Bi directional sparse attention recurrent autoencoder based intrusion detection for VANET security with tuna swarm optimization by R. Gopi, V. Thiruppathy Kesavan, Md. Jakir Hossen, Nor Hidayati Binti Abdul Aziz

“…It is a useful technique for resolving issues with deep layer neural networks, like low velocity and overfitting issues in learning. …”
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Artificial intelligence and molecular dynamics assisted analysis of wear behavior of high entropy alloys by Ling Qiao, Junya Inoue, Jingchuan Zhu

“…The dislocations and defects in the material subsurface layer were captured to understand the wear mechanism. …”
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Phytoplankton Spring Bloom Inhibited by Marine Heatwaves in the North‐Western Mediterranean Sea by Mengyu Li, Emanuele Organelli, Federico Serva, Marco Bellacicco, Angela Landolfi, Andrea Pisano, Salvatore Marullo, Fang Shen, Alexandre Mignot, Simon vanGennip, Rosalia Santoleri

“…Such reduction is related to the enhanced stratification of the water column under MHWs which hinders the renewal of nutrients from deep‐ocean reservoirs, thus preventing surface phytoplankton from blooming. This process negatively impacts particulate organic carbon stocks within the mixed layer, while severe events cause an earlier shift of phytoplankton phenology that provokes changes in zooplankton biomass distribution.…”
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Effects of Fe3+ on EPS secretion and membrane fouling of microalgae-bacteria symbionts for breeding wastewater treatment by TIAN Maozhi, DING Ziyao, SUN Chen, ZHOU Weiyu, WANG Shengzhi, WAN Hanyu, LI Kun

“…The experimental results indicated that the addition of Fe3+ effectively mitigated membrane fouling, with the least fouling observed at iron mass concentration of 150 mg/L. The Hermia classic model was used to fit and analyze the membrane flux attenuation process. …”
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Decoding cancer prognosis with deep learning: the ASD-cancer framework for tumor microenvironment analysis by Ziyuan Huang, Yunzhan Li, Vanni Bucci, John P. Haran

“…This commentary explores the methodological innovations and scalability of ASD-cancer while suggesting future directions, such as the incorporation of additional data layers and the development of adaptive AI models through continuous learning. …”
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Evaluation of Landslide Susceptibility Zonation applying Fuzzy Gamma Operators in Taleghanroud Watershed of Qazvin Province by Jamal Mosaffaie, Amin Salehpour Jam, Faramarz Sarfaraz, Samad Shadfar

“…A total of 15 landslides were identified, 70% of which were used to model and 30% of which were used to evaluate the results of the models. …”
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Visible and near‐infrared image fusion based on information complementarity by Zhuo Li, Shiliang Pu, Mengqi Ji, Feng Zeng, Bo Li

“…Therefore, an information complementarity fusion (ICF) model is designed based on physical signals. In order to separate high‐frequency noise from important information in distinct frequency layers, the authors first extracted texture‐scale and edge‐scale layers using a two‐scale filter. …”
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Review of observations on the boundary of the Martian induced magnetosphere by Jing Wang

“…Based on the comprehensive detection data of plasma and magnetic field from MAVEN, it is confirmed that the boundary of the Martian induced magnetosphere is a magnetohydrodynamic discontinuity, and its physical properties are similar to those of the Earth's magnetopause. The pile-up process of the magnetic fields occurs upstream of the discontinuity, and its properties resemble those of the plasma depletion layer upstream of the Earth's magnetopause. …”
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Industrial-Grade 3D Detection for Laser Cleaning of Metallic Components Based on Neural Radiance Fields and Temporal-Spatial Learning by Dandan Qi

“…Propose a NeRF optimization strategy based on Octree scene partitioning to achieve high-fidelity reconstruction of micro-structures such as rust layer edges and micro-cracks; 3. Improve the collaborative modeling ability between multi-temporal images through cross-scale attention fusion; 4. …”
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Unveiling the effect of bovine serum albumin on the corrosion resistance of high nitrogen stainless steel for cardiac stents by Shiyao Du, Hui Yan, Bingchun Zhang, Ao Tang, Ying Li

“…Most importantly, such an increased defects will further promote the dissolution process of both the passive film and HNS matrix according to point defect model (PDM), which will definitely undermine the protective ability of the passive film and eventually result in the declined corrosion resistance of HNS in BSA-contained solution.…”
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Deep Learning-Assisted Discovery of Analogy-Inspired Designs within Peter Collins' Analogical Architectural Design Classification Framework by Hüseyin Özdemir

“… This study focuses on analogical reasoning and deep learning models to enhance the innovative design process in architecture. …”
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Insight into the Impact of Electrolyte on Passivation of Lithium–Sulfur Cathodes by Walter Cistjakov, Johanna Hoppe, Jinkwan Jung, Fridolin Röder, Hee‐Tak Kim, Ulrike Krewer

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Simulation Analysis on the Mud Film Stability for Urban Slurry Shield Tunnel by ZHOU Yu, ZHANG Zhimin, XIONG Hao, CHEN Fan, HAN Kaihang, HUANG Mingfeng

“…Therefore, it is necessary to study the mud film stability of urban slurry shield tunnel to ensure the construction safety. Method A numerical model is developed to simulate the mud film formation and infiltration process under different permeability conditions by using the DEM-CFD (Discrete Element Method-Computational Fluid Dynamics) coupling method. …”
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Mesoscopic analysis and prediction of in-situ effect in FFF 3D printing CFRP/GFRP by Xiang Yu, Pai Peng, Tian-Yun Yao, Yu Zhao, Yong-Jun Zhou, Yuan Jing

“…The meso-structure indicates that, unlike conventional composite materials, the distinctive FFF 3D printing process diminishes the impact of adjacent layers on clustered plies in thin-layer structures. …”
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Residual channel attention based sample adaptation few-shot learning for hyperspectral image classification by Yuefeng Zhao, Jingqi Sun, Nannan Hu, Chengmin Zai, Yanwei Han

“…Furthermore, a new Random-based Feature Recalibration Module (RFRM) is proposed to reassign the feature weights via random matrix, which fully explore feature weight relationships to guide the sample adaptation process. Besides, we design a joint loss function with combining the FSL loss and domain adaptive loss for further optimization model. …”
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A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network by Zhijian Wang, Likang Zheng, Wenhua Du, Wenan Cai, Jie Zhou, Jingtai Wang, Xiaofeng Han, Gaofeng He

“…Traditional neural networks tend to be more subjective when classifying fault time-frequency graphs, such as pooling layer, and ignore the location relationship of features. …”
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Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data by Chien Wei Oei, Eddie Yin Kwee Ng, Matthew Hok Shan Ng, Yam Meng Chan, Vinithasree Subbhuraam, Lai Gwen Chan, U. Rajendra Acharya

“…The combination of using DL algorithms, such as multi-layer perceptron (MLP) and long short-term memory (LSTM), which can process complex patterns in the data, and the inclusion of new data types, such as sequential data, helped to improve model performance. …”
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Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach by Khadim Hussain, Kaleem Mehmood, Sun Yujun, Tariq Badshah, Shoaib Ahmad Anees, Fahad Shahzad, Nooruddin, Jamshid Ali, Muhammad Bilal

“…The model underwent 10,000 iterations during its training process, and a thorough statistical analysis was conducted to assess the impact of each driving component. …”
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Exploring Trial-and-Error in Deep Learning: Initial Application to Isotope Detection in Mass Spectrometry by Qihong Jiao, Yuxiao Wang, Yongshuai Wang, Shiwei Sun, Xuefeng Cui

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A lightweight multi scale fusion network for IGBT ultrasonic tomography image segmentation by Meng Song, Zhaoba Wang, Youxing Chen, Ya Li, Yong Jin, Bei Jia

“…LMFNet adopts a deep U-shaped encoder-decoder architecture, with the backbone designed using inverted residual blocks to optimize feature transmission while maintaining model compactness. Additionally, we introduce two flexible, plug-and-play modules: the Context Feature Fusion (CFF) module, which effectively integrates multi-scale contextual information at skip connection layers, and the Multi-Scale Perception Aggregation (MPA) module, which focuses on extracting and fusing multi-scale features at bottleneck layers. …”
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