CHARACTERIZATION OF NANOSTRUCTURE, MATERIALS, AND ELECTRON EMISSION PERFORMANCE OF NEXT-GENERATION THERMIONIC SCANDATE CATHODES

Scandate cathodes, where scandia is added to the tungsten cathode pellets, have recently received substantial and renewed research interest owing to significantly improved electron emission capabilities at lower temperatures, as compared with conventional dispenser cathodes. However, there are several persistent issues including non-uniform electron emission, lack of understanding regarding scandium’s role in the emission mechanism, and unreliable reproducibility in terms of scandate cathode fabrication. As a result, scandate cathodes have not yet been widely implemented in actual vacuum electron devices (VEDs). The surface structure and chemical composition of multiple scandate cathodes – prepared with the powder using the liquid-solid (L-S) technique – and exhibiting excellent emission behavior were characterized to give insight into the fundamental mechanism(s) of operation. This was achieved with high-resolution electron microscopy techniques that include high-precision specimen lift-out. These studies showed that the micron-sized tungsten particles that compose the largest fraction of the cathode body are highly faceted and decorated with nanoscale Ba/BaO (~10 nm), as well as larger (~150 nm) Sc2O3 and BaAl2O4 particles. The experimentally identified facets were confirmed through Wulff analysis of the tungsten crystal shape and were determined to consist of {110}, {100}, and {112} facets, in increasing order of surface area prevalence. Furthermore, it is estimated that Ba atoms decorating the tungsten crystal surfaces are present in quantities such that monolayer coverage is possible at elevated temperatures. The high-resolution electron microscopy techniques used to investigate the cross section (near-surface) of the L-S scandate cathodes also revealed that the BaAl2O4 particles (100-500 nm) that attach to the larger tungsten particles are either adjacent to the smaller Sc2O3 nanoparticles or encompass them. Furthermore, high-resolution chemical analysis and 3D elemental tomography show that the two oxides always appear to be physically distinct from each other, despite their close proximity. 3D elemental tomography also showed that the Sc2O3 particles can sometimes appear inside the larger tungsten particles, but are inhomogeneously distributed. Nanobeam electron diffraction confirmed that the crystal structure of the tungsten particles are body-centered cubic, and imply that the structure remains unchanged despite the numerous complex chemical reactions that take place throughout the impregnation and activation procedures. The role of Sc and the emission mechanism for scandate cathodes are discussed. Based on characterization results and materials computation, the role of Sc in scandate cathodes is possibly related to tuning the partial pressure of oxygen in order to establish an oxygen-poor atmosphere around the cathode surface, which is a necessary condition for the formation of the (near) equilibrium tungsten shape. A thin Ba-Sc-O surface layer (~8 nm) was detected near the surface of tungsten particles, using electron energy loss spectroscopy in the scanning transmission electron microscope. This stands in stark contrast to models invoking a ~100 nm Ba-Sc-O semiconducting surface layer, which are broadly discussed in the literature. These results provide new insights into understanding the emission mechanism of scandate cathodes

Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detection

Existing methods for anomaly detection based on memory-augmented autoencoder (AE) have the following drawbacks: (1) Establishing a memory bank requires additional memory space. (2) The fixed number of prototypes from subjective assumptions ignores the data feature differences and diversity. To overcome these drawbacks, we introduce DLAN-AC, a Dynamic Local Aggregation Network with Adaptive Clusterer, for anomaly detection. First, The proposed DLAN can automatically learn and aggregate high-level features from the AE to obtain more representative prototypes, while freeing up extra memory space. Second, The proposed AC can adaptively cluster video data to derive initial prototypes with prior information. In addition, we also propose a dynamic redundant clustering strategy (DRCS) to enable DLAN for automatically eliminating feature clusters that do not contribute to the construction of prototypes. Extensive experiments on benchmarks demonstrate that DLAN-AC outperforms most existing methods, validating the effectiveness of our method. Our code is publicly available at https://github.com/Beyond-Zw/DLAN-AC.Comment: Accepted by ECCV 202

Video Event Restoration Based on Keyframes for Video Anomaly Detection

Video anomaly detection (VAD) is a significant computer vision problem. Existing deep neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or frame prediction. However, the lack of mining and learning of higher-level visual features and temporal context relationships in videos limits the further performance of these two approaches. Inspired by video codec theory, we introduce a brand-new VAD paradigm to break through these limitations: First, we propose a new task of video event restoration based on keyframes. Encouraging DNN to infer missing multiple frames based on video keyframes so as to restore a video event, which can more effectively motivate DNN to mine and learn potential higher-level visual features and comprehensive temporal context relationships in the video. To this end, we propose a novel U-shaped Swin Transformer Network with Dual Skip Connections (USTN-DSC) for video event restoration, where a cross-attention and a temporal upsampling residual skip connection are introduced to further assist in restoring complex static and dynamic motion object features in the video. In addition, we propose a simple and effective adjacent frame difference loss to constrain the motion consistency of the video sequence. Extensive experiments on benchmarks demonstrate that USTN-DSC outperforms most existing methods, validating the effectiveness of our method.Comment: Accepted by CVPR 202

Sand burial compensates for the negative effects of erosion on the dune-building shrub Artemisia wudanica

Author's manuscript made available in accordance with the publisher's policy.Aims Plant species response to erosion or burial has been extensively studied, but few studies have examined the combined effects of erosion and subsequent burial on plants. In active sand dunes of northern China, Artemisia wudanica falls to the ground following wind erosion, accumulating sand among fallen stems in a process that may facilitate its further growth and development. Therefore, we hypothesize that subsequent sand burial might compensate for the negative effects of erosion in the growth of A. wudanica. Methods A common garden experiment was conducted using A. wudanica seedlings to evaluate their growth in response to different degrees of burial and erosion as observed at the field. Seedlings were selected and randomly assigned to six erosion treatments, two burial treatments, twelve erosion and subsequent burial treatments, and control. Each treatment was replicated six times. Results Compared with the control treatment, total biomass and the relative growth rate of shoots were stimulated in the erosion and subsequent burial treatments (significantly under the 10 cm burial), hampered in erosion only treatments, and were not affected in the burial only treatments. Adventitious roots and ramets were only observed under burial only and erosion and subsequent burial treatments. Conclusions Our results indicate that subsequent sand burial following erosion compensate for the negative effects of erosion on the growth of A. wudanica seedlings, and greatly contributed to their tolerance to wind erosion

Decadal Variation in Surface Characteristics over Xinjiang, Western China, from T/P Altimetry Backscatter Coefficients: Evidence of Climate Change

The backscatter coefficient, known as sigma0, is an important measurement of satellite radar altimetry and a key parameter for land altimetry because of its close relationship with the physical properties and geometric features of land coverage under global/regional climate change effects. Using the TOPEX/Poseidon GDR-M dataset from January 1993 to December 2004, we study the spatial and temporal distribution of sigma0 at bands Ku and C over Xinjiang, western China. The results show that the sigma0 is influenced by the water distribution over land and the time evolution of sigma0 has clear seasonal changes. River basins or deserts are classified over the spatial distribution based on different sigma0 values. For example, high sigma0 values are found in the Tarim River Basin and low values are found in the Taklimakan Desert. The periodic components of sigma0 time series are determined using the fast Fourier transformation method. The annual variation is the dominating cycle and the semi-annual variation is the secondary signal. The amplitudes of sigma0 time series at bands Ku and C are also given and most areas have quite low amplitudes except for the Tarim River Basin. Several areas including the Tarim River Basin, Tianshan Mountain and Taklimakan Desert are selected for sigma0 time series spacial analysis to discuss the reasons for variations in sigma0. The main factors are precipitation and vegetation growth, which are affected by the global/regional climate change. The correlation between the brightness temperature, which is related to the water-vapor content in the atmosphere measured by TMR at the 21 GHz channel and sigma0 at two bands, is analyzed