Results 111 to 120 of about 145,055 (276)
Wearable Tailored Passive Radiative Cooling Textile for Flexible Electronic Integration
A scalable, additive‐free wearable tailored passive radiative cooling textile (WRCT) with hierarchically structured fibers delivers exceptional thermal management, combining >95% solar reflectance, 0.96 mid‐infrared emissivity, and ultralow thermal conductivity (0.041 W/m·K).
Lung Chow +24 more
wiley +1 more source
Graph-based vision transformer with sparsity for training on small datasets from scratch
Vision Transformers (ViTs) have achieved impressive results in large-scale image classification. However, when training from scratch on small datasets, there is still a significant performance gap between ViTs and Convolutional Neural Networks (CNNs ...
Peng Li +4 more
doaj +1 more source
Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu +5 more
wiley +1 more source
PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su +7 more
wiley +1 more source
Difference-attention graph convolutional network for skeleton-based gesture recognition
Graph Convolutional Networks (GCNs) have been widely applied to skeleton-based gesture recognition tasks and have achieved remarkable performance. The currently proposed dynamic and topology-non-shared graph convolutional networks outperform conventional
Yadong Wang +5 more
doaj +1 more source
Non-convolutional graph neural networks.
Rethink convolution-based graph neural networks (GNN) -- they characteristically suffer from limited expressiveness, over-smoothing, and over-squashing, and require specialized sparse kernels for efficient computation. Here, we design a simple graph learning module entirely free of convolution operators, coined random walk with unifying memory (RUM ...
Yuanqing Wang, Kyunghyun Cho
openaire +3 more sources
ABSTRACT Blood‐based liquid biopsies hold transformative potential for non‐invasive cancer management, but current approaches relying on rare circulating tumor components limit their broad clinical utility. Platelets, abundant in blood and mediating diverse cancer‐associated responses, represent a compelling yet largely unexplored alternative.
Yan Ma +28 more
wiley +1 more source
Advancing Link Prediction with a Hybrid Graph Neural Network Approach
Social media platforms produce extensive user–item interaction data that demand advanced analytical models for effective personalization. This study investigates the link prediction task within social recommendation systems using Graph Neural Networks ...
Siwar Gharsallah +3 more
doaj +1 more source
CMOS‐Integrated Synaptic Photoreceptor Chip Inspired by Insect Visual Processing
CMOS‐integrated Si QDs/ReS2 synaptic photoreceptor array mimics the parallel processing and wavelength‐selective strategy of insect vision. By combining intrinsic ultraviolet‐violet sensitivity with synaptic plasticity, the chip enables frontend sensory redundancy reduction without external filters, offering a scalable pathway toward lowpower ...
Jian Chai +25 more
wiley +1 more source
Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar +10 more
wiley +1 more source

