Results 81 to 90 of about 14,609 (251)
Quantum‐Like Dynamics in Whole‐Brain Models of the Human Connectome
Quantum‐like dynamics in the human brain. The level of quantum‐like behavior in a non‐quantum system of coupled oscillators is regulated by the spectral gap of the coupling graph. Whole‐brain modelling using QL fits the empirical data significantly better and has a lower model‐derived energy cost than the non‐QL model.
Gustavo Deco +5 more
wiley +1 more source
STWave transforms massive microscopic‐resolution spatial transcriptomics into interpretable fine‐scale tissue maps through patch‐wise inference, wavelet‐based multi‐scale encoding, and dual‐domain reconstruction. It reduces noise while preserving weak spatial signals, enabling efficient analysis of 6 40 000 spots of 2.47 GB GPU memory and revealing ...
Tao Jiang +9 more
wiley +1 more source
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
Fermentation with lactic acid bacteria could improve amino acids, volatile organic compounds (VOCs), and nonvolatile metabolites of Laohan melon juice (LMJ), which provides theoretical guidance for the development of Laohan melon beverage and advances knowledge of the metabolic mechanisms of VOCs in LMJ.
Yun Xie +12 more
wiley +1 more source
GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs
Abstract Piping and Instrumentation Diagrams (P&IDs) are central to process engineering workflows, yet extracting information from them remains a tedious and time‐consuming task. This work introduces ChatP&ID, a framework enabling natural‐language interaction with smart P&IDs through Graph Retrieval‐Augmented Generation (GraphRAG), to our knowledge ...
Achmad Anggawirya Alimin +1 more
wiley +1 more source
Provable Filter Pruning for Efficient Neural Networks
We present a provable, sampling-based approach for generating compact Convolutional Neural Networks (CNNs) by identifying and removing redundant filters from an over-parameterized network. Our algorithm uses a small batch of input data points to assign a saliency score to each filter and constructs an importance sampling distribution where filters that
Lucas Liebenwein +4 more
openaire +3 more sources
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta +3 more
wiley +1 more source
Surface Defect Segmentation Algorithm of Steel Plate Based on Geometric Median Filter Pruning. [PDF]
Hao Z, Wang Z, Bai D, Tong X.
europepmc +1 more source
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley +1 more source
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen +3 more
wiley +1 more source

