Results 91 to 100 of about 79,498 (272)
Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing
Advanced Science, EarlyView.Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale +6 more
wiley +1 more source
Advanced Science, EarlyView.We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua +6 more
wiley +1 more source
Advanced Science, EarlyView.Dysregulated TCA cycle contributes to Alzheimer's disease (AD) pathogenesis. Here, we show that microglial isocitrate dehydrogenase 1 (IDH1) is a critical driver. Elevated IDH1 disrupts citrate metabolism and mitochondrial function, exacerbating AD pathology.
Qianqian Li +13 more
wiley +1 more source
Entropy-Guided Search Space Optimization for Efficient Neural Network Pruning
AlgorithmsNeural network pruning is essential for deploying deep learning models on resource-constrained devices by reducing computational and memory demands.
Yicheng Qiu +4 more
doaj +1 more source
Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks. [PDF]
PLoS Computational Biology, 2015 Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time.
Saket Navlakha +2 more
doaj +1 more source
Advanced Science, EarlyView.A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu +8 more
wiley +1 more source
Advanced Electronic Materials, EarlyView.In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar +9 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi +5 more
wiley +1 more source
Automatic Channel Pruning Method Based on Zebra Optimization Algorithm [PDF]
Jisuanji gongchengThe high computational and storage requirements of Convolutional Neural Networks (CNNs) limit their application in resource-limited mobile edge devices. Model compression techniques can significantly reduce the computational effort and parameters of CNNs
LIU Yajun, WU Dakui, FAN Kefeng, ZHOU Wenju
doaj +1 more source
Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon
, 2017 How to develop slim and accurate deep neural networks has become crucial for real- world applications, especially for those employed in embedded systems.
Chen, Shangyu +2 more
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