The response characteristics and stability evaluation of vegetated slope under strong wind by Yanlin Liu, Fei Wang, Feng Ji, Lianhua Zhang, Jianjun Zhao, Chen Zheng, Jibin Chen

“…The influence of wind and vegetation conditions on slope dynamic parameters and soil strength parameters were subsequently determined through numerical simulations using FLAC3D software, model tests, and direct shear tests. …”
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Ejection fraction, B-lines, and global longitudinal strain evaluated with rest transthoracic echocardiography to assess prognosis in patients with chronic coronary syndromes by Lauro Cortigiani, Maria Francesca Orsino, Marco Favilli, Francesco Bovenzi

“…Integrated TTE score ranged from 0 (all 3 parameters normal) to 3 (all parameters abnormal). All patients were followed-up and a composite endpoint was considered, including all-cause death, acute coronary syndrome (ACS), and myocardial revascularization. …”
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FFM: Flood Forecasting Model Using Federated Learning by Muhammad Shoaib Farooq, Rabia Tehseen, Junaid Nasir Qureshi, Uzma Omer, Rimsha Yaqoob, Hafiz Abdullah Tanweer, Zabihullah Atal

“…Federated Learning is the most advanced technique of machine learning (ML) that guarantees data privacy, ensures data availability, promises data security, and handles network latency trials inherent in prediction of floods by prohibiting data to be transferred over the network for model training. …”
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Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images by Mahmoud Ragab, Iyad Katib, Sanaa A. Sharaf, Hassan A. Alterazi, Alanoud Subahi, Sana G. Alattas, Sami Saeed Binyamin, Jaber Alyami

“…Besides, the squeeze-excitation ResNet (SE-ResNet50) model is applied to derive feature vectors, and its parameters are fine-tuned by the design of the EO model. …”
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Dynamic reconstruction of electroencephalogram data using RBF neural networks by Xuan Wang, Congcong Du, Xianjin Ke, Jian Zhang, Zheng Zheng, Yayan Yue, Ming Yu

“…IntroductionElectroencephalography (EEG) is widely used for analyzing brain activity; however, the nonlinear and nature of EEG signals presents significant challenges for traditional analysis methods. Machine has shown great promise in addressing these limitations. …”
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A model for classifying information objects using neural networks and fuzzy logic by Vadym Mukhin, Valerii Zavgorodnii, Viacheslav Liskin, Sergiy Syrota, Aleksandra Czupryna-Nowak, Bohdan Rusyn, Arkadiusz Banasik, Jacek Woloszyn, Wojciech Kempa

“…This approach combines the advantages of neural machine learning with the flexibility and efficiency of fuzzy logic, making these systems effective tools for solving problems related to fuzzy or uncertain data. …”
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Bridging experiments and models, towards a new paradigm: DROP-PINN, a physics-informed neural network to predict droplet rupture in multiphase systems by Grégory Bana, Fabrice Lamadie, Sophie Charton, Didier Lucor, Nida Sheibat-Othman

“…In this study, we focus on the breakage phenomenon. Recent advances in machine learning, particularly Artificial Neural Networks (ANNs), present new opportunities for predicting the breakage frequencies. …”
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Aerodynamic analysis and ANN-based optimization of NACA airfoils for enhanced UAV performance by Sanan H. Khan, Mohd Danish, Md. Ayaz, Afsar Husain, Shamma Saeed, Shamma Abdulla, Shama Shaheen, Alia Saeed, Ahmed Thaher

“…Overall, this study highlighted the potential of combining computational techniques and machine- learning models to optimize UAV airfoil designs. …”
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AI-Driven Optimization of Fly Ash-Based Geopolymer Concrete for Sustainable High Strength and CO₂ Reduction: An Application of Hybrid Taguchi–Grey–ANN Approach by Muhammad Usman Siddiq, Muhammad Kashif Anwar, Faris H. Almansour, Muhammad Ahmed Qurashi, Muhammad Adeel

“…This study addresses this challenge by developing machine learning-optimized geopolymer concrete (GPC) using industrial waste fly ash as cement replacement. …”
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Computational optimization of 3D printed bone scaffolds using orthogonal array-driven FEA and neural network modeling by Amulya Shetty, Aamirah Fathima, B Anika, Raviraj Shetty, Vinyas, J.P. Supriya, Adithya Hegde

“…The novelty of this work lies in its integrative, multi-modal approach that synergizes experimental design, machine learning-based predictive modeling, and simulation. …”
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Optimization of LED Lighting Strategies using Multi-Spectral Imaging for Enhanced Crop Growth in Vertical Farming Systems by Al-Farouni Mohammed, Ramadan Ghazi Mohamad, Rao G. Mallikarjuna

“…Therefore, this system provides sophisticated control of lighting parameters that respond to environmental changes and plant responses. …”
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An automated adaptive trading system for enhanced performance of emerging market portfolios by Cristiana Tudor, Robert Sova

“…This is done by implementing a recursive window technique and running a user-specified fitness function to dynamically optimize the mean equation parameters throughout the lead time. Back-testing several configurations of the flexible AATS consistently reveals its superiority while assuring the robustness of the results. …”
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CFS-MOES Ensemble Model on Metaheuristic Search-Based Feature Selection by Santosini Bhutia, Bichitrananda Patra, Mitrabinda Ray

“…Due to the availability of highly specialized cancer datasets, molecular classification of cancer by gene expression, machine learning, and deep learning, a part of artificial intelligence (AI) techniques is used in detecting the disease. …”
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Automatic extraction of upper-limb kinematic activity using deep learning-based markerless tracking during deep brain stimulation implantation for Parkinson's disease: A proof of c... by Sunderland Baker, Anand Tekriwal, Gidon Felsen, Elijah Christensen, Lisa Hirt, Steven G Ojemann, Daniel R Kramer, Drew S Kern, John A Thompson

“…A semi-supervised classification model, support vector machine (SVM), trained on the parameters defined by the parabolic fit reliably predicted movement type. …”
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Impact of climate change on river flow, using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin by Fatemeh Avazpour, Mohammad Reza Hadian, Ali Talebi, Ali Torabi Haghighi

“…This study highlights the value of machine learning models in river flow forecasting and the importance of incorporating projections of climate change into water resource management plans to address the impacts of climate change in semi-arid regions.…”
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Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone by Yuyu Sun, Yuchen Zhang, Zhiguo Zhao

“…Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models. …”
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A Lightweight YOLOv8s Algorithm for Ceiling Fan Blade Defect Detection With Optimized Pruning and Knowledge Distillation by Qinyuan Huang, Chen Fan, Yuqi Sun, Jiaxiong Huang, Wengziyang Jiang

“…Experimental results confirm that our algorithm achieves an mAP of 0.976 and operates at 91.4 FPS, while reducing the number of parameters by 76.6% and floating-point operations by 85.2%. …”
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Innovative Technologies and Technical Means for Industrial Nursery Farming by A. A. Zavrazhnov, A. Yu. Izmaylov, A. I. Zavrazhnov, Ya. P. Lobachevskiy, V. Yu. Lantsev

“…In this respect, VIM and Michurinsk State Agrarian University have developed a system of high-clearance machines, taking into account the nursery area, thus providing for effi cient production. …”
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Research on muck conditioning for EPB shield tunnelling in composite formation by Yalong Jiang, Xin Tang, Bitang Zhu, Kai Zhou, Yucong Pan, Changjie Xu

“…According to the analysis of the field tunnelling parameters, including penetration rate, total shield thrust and cutterhead torque, the optimization of the muck conditioning scheme proposed based on laboratory tests is proved effective and deserves further application.…”
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A systems biology approach to define SARS-CoV-2 correlates of protection by Caolann Brady, Tom Tipton, Oliver Carnell, Stephanie Longet, Karen Gooch, Yper Hall, Javier Salguero, Adriana Tomic, Miles Carroll

“…Abstract Correlates of protection (CoPs) for SARS-CoV-2 have yet to be sufficiently defined. This study uses the machine learning platform, SIMON, to accurately predict the immunological parameters that reduced clinical pathology or viral load following SARS-CoV-2 challenge in a cohort of 90 non-human primates. …”
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