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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stGRL: spatial domain identification, denoising, and imputation algorithm for spatial transcriptome data based on multi-task graph contrastive representation learning by Xin Lu, Murong Zhou, Bo Gao, Fang Wang, Shuilin Jin, Qiaoming Liu, Guohua Wang

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Structure-Activity Relationship for Fe(III)-Salen-Like Complexes as Potent Anticancer Agents by Zahra Ghanbari, Mohammad R. Housaindokht, Mohammad Izadyar, Mohammad R. Bozorgmehr, Hossein Eshtiagh-Hosseini, Ahmad R. Bahrami, Maryam M. Matin, Maliheh Javan Khoshkholgh

“…The study of structure and activity relationship was performed with multiple linear regression (MLR) and artificial neural network (ANN). In nonlinear method, the adaptive neuro-fuzzy inference system (ANFIS) was applied in order to choose the most effective descriptors. …”
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Ultrasensitive bionic photonic-electronic skin with wide red-shift mechanochromic response by Tianqi Wang, Lei Chen, Haogeng Liu, Haoran Zhu, Zijie Zeng, Yixin Lu, Ping Zhang, Yaofei Chen, Yue Huang, Gui-Shi Liu, Yunhan Luo, Zhe Chen

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Gravitational-wave Parameter Estimation in Non-Gaussian Noise Using Score-based Likelihood Characterization by Ronan Legin, Maximiliano Isi, Kaze W. K. Wong, Yashar Hezaveh, Laurence Perreault-Levasseur

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Non-Destructive Detection of Fillet Fish Quality Using MQ135 Gas Sensor and Neutrosophic Logic-Enhanced System by M. Y. Shams, M. R. Darwesh, Roheet Bhatnagar, N. S. A. Al-Sattary, A. A. Salama, M. S. Ghoname

“…Using the reference neural network algorithm based on chemical and physical compounds, regression coefficients (R values) achieved were 0.99, 0.98, and 0.97, respectively. …”
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Neural correlates of human fear conditioning and sources of variability in 2199 individuals by Joaquim Radua, Hannah S. Savage, Enric Vilajosana, Alec Jamieson, Birgit Abler, Fredrik Åhs, Tom Beckers, Narcís Cardoner, Josh M. Cisler, Juliana B. Diniz, Dominik R. Bach, Sigrid Elsenbruch, Steven G. Greening, Daphne J. Holt, Antonia N. Kaczkurkin, Andreas Keil, Merel Kindt, Kathrin Koch, Kevin S. LaBar, Charlene L. Lam, Christine L. Larson, Tina B. Lonsdorf, Christian J. Merz, Katie A. McLaughlin, Yuval Neria, Daniel S. Pine, Carien M. van Reekum, Alexander J. Shackman, Carles Soriano-Mas, Victor I. Spoormaker, Daniel M. Stout, Benjamin Straube, Thomas Straube, Lauri Tuominen, Renée M. Visser, Laura Ahumada, Volker Arolt, Marcelo C. Batistuzzo, Paulo R. Bazán, Emma E. Biggs, Marta Cano, Pamela Chavarría-Elizondo, Samuel E. Cooper, Udo Dannlowski, Víctor de la Peña-Arteaga, Stephanie N. DeCross, Katharina Domschke, Mana R. Ehlers, John L. Graner, Alfons O. Hamm, Martin J. Herrmann, Ashley A. Huggins, Adriane Icenhour, Asier Juaneda-Seguí, Markus Junghoefer, Tilo Kircher, Katja Koelkebeck, Manuel Kuhn, Franziska Labrenz, Shmuel M. Lissek, Martin Lotze, Ulrike Lueken, Jürgen Margraf, Ignacio Martínez-Zalacaín, Robert Moeck, Jayne Morriss, María Ortuño, Andre Pittig, Daniel Porta-Casteras, Jan Richter, Isabelle C. Ridderbusch, Winfried Rief, Kati Roesmann, Jörgen Rosén, Alena N. Rußmann, Rachel Sjouwerman, Jennifer Spohrs, Andreas Ströhle, Benjamin Suarez-Jimenez, Martin Ulrich, Hans-Ulrich Wittchen, Xi Zhu, Lea Waller, Henrik Walter, Paul M. Thompson, Janna Marie Bas-Hoogendam, Nynke A. Groenewold, Dan J. Stein, Nic J. Van der Wee, Joseph E. Dunsmoor, Andre F. Marquand, Ben J. Harrison, Miquel A. Fullana

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Using artificial intelligence techniques and econometrics model for crypto-price prediction by Abhidha Verma, Jeewesh Jha

“…To achieve accurate predictions for Ethereum's price one day ahead, we develop a hybrid algorithm combining Genetic Algorithms (GA) and Artificial Neural Networks (ANN). Furthermore, regression analysis serves as an additional prediction tool. …”
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From intelligence to autopoiesis: rethinking artificial intelligence through systems theory by Benedikt Zönnchen, Mariya Dzhimova, Gudrun Socher

“…Building on Luhmann's system theory, it is argued that classical Turing machines are not sense-making systems, as they lack both self-reference in the sense of re-entry and the ability to make contingent selections from possibilities. In contrast, artificial neural networks (ANNs) exhibit a novel, loosely coupled interaction with social systems, as they can extract patterns from societal communication. …”
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Evaluation of Data Mining and Artificial Intelligence Methods to Predict Daily Precipitation by Yaseen Ahmed Hamaamin

“…In this study, data mining techniques were applied to metrological data to predict daily precipitation using Multilinear regression (MLR) along with two artificial intelligence (AI) techniques, specifically Artificial Neural Networks (ANN) and Neuro-Fuzzy Inference System (ANFIS). …”
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Deep Reinforcement Learning-Based Multi-Agent System with Advanced Actor–Critic Framework for Complex Environment by Zihao Cui, Kailian Deng, Hongtao Zhang, Zhongyi Zha, Sayed Jobaer

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