Clinical outcomes, hemodynamics, and leaflet thrombosis following transcatheter aortic valve replacement with novel intra‐annular devices by Juri Iwata, Kentaro Hayashida, Akiyoshi Kajino, Shingo Sakata, Shohei Imaeda, Toshinobu Ryuzaki, Hikaru Tsuruta, Hideyuki Shimizu, Masaki Ieda

“…Despite a smaller annulus, Navitor demonstrated decreased mean pressure gradient by TTE, 9.2 [7.3–13.6] mmHg versus 7.5 [5.9–9.5] mmHg, p = 0.006; but not by invasive measurement 5.1 [3.4–7.7] mmHg versus 5.3 [3.2–7.9] mmHg, p = 0.986). …”
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LRU-Net: lightweight and multiscale feature extraction for localization of ACL tears region in MRI images by Xiaojun Si, Liang Yan, Cui Shi, Yang Xu

“…LRU-Net integrates an advanced attention mechanism that emphasizes gradients and leverages the anatomical position of the ACL, thereby improving boundary sensitivity. …”
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Entropy generation and heat convection analysis of second-grade viscoelastic nanofluid flow in a tilted lid-driven square enclosure: A finite difference approach by Anil Ahlawat, Mukesh Kumar Sharma, K. Loganathan

“…The stream function approach removes the pressure gradient term from the linear momentum equation, and the resulting partial differential equations are discretized via finite differences and then resulting algebraic equations are solved with SOR and SUR methods employing self-developed MATLAB codes. …”
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Estimating vegetation indices and biophysical parameters for Central European temperate forests with Sentinel-1 SAR data and machine learning by Daniel Paluba, Bertrand Le Saux, Francesco Sarti, Přemysl Štych

“…XGB was the most computationally efficient. Moreover, SAR-based estimations over Central Europe achieved comparable results to those obtained in testing within Czechia, demonstrating their transferability for large-scale modeling. …”
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Enhanced intelligent train operation algorithms for metro train based on expert system and deep reinforcement learning. by Yunhu Huang, Wenzhu Lai, Dewang Chen, Geng Lin, Jiateng Yin

“…However, a critical examination reveals computational constraints, adaptability to unforeseen conditions and multi-objective balancing that our research aims to address. …”
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A High-Efficient Modeling Method for Aerodynamic Loads of an Airfoil with Active Leading Edge Based on RFA and CFD by Shengyong Fang, Sheng Zhang, Jinlong Zhou, Weidong Yang

“…For the airfoil in freestream, the pressure difference between the upper and lower surfaces and the variations in pressure gradients are significant at its leading edge area. …”
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Numerical Optimization of Laser Powder Bed Fusion Process Parameters for High-Precision Manufacturing of Pure Molybdenum by İnayet Burcu Toprak, Nafel Dogdu, Metin Uymaz Salamci

“…The powder spreading behavior is simulated using the Discrete Element Method (DEM), while molten pool dynamics are analyzed through Computational Fluid Dynamics (CFD). Optimization of process parameters is performed using FLOW-3D Release 7 software in conjunction with the HEEDS-SHERPA algorithm. …”
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Mathematical Modeling of Cancerous Tumor Evolution Incorporating Drug Resistance by Francis Oketch Ochieng

“…The tumor consumes nutrients at a faster rate than they can diffuse inward, leading to nutrient gradients and potential necrosis in the core. High drug concentrations do not always correlate with increased cell death due to factors such as drug toxicity or resistance development. …”
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Trigonometric Bézier-based isogeometric engineering analysis for heat conduction in curvilinear ducts by Mohd Naufal Zainal Abidin, Md Yushalify Misro

“…The proposed method demonstrates strong potential for accurately resolving localized thermal gradients in geometrically complex domains, confirming its viability and efficiency for engineering heat conduction analysis.…”
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Clinical Applicability of Machine Learning Models for Binary and Multi-Class Electrocardiogram Classification by Daniel Nasef, Demarcus Nasef, Kennette James Basco, Alana Singh, Christina Hartnett, Michael Ruane, Jason Tagliarino, Michael Nizich, Milan Toma

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Developing a Transparent Anaemia Prediction Model Empowered With Explainable Artificial Intelligence by Muhammad Sajid Farooq, Muhammad Hassan Ghulam Muhammad, Oualid Ali, Zahid Zeeshan, Muhammad Saleem, Munir Ahmad, Sagheer Abbas, Muhammad Adnan Khan, Taher M. Ghazal

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Non-Invasive Multiclass Diabetes Classification Using Breath Biomarkers and Machine Learning with Explainable AI by Alberto Gudiño-Ochoa, Julio Alberto García-Rodríguez, Raquel Ochoa-Ornelas, Eduardo Ruiz-Velazquez, Sofia Uribe-Toscano, Jorge Ivan Cuevas-Chávez, Daniel Alejandro Sánchez-Arias

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Evaluation of Personal Radiation Exposure From Wireless Signals in Indoor and Outdoor Environments by Pan Ruijie, Aduwati Sali, Lu Li, Muhammad Zamir Mohyedin, Sangin Qahtan

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Multiband THz MIMO antenna with regression machine learning techniques for isolation prediction in IoT applications by Md Ashraful Haque, Kamal Hossain Nahin, Jamal Hossain Nirob, Md. Kawsar Ahmed, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Abeer D. Algarni, Mohammed ElAffendi, Ahmed A. Abd El-Latif, Abdelhamied A. Ateya

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Transfer Learning Estimation and Transferability of LNC and LMA Across Different Datasets by Yingbo Wang, Mengzhu He, Lin Sun, Yong He, Zengwei Zheng

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Estimating Tea Plant Physiological Parameters Using Unmanned Aerial Vehicle Imagery and Machine Learning Algorithms by Zhong-Han Zhuang, Hui-Ping Tsai, Chung-I Chen

“…Overall, we highlight the effectiveness of integrating gradient boosting models with multispectral data to capture tea plant physiological characteristics. …”
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A Hybrid Regression–Kriging–Machine Learning Framework for Imputing Missing TROPOMI NO₂ Data over Taiwan by Alyssa Valerio, Yi-Chun Chen, Chian-Yi Liu, Yi-Ying Chen, Chuan-Yao Lin

“…The proposed approach combines geostatistical interpolation with nonlinear modeling by integrating RK with ML models—specifically comparing gradient boosting regression (GBR), random forest (RF), and K-nearest neighbors (KNN)—to determine the most suitable auxiliary predictor. …”
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Predicting axial load capacity in elliptical fiber reinforced polymer concrete steel double skin columns using machine learning by Focai Yu, Haytham F. Isleem, Walaa J. K. Almoghayer, Ramy I. Shahin, Saad A. Yehia, Mohammad Khishe, Mohamed Kamel Elshaarawy

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A Comparative Study of Machine Learning Techniques for Predicting Mechanical Properties of Fused Deposition Modelling (FDM)-Based 3D-Printed Wood/PLA Biocomposite by Prashant Anerao, Atul Kulkarni, Yashwant Munde, Namrate Kharate

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A robust transfer learning approach with histopathological images for lung and colon cancer detection using EfficientNetB3 by Raquel Ochoa-Ornelas, Alberto Gudiño-Ochoa, Julio Alberto García-Rodríguez, Sofia Uribe-Toscano

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