Results 51 to 60 of about 15,127 (194)

Integrated Multi‐Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC

Advanced Science, EarlyView.
Coexisting DCIS and IDC samples are profiled using spatial transcriptomics, single‐cell RNA sequencing, and single‐cell DNA sequencing. Integrative multi‐omics analysis reveals distinct malignant epithelial and microenvironmental features between DCIS and IDC, which are further validated using Xenium and multiplex immunohistochemistry.
Ning Zhang, Tong Wan, Siyue Zhang, Yunzhen Jiang, Peng Su, Jixin Liu, Zhitong Chen, Jie Hao, Haoyu Wang, Bing Chen, Wenjing Zhao, Lijuan Wang, Tao Xing, Qihuang Zhang, Ulf Schmitz, Zhiyong Ding, Nicola Crosetto, Bingqiang Liu, Qifeng Yang   +18 more
wiley   +1 more source

Research on data-driven dynamic aggregation of commercial load clusters

Dianzi Jishu Yingyong
The dynamic aggregation of commercial load clusters is crucial for enhancing the flexibility of power grid dispatch, optimizing demand-side management, and promoting the integration of renewable energy.
Xu Yuting, Bai Jingjing, Zhu Daohua, Liu Chang, Xu Sen, Zhang Zheng   +5 more
doaj   +1 more source

AMD-DBSCAN: An Adaptive Multi-density DBSCAN for datasets of extremely variable density [PDF]

, 2023
DBSCAN has been widely used in density-based clustering algorithms. However, with the increasing demand for Multi-density clustering, previous traditional DSBCAN can not have good clustering results on Multi-density datasets.
Wu, Ziling, Liu, Yanying, Mao, Yi, Ye, Zhirong, Wang, Jun, Wang, Ziqing, Du, Yuyang   +6 more
core  

PrOMet: Accurate and Robust Metal‐Binding Site and Type Prediction

Advanced Science, EarlyView.
PrOMet is a two‐stage deep learning framework for jointly predicting metal‐binding sites and ion identities from protein structures. Surface candidate sites are first pruned, followed by refinement of the most probable sites and metal types. This hierarchical strategy enables robust and accurate metal prediction for cryo‐EM and AlphaFold‐derived ...
Gangeun Park, Chaok Seok, Hahnbeom Park
wiley   +1 more source

A new method for noise data detection based on DBSCAN and SVDD

, 2015
To improve the quality of real datasets by remove noise data, a new method for noise data detection based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and support vector data description (SVDD) was proposed in this article ...
Hao SX(郝胜轩), Xiaofeng Zhou, Hong Song, Zhou XF(周晓锋), Shengxuan Hao, Song H(宋宏)   +5 more
core   +1 more source

SuperResNET: Model‐Free Single‐Molecule Network Analysis Software Achieves Molecular Resolution of Nup96

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li, Ismail M. Khater, Christian Hallgrimson, Ben Cardoen, Timothy H. Wong, Ghassan Hamarneh, Ivan R. Nabi   +6 more
wiley   +1 more source

From Swarm to Individual: Emergent Individuality in Light‐Mediated Robot Collectives

Advanced Intelligent Systems, EarlyView.
Can individuality emerge from a swarm? Using nominally homogeneous phototactic robots, we show that collective light conditions reorganize robot‐level behavioral profiles. Global illumination amplifies persistent differences in state occupancy, while robot‐mounted local light cues reduce fixed differentiation and favor transient high‐switching profiles.
John Smith, Atsushi Masumori, Norihiro Maruyama, Takahide Yoshida, Takashi Ikegami   +4 more
wiley   +1 more source

SS-DBSCAN: Semi-Supervised Density-Based Spatial Clustering of Applications With Noise for Meaningful Clustering in Diverse Density Data

IEEE Access
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised clustering algorithm designed to identify clusters of various shapes and sizes in noisy datasets by pinpointing core points.
Tiba Zaki Abdulhameed, Suhad A. Yousif, Venus W. Samawi, Hasnaa Imad Al-Shaikhli   +3 more
doaj   +1 more source

Visualizing ESG Signaling Through User‐Generated Content: A Strategic Foresight Framework for Symbolic Legitimacy in Hospitality Branding

Business Strategy and the Environment, EarlyView.
ABSTRACT Social media platforms today have become essential for consumer‐brand interactions, with visual content playing a pivotal role in shaping engagement and brand perception. Although text‐based user‐generated content (UGC) has been widely studied, the potential of visual UGC, particularly in the travel, tourism and hospitality (TTH) sector ...
Chinchu Abraham, Pabitra Mitra, Sujoy Bhattacharya   +2 more
wiley   +1 more source

Fuzzy core DBScan clustering algorithm

, 2014
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-SISOInternational audienceIn this work we propose an extension of the DBSCAN algorithm to generate clusters with fuzzy density characteristics. The original version of DBSCAN requires
Ienco, Dino, Dino Ienco, Gloria Bordogna, Bordogna, G., Ienco Dino, Bordogna Gloria   +5 more
core   +4 more sources