Results 111 to 120 of about 6,207,310 (278)

Personalized neural cognitive architecture search: AutoML-driven diagnostic model generation for heterogeneous learner profiles

Computers and Education: Artificial Intelligence
With the rapid advancement of digital transformation in education, personalized learning has become a central objective for improving educational quality.
Liyuan Jia, Ke Dong
doaj   +1 more source

Early Retinal UCHL1 Dysregulation Coupled With Synaptic Loss Reflects Alzheimer's Disease Severity

Advanced Science, EarlyView.
This study identifies synapse‐enriched deubiquitinase UCHL1 as an early Aβ‐responsive regulator of retinal synaptopathy in Alzheimer's disease. Retinal UCHL1 loss accompanies excitatory synapse degeneration, p75NTR activation, and neuroinflammation, and predicts Braak stage and cognitive decline. Aβ42 fibrils trigger synaptic and UCHL1 depletion before
Altan Rentsendorj, Jean‐Philippe Vit, Alexandre Hutton, Yosef Koronyo, Saba Shahin, Edward Robinson, Ernesto Barron, Anthony Rodriguez, Ousman Jallow, Julia Sheyn, Bhakta Prasad Gaire, Lalita Subedi, Miyah R. Davis, Barathan Gnanabharathi, Alexander V. Ljubimov, Stuart L. Graham, Vivek K. Gupta, Mehdi Mirzaei, Debra Hawes, Katlin Silm, Keith L. Black, Lon S. Schneider, Alfredo A. Sadun, Jesse G. Meyer, Dieu‐Trang Fuchs, Maya Koronyo‐Hamaoui   +25 more
wiley   +1 more source

Functional Disorder at the Neural Interface: How Disordered Nanostructures Promote Proper Growth and Differentiation in In Vitro Neural Cultures

Advanced Science, EarlyView.
This work provides a practical guide for neuroengineers to design advanced neural interfaces, embracing and tailoring the concept of functional disorder. By bridging 2D and 3D in vitro models, this work highlights how non‐periodic, spatially heterogeneous, multiscale nanotopography can enable more physiologically relevant platforms for studying neural ...
F. Maita, E. Palmieri, I. Lucarini, L. Montaina, L. Maiolo   +4 more
wiley   +1 more source

Deep Learning and Neural Architecture Search for Optimizing Binary Neural Network Image Super Resolution

Biomimetics
The evolution of super-resolution (SR) technology has seen significant advancements through the adoption of deep learning methods. However, the deployment of such models by resource-constrained devices necessitates models that not only perform ...
Yuanxin Su, Li-minn Ang, Kah Phooi Seng, Jeremy Smith   +3 more
doaj   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

emoDARTS: Joint Optimization of CNN and Sequential Neural Network Architectures for Superior Speech Emotion Recognition

IEEE Access
Speech Emotion Recognition (SER) is crucial for enabling computers to understand the emotions conveyed in human communication. With recent advancements in Deep Learning (DL), the performance of SER models has significantly improved. However, designing an
Thejan Rajapakshe, Rajib Rana, Sara Khalifa, Berrak Sisman, Bjorn W. Schuller, Carlos Busso   +5 more
doaj   +1 more source

Review of Gastrointestinal Capsule Robots: Materials, Actuation, Diagnostics, and Therapeutics

Advanced Science, EarlyView.
This review examines gastrointestinal capsule robots through a systems engineering lens, covering shell materials, actuation and localization strategies, diagnostic modalities, therapeutic interventions, and commercialization status. By mapping the complete technological chain from fabrication to clinical deployment, this work identifies critical gaps ...
Zengsheng Li, Zhongguo Ren, Yiliang Lin, Xianfeng Xia, Tianlong Li, Kai Fung Chan, Philip Wai Yan Chiu, Wei Peng Yong, Mengmeng Sun   +8 more
wiley   +1 more source

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source

Machine Learning‐Driven Design of Multicomponent Bone Inorganic Matrix Mimicking Scaffolds for Osteogenesis Enhanced by Neurogenesis

Advanced Science, EarlyView.
Schematic illustration of development of experimental datasets and algorithm models, screening and preparation of the scaffolds and their applications in vivo. ABSTRACT Bone defects require materials with osteogenic, neurogenic, and angiogenic activity, yet designing such materials within high‐dimensional compositional spaces remains challenging. Here,
Kunlu Lin, Ying Yang, Chuyao Zhou, Hanyue Mao, Zhiquan Zhang, Libangxi Liu, Xiaoying Yu, Haoming Liu, Long Liu, Xiaoyan Wang   +9 more
wiley   +1 more source

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source