heaps, Adam J. Pluth, Ashley Shields, Jaren Brownlee

“…Spectroscopic sensors were placed at strategic locations within the contactor bank and were used to predict TRUEX surrogate analyte concentrations at those locations. …”
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Reaction Behavior and Kinetic Model of Hydroisomerization and Hydroaromatization of Fluid Catalytic Cracking Gasoline by Haijun Zhong, Xiwen Song, Shuai He, Xuerui Zhang, Qingxun Li, Haicheng Xiao, Xiaowei Hu, Yue Wang, Boyan Chen, Wangliang Li

“…The model accurately predicted the product yields of FCC gasoline hydro-upgrading, with a relative error of less than 5%. …”
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Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups by Seyoung Mun, Seyoung Mun, Seyoung Mun, HyungWoo Jo, HyungWoo Jo, Young Mok Heo, Chaeyun Baek, Hye-Been Kim, Haeun Lee, Kyeongeui Yun, Kyeongeui Yun, Jinuk Jeong, Wooseok Lee, Dasom Jeon, Dasom Jeon, So Min Kang, So Min Kang, Seunghyun Kang, Young-Bong Choi, Young-Bong Choi, Sangjin Han, Gabriel Kim, Kung Ahn, Dong Hun Lee, Yong Ju Ahn, Dong-Geol Lee, Dong-Geol Lee, Kyudong Han, Kyudong Han, Kyudong Han, Kyudong Han

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”
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From Halos to Galaxies. VI. Improved Halo Mass Estimation for SDSS Groups and Measurement of the Halo Mass Function by Dingyi Zhao, Yingjie Peng, Yipeng Jing, Xiaohu Yang, Luis C. Ho, Alvio Renzini, Anna R. Gallazzi, Cheqiu Lyu, Roberto Maiolino, Jing Dou, Zeyu Gao, Qiusheng Gu, Filippo Mannucci, Houjun Mo, Bitao Wang, Enci Wang, Kai Wang, Yu-Chen Wang, Bingxiao Xu, Feng Yuan, Xingye Zhu

“…The derived SDSS group halo mass function agrees well with the theoretical predictions, and the derived stellar-to-halo mass relations for both the red and blue groups match well with those obtained from direct weak-lensing measurements. …”
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Modeling quinoa growth under saline and water-limiting conditions using SWAP-WOFOST by Diana C. Estrella Delgado, Tom De Swaef, Jan Vanderborght, Eric Laloy, Gerda Cnops, Maarten De Boever, Abdelaziz Hirich, Ayoub El Mouttaqi, Sarah Garré

“…The salinity stress function of SWAP effectively represents these tolerance mechanisms and accurately predicts the impact on yield, under arid conditions. …”
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Computer guided versus freehand dental implant surgery: Randomized controlled clinical trial by Nermine Ramadan Mahmoud, Mohamed Hatem Kamal Eldin, Mai Hassan Diab, Omar Samy Mahmoud, Yasser El-Sayed Fekry

“…A secondary aim is to propose an algorithm for predicting the accuracy of implant placement. …”
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Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review by Daniel H. de la Iglesia, Carlos Chinchilla Corbacho, Jorge Zakour Dib, Vidal Alonso-Secades, Alfonso J. López Rivero

“…This systematic review presents a critical analysis of advanced machine learning (ML) and deep learning (DL) approaches for predicting the remaining useful life (RUL) of electric vehicle (EV) batteries. …”
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Aerodynamic analysis and ANN-based optimization of NACA airfoils for enhanced UAV performance by Sanan H. Khan, Mohd Danish, Md. Ayaz, Afsar Husain, Shamma Saeed, Shamma Abdulla, Shama Shaheen, Alia Saeed, Ahmed Thaher

“…Additionally, the ANN model demonstrated a high accuracy in predicting the aerodynamic performance, closely matching the results of the CFD simulations. …”
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Identification of Factors Causing Land Cover Change in the Cikapundung Watershed by A. B. Harto, A. B. Harto, R. Virtriana, R. Virtriana, R. J. Kusuma, I. K. C. Reynaldi, A. Q. Karima, A. A. Kuntoro

“…This makes it even more important to not only understand historical and current land cover change patterns, but also understand the causes of land cover change and predict future spatiotemporal trends for strategic planning of human settlements, land use, and resource conservation in Bandung City. …”
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