CPFD Simulation of Operation Characteristics of a 10t/d Sludge and Biomass Co-incineration Fluidized Bed Reactor by REN Shaohui, YU Qiao, LIN Li, XIANG Jiatao, MA Lun, ZHANG Shihong

“…The work provides foundational insights for scaling sustainable co-processing systems that address sludge disposal challenges and biomass utilization.MethodsNumerical simulations employed Barracuda™ VR 17.3.0's Multi-Phase Particle-in-Cell (MP-PIC) algorithm, resolving gas-solid reactive flows in a 3D reactor comprising a lower cylindrical section (Ø0.7 m×H1.7 m), upper expansion zone (Ø1.3 m× H3.8 m), and conical transition (H0.5m). …”
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Investigation of aromatic compounds and olfactory profiles in cocoa pulp fermentation using yeast-based starters: A Volatilomics and machine learning approach by Haode Chang, Chunhe Gu, Quanmiao Zhang, Wenjing Zhang, Liru Ma, Fei Liu, Zhen Feng

“…The models showed high prediction accuracy, ranging from 0.85 for sourness by Gradient Boost Machine to 0.28 for sweetness by linear regression. …”
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Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
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A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders by Jorge Magalhães, Tomás Jorge, Rúben Silva, António Guedes, Diogo Ribeiro, Andreia Meixedo, Araliya Mosleh, Cecília Vale, Pedro Montenegro, Alexandre Cury

“…This automatic damage identification algorithm is based on the vertical acceleration evaluated on the rails using a virtual wayside monitoring system and involves the application of a two-step procedure. …”
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A damage model that can be coupled with constitutive behavior prior to necking for SGAFC 780 steel by Seong Jin Lee, Taek Jin Jang, Hyunho Shin, Yongwon Ju, Sangho Bae, Jong-Bong Kim

“…They also predicted damage contours that reasonably correspond to the moments and locations of cracks observed during the tensile fracture tests. …”
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Investigating the Short-Circuit Problem Using the Planarity Index of Complex q-Rung Orthopair Fuzzy Planar Graphs by Abrar Hussain, Ahmed Alsanad, Kifayat Ullah, Zeeshan Ali, Muhammad Kamran Jamil, Mogeeb A. A. Mosleh

“…Some advantages of the projected study over the previous study are observed, and some future study is predicted.…”
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A convolutional neural network driven suspension control strategy to enhance sustainability of high-speed trains by Duo Zhang, Hong-Wei Li, Fang-Ru Zhou, Yin-Ying Tang, Qi-Yuan Peng

“…In conjunction with the neural network algorithm, a bi-objective optimization model is further developed and solved to adjust scale factor of the Skyhook controller according to different running conditions. …”
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Multi sensor based monitoring of paralyzed using Emperor Penguin Optimizer and Deep Maxout Network by Vijaya Gunturu, J. Kavitha, Swapna Thouti, N. K. Senthil Kumar, Kamal Poon, Ayman A. Alharbi, Amar Y. Jaffar, V. Saravanan

“…The Emperor Penguin Optimizer Algorithm (EPOA) was used to select the features sent from the Arduino board to the ESP8266-Wi-Fi module. …”
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Modelling current and future forest fire susceptibility in north-eastern Germany by K. H. Horn, K. H. Horn, S. Vulova, S. Vulova, H. Li, B. Kleinschmit

“…We applied a random forest (RF) machine learning (ML) algorithm to model current and future FFS in the federal state of Brandenburg (Germany) using topographic, climatic, anthropogenic, soil, and vegetation predictors. …”
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Preoperative predictors of thrombosis in children with congenital heart disease by V. A. Lastovka, R. F. Tepaev, O. B. Gordeeva, A. R. Bidzhiev, A. A. Chotchaeva

“…The literature describes in detail the disturbances in the hemostasis system observed after cardiac surgeries performed in conditions of artificial circulation, but there are no indicators that could predict the risk of thrombosis in children. The use of parameters of plasma hemostasis as predictors of thrombosis in the algorithm for diagnosing hemocoagulation disorders in children of the first year of life undergoing surgery for congenital heart defects has been substantiated. …”
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A Novel Machine Learning Model for the Automated Diagnosis of Nasal Pathology in Canine Patients by Andreea Istrate, Radu Constantinescu, Lithicka Anandavel, Shraddha Rajeshkumar Tandel, Simon Dye, Charlotte Dye

“…The machine learning algorithm showed reasonable accuracy (86%) in classifying the diagnosis from an isolated scan slice but high accuracy (99%) when aggregating over slices taken from a full scan. …”
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Design and validation of a CFD model for energy-efficient Ni-Co-Mn cathode calcination process by Jaeseop Jo, Minyoung Hwang, Jungeui Lee, Joo Hyun Park

“…The primary objective is to quantitatively predict and optimize energy consumption in high-temperature solid-state synthesis processes. …”
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Data-Driven Approach for Passenger Mobility Pattern Recognition Using Spatiotemporal Embedding by Chao Yu, Haiying Li, Xinyue Xu, Jun Liu, Jianrui Miao, Yitang Wang, Qi Sun

“…Third, a density-based clustering algorithm is introduced to identify passenger mobility patterns based on the embedded dense trip vectors. …”
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NEUF: Learning Point Cloud Quality by Non-Euclidean Fast Filtering by Eleonora Di Salvo, Azeddine Beghdadi, Tiziana Cattai, Chiara Lumare, Gaetano Scarano, Stefania Colonnese

“…This descriptor, along with its saliency-weighted variant, leverages Non-Euclidean Laplacian Filtering (NEUF). The NEUF algorithm extracts descriptors using advanced non-Euclidean filtering techniques and employs regression learning to predict end-users’ perceived subjective quality by optimally selecting the most relevant features. …”
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Determining IFI44 as a key lupus nephritis’s biomarker through bioinformatics and immunohistochemistry by Yue Tan, Xueyao Wang, Deyou Zhang, Jiahui Wang, Shuxian Wang, Jinyu Yu, Hao Wu

“…Additionally, the study characterizes the immune profiles of LN patients through the CIBERSORT algorithm, focusing on the role of interferon-inducible protein 44 (IFI44) as a key biomarker.Results IFI44 shows elevated expression in LN-affected kidneys, compared to healthy controls. …”
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EEG-Driven Arm Movement Decoding: Combining Connectivity and Amplitude Features for Enhanced Brain–Computer Interface Performance by Hamidreza Darvishi, Ahmadreza Mohammadi, Mohammad Hossein Maghami, Meysam Sadeghi, Mohamad Sawan

“…After preprocessing (resampling, normalization, bandpass filtering), FBCSP and multi-lag PLV features were fused, and the ReliefF algorithm selected the most informative subset. A feedforward neural network achieved average metrics of: Pearson correlation 0.829 ± 0.077, R-squared value 0.675 ± 0.126, and root mean square error (RMSE) 0.579 ± 0.098 in predicting EMG amplitudes indicative of arm movement angles. …”
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Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Mapping the landscape of AI and ML in vaccine innovation: A bibliometric study by Jirui Niu, Ruotian Deng, Zipu Dong, Xue Yang, Zhaohui Xing, Yin Yu, Jian Kang

“…However, despite the substantial benefits of AI and ML in vaccine innovation, challenges remain regarding data quality, algorithm reliability, and ethical considerations. …”
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Enhanced variable step sizes perturb and observe MPPT control to reduce energy loss in photovoltaic systems by Abdelkadir Belhadj Djilali, Elhadj Bounadja, Adil Yahdou, Habib Benbouhenni, Z. M. S. Elbarbary, Ilhami Colak, Saad F. Al-Gahtani

“…Compared to traditional algorithms, the proposed approach reduces response time and undershoots by 30%, demonstrating superior reliability and performance. …”
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Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…By integrating Taguchi experimental design with reinforcement learning and metaheuristic algorithms, the model identifies critical environmental and operational parameters that influence fish growth and economic outcomes. …”
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