Neural Functions of Matrix Metalloproteinases: Plasticity, Neurogenesis, and Disease by Hiromi Fujioka, Yusuke Dairyo, Kei-ichiro Yasunaga, Kazuo Emoto

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EEG as a neural measure of hypoxia-related impairment by Stephanie R. Otto, Stephanie R. Otto, Cammi K. Borden, Cammi K. Borden, Daniel G. McHail, Kara J. Blacker

“…Recent advances in neuroscience have permitted non-invasive observation of neural activity under controlled hypoxia exposures and have begun to uncover how the brain responds to hypoxia. …”
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Uncovering Psychedelics: From Neural Circuits to Therapeutic Applications by Alice Melani, Marco Bonaso, Letizia Biso, Benedetta Zucchini, Ciro Conversano, Marco Scarselli

“…Psychedelics, historically celebrated for their cultural and spiritual significance, have emerged as potential breakthrough therapeutic agents due to their profound effects on consciousness, emotional processing, mood, and neural plasticity. This review explores the mechanisms underlying psychedelics’ effects, focusing on their ability to modulate brain connectivity and neural circuit activity, including the default mode network (DMN), cortico-striatal thalamo-cortical (CSTC) loops, and the relaxed beliefs under psychedelics (REBUS) model. …”
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Survey of FPGA based recurrent neural network accelerator by Chen GAO, Fan ZHANG

Subjects: “…recurrent neural network…”
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The Estimate for Approximation Error of Neural Network with Two Weights by Fanzi Zeng, Yuting Tang

“…The neural network with two weights is constructed and its approximation ability to any continuous functions is proved. …”
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Robust Linear Neural Network for Constrained Quadratic Optimization by Zixin Liu, Yuanan Liu, Lianglin Xiong

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Prediction and Evaluation of Rockburst Based on Depth Neural Network by Jin Zhang, Mengxue Wang, Chuanhao Xi

“…Training through existing data. The neural network model shows that the rockburst risk is closely related to the maximum principal stress. …”
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A Novel Kernel for RBF Based Neural Networks by Wasim Aftab, Muhammad Moinuddin, Muhammad Shafique Shaikh

“…In this work, we introduce a novel RBF artificial neural network (ANN) where the basis function utilizes a linear combination of ED based Gaussian kernel and a cosine kernel where the cosine kernel computes the angle between feature and center vectors. …”
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Neural Blockade in the Evaluation and Management of Chronic Pain: An Overview by Ian Gilron

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Flood Forecasting for Small Reservoirs Based on Neural Networks by PENG Wei, XIONG Jiayi, JIANG Xianqun, GAO Yueming

Subjects: “…neural network…”
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Neural Networks in Mechanical System Simulation, Identification, and Assessment by Thomas L. Paez

“…Artificial neural networks (ANNs) have been used in the solution of a variety of mechanical system design, analysis, and control problems. …”
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More on (𝜶,𝜷)-Normal Operators in Hilbert Spaces by Rasoul Eskandari, Farzollah Mirzapour, Ali Morassaei

“…We study some properties of (𝛼,𝛽)-normal operators and we present various inequalities between the operator norm and the numerical radius of (𝛼,𝛽)-normal operators on Banach algebra ℬ(ℋ) of all bounded linear operators 𝑇∶ℋ→ℋ, where ℋ is Hilbert space.…”
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Local asymptotic normality of statistical models of discrete martingales by Vaidotas Kanišauskas

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A New Chief Editor for Neural Plasticity Growth by Michel Baudry

“…Neural Plasticity…”
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GuardianMPC: Backdoor-Resilient Neural Network Computation by Mohammad Hashemi, Domenic Forte, Fatemeh Ganji

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Visual Scanning and Reading Ability in Normal and Dyslexic Children by G. Ferretti, S. Mazzotti, D. Brizzolara

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The neural substrate of navigation using hydrostatic cues in goldfish by Shachar Givon, Renana Altsuler-Nagar, Ronen Segev

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Two Mesolithic burials from Khor Shambat, Sudan by Maciej Jórdeczka, Łukasz Maurycy Stanaszek

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Antifungal Resistance and New Strategies to Control Fungal Infections by Patrick Vandeputte, Selene Ferrari, Alix T. Coste

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Driver Distraction Identification with an Ensemble of Convolutional Neural Networks by Hesham M. Eraqi, Yehya Abouelnaga, Mohamed H. Saad, Mohamed N. Moustafa

“…The system consists of a genetically weighted ensemble of convolutional neural networks; we show that a weighted ensemble of classifiers using a genetic algorithm yields a better classification confidence. …”
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