Curvature-Adaptive Learning Rate Optimizer: Theoretical Insights and Empirical Evaluation on Neural Network Training by Kehelwala Dewage Gayan Maduranga

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A Review of Short-Term, Long-Term, and Memory Consolidation Mechanisms in the Hippocampus and Cerebral Cortex by Zuomin Yang, Anis Salwa Binti Mohd Khairuddin, Joon Huang Chuah, Wei Ru Wong, Hafiz Muhammad Fahad Noman, Tri Wahyu Oktaviana Putri, Xin Xu, Md Minhazul Haq

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Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

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Prosumer Cost Efficiency and Ensuring Grid Stability Through a Hierarchical PPO Framework in Decentralized Community Energy Management by Ajay Singh, Bijaya Ketan Panigrahi

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Learning Dendritic-Neuron-Based Motion Detection for RGB Images: A Biomimetic Approach by Tianqi Chen, Yuki Todo, Zhiyu Qiu, Yuxiao Hua, Delai Qiu, Xugang Wang, Zheng Tang

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A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions by Zhenyu Zhou, Lulu Wang, Gongjie Liu, Yuchen Li, Zhiyuan Guan, Zixuan Zhang, Pengfei Li, Yifei Pei, Jianhui Zhao, Jiameng Sun, Yahong Wang, Yiduo Shao, Xiaobing Yan

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Classification of iPSC-derived cultures using convolutional neural networks to identify single differentiated neurons for isolation or measurement by Purva Patel, Lina K. Mohammed Ali, Uma Kaushik, Mallory Wright, Kaylee Green, Jason E. Waligorski, Colin L. Kremitzki, Graham W. Bachman, Serena N. Elia, William J. Buchser

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Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach by Ajit Kumar Rout, P.K. Dash, Rajashree Dash, Ranjeeta Bisoi

“…The paper presents a low complexity recurrent Functional Link Artificial Neural Network for predicting the financial time series data like the stock market indices over a time frame varying from 1 day ahead to 1 month ahead. …”
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Reconstructing Equatorial Electron Flux Measurements From Low‐Earth‐Orbit: A Conjunction Based Framework by D. L. Stumbaugh, J. Bortnik, S. G. Claudepierre

“…Abstract We present an artificial neural network model that reconstructs >30 keV electron flux measurements near the geomagnetic equator from low‐Earth‐orbit (LEO) observations, exploiting the global coherent nature of the high‐energy trapped electrons that constitute the radiation belts. …”
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Common and distinct neural underpinnings of the association between childhood maltreatment and depression and aggressive behavior by Yuan Li, Ting Zhang, Xin Hou, Xiaoyi Chen, Yu Mao

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CFD investigation and ANN prediction of heat transfer coefficient for fully developed turbulent air flow around double V-baffle turbulators by Abdulaziz Alasiri, H.E. Fawaz

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Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

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Reconfigurable neuromorphic functions in antiferroelectric transistors through coupled polarization switching and charge trapping dynamics by Jing Gao, Yu-Chieh Chien, Jiali Huo, Lingqi Li, Haofei Zheng, Heng Xiang, Kah-Wee Ang

“…Additionally, we further demonstrate synaptic and neuronal functions for implementing unsupervised learning rules and spiking behavior in spiking neural networks. …”
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Embedded Legendre expansion layer of physics-informed neural network with restarting strategy in solving partial differential equation in fluid dynamics by Danang A. Pratama, Maharani A. Bakar, Ruwaidiah Idris, Norizan Mohamed

“…On the other hand, single-layer Functional Link Artificial Neural Network (FLANN) has been a topic of interest in the field of artificial intelligence due to its unique architecture and computational efficiency. …”
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Estudio y simulación de las deformaciones corticales asociadas a la variación del campo gravitacional, usando redes neuronales artificiales by Figueredo Báez Yaqueline, Díaz Ramiro

“…These deformations can be used for the calculation of the gravity anomaly and magnetic anomaly through the method of Talwani. The neural computation assimilates the biological neurons as process elements that are assumed as the gravity information and the magnetic information in the inverse problem, being processed in a Neural Network Artificial with architecture Hopfield and in a Neural Network Artificial with structure cluster.…”
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Expanding structural insights into DNA packaging apparatus and endolysin LysSA05 function of Epsilon15 bacteriophage by Muhammad Saleem Iqbal Khan, Ju Wu, Shenlin Ji, Demeng Tan, Bingrui Sui, Shanshan Peng, Jinbiao Zhan, Jiajun Yin

“…Concurrently, we characterized LysSA05, a dual-acting endolysin harboring a glycoside hydrolase 19 (GH19) catalytic domain accommodating peptidoglycan (PG) residues N-acetylmuramic acid (NAM) and N-acetylglucosamine (NAG) through structural docking, indicating plausible binding interactions that promote hydrolysis support vector machine (SVM), random forest (RF), discriminant analysis (DA), artificial neural network (ANN) and physicochemical scanning identified an amphipathic helix (residues 59-112) with predicted antimicrobial peptide (AMP)-like properties. …”
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Optimizing Graphene Oxide Content in Cellulose Matrices: A Comprehensive Review on Enhancing the Structural and Functional Performance of Composites by Ghazaleh Ramezani, Ion Stiharu, Theo G. M. van de Ven, Vahe Nerguizian

“…Various optimization techniques, including response surface methodology, particle swarm optimization, and artificial neural networks, have been employed to identify optimal graphene concentrations and processing conditions. …”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…From this number of samples, 150 data were separated for training data and 48 data as model test based on a random function. In the last stage, i.e. modeling, the adaptive neural-fuzzy inference method was used for the model. …”
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Dynamic Analysis and FPGA Implementation of Fractional-Order Hopfield Networks with Memristive Synapse by Andrés Anzo-Hernández, Ernesto Zambrano-Serrano, Miguel Angel Platas-Garza, Christos Volos

“…When integrated into systems like Hopfield neural networks, memristors enable the study of complex dynamic behaviors, such as chaos and multistability. …”
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AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction by Kecheng Huang, Chujun Wu, Rongpeng Pi, Jieyu Fang

“…AI frameworks, particularly convolutional neural networks and hybrid models like TD-CNNLSTM-LungNet, demonstrate exceptional performance in detecting pulmonary inflammation and stratifying hypoxemia risk, achieving up to 96.57% accuracy in pneumonia subtype differentiation and an area under the curve of 0.96 for postoperative hypoxemia prediction. …”
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