Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions by Jinjun Xu, Han Wang, Wenjun Wu, Lang Lin, Yong Yu

“…(iv) The integrated mix design, which achieves a reduction of up to 40 % in carbon emissions and 30 % in costs, while preserving mechanical strength, comes highly recommended.…”
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Machine learning potential predictor of idiopathic pulmonary fibrosis by Chenchun Ding, Quan Liao, Renjie Zuo, Shichao Zhang, Zhenzhen Guo, Junjie He, Ziwei Ye, Weibin Chen, Sunkui Ke

“…Furthermore, GSEA revealed enrichment in multiple pathways, while immune function analysis demonstrated a significant correlation between IPF onset and immune cell infiltration. …”
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Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…In this paper, we propose Parallel SMO, a new algorithm that selects multiple violating pairs in each iteration, allowing batch-wise updates that enhance convergence speed and optimize parallel computation. …”
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Two-layer multi-objective optimal sizing of electric-hydrogen energy storage with the integration of extreme scenario generation and preference-information decision-making by Zihan Sun, Jian Chen, Yang Chen, Wen Zhang, Tingting Zhang, Yicheng Zhang, Guangsheng Pan

“…First, an integrated generative adversarial network-based method is developed to synthesize diverse scenarios while preserving long-duration temporal dependencies and accurately capturing wind-solar-load correlations. …”
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Failure mechanism-driven multi-adversarial domain transfer learning for rolling bearing fault diagnosis by Zhihui Zhang, Zhidan Zhong, Zhe Li, Wentao Mao, Yunhao Cui

“…To address these challenges, this paper proposes a Failure Mechanism-Driven Multi-Adversarial Domain Transfer Learning algorithm. The core of this method is the deep integration of physical prior knowledge with data-driven models. …”
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An Improved Galerkin Framework for Solving Unsteady High-Reynolds Navier–Stokes Equations by Jinlin Tang, Qiang Ma

“…Standard Galerkin finite element methods often suffer from non-physical oscillations in convection-dominated regimes, while the multiscale nature of these flows demands prohibitively high computational resources for uniformly refined meshes. …”
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Leveraging machine learning models in evaluating ADMET properties for drug discovery and development by Magesh Venkataraman, Gopi Chand Rao, Jeevan Karthik Madavareddi, Srinivas Rao Maddi

“…Conclusion: Machine learning has emerged as a transformative tool in ADMET prediction, offering new opportunities for early risk assessment and compound prioritization. While challenges such as data quality, algorithm transparency, and regulatory acceptance persist, continued integration of ML with experimental pharmacology holds the potential to substantially improve drug development efficiency and reduce late-stage failures. …”
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A Ship’s Maritime Critical Target Identification Method Based on Lightweight and Triple Attention Mechanisms by Pu Wang, Shenhua Yang, Guoquan Chen, Weijun Wang, Zeyang Huang, Yuanliang Jiang

“…To verify the effectiveness of these algorithmic improvements, the DTI-YOLO algorithm was tested on a self-made dataset of 2300 ship navigation images. …”
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Interpretable machine learning model of effective mass in perovskite oxides with cross-scale features by Changjiao Li, Zhengtao Huang, Hua Hao, Zhonghui Shen, Guanghui Zhao, Ben Xu, Hanxing Liu

“…However, previous works were mainly devoted to algorithm improvement, while the essential multi-scale characteristics are not well addressed. …”
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Exploring the synchronization of cortical networks via entrainment to intrinsic frequencies by Sandeep Kumar Agnihotri, Jiang Cai, Zhen Wang

“…Both tACS and tDCS were simulated to assess their effect on network synchronization. An algorithm was employed to extract the network's intrinsic frequency and align stimulation frequencies accordingly. …”
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Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…To address the challenges of significant scale variations and difficulty in extracting discriminative features for small targets in airborne remote sensing object detection, while considering the constraints and efficiency requirements of onboard systems, this article proposes a lightweight detection algorithm. …”
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Protection of high-performance concrete on the durability of GFRP bars: Deterioration mechanism and tensile strength prediction by Yuan Yue, Wen-Wei Wang, Lei Zhang, Liang Liang, Qiang Zhao, Yuzhou Zheng

“…It greatly reducing manual calculation burden while providing a practical tool for researchers to analyze accelerated material degradation.…”
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Reduced Complexity Initial Synchronization for 5G NR Multibeam LEO-Based Non-Terrestrial Networks by Ashish Kumar Meshram, Sumit Kumar, Jorge Querol, Stefano Andrenacci, Symeon Chatzinotas

“…We provide practical design parameters for the proposed algorithm to ensure that UE can efficiently perform initial synchronization by evaluating approximate bounds on the spot beam radius along with the No-Benefit Region (NBR) bounds of DPC. …”
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Sampling calorimeter to measure the photon’s incident angle by Lim GeiYoub, Abe Ryota, Ahn JungKeun, Ji Su-Jeong, Kim Chong, Kim Eun-Joo, Kim Junlee, Kim YoungJun, Kim YoungJun, Kotera Katsushige, Lim Sanghoon, Naito Taichi, Park JeongWoo, Shiomi Koji, Tajima Yasuhisa, Yang Seongbae, Yoshida Hiroshi

“…This updated configuration indicates no significant difference in the angular resolution, while the energy resolution significantly improves. …”
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Analisis Perbandingan Algoritma SVM, KNN, dan CNN untuk Klasifikasi Citra Cuaca by Mohammad Farid Naufal

“…KNN and SVM are Machine Learning classification algorithms, while CNN is a Deep Neural Networks classification algorithm. …”
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Efficient Nearly Piecewise Continuous Signal Basis Expansion by Precision Calculation by Hsin-Jung Lee, Cheng-Che Lee, Kuei-Chen Chen, Shao-Yun Luo, Shu-Ping Chang, Jian-Jiun Ding

“…In this paper, we propose a novel algorithm, called “precise calculation,” to adaptively expand such signals. …”
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Computational modelling and optimization of porous plates for mandibular fracture fixation accounting for bone healing by Ali Mehboob, Imad Barsoum, Hassan Mehboob, Abdelhak Ouldyerou, Rashid K. Abu Al-Rub

“…Five distinct bone plates were assessed: conventional one dense bone plate (1 DP), two dense bone plates (2 DP), two porous plates (2 PP), a topology-optimized bone plate (OBP), and two modified porous bone plates (2 MPP), while the volume was constrained to 160 mm3 for the designs 2 PP, OBP, and 2 MPP. …”
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Associations between exposure to multiple environmental chemicals and metabolic syndrome: A mixture analysis by Ruiqiang Li, Xiaoyi Lin, Tingyu Lu, Jiao Wang, Ying Wang, Lin Xu

“…Exposure to environmental chemicals is prevalent. While previous studies reported associations between multiple chemical exposures and metabolic syndrome (MetS), they did not comprehensively account for correlations among exposures. …”
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Comparative Study of Machine Learning Techniques for Predicting UCS Values Using Basic Soil Index Parameters in Pavement Construction by Mudhaffer Alqudah, Haitham Saleh, Hakan Yasarer, Ahmed Al-Ostaz, Yacoub Najjar

“…This study investigated the prediction of unconfined compressive strength (UCS), a common measure of soil’s undrained shear strength, using fundamental soil characteristics. While traditional pavement subgrade design often relies on parameters like the resilient modulus and California bearing ratio (CBR), researchers are exploring the potential of incorporating more easily obtainable strength indicators, such as UCS. …”
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Leveraging Thermal Infrared Imaging for Pig Ear Detection Research: The TIRPigEar Dataset and Performances of Deep Learning Models by Weihong Ma, Xingmeng Wang, Simon X. Yang, Lepeng Song, Qifeng Li

“…The stable physiological structure and rich vascular network of pig ears contribute to distinct thermal characteristics, which can reflect temperature variations. While the temperature of the pig ear does not directly represent core body temperature due to the ear’s role in thermoregulation, thermal infrared imaging offers a feasible approach to analyzing individual pig status. …”
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