Research Framework and Anticipated Results of Key Technologies for Distributed Certificate-less Network Identity Systems by ZHANG Xiaosong, CAO Sheng, LU Tianbo, YANG Kun, GUI Xun, XIE Guotao, NIU Weina

“…This project provides theoretical models and technical methods for digital identity authentication that are suitable for large-scale IoT identity authentication by constructing a high-performance hardware layer and developing multi-level smart contract virtual machines. …”
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2D/2D Heterojunctions of Layered TiO₂ and (NH₄)₂V₃O₈ for Sunlight-Driven Methylene Blue Degradation by Juan Aliaga, Matías Alegria, J. Pedro Donoso, Claudio J. Magon, Igor D. A. Silva, Harold Lozano, Elies Molins, Eglantina Benavente, Guillermo González

“…The photocatalytic results indicate that the 2D/2D heterojunction layered TiO₂/vanadate at a ratio (1:0.050) removed 100% of the methylene blue, used as a model contaminant in this study. …”
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Political Aspects of Digitalization and Networking of the State by D. Yu. Ivanov, V. A. Volkov

“…A meaningful analysis of an extensive layer of scientific publications shows that the digitalization of the state has acquired a mostly problematic connotation. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…This multi-module collaborative architecture effectively processes multi-scale features of time series data while providing model interpretability. …”
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Model Optimization for High-Yield Biocrude in Co-Hydrothermal Liquefaction of Municipal Sludge by Botian HAO, Yunfei DIAO, Ya WEI, Donghai XU

“…In contrast, the ANN employed a three-layer topological structure (3-node input layer, 10-node hidden layer, and 1-node output layer). …”
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A bearing fault diagnosis method based on hybrid artificial intelligence models. by Lijie Sun, Xin Tao, Yanping Lu

“…The process employs Maximum Second-order Cyclostationary Blind Deconvolution (CYCBD) to filter out noise from the vibration signals emitted by bearings; secondly, considering the issue with the conventional Harris Hawks Optimization (HHO) algorithm which tends to prematurely converge to local optima, the differential evolution mutation operator is introduced and the escape energy factor is improved from linear to nonlinear in IHHO; then, a double-layer network model based on DBN-ELM is proposed, to avoid the number of hidden layer nodes of DBN from human experience interference, and IHHO is used to optimize DBN structure, which is denoted as IHHO-DBN-ELM method; with the optimal structure is obtained by using a combined IHHO optimized DBN and ELM; in conclusion, the proposed IHHO-DBN-ELM approach is applied to the bearing fault detection using the Western Reserve University's bearing fault dataset. …”
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Cartwheel aerenchyma in Cardamine amara as a model of schizogenous tissue formation in plants by Hiroshi Kudoh, Masato Sakane, Karol Marhold, Rie Shimizu-Inatsugi, Kentaro K. Shimizu, Hidehiro Fukaki

“…The formation of the aerenchyma was suggested to involve three developmental processes: (1) formation of a three-layered cortex, (2) circumferential division of the outer layer of the cortex, and (3) circumferential detachment of cells in the middle layer of the cortex. …”
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3-D modeling for simultaneous heat and mass transfer in fixed-bed drying of soybean grains applying CFD code by A.R. Visconcini, M. Souza, A.M.S. Costa

“…The drying was developed in a fixed bed considered a porous medium, applying the thermal non-equilibrium mathematical model with the drying kinetics for thin-layers. The constitutive and property equations were developed for soybeans, air, and vapor. …”
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Modeling Electrochemical Impedance Spectroscopy Using Time-Dependent Finite Element Method by Yawar Abbas, Laura van Smeden, Alwin R. M. Verschueren, Marcel A. G. Zevenbergen, Jos F. M. Oudenhoven

“…Developed in COMSOL Multiphysics, the model incorporates ion transport, electric field distribution, Stern layer effects, and electrode sheet resistance, governed by the Poisson and Nernst–Planck equations. …”
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Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data by Nazir Jan, Nasru Minallah, Madiha Sher, Muhammad Wasim, Shahid Khan, Amal Al‐Rasheed, Hazrat Ali

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Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network by Zhe-min LI, Li-guo CUI, Shi-wei XU, Ling-yun WENG, Xiao-xia DONG, Gan-qiong LI, Hai-peng YU

“…In the process of determining the structure of the chaotic neural network, the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension, and then the number of hidden layer nodes is estimated by trial and error. …”
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Landslide Susceptibility Evaluation Based on Empowerment Information Quantity Model of Game Theory by CUI Chengtao, LI Limin, FU Zhentao, REN Ruibin, WANG Lianxia, FENG Qingqing

“…In the process of employing information quantity models for landslide susceptibility zoning,given that the information quantity of influencing factors is directly added or multiplied by a single weight,without considering the main and objective weight of the factor,this paper proposes an evaluation method based on the empowerment information quantity model of game theory.First,the analytic hierarchy process (AHP) is adopted to calculate the subjective weight,the objective weight is determined by the coefficient of variation method,and then the game theory principle is utilized to optimize the main and objective weight to get the combination weight.Meanwhile,the information layer of each evaluation factor is weighted and summed based on the combination weight,and the evaluation results are divided into five categories by the natural intermittent point method.Finally,by taking Shanyang County of Shaanxi Province as the research area,the proposed model is compared with the information quantity model of single weight in landslide-susceptibility zoning maps,zoning point density,and ROC curves respectively.The results show that the accuracy and reliability of the proposed method outperform traditional weighted information measurement methods.…”
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DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Zhenghai Liu

“…To address these limitations, a lightweight and efficient anti-UAV detection model, DRBD-YOLOv8, is proposed in this paper. The model integrates several innovations, including the application of a Re-parameterization Cross-Stage Efficient Layered Attention Network (RCELAN) and a Bidirectional Feature Pyramid Network (BiFPN), to enhance feature processing capabilities while maintaining a lightweight design. …”
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Research on PRBP Neural Network Flood Forecasting Model in Chongyang River Basin by SI Qi, JIN Baoming, LU Wangming, CHEN Zhaoqing

“…The rainfall volume of six rainfall stations in the upper reaches of Chongyang River basin and the previous discharge of Wuyishan Hydrological Station were regarded as input, and its corresponding discharge was regarded as output; the number of hidden layer units was determined by trial calculation, and then PRBP neural network flood forecasting model of Chongyangxi River Basin was established. …”
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Research on PRBP Neural Network Flood Forecasting Model in Chongyang River Basin by SI Qi, JIN Baoming, LU Wangming, CHEN Zhaoqing

“…The rainfall volume of six rainfall stations in the upper reaches of Chongyang River basin and the previous discharge of Wuyishan Hydrological Station were regarded as input, and its corresponding discharge was regarded as output; the number of hidden layer units was determined by trial calculation, and then PRBP neural network flood forecasting model of Chongyangxi River Basin was established. …”
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Somatostatin interneuron fate-mapping and structure in a Pten knockout model of epilepsy by Austin W. Drake, Austin W. Drake, Austin W. Drake, Lilian G. Jerow, Lilian G. Jerow, Justin V. Ruksenas, Carlie McCoy, Steve C. Danzer, Steve C. Danzer, Steve C. Danzer, Steve C. Danzer

“…Surviving SST neurons in the dentate gyrus had larger somas, and the density of GFP+ processes in the dentate molecular layer was unchanged despite SST cell loss and expansion of the molecular layer, implying compensatory sprouting of surviving cells. …”
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Neuron Network Modeling of Intensification of Isogumulone Extraction in a Rotary Pulse Generator by Anton V. Shafrai, Elena A. Safonova, Dmitry M. Borodulin, Yana S. Golovacheva, Sergey A. Ratnikov, Wasfie Barsoom Wasef Kerlos

“…Results and discussion. The resulting model had the following parameters: two hidden layers, 30 neurons each; neuron activation function – GELU; loss function – MSELoss; learning step – 0.001; optimizer – Adam; L2 regularization at 0.00001; training set of four batches, 16 records each; 9,801 epochs. …”
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Modeling of Point Defects Annihilation in Multilayered Cu/Nb Composites under Irradiation by Sarah Fadda, Antonio Mario Locci, Francesco Delogu

“…Layer thickness, temperature, radiation intensity, and surface recombination coefficients were varied systematically to investigate their effect on point defect annihilation processes at interfaces. …”
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Exploring slip flow and heat transfer of power-law fluid past an induced magnetic stretching regime subject to Cattaneo-Christov flux theory by T.H. AlAbdulaal, Sohail Rehman, Hameed Ali, Usman Riaz, Sami Znaidia

“…The power-law fluid, induced magnetic field, and finite thermal relaxation have significant applications in a variety of industrial settings, including thin-layer growth, cooling systems, the extrusion process, and coating and shaping operations in a heat transfer mechanism. …”
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Increasing model resolution improves but overestimates global mid-depth circulation simulation by Haihong Guo, Zhaohui Chen, Ruichen Zhu, Jinzhuo Cai

“…Abstract Increasing the spatial resolution in climate models has significantly improved the simulation of global upper-layer ocean circulation. …”
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