Results 161 to 170 of about 10,610,136 (340)

Fuzzy fractional more sigmoid function activated neural network approximations revisited

, 2022
George A. Anastassiou
openalex   +1 more source

XBP1s Mediates Cross‐resistance to Combination Treatment of CDK4/6 Inhibitors plus Endocrine Therapy in Breast Cancer

Advanced Science, EarlyView.
Elevated spliced form of X‐box–binding protein 1 (XBP1) correlates with unfavorable responses to endocrine therapy plus CDK4/6 inhibitors in HR+/HER2− advanced breast cancer. XBP1s facilitates cell proliferation and G1/S transition by transcriptionally activating SND1, thereby activating the E2F1 pathway.
Yuting Sang, Shiyang Liu, Xujie Zhou, Weiru Chi, Min Xiong, Ming Chen, Hengyu Ren, Douwaner Liu, Liyi Zhang, Jingyan Xue, Yayun Chi, Jiong Wu   +11 more
wiley   +1 more source

Multifactor prediction model for stock market analysis based on deep learning techniques

Scientific Reports
Stock market stability relies on the shares, investors, and stakeholders’ participation and global commodity exchanges. In general, multiple factors influence the stock market stability to ensure profitable returns and commodity transactions.
Kangyi Wang
doaj   +1 more source

Voltage-to-Voltage Sigmoid Neuron Activation Function Design for Artificial Neural Networks

, 2022
Tatiana Moposita, Lionel Trojman, Felice Crupi, Marco Lanuzza, Andrei Vladimirescu   +4 more
openalex   +2 more sources

VDLIN: A Deep Learning‐Based Platform for Methylcobalamin‐Inspired Immunomodulatory Compound Screening

Advanced Science, EarlyView.
Using the convolutional neural network model VDLIN, Co7 is identified as a promising therapeutic candidate. Co7 demonstrates distinct advantages over MCB by effectively balancing anti‐inflammatory and immune‐stimulatory functions, making it a potential novel approach for immune modulation.
Xuefei Guo, Yang Zhao, Xianle Rong, Chenxi Niu, Shiyu Hu, Qiang Liu, Fuping You   +6 more
wiley   +1 more source

Phase‐Change Materials for Volatile Threshold Resistive Switching and Neuronal Device Applications

Advanced Science, EarlyView.
Volatile threshold switching materials are an important pathway to simulate neuronal behavior. This review summarizes recent advances in the development of volatile resistive switching devices and neuronal oscillators based on three representative phase change materials, emphasizes the major challenges in this rapidly evolving field, and provides an ...
Huandong Chen, Jayakanth Ravichandran
wiley   +1 more source

Coefficient inequalities for subclasses of analytic functions based on quasi-subordination and majorization related with sigmoid functions

, 2022
L. Vanitha, C. Ramachandran, G. Murugusundaramoorthy, Halit Orhan   +3 more
openalex   +1 more source

Efficient FPGA Implementation of Sigmoid and Bipolar Sigmoid Activation Functions for Multilayer Perceptrons

IOSR Journal of Engineering, 2012
Artificial Neural Networks base their processing capabilities in a parallel architecture. This makes them extremely useful in pattern recognition, system identification and control problems. Multilayer Perceptron is an artificial neural network with one or more hidden layers. The Activation function determines the performance of a Multilayer Perceptron.
openaire   +2 more sources

Update Disturbance‐Resilient Analog ReRAM Crossbar Arrays for In‐Memory Deep Learning Accelerators

Advanced Science, EarlyView.
Conductive metal oxide/HfOx analog ReRAM on 350 nm technology is presented for in‐memory deep learning accelerators. The device exhibits analog and nonvolatile conductance switching and high resilience to update disturbances, which is supported by COMSOL Multiphysics simulations.
Wooseok Choi, Tommaso Stecconi, Donato Francesco Falcone, Matteo Galetta, Victoria Clerico, Elisa Zaccaria, Mamidala Saketh Ram, Antonio La Porta, Folkert Horst, Daniel Jubin, Matias Senger, Marilyne Sousa, Steffen Reidt, Ralph Heller, Bernabe Linares‐Barranco, Valeria Bragaglia, Bert Jan Offrein   +16 more
wiley   +1 more source

Spatiotemporal Characterization of the Functional MRI Latency Structure with Respect to Neural Signaling and Brain Hierarchy

Advanced Science, EarlyView.
Resting‐state fMRI captures intrinsic brain activity, yet the physical significance of latency structures remains unclear. In this study, the spatiotemporal properties of fMRI‐derived latency structures are examined by linking them to biophysical model‐based neural functions, intrinsic neural timescales, and functional gradients.
Hyoungshin Choi, Yeongjun Park, Jong‐eun Lee, Sunghun Kim, Bo‐yong Park, Hyunjin Park   +5 more
wiley   +1 more source