Results 181 to 190 of about 459,658 (315)

A Bottom‐Up Design Framework for Multifunctional Lattice Metamaterials

open access: yesAdvanced Science, EarlyView.
This study introduces a generative AI framework for designing multifunctional lattice metamaterials. The method combines 3D Gaussian voxel generation with deep learning, enabling greater design freedom and structural performance. The optimized lattice metamaterials achieve enhanced energy absorption by 40–200% compared to conventional structures and ...
Zongxin Hu   +13 more
wiley   +1 more source

OPTIMIZING MATHEMATICS LEARNING OUTCOMES USING ARTIFICIAL INTELLIGENCE TECHNOLOGY

open access: yesMaPan
The use of technology in learning has become inevitable in modern education. It plays an important role in optimizing the learning process, including in the context of mathematics learning. This study aims to describe the optimization of mathematics learning outcomes using Artificial Intelligence technology. This research uses a qualitative method with
Topanus Tulak   +2 more
openaire   +1 more source

Diminished Signal‐to‐Noise Ratio Disrupts Somatosensory Population Encoding and Drives Tactile Hyposensitivity in the Fmr1−/y Autism Model

open access: yesAdvanced Science, EarlyView.
This study provides a translational approach for linking neural activity to tactile deficits in autism. By combining psychophysics with cortical recordings in a mouse model of autism, we show that low signal‐to‐noise ratio in somatosensory neurons weakens population encoding of fine touch, impairing detection, decoding, and leading to perceptual ...
Ourania Semelidou   +7 more
wiley   +1 more source

Encoding Cumulation to Learn Perturbative Nonlinear Oscillatory Dynamics

open access: yesAdvanced Science, EarlyView.
Weak nonlinearities critically shape the long term behavior of oscillatory systems but are difficult to identify from data. A data‐driven framework is introduced to infer governing equations of weakly nonlinear oscillators from sparse and noisy observations.
Teng Ma   +5 more
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

open access: yesAdvanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia   +7 more
wiley   +1 more source

Learnable Diffusion Framework for Mouse V1 Neural Decoding

open access: yesAdvanced Science, EarlyView.
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng   +2 more
wiley   +1 more source

An On‐Demand Neuromorphic Vision System Enabled by a Multi‐Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level

open access: yesAdvanced Science, EarlyView.
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang   +7 more
wiley   +1 more source

3D Large‐Scale Subwavelength‐Resolution Sound Sheet Tomography Based on an Active and Programmable Circular Meta‐Array

open access: yesAdvanced Science, EarlyView.
A programmable 2048‐element circular ultrasound array combined with a compact acoustic lens produces a thin “sound sheet” over a large field of view, and records echoes with wide angular diversity across the ring aperture. Coherence‐enhanced beamforming converts full‐matrix data into high‐contrast tomographic slices, delivering near‐diffraction‐limited
Qiu‐De Zhang   +11 more
wiley   +1 more source

Spintronic Bayesian Hardware Driven by Stochastic Magnetic Domain Wall Dynamics

open access: yesAdvanced Science, EarlyView.
Magnetic Probabilistic Computing (MPC) utilizes intrinsic stochastic dynamics in domain walls to establish a hardware foundation for uncertainty‐aware artificial intelligence. Thermally driven domain‐wall fluctuations, voltage‐controlled magnetic anisotropy, and TMR readout enable fully electrical, tunable probabilistic inference.
Tianyi Wang   +11 more
wiley   +1 more source

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