[This corrects the article DOI: 10.1371/journal.pone.0288429.].
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11694955 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0317020 | PLOS |
Brief Bioinform
November 2024
Institute of Statistics and Big Data, Renmin University of China, No. 59 Zhongguancun Street, 100872 Beijing, China.
The spatial transcriptomics is a rapidly evolving biological technology that simultaneously measures the gene expression profiles and the spatial locations of spots. With progressive advances, current spatial transcriptomic techniques can achieve the cellular or even the subcellular resolution, making it possible to explore the fine-grained spatial pattern of cell types within one tissue section. However, most existing cell spatial clustering methods require a correct specification of the cell type number, which is hard to determine in the practical exploratory data analysis.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Department of Physics, Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands.
We study the effects of patch potentials in the electrostatic double-layer force. In the limit of small potentials, we derive an analytic expression where the force is additive in terms of the Fourier components of the potential. Moreover, each term has a contribution of the same form as the standard double-layer force with an effective Debye length.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Computer and Control Engineering, Qiqihar University, Qiqihar, 161000, China.
The rapid advancement of quantum key distribution technology in recent years has spurred significant innovation within the field. Nevertheless, a crucial yet frequently underexplored challenge involves the comprehensive evaluation of security quantum state modulation. To address this issue, we propose a novel framework for quantum group key distribution.
View Article and Find Full Text PDFNeural Netw
December 2024
School of Computer Science and Technology, Soochow University, Suzhou, 215006, China. Electronic address:
Certifying robustness against external uncertainties throughout the control process to reduce the risk of instability is very important. Most existing approaches based on adversarial learning use a fixed parameter to adjust the intensity of adversarial perturbations and design these perturbations in a greedy manner without considering future implications. However, they often lead to severe vulnerabilities when attack budgets vary dynamically or under foresighted attacks.
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