MS-Pansharpening Algorithm Based on Dual Constraint Guided Filtering

The difference and complementarity of spatial and spectral information between multispectral (MS) image and panchromatic (PAN) image have laid the foundation for the fusion of the two types of images. In recent years, MS and PAN image fusion (also known as MS-Pansharpening) has gained attention as an important research area in remote sensing (RS) image processing. This paper proposes an MS-Pansharpening algorithm based on dual constraint Guided Filtering in the nonsubsampled shearlet transform (NSST) domain. The innovation is threefold. First, the dual constraint guided image filtering (DCGIF) model, based on spatial region average gradient correlation and vector correlation formed by neighborhood elements is proposed. Further, the PAN image detail information extraction scheme, based on the model, is provided, which extracts more complete and accurate detail information, thus avoiding, to some extent, the spectral distortion caused by the injection of non-adaptive information. Second, the weighted information injection model, based on the preservation of the correlation between the band spectra, is proposed. The model determines the information injection weight of each band pixel based on the spectral proportion between bands of the original MS image, which ensures the spectral correlation between bands of the fused MS image. Finally, a new MS-Pansharpening algorithm in NSST domain is proposed. The MS and PAN high frequency sub-bands of NSST are used to extract more effective spatial details. Then the proposed DCGIF model is used to extract the effective spatial detail injection information through the weighted joint method based on the regional energy matrix. Finally, the weighted information injection model is used to inject it into each band of MS to complete information fusion. Experimental results show that the proposed approach has better fusion effect than some conventional MS-Pansharpening algorithms, which can effectively improve the spatial resolution of the fused MS image and maintain the spectral characteristics of MS

MS-Pansharpening Algorithm Based on Dual Constraint Guided Filtering

The difference and complementarity of spatial and spectral information between multispectral (MS) image and panchromatic (PAN) image have laid the foundation for the fusion of the two types of images. In recent years, MS and PAN image fusion (also known as MS-Pansharpening) has gained attention as an important research area in remote sensing (RS) image processing. This paper proposes an MS-Pansharpening algorithm based on dual constraint Guided Filtering in the nonsubsampled shearlet transform (NSST) domain. The innovation is threefold. First, the dual constraint guided image filtering (DCGIF) model, based on spatial region average gradient correlation and vector correlation formed by neighborhood elements is proposed. Further, the PAN image detail information extraction scheme, based on the model, is provided, which extracts more complete and accurate detail information, thus avoiding, to some extent, the spectral distortion caused by the injection of non-adaptive information. Second, the weighted information injection model, based on the preservation of the correlation between the band spectra, is proposed. The model determines the information injection weight of each band pixel based on the spectral proportion between bands of the original MS image, which ensures the spectral correlation between bands of the fused MS image. Finally, a new MS-Pansharpening algorithm in NSST domain is proposed. The MS and PAN high frequency sub-bands of NSST are used to extract more effective spatial details. Then the proposed DCGIF model is used to extract the effective spatial detail injection information through the weighted joint method based on the regional energy matrix. Finally, the weighted information injection model is used to inject it into each band of MS to complete information fusion. Experimental results show that the proposed approach has better fusion effect than some conventional MS-Pansharpening algorithms, which can effectively improve the spatial resolution of the fused MS image and maintain the spectral characteristics of MS

DLRW: Dual-Link Weight Random Walk Model for Aquaculture Boundary Extraction by Single-Polarized SAR Imagery

Coastal aquaculture is undertaken in shallow and usually sheltered waters along the coast, delineated by aquaculture ponds. Illegal usage of coastal aquaculture can lead to conflicts with local communities and environmental problems. Thus, it is necessary to extract the aquaculture boundary to monitor the expansion of coastal aquaculture to the sea. However, it is challenging for most existing algorithms to extract the aquaculture boundary for synthetic aperture radar (SAR) images under a high incident angle (>30 degree) with horizontal transmitted and received (HH) or vertical transmitted and received (VV) polarization. The difficulties come from the following: (1) seawater can be seen on both sides of such boundaries, (2) the contrast of such boundaries is uneven, and (3) the backscattering coefficients in some parts of such boundaries are low. In this paper, a novel dual-link weight random walk (DLRW)-based method is proposed to extract such boundaries. The proposed DLRW is composed of an automatic seed points generation strategy, and the establishment and solving of a random walk model with the dual-link weight. By a coarse-to-fine procedure, DLRW is used to extract the aquaculture boundaries in the whole imagery. Sentinel-1 and GF-3 images in Dalian and Liaodong Bay, China have been used in experiments. Mean offset (MO), root mean square error (RMSE), Overlapped, accuracy within one pixel (WOP), and accuracy within two pixels (WTP) have been used to evaluate the performance with existing methods. Experimental results have demonstrated the proposed DLRW-based method outperforms existing methods in the extraction on aquaculture boundaries. Under the low tide, the DLRW-based method is better than the other two methods with MO, RMSE, Overlapped, WOP, and WTP by at least 5.75 pixels, 10.43 pixels, 2.88%, 11.09%, and 18.04%, respectively. Under the high tide, the DLRW-based method is superior to the other two methods with MO, RMSE, and WTP by at least 3.8 pixels, 10.5 pixels, and 6.3%. In addition, the proposed DLRW-based method has a good ability to extract the shoreline with bedrock, ports, and silt. Therefore, the proposed DLRW-based method can be of great value to coastal aquaculture monitoring, coastal mapping, and other coastal applications

Selective Hydrogenolysis of Glycerol over Acid-Modified Co–Al Catalysts in a Fixed-Bed Flow Reactor

In this study, different acid-modified Co–Al catalysts were prepared and employed for glycerol hydrogenolysis by the addition of B, Ce, Zr, and heteropolyacids (HSiW, HPW, HPMo) to Co–Al catalysts. The catalysts prepared in this work were thoroughly examined by various characterization methods such as BET, ICP, SEM, H₂ chemisorption, TEM, XRD, H₂-TPR, NH₃-TPD, XPS, and FTIR. The results showed an increase in the acid strength and Co dispersion on the catalytic surface for the modified Co–Al catalysts. This facilitated the conversion of glycerol. When ethanol was used as a solvent, the selectivity of 1,2-propanediol (1,2-PDO) by the acid-modified Co–Al catalysts decreased slightly, attributable to the enhanced etherification activity of glycerol with ethanol. However, when water was used as a solvent, the modified Co–Al catalyst with the B, Ce, and Zr species increased the selectivity of 1,2-PDO. Addition of heteropolyacids to the Co–Al catalyst enhanced the selectivity of 1,3-propanediol (1,3-PDO) as compared to 1,2-PDO selectivity which was relatively low due to its association with Brønsted acid sites on the modified Co–Al catalysts. The optimal HSiW/Co–Al catalyst (in terms of both 1,2- and 1,3-PDO selectivity) showed 76.3% glycerol conversion and 18.3% 1,3-PDO selectivity with a good stability. This could be attributed to the existence of well-dispersed Co particles with strong interaction between Co and W species

Theory of transformation-mediated twinning

High-density and nanosized deformation twins in face-centered cubic (fcc) materials can effectively improve the combination of strength and ductility. However, the microscopic dislocation mechanisms enabling a high twinnability remain elusive. Twinning usually occurs via continuous nucleation and gliding of twinning partial dislocations on consecutive close-packed atomic planes. Here we unveil a completely different twinning mechanism being active in metastable fcc materials. The transformation-mediated twinning (TMT) is featured by a preceding displacive transformation from the fcc phase to the hexagonal close-packed (hcp) one, followed by a second-step transformation from the hcp phase to the fcc twin. The nucleation of the intermediate hcp phase is driven by the thermodynamic instability and the negative stacking fault energy of the metastable fcc phase. The intermediate hcp structure is characterized by the easy slips of Shockley partial dislocations on the basal planes, which leads to both fcc and fcc twin platelets during deformation, creating more twin boundaries and further enhancing the prosperity of twins. The disclosed fundamental understanding of the complex dislocation mechanism of deformation twinning in metastable alloys paves the road to design novel materials with outstanding mechanical properties

Can experiment determine the stacking fault energy of metastable alloys?

Stacking fault energy (SFE) plays an important role in deformation mechanisms and mechanical properties of face-centered cubic (fcc) metals and alloys. In many concentrated fcc alloys, the SFEs determined from density functional theory (DFT) calculations and experimental methods are found having opposite signs. Here, we show that the negative SFE by DFT reflects the thermodynamic instability of the fcc phase relative to the hexagonal close-packed one; while the experimentally determined SFEs are restricted to be positive by the models behind the indirect measurements. We argue that the common models underlying the experimental measurements of SFE fail in metastable alloys. In various concentrated solid solutions, we demonstrate that the SFEs obtained by DFT calculations correlate well with the primary deformation mechanisms observed experimentally, showing a better resolution than the experimentally measured SFEs. Furthermore, we believe that the negative SFE is important for understanding the abnormal behaviors of partial dislocations in metastable alloys under deformation. The present work advances the fundamental understanding of SFE and its relation to plastic deformations, and sheds light on future alloy design by physical metallurgy. ? 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Interactive effect of increased high sensitive C-reactive protein and dyslipidemia on cardiovascular diseases: a 12-year prospective cohort study

Abstract Background Dyslipidemia and inflammation are significant factors for the onset of cardiovascular diseases (CVD); however, studies regarding their interactions on the risk of CVD are scarce. This study aimed to assess the interaction of dyslipidemia and high-sensitivity C-reactive protein (hs-CRP) on CVD. Methods This prospective cohort enrolled 4,128 adults at baseline in 2009 and followed them up until May 2022 for collecting CVD events. Cox-proportional hazard regression analysis estimated the hazard ratios (HRs) and 95% confidence intervals (CIs) of the associations of increased hs-CRP (≥ 1 mg/L) and dyslipidemia with CVD. The additive interactions were explored using the relative excess risk of interaction (RERI) and the multiplicative interactions were assessed with HRs (95% CI) while the multiplicative interactions were assessed by the HRs (95% CI) of interaction terms. Results The HRs of the association between increased hs-CRP and CVD were 1.42 (95% CI: 1.14–1.79) and 1.17 (95% CI: 0.89–1.53) among subjects with normal lipid levels and subjects with dyslipidemia, respectively. Stratified analyses by hs-CRP levels showed that among participants with normal hs-CRP ( 2.10 g/L had a significant association with CVD [HR (95% CI): 1.69 (1.14–2.51)]. Interaction analyses showed that increased hs-CRP had multiplicative and additive interactions with LDL-C ≥ 160 mg/dL and non-HDL-C ≥ 190 mg/dL on the risk of CVD [HRs (95%CIs): 0.309 (0.153–0.621), and 0.505 (0.295–0.866); RERIs (95%CIs): -1.704 (-3.430-0.021 and − 0.694 (-1.476-0.089), respectively, all P < 0.05]. Conclusion Overall our findings indicate negative interactions between abnormal blood lipid levels and hs-CRP on the risk of CVD. Further large-scale cohort studies with trajectories measurement of lipids and hs-CRP might verify our results as well explore the biological mechanism behind that interaction