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Abstract Track‐to‐track association methods based on machine learning and deep learning have greatly improved the association results, but the scope of application is limited by the poor interpretability and manual association labelling. To enhance the interpretability of the neural networks, enhance the credibility of association decisions, and reduce the consumption for labelling associated track pairs, the authors estimate and counteract radar bias by homography estimation to achieve track‐to‐track association. The proposed model is composed of a mixing extraction module and a homography estimation module. Aiming at the interaction of temporal and spatial features of tracks, the spatial‐temporal mixing features are extracted by a mixing extraction module. Focusing on attaining explainable discriminant factors, the homography matrix is generated by the homography estimation module. Targeting at the unsupervised learning, the radar bias and association matrix are estimated jointly so that the labelled track association pairs are not demanded. Finally, a track from one radar is transformed into the other radar, and the homography matrix that counteracts the radar bias can provide explainable discriminant factors and make the association decision more credible. Extensive experiments demonstrated that the proposed method can achieve better association results and the association results can be well interpreted.

Abstract The point‐track association methods are proposed on the premise that the system models are known, which obviously does not conform to the actual air target detection environment. Considering this situation, for the point‐track association problems in clutter environment, a point‐track association method with unknown system model (USMA) is proposed. The method integrates reinforcement learning (RL) theory and traditional point‐track association framework, utilises the association process migration of different models, simplifies the entire learning process, and improves the generalisation ability by designing an adaptive mechanism. The experimental results show that when the system model is unknown, the USMA method can more accurately correlate to the measurements, and can also solve the problems of point‐track association with a certain clutter density. Compared with other methods, the USMA method performs better.

Background: Bones undergo a constant remodeling, a process involving osteoclast‐mediated bone resorption and osteoblast‐mediated bone formation, crucial for maintaining healthy bone mass. We previously observed that miR‐185 depletion may promote bone formation by regulating Bgn expression and the BMP/Smad signaling pathway. However, the effects of miR‐185‐5p on the osteoclasts and bone remodeling have not been elucidated, warranting further exploration. Methods: Tartrate‐resistant acid phosphatase staining was utilized to assess the differentiation ability of bone marrow mononuclear macrophages (BMMs) from mmu‐miR‐185 gene knockout (KO) mice and wild‐type (WT) mice. A reverse transcriptase‐quantitative PCR was conducted to compare differences in miR‐185‐5p and osteoclast marker molecules, including Trap, Dcstamp, Ctsk and Nfatc1, between the KO group and WT group BMMs. Western blot analysis was employed to observe the expression of osteoclast marker molecules. A cell‐counting kit‐8 was used to analyze cell proliferation ability. Transwell experiments were conducted to detect cell migration. Dual‐luciferase reporter assays were employed to confirm whether Btk is a downstream target gene of miR‐185‐5p. Results: miR‐185 depletion promoted osteoclast differentiation in bone marrow‐derived monocytes/macrophages. Overexpression of miR‐185‐5p in RAW264.7 cells inhibited differentiation and migration of osteoclasts. Furthermore, Btk was identified as a downstream target gene of miR‐185‐5p, suggesting that miR‐185‐5p may inhibit osteoclast differentiation and migration by targeting Btk. Conclusions: miR‐185 regulates osteoclasts differentiation, with overexpression of miR‐185‐5p inhibiting osteoclast differentiation and migration in vitro. Additionally, miR‐185‐5p may modulate osteoclastic differentiation and migration by regulating Btk expression. [ABSTRACT FROM AUTHOR]