Results 41 to 50 of about 162,584 (247)

Optimal Artificial Neural Network Type Selection Method for Usage in Smart House Systems

Sensors, 2020
In the process of the “smart” house systems work, there is a need to process fuzzy input data. The models based on the artificial neural networks are used to process fuzzy input data from the sensors. However, each artificial neural network has a certain
Vasyl Teslyuk, Artem Kazarian, Natalia Kryvinska, Ivan Tsmots   +3 more
doaj   +1 more source

Structural biology of ferritin nanocages

FEBS Letters, EarlyView.
Ferritin is a conserved iron‐storage protein that sequesters iron as a ferric mineral core within a nanocage, protecting cells from oxidative damage and maintaining iron homeostasis. This review discusses ferritin biology, structure, and function, and highlights recent cryo‐EM studies revealing mechanisms of ferritinophagy, cellular iron uptake, and ...
Eloise Mastrangelo, Flavio Di Pisa
wiley   +1 more source

On the relationship between predictive coding and backpropagation.

PLoS ONE, 2022
Artificial neural networks are often interpreted as abstract models of biological neuronal networks, but they are typically trained using the biologically unrealistic backpropagation algorithm and its variants.
Robert Rosenbaum
doaj   +1 more source

Potential therapeutic targeting of BKCa channels in glioblastoma treatment

Molecular Oncology, EarlyView.
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak, Karolina Pytlak, Sandra Jaworowska, Bogusz Kulawiak, Piotr Bednarczyk   +4 more
wiley   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

Asymmetric representation of symmetric semantic information in the human brain

NeuroImage: Reports
Specific pairs of semantic entities have symmetric relationships, such as word pairs with opposite meanings (e.g., “intelligent” and “stupid”; “human” and “mechanical”). Such semantic symmetry is a key feature of semantic information.
Jiaxin Wang, Kiichi Kawahata, Antoine Blanc, Naoya Maeda, Shinji Nishimoto, Satoshi Nishida   +5 more
doaj   +1 more source

Research Progress of Oilfield Development Index Prediction Based on Artificial Neural Networks

Energies, 2021
Accurately predicting oilfield development indicators (such as oil production, liquid production, current formation pressure, water cut, oil production rate, recovery rate, cost, profit, etc.) is to realize the rational and scientific development of ...
Chenglong Chen, Yikun Liu, Decai Lin, Guohui Qu, Jiqiang Zhi, Shuang Liang, Fengjiao Wang, Dukui Zheng, Anqi Shen, Lifeng Bo, Shiwei Zhu   +10 more
doaj   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Application of ANN in Milling Process: A Review

Modelling and Simulation in Engineering, 2011
In recent years the trends were towards modeling of machining using artificial intelligence. ANN is considered one of the important methods of artificial intelligence in the modeling of nonlinear problems like machining processes.
Salah Al-Zubaidi, Jaharah A. Ghani, Che Hassan Che Haron   +2 more
doaj   +1 more source

Bionic Artificial Neural Networks in Medical Image Analysis

Biomimetics, 2023
Bionic artificial neural networks (BANNs) are a type of artificial neural network (ANN) [...]
Shuihua Wang, Huiling Chen, Yudong Zhang
doaj   +1 more source