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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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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The Role of Immunohistochemistry as a Surrogate Marker in Molecular Subtyping and Classification of Bladder Cancer by Tatiana Cano Barbadilla, Martina Álvarez Pérez, Juan Daniel Prieto Cuadra, Mª Teresa Dawid de Vera, Fernando Alberca-del Arco, Isabel García Muñoz, Rocío Santos-Pérez de la Blanca, Bernardo Herrera-Imbroda, Elisa Matas-Rico, Mª Isabel Hierro Martín

“…Background/Objectives: Bladder cancer (BC) is a highly heterogeneous disease, presenting clinical challenges, particularly in predicting patient outcomes and selecting effective treatments. …”
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Study on the factors influencing the impaired abilities of daily living in middle-aged and older adult arthritis patients based on binary logistic regression and categorical decisi... by Bao-xuan Zhang, Bao-xuan Zhang, Bao-xuan Zhang, Jin-ping Luo, Jin-ping Luo, Jin-ping Luo, Jia-ying Sun, Jia-ying Sun, Jia-ying Sun, Ming-hui Geng, Ming-hui Geng, Ming-hui Geng, Yi-fan Mou, Yi-fan Mou, Yi-fan Mou, Nan-nan Cheng, Nan-nan Cheng, Nan-nan Cheng, Zhao-xuan Wang, Zhao-xuan Wang, Zhao-xuan Wang, Wen-qiang Yin, Wen-qiang Yin, Wen-qiang Yin, Zhong-ming Chen, Zhong-ming Chen, Zhong-ming Chen, Dong-ping Ma, Dong-ping Ma, Dong-ping Ma

“…The decision tree results showed that pain was the most important variable predicting impaired ADL in middle-aged and older adult arthritis patients. …”
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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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Unveiling shadows: A data-driven insight on depression among Bangladeshi university students by Sanjib Kumar Sen, Md. Shifatul Ahsan Apurba, Anika Priodorshinee Mrittika, Md. Tawhid Anwar, A.B.M. Alim Al Islam, Jannatun Noor

“…Seven machine learning models, including Support Virtual Machine (SVM), K-Nearest Neighbor (K-NN), Gaussian Naive Bayes (GNB), Decision Tree (DT), Random Forest Classifier (RFC), Artificial Neural Network (ANN), and Gradient Boosting (GB), were trained and tested using the collected data (n = 750) to identify the most effective method for predicting depression. After rigorous analysis, Random Forest emerged as the best-performing algorithm, exhibiting remarkable accuracy (87%), precision (78%), recall (95%), and f1-score (86%). …”
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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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Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems by Yongxin Li, Ali Basem, As'ad Alizadeh, Pradeep Kumar Singh, Saurav Dixit, Hanaa Kadhim Abdulaali, Rifaqat Ali, Pancham Cajla, Husam Rajab, Kaouther Ghachem

“…In a case study of a phase change material (PCM)-based PVT system, a GMDH-type ANN model was applied to predict electrical power (EP), thermal power (TP), and entropy generation (EG) based on inputs including PCM melting temperature, PCM thickness, solar radiation, and ambient temperature. …”
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Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders by Xiaoman Xing, Sizhi Ai, Jihui Zhang, Rui Huang, Yaping Liu, Dongming Quan, Jiacheng Ma, Guoli Wu, Jiangen Xu, Yuan Zhang, Hongliang Feng, Wen-fei Dong

“…Apex-centric tokenization enhances sensitivity to OSA events, while MHCA refines predictions and increases specificity in detecting oxygen desaturation. …”
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The miR-941/FOXN4/TGF-β feedback loop induces N2 polarization of neutrophils and enhances tumor progression of lung adenocarcinoma by Xiaojing Zhang, Xitong Huang, Xianying Zhang, Lichang Lai, Baoyi Zhu, Peibin Lin, Zhanfang Kang, Dazhong Yin, Dongbo Tian, Zisheng Chen, Jun Gao

“…The target gene and underlying signaling pathway of miR-941 were predicted and validated with qPCR, luciferase assay, WB and ELISA assay.ResultsThe results indicated the crucial role of TANs, especially N2-TANs in LUAD and miR-941 activity was significantly upregulated in TANs of LUAD patients. …”
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Clinical-oriented 3D visualization and quantitative analysis of gingival thickness using convolutional neural networks and CBCT by Lan Yang, Lan Yang, ZiCheng Zhu, Yongshan Li, Jieying Huang, Xiaoli Wang, Haoran Zheng, Jiang Chen

“…The intuitive 3D visualization serves as an innovative preoperative tool that identifies high-risk areas and guides personalized surgical planning, enhancing predictability for aesthetic and complex implant cases.…”
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The Mass of the Vela Pulsar Progenitor and the Age of the Vela-Puppis Complex by Jeremiah W. Murphy, Andrés F. Barrientos, René Andrae, Joseph Guzman, Benjamin F. Williams, Julianne J. Dalcanton, Brad Koplitz

“…While stellar population models with standard assumptions suggest a likely progenitor age and mass, these predictions are internally inconsistent with the observed population, indicating that something is missing in the standard modeling approach. …”
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