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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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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Predicting the compressive strength of polymer-infused bricks: A machine learning approach with SHAP interpretability by Sathvik Sharath Chandra, Rakesh Kumar, Archudha Arjunasamy, Sakshi Galagali, Adithya Tantri, Sujay Raghavendra Naganna

“…The primary innovation lies in leveraging advanced machine learning techniques, namely, artificial neural networks (ANN), support vector machines (SVM), Random Forest and AdaBoost to predict the compressive strength of these Polymer-infused bricks. …”
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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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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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A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging by Joy Chakra Bortty, Gouri Shankar Chakraborty, Inshad Rahman Noman, Salil Batra, Joy Das, Kanchon Kumar Bishnu, Md Tanvir Rahman Tarafder, Araf Islam

“…<b>Background/Objectives:</b> Alzheimer’s disease (AD) is a progressive, neurodegenerative disorder, which causes memory loss and loss of cognitive functioning, along with behavioral changes. Early detection is important to delay disease progression, timely intervention and to increase patients’ and caregivers’ quality of life (QoL). …”
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A method for detection of functional deficiencies due to unilateral vestibular impairment using the TUG test and IMU sensors by Marek Kamiński, Rafał Kotas, Wojciech Tylman, Magdalena Janc, Ewa Zamysłowska-Szmytke, Magdalena Józefowicz-Korczyńska

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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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Automated bone scan index as predictors of survival in prostate cancer by Joko Wiyanto, Rini Shintawati, Budi Darmawan, Basuki Hidayat, Achmad Kartamihardja

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Dynamics of specialization in neural modules under resource constraints by Gabriel Béna, Dan F. M. Goodman

“…Using a simple, toy artificial neural network setup that allows for precise control, we find that structural modularity does not in general guarantee functional specialization (across multiple measures of specialization). …”
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Application of artificial intelligence for commodity identification for customs purposes by Galina Yu. Fedotova, Anna Yu. Komelova

“…As a model, the neural network of artificial intelligence developed by the World Customs Organization is used. …”
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Effect of Artificial Food Additives on Lung Health—An Overview by Yousef Saad Aldabayan

“…Flavoring agents such as diacetyl contribute to occupational respiratory diseases like bronchiolitis obliterans. In animal models, prenatal exposure to additives, such as titanium dioxide (E171), might disrupt the development of respiratory neural networks, with long-term consequences. …”
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