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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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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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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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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Simulation of Quantity and Quality of Saq Aquifer Using Artificial Intelligence and Hydraulic Models by Abdul Razzaq Ghumman, Ghufran Ahmed Pasha, Md. Shafiquzzaman, Afaq Ahmad, Afzal Ahmed, Riaz Akhtar Khan, Rashid Farooq

“…Groundwater modelling with respect to its quantity and quality has been performed in this paper using Artificial Neural Networks (ANNs), Adaptive Neurofuzzy Inference System (ANFIS), and hydraulic model MODFLOW. …”
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Frontotemporal dementia: a systematic review of artificial intelligence approaches in differential diagnosis by Serena Dattola, Augusto Ielo, Giuseppe Varone, Giuseppe Varone, Alberto Cacciola, Angelo Quartarone, Lilla Bonanno

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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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3D in vitro modeling of neural microenvironment through a multi-scaffold assembly approach by Cecilia Traldi, Vanessa Chiappini, Silvia Chasseur, Federica Aiello, Marina Boido, Chiara Tonda-Turo

“…The inclusion of such scaffold in the 3D bioprinted system effectively steers neural cell organization in a 3D setting, guiding neural cell elongation in a preferred direction and promoting the establishment of a functional neural network. …”
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Estimation of Positive‐, Negative‐, and Zero‐Sequence Current and Voltage Phasors of UIPC VSCs for Short‐Circuit Faults in Transmission Lines by Babak Bahadori, Ali Nahavandi, Mahyar Abasi

“…This research presents an estimation scheme utilizing artificial neural networks to determine the magnitude and phase angle of voltage and current in voltage source converters of the UIPC during short‐circuit faults in transmission lines. …”
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Human and artificial visual systems share a computational principle for transforming binocular disparity into depth representation by Bayu Gautama Wundari, Ichiro Fujita, Hiroshi Ban

“…A deep neural network (DNN) trained for stereo vision undergoes a similar transformation across its layers, progressing through distinct phases that exploit dissimilar features to achieve coherent depth. …”
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Role of Artificial Intelligence and Deep Learning in Easier Skin Cancer Detection through Antioxidants Present in Food by Sreevidya R. C., Jalaja G, Sajitha N, D. Lakshmi Padmaja, S. Nagaprasad, Kumud Pant, Yekula Prasanna Kumar

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Enhancing Early Detection of Diabetic Retinopathy Through the Integration of Deep Learning Models and Explainable Artificial Intelligence by Kazi Ahnaf Alavee, Mehedi Hasan, Abu Hasnayen Zillanee, Moin Mostakim, Jia Uddin, Eduardo Silva Alvarado, Isabel de la Torre Diez, Imran Ashraf, Md Abdus Samad

“…Specifically, we employ transfer learning models such as DenseNet121, Xception, Resnet50, VGG16, VGG19, and InceptionV3, and machine learning models such as SVM, and neural network models like (RNN) for binary and multi-class classification. …”
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Artificial intelligence Defect Detection Robustness inReal-time Non-Destructive Testing of Metal Surfaces by Chaoyu Dong, Jovian Sanjaya Putra, Andrew A. Malcolm

“…Through machine learning methods and deep neural networks, it is possible for AI systems to learn from diverse datasets and accurately identify defects across various applications. …”
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Seismic Vibration Control and Multi-Objective Optimization of Transmission Tower with Tuned Mass Damper Under Near-Fault Pulse-like Ground Motions by Ying Lin, Tao Liu

“…Based on the obtained analysis results, artificial neural network (ANN) is trained to predict the vibration reduction ratios of peak responses and the corresponding vibration reduction cost. …”
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