Reduced-Dynamic Precise Orbit Determination for Low Earth Orbiters Based on Helmert Transformation
A model based on Helmert transformation is presented in reduced-dynamic Precise Orbit Determination(POD). As an implementation, a reduced-dynamic POD approach was developed. The approach includes two steps: firstly, kinematic POD and then reduced-dynamic POD. Based on the approach, a set of programs were developed. POD of CHAMP and GRACE was then carried out. Kinematic and reduced-dynamic POD for CHAMP and GRACE satellite over 2 weeks time show that reduced-dynamic orbits of CHAMP have a mean 3D RMS of 0.26 m compared to PSO orbit of GFZ, and the mean 3D RMS of GRACE-A has the same value compared to GNV1B orbit of JPL. The 3D RMS is reduced by up to 40% compared to kinematic solutions.
Fault tolerant control of switched nonlinear systems with time delay under asynchronous switching
This paper investigates the problem of fault tolerant control of a class of uncertain switched nonlinear systems with time delay under asynchronous switching. The systems under consideration suffer from delayed switchings of the controller. First, a fault tolerant controller is proposed to guarantee exponentially stability of the switched systems with time delay. The dwell time approach is utilized for stability analysis and controller design. Then the proposed approach is extended to take into account switched time delay systems with Lipschitz nonlinearities and structured uncertainties. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
Large scaled projects are conducted in South Yellow Sea in recent years. Topographic effect and tidal current are key issues to the coastal engineering and the ocean engineering. In this study, field surveys were conducted to investigate the tidal level, current velocity, and current direction in South Yellow Sea. A numerical model was developed to simulate the radial current field based on the field data. To investigate the mechanism of the radial current field, the actual topography and a smoothed topography were applied in the numerical model, respectively. Results show that, the current field appeares radial because of the tidal system rather than the submarine topography. Local topography centralized the radiation centre and shifted the high-velocity zones. The actual topographic effect is proposed, and results show that local topography increases the flood tide velocity and decreases the ebb tide velocity. Lagrangian residual currents are calculated to illustrate possible sediment sources and transport routes.
During the coronavirus global pandemic crisis, we have received information from authentic and inauthentic sources. Fake news, continuous rumors, and prejudiced opinions from digital platforms and social media have the capacity to disrupt social harmony, to stall personal development, and to undermine trust on all levels of human interaction. Despite the wide plurality of perspectives, the diversity of contents, the variety of voices, and the many often-conflicting reasons for publishing, our interactions with information on digital devices are progressively shaping such situations and affecting decisions on all levels. We look at the limitations of existing designs and guidelines in the current paradigm, and we ask to what extent researchers and developers can focus and contribute, through their innovations, to the reduction of uncertainty and cases of misdirection, how they can mitigate tensions between information and humans, and how they can contribute to the maintenance and enhancement of worthy human values. Human-engaged computing (HEC) calls for innate user capacities to be enhanced rather than displaced by digital technologies so that the human factor in interactions is fully exploited and truly efficient symbiotic relationships between humans and devices can be achieved. Under the framework of HEC, we propose 12 research agendas from the theoretical, principled, and practical aspects, in order to develop future synergized interactions between humans and information. The present crisis presents us with a good opportunity to reflect on the need to empower humans in relation to the tools they use and to consider the next paradigm shift for designing information interaction.
Rheumatoid arthritis (RA) is an inflammatory autoimmune disease characterized by inflammatory cell infiltration, high levels of cytokines, and erosion of cartilage and bone in joints. Calprotectin (CLP), as a recently described member of S100 family proteins, is a heterodimeric complex of S100A8 and S100A9. Currently, plenty of studies have indicated significantly increased serum and synovial fluid levels of CLP in patients with RA. It was reported that CLP was related to cell differentiation, migration, apoptosis, and production of pro-inflammatory factors in RA. In addition, there are the positive relationships between serum, synovial CLP and traditional acute phase reactants, disease activity, ultrasound and radiographic progression of joints, and treatment response of RA. In this review, we mainly discuss the role of CLP in the pathogenesis of RA as well as its potential to estimate clinical disease progression of RA patients.
The adjacency matrix of a graph is a matrix which represents adjacent relation between the vertices of the graph. Its minimum eigenvalue is defined as the least eigenvalue of the graph. Let Gn be the set of the graphs of order n, whose complements are connected and have pendent paths. This paper investigates the least eigenvalue of the graphs and characterizes the unique graph which has the minimum least eigenvalue in Gn.
Defect Detection is one of the most important parts of Automatic Identification and Data transmission. Quick Response code (QRcode) is one of the most popular types of two-dimensional barcodes. It isachallenge to detect defect of various QRcode images efficiently and accurately. In this paper, we propose the procedure byaserial of carefully designed preprocessing methods. The defect detection procedure consists of QRcode identification, QRcode reconstruction, perspective transformation, image binarization, morphological operation, image matching, and Blob analysis. By these steps, we can detect defect of different types of QRcode images. The experiment results show that our method has stronger robustness and higher efficiency. Moreover, experiment results on QRcode images show that the prediction accuracy of proposed method reaches 99.07%with an average execution time of 6.592 ms. This method can detect defect of these images in real time.
Transcription factor NF-E2-related factor 2 (Nrf2) is important for cell protection against chemical-induced oxidative stress. Previously, we have reported that in PC12 cells, Nrf2 can be triggered by deltamethrin (DM), a commonly used pyrethroid insecticide. Molecular mechanisms behind Nrf2 activation by DM are still unclear. Here we studied the effects of cell glutathione (GSH) depletion on Nrf2 activation by DM. We found that DM enhanced Nrf2 expression at the mRNA and protein levels and increased nuclear Nrf2 levels. Activation of Nrf2 was associated with activation of its downstream targets, such as heme oxygenase-1 (HO-1) and glutamate cysteine ligase catalytic subunit (GCLC). In contrast, DL-buthionine-[S,R]- sulfoximine (BSO), a known GSH-depleting agent, did not increase Nrf2 protein expression or cause its nuclear accumulation. However, pre-treatment with BSO triggered mRNA expression of HO-1 and GCLC. Furthermore, BSO pre-treatment suppressed DM-induced Nrf2 upregulation and activation and lowered mRNA expression of HO-1 and GCLC upon DM treatment. These data demonstrate that GSH depletion is not necessary for the activation of Nrf2/ARE by DM in PC12 cells, and that GCLC and HO-1 expression can increase through other signalling pathways.
Early identification can significantly improve the prognosis of children with autism spectrum disorder (ASD). Yet existing identification methods are costly, time consuming, and dependent on the manual judgment of specialists. In this study, we present a multimodal framework that fuses data on a child’s eye fixation, facial expression, and cognitive level to automatically identify children with ASD, to improve the identification efficiency and reduce costs. The proposed methodology uses an optimized random forest (RF) algorithm to improve classification accuracy and then applies a hybrid fusion method based on the data source and time synchronization to ensure the reliability of the classification results. The classification accuracy of the framework was 91%, which is higher than that of the RF, support vector machine, and discriminant analysis methods. The results suggest that data on a child’s eye fixation, facial expression, and cognitive level are useful for identifying children with ASD. Because the proposed framework can separate ASD children from typically developing (TD) children, it can facilitate the early identification of ASD and may improve intervention programs for children with ASD.
Highly-ordered ternary Fe-Co-Ni alloy nanowire arrays with diameters of about 50 nm have been fabricated by alternating current (AC) electrodeposition into the nanochannels of porous anodic aluminum oxide templates. SEM and TEM results indicate that the alloy nanowires are highly ordered. XRD and HRTEM results show that the ternary FeCoNi alloy nanowires are polycrystalline, with HCP-FCC dual phase structure. Magnetic measurements demonstrate that the ternary alloy nanowire arrays have an obvious magnetic anisotropy with an easy magnetization direction being parallel to the nanowire arrays. Along the easy magnetization direction, the coercivity (Hc) and squareness ratio (S) increase as the annealing temperature increases, and reach a maximum level (Hc = 1337 Oe, S = 0.96) at 300 °C.