Index-Based Neural Network Framework for Truss Structural Analysis via a Mechanics-Informed Augmented Lagrangian Approach by Hyeonju Ha, Sudeok Shon, Seungjae Lee

“…The IBNN framework approximates member forces and nodal displacements using separate neural networks and incorporates structural equations derived from the force method as mechanics-informed constraints within the loss function. Training was conducted using the Augmented Lagrangian Method (ALM), which improves the convergence stability and learning efficiency through a combination of penalty terms and Lagrange multipliers. …”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Following that, machine learning (ML) models are constructed based on the prominent pro-groups, which enable the extraction of promising biomarkers for distinguishing BRCA sub-types. …”
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Brain Neurotrophins and Plant Polyphenols: A Powerful Connection by Marco Fiore, Sergio Terracina, Giampiero Ferraguti

“…Together, these effects contribute to potentiated enhanced synaptic function, neuronal integrity, and better learning and memory processes. …”
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Study on GPR Image Restoration for Urban Complex Road Surfaces Using an Improved CycleGAN by Xinxin Huang, Jialin Liu, Feng Yang, Xu Qiao, Liang Gao, Tingyang Fu, Jianshe Zhao

“…To address these issues, this study proposes an innovative strategy using unsupervised learning for GPR image restoration. Specifically, it utilizes the Cycle-Consistent Adversarial Network (CycleGAN) with the Convolutional Block Attention Module (CBAM) generator and integrates the Multi-Scale Structural Similarity Index (MS-SSIM) loss function to enhance restoration quality. …”
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A PRISMA systematic review through time on predictive musculoskeletal simulations by Menthy Denayer, Eligia Alfio, María Alejandra Díaz, Massimo Sartori, Friedl De Groote, Kevin De Pauw, Tom Verstraten

“…We recognize six classes of cost function terms and note they are often combined using linear combinations. …”
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Advanced dynamic ensemble framework with explainability driven insights for precision brain tumor classification across datasets by Retinderdeep Singh, Sheifali Gupta, Ashraf Osman Ibrahim, Lubna A. Gabralla, Salil Bharany, Ateeq Ur Rehman, Seada Hussen

“…This study proposes a novel ensemble deep learning system for accurate brain tumor classification using MRI data. …”
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Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…Finally, the Mish activation function is applied in deep convolutional layers to maintain feature extraction accuracy and mitigate overfitting. …”
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Repurposing nicardipine leads to improved development in a young patient with Pitt–Hopkins syndrome by Marta Agnes Somorai, Marta Agnes Somorai, Marta Agnes Somorai, Sean Ekins, Claudia Rupprecht, Clara Lettl, Volker Mall, Volker Mall, Volker Mall

“…We describe a drug repurposing treatment involving the use of nicardipine in a young patient with Pitt-Hopkins syndrome (a rare neurodevelopmental disorder that results from variants of TCF4 gene) as a bench-to-bedside approach. Loss of TCF4 function in Pitt–Hopkins syndrome leads to increased excitability of Nav1.8 in neurons. …”
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Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. …”
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Sec-CLOCs: Multimodal Back-End Fusion-Based Object Detection Algorithm in Snowy Scenes by Rui Gong, Xiangsuo Fan, Dengsheng Cai, You Lu

“…First, the quality of image data is enhanced through the Two-stage Knowledge Learning and Multi-contrastive Regularization (TKLMR) image processing algorithm. …”
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Energy-Efficient Coverage of Rechargeable UAV Networks in Forest Scenarios by Chi Zheng, Ting Su, Jianming Liu, Kuo Chi, Yongqin Yang

“…We first designed an energy efficiency objective function based on the finite difference time domain method (FDTD) radio wave propagation model, and the energy efficiency coverage problem is formulated as a constrained optimization problem. …”
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Automated classification of epileptic seizures using modified one-dimensional convolution neural network based on empirical mode decomposition with high accuracy by Ibtihal Hassan Elshekhidris, Magdi B. M. Amien, Ahmed Fragoon

“…We used the stationary wavelet transform with mother function symlet2 for denoising EEG signal and used the empirical mode decomposition for signal decomposition. …”
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A study on the detection of conductor quantity in cable cores based on YOLO-cable by Xiaoguang Xu, Jiale Ding, Qi’an Ding, Qikai Wang, Yi Xun

“…This study provides new insights and technical support for the application of deep learning in industrial inspections.…”
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The Lowering of the Horizon Line in the Representation of Terrain: from the Cartographic Vision to the View of the Landscape by Fernando Linares García

“…Representing a landscape requires some prior instruction to be able to understand it, it requires prior learning. In the West, painting and geography have been provided to serve that function. …”
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Convolutional Edge Constraint-Based U-Net for Salient Object Detection by Le Han, Xuelong Li, Yongsheng Dong

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DSR-YOLO: A lightweight and efficient YOLOv8 model for enhanced pedestrian detection by Mustapha Oussouaddi, Omar Bouazizi, Aimad El mourabit, Zine el Abidine Alaoui Ismaili, Yassine Attaoui, Mohamed Chentouf

“…A second version of the C2f block using SimAM and standard convolutions ensures robust feature extraction in deeper layers with optimized computational efficiency. The WIoUv3 loss function was utilized to reduce the regression loss associated with bounding boxes, further boosting the performance. …”
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Design of a Classification Recognition Model for Bone and Muscle Anatomical Imaging Based on Convolutional Neural Network and 3D Magnetic Resonance by Ting Pan, Yang Yang

“…After that, a new activation function Mish is introduced, and its advantages over other activation functions are experimentally demonstrated. …”
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Novel nonlinear wind power prediction based on improved iterative algorithm by Fu Zhen-yu, Lin Gui-quan, Tian Wei-da, Pan Zhi-hao, Zhang Wei-cong

“…To effectively improve the accuracy of wind power prediction and reduce the load on the power grid, a new nonlinear wind power prediction model based on an improved iterative learning algorithm was investigated. Firstly, the actual wind conditions are equated to a non-linear model. …”
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DAHD-YOLO: A New High Robustness and Real-Time Method for Smoking Detection by Jianfei Zhang, Chengwei Jiang

“…Recent advancements in AI technologies have driven the extensive adoption of deep learning architectures for recognizing human behavioral patterns. …”
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Altered Short-Term Synaptic Plasticity in Mice Lacking the Metabotropic Glutamate Receptor mGlu7 by Trevor J. Bushell, Gilles Sansig, Valerie J. Collett, Herman van der Putten, Graham L. Collingridge

“…This input, the Schaffer collateral-commissural pathway, displays robust long-term potentiation (LTP), a process believed to utilise molecular mechanisms that are key processes involved in the synaptic basis of learning and memory. To investigate the possible function in LTP of mGlu7 receptors, a subtype for which no specific antagonists exist, we generated a mouse lacking this receptor, by homologous recombination. …”
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