Results 51 to 60 of about 162,584 (247)

Efficacy of Intermittent Theta‐Burst Stimulation for Prolonged Disorders of Consciousness: A Prospective, Randomized, Controlled Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu, Jun Hu, Qianqian Wu, Min Wu, Yamei Yu, Hangcheng Li, Jian Gao, Jingqi Li, Nai Ding, Jie Yu, Benyan Luo   +10 more
wiley   +1 more source

Training Artificial Neural Networks Using a Global Optimization Method That Utilizes Neural Networks

AI, 2023
Perhaps one of the best-known machine learning models is the artificial neural network, where a number of parameters must be adjusted to learn a wide range of practical problems from areas such as physics, chemistry, medicine, etc.
Ioannis G. Tsoulos, Alexandros Tzallas
doaj   +1 more source

Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials

Advanced Engineering Materials, EarlyView.
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai, Xinrui Sarah Niu, Zhao Qin   +2 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
wiley   +1 more source

Advancing Neural Networks: Innovations and Impacts on Energy Consumption

Advanced Electronic Materials
The energy efficiency of Artificial Intelligence (AI) systems is a crucial and actual issue that may have an important impact on an ecological, economic and technological level.
Alina Fedorova, Nikola Jovišić, Jordi Vallverdù, Silvia Battistoni, Miloš Jovičić, Milovan Medojević, Alexander Toschev, Evgeniia Alshanskaia, Max Talanov, Victor Erokhin   +9 more
doaj   +1 more source

Golden‐Ratio–Guided Aperiodic Architected Metamaterials with Simultaneously Enhanced Strength and Toughness

Advanced Functional Materials, EarlyView.
Guided by the golden ratio, a class of aperiodic architected metamaterials is introduced to address the intrinsic trade‐off between strength and toughness. By unifying local geometric heterogeneity with global order, the golden‐ratio‐guided aperiodic architecture promotes spatial delocalization of damage tolerence regions, leading to more tortuous ...
Junjie Deng, Xinxin Wang, Ruochao Zhao, Zhendong Li, Kai Liu, Ke Yuan, Jia An, Xinwei Li, Chee Kai Chua, Zhonggang Wang   +9 more
wiley   +1 more source

Ultrahigh‐Yield, Multifunctional, and High‐Performance Organic Memory for Seamless In‐Sensor Computing Operation

Advanced Functional Materials, EarlyView.
Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim, Jaehyoung Ko, Namju Kim, Quynh H. Nguyen, Hoyeon Lee, Joohwan Eo, Seongeon Jin, Ji Eon Kwon, Seung‐Yeol Jeon, Youngdo Jeong, Dongseok Kwon, Sung Gap Im, Sanghan Lee, Byung Chul Jang, Yongho Joo   +14 more
wiley   +1 more source

Application of artificial neural networks in modeling and optimization of biofuels production [PDF]

Journal on Processing and Energy in Agriculture, 2017
Artificial neural networks, the artificial intelligence systems that imitate functions of biological neurons, have been widely used in different areas due to their variety and ability to conform to specificities of different applications.
Pajčin Ivana, Grahovac Jovana, Dodić Jelena, Jokić Aleksandar, Dodić Siniša, Vučurović Damjan, Milović Nemanja   +6 more
doaj   +1 more source