Evaluation of Wear Resistance of a Modified Radial Bearing Design Taking into Account Compressibility and Viscosity of the Lubricant by E. A. Bolgova, M. A. Mukutadze, V. M. Prikhodko, I. A. Kolobov

“…In the literature, the composites used to strengthen the bearing surface are compared, the most effective compositions are determined, and the advantages and disadvantages of the components are analyzed. Mathematical models have been proposed and tested for some of the processes of the interaction under consideration, and acceptable adequacy has been proved for some of them. …”
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Design and Numerical Simulation of a Device for Film–Soil Vibrating Conveying and Separation Based on DEM–MBD Coupling by Shilong Shen, Jiaxi Zhang, Hu Zhang, Yongxin Jiang, Xin Zhou, Yichao Wang, Xuanfeng Liu, Haichun Zhang

“…By establishing a mechanical model for the balanced conveyance of the film–soil composite, the range of conveyor chain inclination angles enabling stable transport was determined. …”
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Effect of wall design on heat loss and drying kinetics in a solar greenhouse for yellow pepper by Leonard Akuwueke, Godwin Usoh, Godwin Akpan, Ibeh Mathew, George Uwadiegwu Alaneme, Etim Promise, Ekop Inemesit, Felix U. Asoiro, M. C. Ndukwu

“…Comparative analysis revealed significant variations in energy payback time (0.8581–0.8632 years) and embodied energy (626.67-627.77 kWh) across configurations. Thin layer models were used to predict the drying curve of yellow pepper for the three solar greenhouse dryer configurations. …”
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A Multi-Scale Deep Learning Framework Combining MobileViT-ECA and LSTM for Accurate ECG Analysis by Abduljabbar S. Ba Mahel, Mehdhar S. A. M. Al-Gaashani, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Mohammed Saleh Ali Muthanna, Ammar Muthanna, Ahmed Aziz

“…The proposed model outperforms existing methods on the same AF dataset, demonstrating its superior performance. …”
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An artificial intelligence approach to palaeogeographic studies: a case study of the Late Ordovician brachiopods of Laurentia by Akbar Sohrabi

“…Figure (6) shows the TANSIG and PURLIN transfer functions which were considered from layers one to two and from layers two to three. In order to measure the reliability of the neural network model, the mean square error performance function was used. …”
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Deep learning based bio-metric authentication system using a high temporal/frequency resolution transform by Sajjad Maleki Lonbar, Akram Beigi, Nasour Bagheri, Nasour Bagheri, Pedro Peris-Lopez, Carmen Camara

“…The results from the NSRDB and MITDB datasets reflect the high reliability of the model, with exceptionally low error rates. This approach could be extended to other biometric modalities or combined with additional layers of security to enhance its practical applications. …”
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All-optical combinational logical units featuring fifth-order cascade by Haiqi Gao, Yu Shao, Yipeng Chen, Junren Wen, Yuchuan Shao, Yueguang Zhang, Weidong Shen, Chenying Yang

“…Extensive simulations and experimental validations demonstrate the potential of the model as a foundational technology for future optical computing architectures, which paves the way toward more sustainable and efficient optical data processing platforms.…”
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Characterization of reactive oxidized nitrogen in the global upper troposphere using recent and historic commercial and research aircraft campaigns and GEOS-Chem by N. Wei, E. A. Marais, G. Lu, G. Lu, R. G. Ryan, R. G. Ryan, B. Sauvage

“…A model underestimate in MPN of at least <span class="inline-formula">∼</span> 50 pptv (13-fold) over the Southeast US results from uncertainties in processes that sustain MPN production as air ages. …”
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Landslides and sinkholes of the karst environment in the vicinity of the Ufa river by N. A. Orlova

“…As a result of the conducted route reconnaissance and geological engineering surveys, data about the development pattern of exogenous processes at a site adjoining the city of Ufa were obtained. …”
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A novel sub-network level ensemble deep neural network with a regularized loss function to improve prediction performance by Jalil Toosifar, Yahya Forghani, Seyyed Abed Hosseini, Nasser Shoeibi

“…Ensemble learning is a well-established technique to improve the accuracy and generalization of neural networks by aggregating multiple models. Unlike conventional ensemble methods that combine the final outputs of independent models, this paper introduces a novel sub-network-level ensemble approach which integrates neurons, layers, and blocks within a single network. …”
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MSCPUnet: A multi-task neural network for plot-level crop classification in complex agricultural areas by Kedi Fang, Shengwei Zhang, Yongting Han, Lin Yang, Meng Luo, Lu Liu, Qian Zhang, Bo Wang

“…MSCPUnet is based on the Unet model and enhances performance through the incorporation of attention mechanisms, multi-scale pooling layers, and a multi-task learning approach for parallel processing. …”
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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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Is additive manufacturing of patient-specific implant is beneficial for orthopedics by Aleena Ariz, Ilma Tasneem, Devyani Bharti, Abhishek Vaish, Abid Haleem, Mohd Javaid

“…The part is manufactured layer by layer, using different materials such as metal, plastic, nylon, and over a hundred other materials. …”
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Representation Learning of Multi-Spectral Earth Observation Time Series and Evaluation for Crop Type Classification by Andrea González-Ramírez, Clement Atzberger, Deni Torres-Roman, Josué López

“…The proposed methodology includes a set of single-layer AEs with a very limited number of neurons, each one trained with the mono-temporal spectral features of a small set of samples belonging to a class, resulting in a model capable of processing very large areas in a short computational time. …”
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Automating multi-task learning on optical neural networks with weight sharing and physical rotation by Shanglin Zhou, Yingjie Li, Weilu Gao, Cunxi Yu, Caiwen Ding

“…Second, we leverage the rotability of the physical optical system and replace task-specific layers with rotation of the corresponding shared layers. …”
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A Multiscale Convolution SAR Image Target Recognition Method Based on Complex-Valued Neural Networks by Guangyu Hou, Zhihui Xin, Guisheng Liao, Penghui Huang, Yuhao Huang, Rui Zou

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The pulsatory liposome works as a neuronal network (II) by Dumitru POPESCU, Diana Rodica RADNEF-CONSTANTIN, Valentin Ioan Remus NICULESCU

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Bridging Biomimetics and Additive Manufacturing for Dynamic Design Solutions by Silvia Titotto

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Numerical Simulation of the Impact of Oxygen Enrichment Technology on Fuel Combustion and CO Emissions During Sintering by Zhen LI, Zhengjian LIU, Jianliang ZHANG, Yaozu WANG

“…Against the backdrop of China′s "Dual Carbon", CO emission reduction technologies are crucial in the sintering process. We employed Computational Fluid Dynamics (CFD) to develop separate models for the combustion of fuel particles and for sintering machines. …”
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Effect of intrinsic heat treatment on the microstructure and mechanical properties of Al-Cu alloy fabricated by wire arc directed energy deposition by Bin Yang, Xiaodong Li, Shuang Lei, Yating Li, Xinyuan Jin, Guoping Zhao, Xianfeng Li

“…Abstract Wire arc directed energy deposition (WADED) represents an appealing approach for producing complex, large-scale, and three-dimensional metallic components from metallic wire, guided by computer-aided design models. In the additive manufacturing process, where components are incrementally constructed layer upon layer, the deposited material experiences a recurring series of temperature fluctuations, essentially undergoing reheating cycles. …”
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