Results 131 to 140 of about 53,359 (288)

Bi-Level Unsupervised Feature Selection

CoRR
Unsupervised feature selection (UFS) is an important task in data engineering. However, most UFS methods construct models from a single perspective and often fail to simultaneously evaluate feature importance and preserve their inherent data structure, thus limiting their performance.
Jingjing Liu 0004, Xiansen Ju, Xianchao Xiu, Wanquan Liu   +3 more
openaire   +2 more sources

Astrocytic Phenotypic Switching in Posterior Piriform Cortex Orchestrates Bone Cancer Pain–Depression Comorbidity via Purinergic–Noradrenergic Signaling

Advanced Science, EarlyView.
Bone cancer pain and depression share a common origin: astrocytic A2‐to‐A1 transition in the posterior piriform cortex. This phenotypic shift disrupts the ATP–adenosine–A2AR–norepinephrine axis, simultaneously driving nociceptive and affective dysfunction.
Jiang‐Ping Liu, Jun‐Han Zhang, Zhi‐Xuan Tan, Wei‐Bing Yan, Ya‐Ru Yuan, Yao Liu, Bing‐Di Wei, Meng‐Qi Ding, Zhuo‐Min Fu, Ying Liu, An‐Qi Wang, Lin Ma, Yong‐Hong Li, Er‐Qing Chai, Chao‐Jun Wei   +14 more
wiley   +1 more source

AUFS-Samba: Adaptive Unsupervised Feature Selection for Mixed Data Type Using Simulated Annealing and Multi-Armed Bandit

IEEE Access
Unsupervised feature selection (UFS) for mixed-type data is challenging because there are no labels, and traditional methods cannot handle heterogeneous feature spaces effectively.
Hasta Pratama, Fetty Fitriyanti Lubis, Jaka Sembiring   +2 more
doaj   +1 more source

Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES

Advanced Science, EarlyView.
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu, Wanpeng Zou, Yuekai Li, Jiayi Wang, Mingxuan Cai, Hongmin Cai   +5 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Multimodal Imaging Reveals Rapid Catecholamine Uptake and Release by Neutrophils

Advanced Science, EarlyView.
We show that immune cells (neutrophils) synthesize, uptake, and store catecholamine neurotransmitters such as dopamine or adrenaline. They also release them in response to specific stimuli (serotonin), which we directly visualize using fluorescent nanosensors. We further demonstrate that catecholamines affect neutrophil functions (NETosis) and platelet
Jennifer Mohr, Anne Schmitz, Meshkat Dinarvand, Franziska Wulfert, Sangeetha Shankar, Bjoern F. Hill, Michael Wojak, Juliana Gretz, Marie Britz, Elsa Neubert, Magdalena Shumanska, Sofia Kaushik, Linda Kartaschew, Ivan Bogeski, James Daniel, Sebastian Jung, Johannes Eble, Guido Wabnitz, Luise Erpenbeck, Sebastian Kruss   +19 more
wiley   +1 more source

tBid‐Mediated Genetic Ablation of Connective Tissue Cells Reveals Their Key Regulatory Function During Limb Regeneration in Axolotls

Advanced Science, EarlyView.
We establish a tBid‐mediated cell ablation system in axolotls, achieve rapid and efficient ablation of multiple cell types, including muscle stem cell, spinal cord cell, and connective tissue (CT) cells. We investigate the role of CT using tBid‐mediated CT ablation and identify its essential role for limb development and regeneration.
Yan Hu, Weimin Feng, Zitian He, Jiayi Zeng, Jingyi Tang, Shulin Li, Tongbo Yu, Sulei Fu, Hui Ma, Binbin Lu, Yanmei Liu, Ji‐Feng Fei   +11 more
wiley   +1 more source

Unsupervised Feature Selection Based on Low Dimensional Embedding and Subspace Learning

International Journal of Information and Communication Technology Research, 2020
— Nowadays, we face a huge number of high-dimensional data in different applications and technologies. To tackle the challenge, various feature selection methods have been recently proposed for reducing the computational complexity of the learning ...
Hadi Zare, Ghasemi Parsa Ghasemi Parsa, Mehdi Ghatee, Sasan H. Alizadeh   +3 more
doaj  

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source