An inexact proximal majorization-minimization Algorithm for remote sensing image stripe noise removal

The stripe noise existing in remote sensing images badly degrades the visual quality and restricts the precision of data analysis. Therefore, many destriping models have been proposed in recent years. In contrast to these existing models, in this paper, we propose a nonconvex model with a DC function (i.e., the difference of convex functions) structure to remove the strip noise. To solve this model, we make use of the DC structure and apply an inexact proximal majorization-minimization algorithm with each inner subproblem solved by the alternating direction method of multipliers. It deserves mentioning that we design an implementable stopping criterion for the inner subproblem, while the convergence can still be guaranteed. Numerical experiments demonstrate the superiority of the proposed model and algorithm.Comment: 19 pages, 3 figure

Motion-aware Memory Network for Fast Video Salient Object Detection

Previous methods based on 3DCNN, convLSTM, or optical flow have achieved great success in video salient object detection (VSOD). However, they still suffer from high computational costs or poor quality of the generated saliency maps. To solve these problems, we design a space-time memory (STM)-based network, which extracts useful temporal information of the current frame from adjacent frames as the temporal branch of VSOD. Furthermore, previous methods only considered single-frame prediction without temporal association. As a result, the model may not focus on the temporal information sufficiently. Thus, we initially introduce object motion prediction between inter-frame into VSOD. Our model follows standard encoder--decoder architecture. In the encoding stage, we generate high-level temporal features by using high-level features from the current and its adjacent frames. This approach is more efficient than the optical flow-based methods. In the decoding stage, we propose an effective fusion strategy for spatial and temporal branches. The semantic information of the high-level features is used to fuse the object details in the low-level features, and then the spatiotemporal features are obtained step by step to reconstruct the saliency maps. Moreover, inspired by the boundary supervision commonly used in image salient object detection (ISOD), we design a motion-aware loss for predicting object boundary motion and simultaneously perform multitask learning for VSOD and object motion prediction, which can further facilitate the model to extract spatiotemporal features accurately and maintain the object integrity. Extensive experiments on several datasets demonstrated the effectiveness of our method and can achieve state-of-the-art metrics on some datasets. The proposed model does not require optical flow or other preprocessing, and can reach a speed of nearly 100 FPS during inference.Comment: 12 pages, 10 figure

Observation of the chiral anomaly induced negative magneto-resistance in 3D Weyl semi-metal TaAs

Weyl semi-metal is the three dimensional analog of graphene. According to the quantum field theory, the appearance of Weyl points near the Fermi level will cause novel transport phenomena related to chiral anomaly. In the present paper, we report the first experimental evidence for the long-anticipated negative magneto-resistance generated by the chiral anomaly in a newly predicted time-reversal invariant Weyl semi-metal material TaAs. Clear Shubnikov de Haas oscillations (SdH) have been detected starting from very weak magnetic field. Analysis of the SdH peaks gives the Berry phase accumulated along the cyclotron orbits to be {\pi}, indicating the existence of Weyl points.Comment: Submitted in February'1

The identification and characterization of nucleic acid chaperone activity of human enterovirus 71 nonstructural protein 3AB

AbstractHuman enterovirus 71 (EV71) belongs to the genus Enterovirus in the family Picornaviridae and has been recognized as one of the most important pathogens that cause emerging infectious disease. Despite of the importance of EV71, the nonstructural protein 3AB from this virus is little understood for its function during EV71 replication. Here we expressed EV71 3AB protein as recombinant protein in a eukaryotic expression system and uncovered that this protein possesses a nucleic acid helix-destabilizing and strand annealing acceleration activity in a dose-dependent manner, indicating that EV71 3AB is a nucleic acid chaperone protein. Moreover, we characterized the RNA chaperone activity of EV71 3AB, and revealed that divalent metal ions, such as Mg2+ and Zn2+, were able to inhibit the RNA helix-destabilizing activity of 3AB to different extents. Moreover, we determined that 3B plus the last 7 amino acids at the C-terminal of 3A (termed 3B+7) possess the RNA chaperone activity, and five amino acids, i.e. Lys-80, Phe-82, Phe-85, Tyr-89, and Arg-103, are critical and probably the active sites of 3AB for its RNA chaperone activity. This report reveals that EV71 3AB displays an RNA chaperone activity, adds a new member to the growing list of virus-encoded RNA chaperones, and provides novel knowledge about the virology of EV71

Impacts of Stress on Forest Recovery and Its Interaction with Canopy Height

Global climate change is leading to an increase in the frequency, intensity, and duration of drought events, which can affect the functioning of forest ecosystems. Because human activities such as afforestation and forest attributes such as canopy height may exhibit considerable spatial differences, such differences may alter the recovery paths of drought-impacted forests. To accurately assess how climate affects forest recovery, a quantitative evaluation on the effects of forest attributes and their possible interaction with the intensity of water stress is required. Here, forest recovery following extreme drought events was analyzed for Yunnan Province, southwest China. The variation in the recovery of forests with different water availability and canopy heights was quantitatively assessed at the regional scale by using canopy height data based on light detection and ranging (LiDAR) measurements, enhanced vegetation index data, and standardized precipitation evapotranspiration index (SPEI) data. Our results indicated that forest recovery was affected by water availability and canopy height. Based on the enhanced vegetation index measures, shorter trees were more likely to recover than taller ones after drought. Further analyses demonstrated that the effect of canopy height on recovery rates after drought also depends on water availability—the effect of canopy height on recovery diminished as water availability increased after drought. Additional analyses revealed that when the water availability exceeded a threshold (SPEI \u3e 0.85), no significant difference in the recovery was found between short and tall trees (p \u3e 0.05). In the context of global climate change, future climate scenarios of RCP2.6 and RCP8.5 showed more frequent water stress in Yunnan by the end of the 21st century. In summary, our results indicated that canopy height casts an important influence on forest recovery and tall trees have greater vulnerability and risk to dieback and mortality from drought. These results may have broad implications for policies and practices of forest management

Genome-Wide Association Mapping for Tomato Volatiles Positively Contributing to Tomato Flavor

Tomato volatiles, mainly derived from essential nutrients and health-promoting precursors, affect tomato flavor. Taste volatiles present a major challenge for flavor improvement and quality breeding. In this study, we performed genome-wide association studies (GWAS) to investigate potential chromosome regions associated with the tomato flavor volatiles. We observed significant variation (1200x) among the selected 28 most important volatiles in tomato based on their concentration and odor threshold importance across our sampled accessions. Using 174 tomato accessions, GWAS identified 125 significant associations (P<0.005) among 182 SSR markers and 28 volatiles (27 volatiles with at least one significant association). Several significant associations were co-localized in previously identified quantitative trait loci (QTL). This result provides new potential candidate loci affecting the metabolism of several volatiles

Forest Drought Resistance Distinguished by Canopy Height

How are the survival and growth of trees under severe drought affected by their size? While some studies have shown that large trees are more vulnerable to drought than smaller trees, others found that small trees are the more vulnerable. We explored the potential relationships between canopy height and forest responses to drought indicated by tree mortality, tree ring width index (RWI), and normalized difference vegetation index (NDVI) in the southwestern United States (SWUS) in 2002. In that year many trees had zero tree ring growth due to mortality and dieback, presumably related to drought-stress. With RWI data from a tree ring data base and climate data co-located with the field measurements, we found size-dependent linear correlations between these forest responses and canopy height in SWUS under severe drought condition. During that drought period, both trunk growth (RWI) and leaf growth (NDVI) were positively correlated with canopy height of the smaller trees (less than 18 m) and negatively correlated with canopy height of greater than 18 m. Tree mortality was negatively correlated with canopy height up to 15 m. Both local-scale and regional-scale data are consistent in showing that forests with medium canopy height (around 18 meters) showed the greatest resistance to severe drought. We suggest that negative impacts of severe drought on forests could be modified with active management of canopy structure