Algorithm for Cloud Particle Phase Identification Based on Bayesian Random Forest Method by Fu Tao, Yang Zhipeng, Tao Fa, Hu Shuzhen, Lu Yuxiang, Fu Changqing

“…Through case analysis of the evolution of observed factors such as reflectivity factor, radial velocity, and depolarization ratio, model recognition results show to be consistent with cloud microphysical processes. …”
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Thermal damage detection of EAST internal component based on machine learning by Zhongfang Guan, Bin Zhang, Jian Liu, Jinping Qian, Xianzu Gong, Runze Chen, Zuhao Wang, Binfu Gao, Yutong Guo, Chuannan Xuan, Cong Cao, Tianqi Jia, Pan Li, Wenbin Liu, Wei Wang, Yunchan Hu, Yifan He, Kangjia Yang, Wenyi Lu, Chunyu He, the EAST team

“…Improvements are needed for specialized tasks, particularly for early warning and precise identification of small internal component damage during the initial stages of EAST discharges. we enhance the YOLOv8 model by incorporating specialized layers for detecting small targets and integrating the CBAM attention mechanism. …”
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Molecular correlates of childhood adversity – a multi-omics perspective on stress regulation by Johannes C. S. Zang, Caroline May, Katrin Marcus, Robert Kumsta

“…In search of mediators of this relationship, alterations of bio-behavioral and cellular regulatory systems came into focus, including those dealing with basic gene regulatory processes. System biology oriented approaches have been proposed to gain a more comprehensive understanding of the complex multiple interrelations between and within layers of analysis. …”
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Development Performance and Pressure Field Evolution of ASP Flooding by Junjian Li, Hao Wang, Jinchuan Hu, Hanqiao Jiang, Rongda Zhang, Lihui Tang

“…A large sandpack laboratory model with vertical heterogeneous layers is used to monitor pressure performance during the ASP flooding. …”
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Power Quality State Estimation for Distribution Grids Based on Physics-Aware Neural Networks—Harmonic State Estimation by Patrick Mack, Markus de Koster, Patrick Lehnen, Eberhard Waffenschmidt, Ingo Stadler

“…This article examines a new flexible, close-to-real-time concept of harmonic state estimation using synchronized measurements processed in a neural network. A physics-aware approach enhances a data-driven model, taking into account the structure of the electrical network. …”
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Numerical Simulation on an Ultra-Large Seven-Ring Internal Support System Considering the Effects of Soil–Structure Interaction and Temperature by Hexiang Hu, Yu Tian, Neimeng Zheng, Xiuli Du, Haishan Guo, Zhonghua Xu

“…The Hardening Soil model with small strain stiffness is used to simulate and analyze the whole excavation process of the foundation pit. …”
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Application of Medical Images for Melanoma Detection Using a Multi‐Architecture Convolutional Neural Network From a Deep Learning Approach by Justice Williams Asare, Emmanuel Akwah Kyei, Seth Alornyo, Emmanuel Freeman, Martin Mabeifam Ujakpa, William Leslie Brown‐Acquaye, Alfred Coleman, Forgor Lempogo

“…The cascading combination technique was then utilized to develop a multi‐architecture model. With the cascading multi‐architecture technique, we combined all the layers (multiple layers) output of the models and processed them (the output of the multiple layers) in a structured pipeline, which improves upon the previous output. …”
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BAM-SLDK: biologically inspired attention mechanism with spiking learnable delayed kernel synapses by Mario Chacón-Falcón, Alberto Patiño-Saucedo, Luis Camuñas-Mesa, Teresa Serrano-Gotarredona, Bernabé Linares-Barranco

“…However, in order to effectively process data with rich spatial and temporal dependencies, the usual static projections (feedforward and recurrent) among layers of spiking neurons fail to represent all the information needed. …”
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Design and Prototype Verification of a 3-meter Aperture Wrap-rib Reflector by ZHANG Han, YAN Zhongxi, XIANG Ping, WU Minger

“…In order to solve the problem of high stress in the root area of the wrapped wrap-ribs, a method of setting a wrapping guide on the root area of the wrap-ribs was proposed. A finite element model was established based on the material parameters obtained from the tensile test, and the stress during the wrapping process of a single CFRP lenticular tube with a wrapping guide was analyzed using the explicit dynamic method. …”
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Extracting Features from Oblique Ground-Based Multispectral Images for Monitoring Cotton Physiological Response to Nitrogen Treatments by Vaishali Swaminathan, J. Alex Thomasson, Nithya Rajan, Robert G. Hardin

“…A pre-trained monocular depth estimation model (MiDaS) was used to estimate plant height from aligned RGB images and an empirically derived tangential model corrected for perspective distortion. …”
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Prediction of teaching quality in the context of smart education: application of multimodal data fusion and complex network topology structure by Chunzhong Li, Chenglan Liu, Wenliang Ju, Yuanquan Zhong, Yonghui Li

“…Firstly, the article utilized a score management system and intelligent cameras to collect multimodal learning data; then, the original signal was decomposed into detail layers and approximation layers of different frequencies using wavelet transform, and high-frequency detail layers were processed for denoising through threshold functions; afterwards, in order to reduce the network size and parameters, attention mechanism was applied to screen the input features of the neural network; using students, teachers, and learning resources as network nodes, the connections between nodes were analyzed and a complex network topology structure was constructed; then, attention mechanism was used to fuse multimodal data, assigning different weights to each modality, integrating educational information, and highlighting key information in the prediction task. …”
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Cyanoguanidine-Modified Chitosan as an Efficacious Adsorbent for Removing Cupric Ions from Aquatic Solutions: Kinetics, Isotherms, and Mechanisms by Ard elshifa M. E. Mohammed, Nouf F. Al-Harby, Muneera Alrasheedi, Shaimaa M. Ibrahim, Nadia A. Mohamed

“…The adsorbent’s removal efficacy was 96.05%, and the adsorption isotherms, which conform to the Freundlich model, show that adsorption is multi-layered and homogeneous. …”
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Physics informed neural networks for fluid flow analysis with repetitive parameter initialization by Jongmok Lee, Seungmin Shin, Taewan Kim, Bumsoo Park, Ho Choi, Anna Lee, Minseok Choi, Seungchul Lee

“…Furthermore, principal component analysis confirmed its capability to dynamically modulate model parameters during the training process. These results show the effectiveness of the proposed training strategy in addressing stiff fluid problems. …”
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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…The predicted locations of MS lesions were compared with the corresponding layers of white matter, gray matter, and cerebrospinal fluid within the brain. …”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…The architecture is composed of multiple convolutional and pooling layers, ensuring both depth and performance efficiency. …”
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BRYANSK-KURSK-VORONEZH INTRA-CONTINENTAL COLLISIONAL OROGEN (EAST EUROPEAN CRATON) by M. V. Mints, W. A. Bush, S. N. Ageev

“…It is difficult or impossible to explain specific features of the structure and evolution of the orogen in framework of the model of the Cordilleras type  accretionary orogen. …”
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VAE-Based Real-Time Anomaly Detection Approach for Enhanced V2X Communication Security by Yonas Teweldemedhin Gebrezgiher, Sekione Reward Jeremiah, Stefanos Gritzalis, Jong Hyuk Park

“…This paper proposes a real-time anomaly detection framework that integrates the reconstruction capabilities of Variational Autoencoders (VAEs) with the feature extraction power of Convolutional Neural Networks (CNNs). Our model processes streaming data using a sliding window mechanism, ensuring prompt detection of anomalies in the dynamic V2X environment. …”
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A Novel Multi-Objective Fuzzy Deep Learning Framework for Predictive Maintenance in Industrial Internet of Things by Jiangang Feng, Jicheng Kan

“…This paper introduces MO-FCNN, a novel PdM model that integrates fuzzy logic with deep convolutional neural networks (DCNN) to manage data uncertainty and utilizes non-dominated sorting biogeography-based optimization (NSBBO) to improve the overall maintenance decision-making process. …”
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High-resolution 3D spatial distribution of complex microbial colonies revealed by mass spectrometry imaging by Yuting Shen, Yisu Wang, Jianing Wang, Peisi Xie, Chengyi Xie, Yanyan Chen, Niaz Banaei, Kangning Ren, Zongwei Cai

“…Moreover, analyzed colonies are revived into 3D models, vividly depicting molecular distribution from inner to outer layers. …”
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Fracturing simulation with different perforation positions at deep coal seam and roof/ floor rock — case study at the No.8 deep coal seam of a gas field in the Ordos basin by Dong XIONG, Jiayuan HE, Xinfang MA, Zhaoliang QU, Tiankui GUO, Shiyu MA

“…The No.8 deep coal seam in the Ordos basin is situated at a burial depth of over 2 000 meters and has a complex geological structure. The roof and floor layers of the target coal seam are composed of limestone and mudstone, respectively. …”
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