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The pose estimation is increasingly attracting attention in research fields such as constrained guidance and control, robotics, and communication technology. In the extreme environment of space, existing spacecraft pose estimation methods are not mature. In this regard, this paper introduces a spacecraft quadrilateral pose estimation method based on deep learning and keypoint filtering, specifically designed for spacecraft with coplanar features. A two-stage neural network is employed to detect and extract features from the spacecraft's solar panels, generating a heatmap of 2D keypoints. Geometric constraint equations are formulated based on the homographic relationship between the solar panels and the image plane, yielding the spacecraft's rough pose through the solution of these equations. The predicted confidence of 2D keypoints and rough pose are utilized to construct a pixel error loss function for keypoint filtering. The refined pose is obtained by optimizing this loss function. Extensive experiments are conducted using commonly used spacecraft pose estimation data sets, demonstrating the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The utilization of optical and synthetic aperture radar (SAR) multi-source data to obtain better land classification results has received increasing research attention. However, there is a large property and distributional difference between optical and SAR data, resulting in an enormous challenge to fuse the inherent correlation information to better characterize land features. Additionally, scale differences in various features in remote sensing images also influence the classification results. To this end, an optical and SAR Siamese semantic segmentation network, OPT-SAR-MS2Net, is proposed. This network can intelligently learn effective multi-source features and realize end-to-end interpretation of multi-source data. Firstly, the Siamese network is used to extract features from optical and SAR images in different channels. In order to fuse the complementary information, the multi-source feature fusion module fuses the cross-modal heterogeneous remote sensing information from both high and low levels. To adapt to the multi-scale features of the land object, the multi-scale feature-sensing module generates multiple information perception fields. This enhances the network's capability to learn contextual information. The experimental results obtained using WHU-OPT-SAR demonstrate that our method outperforms the state of the art, with an mIoU of 45.2% and an OA of 84.3%. These values are 2.3% and 2.6% better than those achieved by the most recent method, MCANet, respectively. [ABSTRACT FROM AUTHOR]

Epoxides are important synthetic intermediates due to their high propensity to undergo ring-opening to give a variety of products with useful functional groups. In this study, we disclose a non-halide-mediated electrochemical epoxidation of alkenes to form epoxides using water as an oxygen source. This method catalyzed by (TMP)MnCl (TMP = tetramesitylporphyrin) exhibits remarkable efficiency, enabling the epoxidation of both aromatic and aliphatic alkenes with excellent faradaic efficiencies (up to 89%). Preliminary mechanistic studies suggest the MnV＝O species generated from single electron oxidations serves as the key intermediate for the epoxidation reaction. [ABSTRACT FROM AUTHOR]

Trihelix proteins are plant-specific transcription factors that are classified as GT factors due to their binding specificity for GT elements, and they play crucial roles in development and stress responses. However, their involvement in fruit ripening and transcriptional regulatory mechanisms remains largely unclear. In this study, we cloned SlGT31 , encoding a trihelix protein in tomato (Solanum lycopersicum), and determined that its relative expression was significantly induced by the application of exogenous ethylene whereas it was repressed by the ethylene-inhibitor 1-methylcyclopropene. Suppression of SlGT31 expression resulted in delayed fruit ripening, decreased accumulation of total carotenoids, and reduced ethylene content, together with inhibition of expression of genes related to ethylene and fruit ripening. Conversely, SlGT31 -overexpression lines showed opposite results. Yeast one-hybrid and dual-luciferase assays indicated that SlGT31 can bind to the promoters of two key ethylene-biosynthesis genes, ACO1 and ACS4. Taken together, our results indicate that SlGT31 might act as a positive modulator during fruit ripening. [ABSTRACT FROM AUTHOR]

An ultra‐low quiescent current tri‐mode DC–DC boost converter is proposed in this paper, which can efficiently handle loads from 1 μA to 300 mA, providing 5‐V output from 3 to 4.2‐V input. Hysteresis current mode control is adopted to realize seamless mode switching between continuous conduction mode (CCM) and discontinuous conduction mode (DCM). In order to deal with the light load situation, this paper proposes a quasi burst mode (QBM). In this mode, most of the modules are turned off and only the QBM controller, low‐power current bias and sample and hold circuit are retained, which significantly reduces the static current of the converter, and thus improves the light load efficiency. Meanwhile, the average current of error amplifier and comparator are reduced significantly by dynamic biasing. Finally, the efficiency of the converter is greatly improved and kept at a reasonable output ripple. The proposed converter is implemented in a 0.13‐μm BCD process design and manufacturing. The test results show that the quiescent current of the converter is only 780 nA, which can achieve a peak efficiency of 95.6%, and ensure that the efficiency is maintained above 80% in the load range of 10 μA to 300 mA. [ABSTRACT FROM AUTHOR]

In order to achieve high efficiency in a wider load range, a PWM/PFM/Power-Saved mode dc–dc buck converter is proposed. The mode switching technique is based on an accurate power loss model consisting of critical components/parameters: The size of the power transistor and the ON/OFF status of power-hungry subcircuits. The circuit of mode switching technique is achieved by the reference, pulse skipped modulation (PSM) comparator and feedback resistors, and its own consumption of quiescent current is extremely low. At ultra-light load, by detecting the ZCD duration and the ripple of the output, the system can switch to the Power-Saved-Mode. The proposed buck converter was implemented by using a 0.18 μ m CMOS process. It achieves a peak efficiency of 97% and > 90% efficiency from 100 μ A to 600 mA. A 360 nA quiescent current is achieved. With a low output ripple of less than 60 mV, the input voltage range and regulated output voltage are 3.6–5 V and 1.2–3.3 V, respectively. [ABSTRACT FROM AUTHOR]

The application safety of rigid polyurethane foam (RPUF) is greatly restricted by its flammable characteristics, and the existing inorganic flame retardants have dispersibility and compatibility problems with organic matrices. Taking advantage of the good coating performance and chemical structure of biomass polydopamine (PDA), an inorganic additive flame retardant aluminium hydroxide (ATH) with biomass surface modification was prepared. The effects of unmodified and silane coupling agent modified flame retardants on the thermal, mechanical, and flame retardant properties of RPUF were compared. The study found that the overall performance of the composite material was maximized by PDA by enhancing the interaction between ATH and the matrix. Compared with RPUF and RPUF/ATH, the compressive strength of RPUF/ATH@PDA increased by 3.4% and 10.0%, respectively, and the ultimate flexural strength surged by 26.5% and 30.3%. Compared with RPUF and RPUF/ATH, the addition of ATH@PDA reduced the peak heat release rate of RPUF composites by 39.9% and 24.9%, and the total heat release by 33.6% and 31.9%. In addition, PDA promoted the conversion of RPUF to a dense and highly graphitized carbon residue during combustion and reduced the flammable and harmful gases in the combustion gas. It played a crucial role in the condensed and gas phases, which minimized the fire hazard of RPUF. [ABSTRACT FROM AUTHOR]

The sweet potato is very sensitive to low temperature. Our previous study revealed that IbMPK3-overexpressing transgenic sweet potato (M3) plants showed stronger low-temperature stress tolerance than wild-type plants (WT). However, the mechanism of M3 plants in response to low-temperature stress is unclear. To further analyze how IbMPK3 mediates low-temperature stress in sweet potato, WT and M3 plants were exposed to low-temperature stress for 2 h and 12 h for RNA-seq analysis, whereas normal conditions were used as a control (CK). In total, 3436 and 8718 differentially expressed genes (DEGs) were identified in WT at 2 h (vs. CK) and 12 h (vs. CK) under low-temperature stress, respectively, whereas 1450 and 9291 DEGs were detected in M3 plants, respectively. Many common and unique DEGs were analyzed in WT and M3 plants. DEGs related to low temperature were involved in Ca2+ signaling, MAPK cascades, the reactive oxygen species (ROS) signaling pathway, hormone transduction pathway, encoding transcription factor families (bHLH, NAC, and WRKY), and downstream stress-related genes. Additionally, more upregulated genes were associated with the MAPK pathway in M3 plants during short-term low-temperature stress (CK vs. 2 h), and more upregulated genes were involved in secondary metabolic synthesis in M3 plants than in the WT during the long-time low-temperature stress treatment (CK vs. 12 h), such as fatty acid biosynthesis and elongation, glutathione metabolism, flavonoid biosynthesis, carotenoid biosynthesis, and zeatin biosynthesis. Moreover, the interaction proteins of IbMPK3 related to photosynthesis, or encoding CaM, NAC, and ribosomal proteins, were identified using yeast two-hybrid (Y2H). This study may provide a valuable resource for elucidating the sweet potato low-temperature stress resistance mechanism, as well as data to support molecular-assisted breeding with the IbMPK3 gene. [ABSTRACT FROM AUTHOR]

This study surveys the developments in satellite attitude determination and control system, especially for microsats. This survey is not intended to be complete but is limited to the most significant developments of sensors, actuators, and algorithms in the last two decades. First, attitude determination methods including algorithms and sensors together with actuator-based control methods are introduced. Furthermore, current problems in alignment error, flexible satellites, and low redundancy of microsats attitude determination and control system are discussed. Moreover, developments of some deep-neural-networks-based methods, which have great potential in solving current problems, are summarized. [ABSTRACT FROM AUTHOR]

Radar sea clutters are echoes reflected from a patch of ocean surface, which may significantly interfere with the signals from targets, and seriously degrade the performance of marine radar remote sensing. Thus, it is vital to eliminate the effects of sea clutter. In this paper, we aim at normalizing sea clutter to a uniform level. Firstly, a detailed analysis about the characteristics and differences of clutter and targets is presented; then, we present a heuristic processing scheme which works by solving the task of sea clutter normalization as a classification problem followed by energy normalization. Multiscale and speed-up strategies are incorporated into the dynamic clustering algorithm to found a robust real-time normalization method. Finally, extensive experiments show state-of-the-art results on challenging sea clutter echoes, which demonstrate the feasibility and robustness of the proposed adaptive clustering normalization method. [ABSTRACT FROM AUTHOR]

When measuring surface deformation, because the overlap of point clouds before and after deformation is small and the accuracy of the initial value of point cloud registration cannot be guaranteed, traditional point cloud registration methods cannot be applied. In order to solve this problem, a complete solution is proposed, first, by fixing at least three cones to the target. Then, through cone vertices, initial values of the transformation matrix can be calculated. On the basis of this, the point cloud registration can be performed accurately through the iterative closest point (ICP) algorithm using the neighboring point clouds of cone vertices. To improve the automation of this solution, an accurate and automatic point cloud registration method based on biological vision is proposed. First, the three-dimensional (3D) coordinates of cone vertices are obtained through multi-view observation, feature detection, data fusion, and shape fitting. In shape fitting, a closed-form solution of cone vertices is derived on the basis of the quadratic form. Second, a random strategy is designed to calculate the initial values of the transformation matrix between two point clouds. Then, combined with ICP, point cloud registration is realized automatically and precisely. The simulation results showed that, when the intensity of Gaussian noise ranged from 0 to 1 mr (where mr denotes the average mesh resolution of the models), the rotation and translation errors of point cloud registration were less than 0.1° and 1 mr, respectively. Lastly, a camera-projector system to dynamically measure the surface deformation during ablation tests in an arc-heated wind tunnel was developed, and the experimental results showed that the measuring precision for surface deformation exceeded 0.05 mm when surface deformation was smaller than 4 mm. [ABSTRACT FROM AUTHOR]

A Laplace ℓ1 robust student's T-filter is presented for satellites to estimate their attitude state despite severe measurement noise and modeling error. Although the student's T-filter (STF) has the capability of handling measurement noise, it cannot address the unknown modeling error. It is further sensitive to the degree of freedom (DOF). Hence, the measurement covariance is updated by using the maximum correntropy criterion to accommodate the covariance of unknown modeling error in robust filtering design. Moreover, the Laplace distribution is derived to reduce the influence of the DOF parameter by forming a surrogate function of an optimization problem. Then, the majorization minimization approach is formulated to solve such an optimization problem and present the proposed filtering algorithm in the STF framework. Numerical simulation of applying the proposed attitude estimation scheme is performed by comparing it with the third/fifth-order cubature Kalman filters. [ABSTRACT FROM AUTHOR]

Energy-dissipating or damping systems have been widely used in new and retrofitted structures for reducing earthquake damage to structural frames. Most damping devices were installed using diagonal or chevronbrace configurations, until the development of toggle-brace and scissor-jack configurations. This paper presents a modified scissor-jack-damper configuration with substantially improved efficiency. The mechanical behavior of the efficient scissor-jack-damper configuration is analyzed theoretically, and a formula for the displacement magnification factor of the configuration is proposed. A steel-frame specimen installed with the efficient scissor-jack-damper configuration was tested to verify the accuracy of the formula. The seismic responses of an uncontrolled steel-frame structure and of two controlled structures, installed with a diagonal brace and efficient scissor-jack-damper configurations, were analyzed using SAP2000. The high efficiency of the proposed scissor-jack-damper configuration is thus verified for practical engineering situations. [ABSTRACT FROM AUTHOR]