Institute of Fundamental Technological Research
Polish Academy of Sciences

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B.-Y. Xu

Tsinghua University (CN)

Recent publications
1.  Shen X.-P., Mróz Z., Xu B.-Y., Constitutive theory of plasticity coupled with orthotropic damage for geomaterials, APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION, ISSN: 0253-4827, DOI: 10.1007/BF02438321, Vol.22, No.9, pp.1028-1034, 2001

Abstract:
Constitutive theory of plasticity coupled with orthotropic damage for geomaterials was established in the framework of irreversible thermodynamics. Prime results include: 1) evolution laws are presented for coupled evolution of plasticity and orthotropic damage; 2) the orthotropic damage tensor is introduced into the Mohr-Coulomb criterion through homogenization. Both the degradation of shear strength and degradation of friction angle caused by damage are included in this model. The dilatancy is calculated with the so-called damage strain.

Keywords:
damage plasticity, coupling, dilatancy, geomaterial

Affiliations:
Shen X.-P. - Shenyang University of Technology (CN)
Mróz Z. - IPPT PAN
Xu B.-Y. - Tsinghua University (CN)

Conference papers
1.  Poon Ch., Rachmadi M.F., Byra M., Schlachter M., Xu B., Shimogori T., Skibbe H., AN AUTOMATED PIPELINE TO CREATE AN ATLAS OF IN SITU HYBRIDIZATION GENE EXPRESSION DATA IN THE ADULT MARMOSET BRAIN, ISBI, 2023 IEEE 20th International Symposium on Biomedical Imaging, 2023-04-18/04-21, Cartagena (CO), DOI: 10.1109/ISBI53787.2023.10230544, pp.1-5, 2023

Abstract:
We present the first automated pipeline to create an atlas of in situ hybridization gene expression in the adult marmoset brain in the same stereotaxic space. The pipeline consists of segmentation of gene expression from microscopy images and registration of images to a standard space. Automation of this pipeline is necessary to analyze the large volume of data in the genome-wide whole-brain dataset, and to process images that have varying intensity profiles and expression patterns with minimal human bias. To reduce the number of labelled images required for training, we develop a semi-supervised segmentation model. We further develop an iterative algorithm to register images to a standard space, enabling comparative analysis between genes and concurrent visualization with other datasets, thereby facilitating a more holistic understanding of primate brain structure and function.

Keywords:
contrastive learning, gene atlas, segmen-tation, semi-supervised learning, registration

Affiliations:
Poon Ch. - other affiliation
Rachmadi M.F. - other affiliation
Byra M. - IPPT PAN
Schlachter M. - other affiliation
Xu B. - Tsinghua University (CN)
Shimogori T. - other affiliation
Skibbe H. - other affiliation

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