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CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point +7 more
wiley +1 more source
dUTPases are involved in balancing the appropriate nucleotide pools. We showed that dUTPase is essential for normal development in zebrafish. The different zebrafish genomes contain several single‐nucleotide variations (SNPs) of the dut gene. One of the dUTPase variants displayed drastically lower protein stability and catalytic efficiency as compared ...
Viktória Perey‐Simon +6 more
wiley +1 more source
Chemoresistance in bladder cancer: Macrophage recruitment associated with CXCL1, CXCL5 and CXCL8 expression is characteristic of Gemcitabine/Cisplatin (Gem/Cis) Non‐Responder tumors (right side) while Responder tumors did not show substantial tumor‐stromal crosstalk (left side). All biological icons are attributed to Bioicons: carcinoma, cancerous‐cell‐
Sophie Leypold +11 more
wiley +1 more source
A tri‐culture of iPSC‐derived neurons, astrocytes, and microglia treated with ferroptosis inducers as an Induced ferroptosis model was characterized by scRNA‐seq, cell survival, and cytokine release assays. This analysis revealed diverse microglial transcriptomic changes, indicating that the system captures key aspects of the complex cellular ...
Hongmei Lisa Li +6 more
wiley +1 more source
Vision-based Human Action Recognition: A Sparse Representation Perspective
Zhe Zhang
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Enhanced skeleton visualization for view invariant human action recognition
Pattern Recognition, 2017Mengyuan Liu, Hong Liu
exaly +2 more sources
Graph Convolutional Neural Network for Human Action Recognition: A Comprehensive Survey
IEEE Transactions on Artificial Intelligence, 2021Tasweer Ahmad, Lianwen Jin, Xin Zhang
exaly +2 more sources
Human Action Recognition with Transformers
2022Having a reliable tool to predict the actions performed in a video can be very useful for intelligent security systems, for many applications related to robotics and for limiting human interactions with the system. In this work we present an architecture trained to predict the action present in digital video sequences.
Pier Luigi Mazzeo +3 more
openaire +2 more sources
Skeleton-based Human Action Recognition via Large-kernel Attention Graph Convolutional Network
IEEE Transactions on Visualization and Computer Graphics, 2023The skeleton-based human action recognition has broad application prospects in the field of virtual reality, as skeleton data is more resistant to data noise such as background interference and camera angle changes.
Yanan Liu +4 more
semanticscholar +1 more source

