Context-aware and Scale-insensitive Temporal Repetition Counting

Temporal repetition counting aims to estimate the number of cycles of a given repetitive action. Existing deep learning methods assume repetitive actions are performed in a fixed time-scale, which is invalid for the complex repetitive actions in real life. In this paper, we tailor a context-aware and scale-insensitive framework, to tackle the challenges in repetition counting caused by the unknown and diverse cycle-lengths. Our approach combines two key insights: (1) Cycle lengths from different actions are unpredictable that require large-scale searching, but, once a coarse cycle length is determined, the variety between repetitions can be overcome by regression. (2) Determining the cycle length cannot only rely on a short fragment of video but a contextual understanding. The first point is implemented by a coarse-to-fine cycle refinement method. It avoids the heavy computation of exhaustively searching all the cycle lengths in the video, and, instead, it propagates the coarse prediction for further refinement in a hierarchical manner. We secondly propose a bidirectional cycle length estimation method for a context-aware prediction. It is a regression network that takes two consecutive coarse cycles as input, and predicts the locations of the previous and next repetitive cycles. To benefit the training and evaluation of temporal repetition counting area, we construct a new and largest benchmark, which contains 526 videos with diverse repetitive actions. Extensive experiments show that the proposed network trained on a single dataset outperforms state-of-the-art methods on several benchmarks, indicating that the proposed framework is general enough to capture repetition patterns across domains.Comment: Accepted by CVPR202

Study on Stability and Control of Pre-excavated Withdrawal Channel under Mining Influence

AbstractPre-excavated withdrawal channel (PWC) is an effective means to shorten the withdrawal time of fully mechanized working face and improve the efficiency, safety, and reliability during the withdrawal. However, the key to the success of the withdrawal method is the influence of mining on the stability of PWC, taking the III32upper1 working face of Zhuzhuang Coal Mine as the engineering background. By theoretical analysis and numerical simulation, the deformation of the PWC is analyzed and the mechanical model of the influence of the instability of the main roof fracture on the PWC is established. And the effect of the fracture and rotation of the main roof on the PWC is analyzed. The result shows that the instability of the coal pillar leads to the fracture and rotary deformation of the main roof as the width of the coal pillar gradually decreases, which further aggravates the deformation of the PWC and the degree of ground pressure behavior. Based on the influence of mining on the PWC, a control method is proposed. This method uses hydraulic fracturing technology to weaken the mining stress and prevent the fracture of the main roof above the PWC. The control effect of hydraulic fracturing on PWC is analyzed through the establishment of numerical calculation model. The result of engineering practice demonstrates that the mining stress is significantly reduced, and the deformation of surrounding rock in the PWC is effectively controlled after hydraulic fracturing

Single-shot 3D coherent diffractive imaging of core-shell nanoparticles with elemental specificity.

We report 3D coherent diffractive imaging (CDI) of Au/Pd core-shell nanoparticles with 6.1 nm spatial resolution with elemental specificity. We measured single-shot diffraction patterns of the nanoparticles using intense x-ray free electron laser pulses. By exploiting the curvature of the Ewald sphere and the symmetry of the nanoparticle, we reconstructed the 3D electron density of 34 core-shell structures from these diffraction patterns. To extract 3D structural information beyond the diffraction signal, we implemented a super-resolution technique by taking advantage of CDI's quantitative reconstruction capabilities. We used high-resolution model fitting to determine the Au core size and the Pd shell thickness to be 65.0 ± 1.0 nm and 4.0 ± 0.5 nm, respectively. We also identified the 3D elemental distribution inside the nanoparticles with an accuracy of 3%. To further examine the model fitting procedure, we simulated noisy diffraction patterns from a Au/Pd core-shell model and a solid Au model and confirmed the validity of the method. We anticipate this super-resolution CDI method can be generally used for quantitative 3D imaging of symmetrical nanostructures with elemental specificity

Identification of the C-Reactive Protein Interaction Network Using a Bioinformatics Approach Provides Insights into the Molecular Pathogenesis of Hepatocellular Carcinoma

Background/Aims: C reactive protein (CRP) levels are elevated in many diseases, including malignant tumors and cardiovascular disorders. In this study, the protein interaction network for CRP was evaluated to determine the importance of CRP and its interacting proteins in the molecular pathogenesis of hepatocellular carcinoma (HCC). Methods: Isobaric tags for relative and absolute quantitation (iTRAQ) and mass spectrometry were used to identify CRP interacting proteins in SMMC7721 cells. Moreover, Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to evaluate enriched genes and pathways for differentially expressed genes using DAVID and WebGestalt. Co-immunoprecipitation and western blot analyses were employed to assess interactions between CRP and KRT8, ANXA2, ENO2, and HSP90B1. Results: In total, 52 proteins that interact with CRP were identified. A GO analysis suggested that most of the interacting proteins were involved in CRP complexes and regulated metabolic processes. A KEGG pathway analysis suggested that most CRP-interacting proteins contribute to the TRAIL signaling pathway, Class I PI3K/Akt signaling pathway, plasma membrane estrogen receptor signaling, Nectin adhesion pathway, and S1P1 pathway. Immunoprecipitation and western blot analyses revealed interactions between CRP and KRT8, ANXA2, ENO2, and HSP90B1. Conclusions: iTRAQ based proteomic profiling revealed the network of CRP interacting proteins. This network may activate the PI3K/Akt signaling pathway, thereby contributing to the pathogenesis of HCC

Single-shot 3D coherent diffractive imaging of core-shell nanoparticles with elemental specificity

We report 3D coherent diffractive imaging (CDI) of Au/Pd core-shell nanoparticles with 6.1 nm spatial resolution with elemental specificity. We measured single-shot diffraction patterns of the nanoparticles using intense x-ray free electron laser pulses. By exploiting the curvature of the Ewald sphere and the symmetry of the nanoparticle, we reconstructed the 3D electron density of 34 core-shell structures from these diffraction patterns. To extract 3D structural information beyond the diffraction signal, we implemented a super-resolution technique by taking advantage of CDI's quantitative reconstruction capabilities. We used high-resolution model fitting to determine the Au core size and the Pd shell thickness to be 65.0 +/- 1.0 nm and 4.0 +/- 0.5 nm, respectively. We also identified the 3D elemental distribution inside the nanoparticles with an accuracy of 3%. To further examine the model fitting procedure, we simulated noisy diffraction patterns from a Au/Pd core-shell model and a solid Au model and confirmed the validity of the method. We anticipate this super-resolution CDI method can be generally used for quantitative 3D imaging of symmetrical nanostructures with elemental specificity.111Ysciescopu

Structural and Functional Analysis of Validoxylamine A 7′-phosphate Synthase ValL Involved in Validamycin A Biosynthesis

Validamycin A (Val-A) is an effective antifungal agent widely used in Asian countries as crop protectant. Validoxylamine A, the core structure and intermediate of Val-A, consists of two C7-cyclitol units connected by a rare C-N bond. In the Val-A biosynthetic gene cluster in Streptomyces hygroscopicus 5008, the ORF valL was initially annotated as a validoxylamine A 7′-phosphate(V7P) synthase, whose encoded 497-aa protein shows high similarity with trehalose 6-phosphate(T6P) synthase. Gene inactivation of valL abolished both validoxylamine A and validamycin A productivity, and complementation with a cloned valL recovered 10% production of the wild-type in the mutant, indicating the involvement of ValL in validoxylamine A biosynthesis. Also we determined the structures of ValL and ValL/trehalose complex. The structural data indicates that ValL adopts the typical fold of GT-B protein family, featuring two Rossmann-fold domains and an active site at domain junction. The residues in the active site are arranged in a manner homologous to that of Escherichia coli (E.coli) T6P synthase OtsA. However, a significant discrepancy is found in the active-site loop region. Also noticeable structural variance is found around the active site entrance in the apo ValL structure while the region takes an ordered configuration upon binding of product analog trehalose. Furthermore, the modeling of V7P in the active site of ValL suggests that ValL might have a similar SNi-like mechanism as OtsA

Single-shot 3D coherent diffractive imaging of core-shell nanoparticles with elemental specificity

We report 3D coherent diffractive imaging (CDI) of Au/Pd core-shell nanoparticles with 6.1 nm spatial resolution with elemental specificity. We measured single-shot diffraction patterns of the nanoparticles using intense x-ray free electron laser pulses. By exploiting the curvature of the Ewald sphere and the symmetry of the nanoparticle, we reconstructed the 3D electron density of 34 core-shell structures from these diffraction patterns. To extract 3D structural information beyond the diffraction signal, we implemented a super-resolution technique by taking advantage of CDI’s quantitative reconstruction capabilities. We used high-resolution model fitting to determine the Au core size and the Pd shell thickness to be 65.0 ± 1.0 nm and 4.0 ± 0.5 nm, respectively. We also identified the 3D elemental distribution inside the nanoparticles with an accuracy of 3%. To further examine the model fitting procedure, we simulated noisy diffraction patterns from a Au/Pd core-shell model and a solid Au model and confirmed the validity of the method. We anticipate this super-resolution CDI method can be generally used for quantitative 3D imaging of symmetrical nanostructures with elemental specificity