Supervised local descriptor learning for human action recognition

Local features have been widely used in computer vision tasks, e.g., human action recognition, but it tends to be an extremely challenging task to deal with large-scale local features of high dimensionality with redundant information. In this paper, we propose a novel fully supervised local descriptor learning algorithm called discriminative embedding method based on the image-to-class distance (I2CDDE) to learn compact but highly discriminative local feature descriptors for more accurate and efficient action recognition. By leveraging the advantages of the I2C distance, the proposed I2CDDE incorporates class labels to enable fully supervised learning of local feature descriptors, which achieves highly discriminative but compact local descriptors. The objective of our I2CDDE is to minimize the I2C distances from samples to their corresponding classes while maximizing the I2C distances to the other classes in the low-dimensional space. To further improve the performance, we propose incorporating a manifold regularization based on the graph Laplacian into the objective function, which can enhance the smoothness of the embedding by extracting the local intrinsic geometrical structure. The proposed I2CDDE for the first time achieves fully supervised learning of local feature descriptors. It significantly improves the performance of I2C-based methods by increasing the discriminative ability of local features while greatly reducing the computational burden by dimensionality reduction to handle large-scale data. We apply the proposed I2CDDE algorithm to human action recognition on four widely used benchmark datasets. The results have shown that I2CDDE can significantly improve I2C-based classifiers and achieves state-of-the-art performance

Serum CIRP increases the risk of acute kidney injury after cardiac surgery

IntroductionAcute kidney injury (AKI) is a frequent perioperative complication. The underlying mechanisms of cardiac surgery-associated AKI are still not completely elucidated. Cold-induced RNA-binding protein (CIRP) has been subsequently found to be regulated by various stress conditions. During cardiac surgery and cardiopulmonary bypass (CPB), the host is subjected to hypothermia and inadequate organ perfusion, resulting in an upregulation of CIRP secretion. The aim of this study is to evaluate the role of elevated extracellular CIRP level as a contributing factor in the development of AKI.MethodsA total of 292 patients who underwent cardiac surgery were retrospectively enrolled and their serum samples were collected preoperative and postoperative. Demographic data, intraoperative data, in-hospital outcomes, and the occurrence of AKI were also collected for the patients. The correlation between CIRP and intraoperative procedures, as well as its association with postoperative outcomes were analyzed.ResultsIn multivariable analysis, higher ΔCIRP (p = 0.036) and body mass index (p = 0.015) were independent risk factors for postoperative AKI. Meanwhile, patients with postoperative AKI exhibited lower survival rate in 2-year follow-up (p = 0.008). Compared to off-pump coronary artery bypass grafting surgery, patients who underwent on-pump coronary artery bypass grafting, valve surgery, aortic dissection and other surgery showed higher ΔCIRP, measuring 1,093, 666, 914 and 258 pg/mL, respectively (p < 0.001). The levels of ΔCIRP were significantly higher in patients who underwent CPB compared to those who did not (793.0 ± 648.7 vs. 149.5 ± 289.1 pg/mL, p < 0.001). Correlation analysis revealed a positive correlation between ΔCIRP levels and the duration of CPB (r = 0.502, p < 0.001). Patients with higher CIRP levels are at greater risk of postoperative AKI (OR: 1.67, p = 0.032), especially the stage 2–3 AKI (OR: 2.11, p = 0.037).ConclusionCIRP secretion increases with prolonged CPB time after cardiac surgery, and CIRP secretion is positively correlated with the duration of CPB. Cardiac surgeries with CPB exhibited significantly higher levels of CIRP compared to non-CPB surgeries. Elevation of CIRP level is an independent risk factor for the incidence of AKI, especially the severe AKI, and were associated with adverse in-hospital outcomes

Attentive Temporal Pyramid Network for Dynamic Scene Classification

Dynamic scene classification is an important yet challenging problem especially with the presence of defected or irrelevant frames due to unconstrained imaging conditions such as illumination, camera motion and irrelevant background. In this paper, we propose the attentive temporal pyramid network (ATP-Net) to establish effective representations of dynamic scenes by extracting and aggregating the most informative and discriminative features. The proposed ATP-Net detects informative features of frames that contain the most relevant information to scenes by a temporal pyramid structure with the incorporated attention mechanism. These frame features are effectively fused by a newly designed kernel aggregation layer based on kernel approximation into a discriminative holistic representations of dynamic scenes. The proposed ATP-Net leverages the strength of attention mechanism to select the most relevant frame features and the ability of kernels to achieve optimal feature fusion for discriminative representations of dynamic scenes. Extensive experiments and comparisons are conducted on three benchmark datasets and the results show our superiority over the state-of-the-art methods on all these three benchmark datasets

Construction and analysis of competing endogenous RNA ceRNA networks in the liver of black rockfish (Sebastes schlegelii) following Aeromonas salmonicida infection

Given the dual roles in immune function and metabolism, the liver emerge as a compelling candidate to bridge host defense and metabolic adjustments during pathogen infections in teleosts. In order to dissect the roles of the liver in the immune response of Sebastes schlegelii, we conducted an investigation into the activities of SOD, CAT and GPX4, performed a systematic analysis of circRNA, miRNA and mRNA expression profiles, as well as constructed circRNA-miRNA-mRNA regulatory networks in the liver of S. schlegelii following Aeromonas salmonicida infection were performed in the present study. The present results demonstrated the content of SOD, CAT and GPX4 increased significantly at early infection stage to protect the liver tissue from excessive damage. Additionally, 622 circRNA-miRNAs pairs, 78 miRNA-mRNA pairs and 327 circRNA-miRNA-mRNA pairs were identified in our study. These differently expressed circRNAs and miRNAs were found to be associated with the regulation of LMNB1, DMBT1, NAMPT, IFIT1, CELSRs, PYGL. GO and KEGG enrichment analysis revealed that these differently expressed genes were involved in TLR signal pathway, RLRs signal pathway, PPAR signal pathway, shedding light on antibacterial ceRNA networks within the liver of S. schlegelii post A. hydrophila post infection, which provides new insights into the immune mechanisms of teleost

Fe-doped InN layers grown by molecular beam epitaxy

Iron(Fe)-doped InN (InN:Fe) layers have been grown by molecular beam epitaxy. It is found that Fe-doping leads to drastic increase of residual electron concentration, which is different from the semi-insulating property of Fe-doped GaN. However, this heavy n-type doping cannot be fully explained by doped Fe-concentration ([Fe]). Further analysis shows that more unintentionally doped impurities such as hydrogen and oxygen are incorporated with increasing [Fe] and the surface is degraded with high density pits, which probably are the main reasons for electron generation and mobility reduction. Photoluminescence of InN is gradually quenched by Fe-doping. This work shows that Fe-doping is one of good choices to control electron density in InN. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4764013