S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu +6 more
wiley +1 more source
A hybrid fuzzy and convolutional neural network framework for urban road traffic risk and sustainability assessment. [PDF]
Zhong Z, Ren Z.
europepmc +1 more source
A NEW RANKING METHOD FOR TRIANGULAR INTUITIONISTIC FUZZY NUMBER BASED ON GERGONNE POINT
Gültekin Atalik, Sevil Şentürk
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A Quest for the Mechanism of Ultrahigh Resolution SEM Imaging
Using Monte Carlo simulations with explicit definitions of SE1 and SE2 align with a cascade secondary electron production model, this work shows that the 3D nanostructure modulated SE2 emission enhances other than to reduce topographical contrast via a “miniature Faraday cup” effect.
Hao Tian Chen +3 more
wiley +1 more source
Exploiting fuzzy weights in CNN model-based taxonomic classification of 500-bp sequence bacterial dataset. [PDF]
Algarni AD +6 more
europepmc +1 more source
Discussion on fuzzy decision making based on fuzzy number and compositional rule of inference
Ping-Teng Chang, Lung-Ting Hung
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Integrating spatial transcriptomics and single‐cell RNA sequencing, this study identifies a novel subpopulation of SLPI⁺ AT2‐like cells at the invasive margin of lung adenocarcinoma (LUAD). These cells, through stromal crosstalk and Wnt pathway activation, promote tumor stemness and invasion.
Zhoufeng Wang +13 more
wiley +1 more source
Advancing sports performance evaluation through T spherical fuzzy FUCA MCDM approach to real time basketball analytics. [PDF]
Liu D, Wang W.
europepmc +1 more source
Fuzzy super resolving number and resolving number of some special graphs
R. Shanmugapriya, Mary Jiny D
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