The ocean covers 71% of the Earth's surface. At present, only about 20% of the seafloor topography (ST) has been directly measured by ships, and most areas are predicted from satellite altimetry‐derived gravity products. In this study, an adaptive nonlinear iterative (ANI) method is proposed to address two major problems in gravity ST inversion: linear approximation and empirical seafloor density contrast (SDC). In ANI, the SDC is adaptively estimated as an output, while higher‐order Parker expansion and modified Bott's iteration are combined to recover nonlinear topography. We apply our new method using the DTU21GRA altimetric gravity model and single‐beam bathymetry to predict the ST in a part of the South China Sea. Results reveal that the average SDC in the study area is 1.24 g/cm3, which compares well to CRUST1.0. The root‐mean‐square (RMS) error between the nonlinear model and single‐beam checkpoints is 102.1 m, which is improved by 34.5%, 29.2%, and 18.3% compared with the non‐gravity model, topo_24.1, and linear model, respectively. The RMS error between the nonlinear model and multibeam bathymetry is 91.0 m, which is better than the linear model. Analysis of two‐dimensional profiles shows that the nonlinear model reveals more terrain details than the linear model.
The healing of infected bone defects (IBD) is a complex physiological process involving a series of spatially and temporally overlapping events, including pathogen clearance, immunological modulation, vascularization, and osteogenesis. Based on the theory that bone healing is regulated by both biochemical and biophysical signals, in this study, a copper doped bioglass (CuBGs)/methacryloyl‐modified gelatin nanoparticle (MA‐GNPs)/methacrylated silk fibroin (SilMA) hybrid hydrogel is developed to promote IBD healing. This hybrid hydrogel demonstrates a dual‐photocrosslinked interpenetrating network mechanism, wherein the photocrosslinked SilMA as the main network ensures structural integrity, and the photocrosslinked MA‐GNPs colloidal network increases strength and dissipates loading forces. In an IBD model, the hydrogel exhibits excellent biophysical characteristics, such as adhesion, adaptation to irregular defect shapes, and in situ physical reinforcement. At the same time, by sequentially releasing bioactive ions such as Cu2+, Ca2+, and Si2+ ions from CuBGs on demand, the hydrogel spatiotemporally coordinates antibacterial, immunomodulatory and bone remodeling events, efficiently removing infection and accelerating bone repair without the use of antibiotics or exogenous recombinant proteins. Therefore, the hybrid hydrogel can be used as a simple and effective method for the treatment of IBD.
SUMMARY The precise estimation of the mass changes in Madagascar is a challenge by using the Gravity Recovery and Climate Experiment (GRACE) mission Level-2 products since they are contaminated by noise. Although this issue can be alleviated by the empirical destriping method or spatial filtering, they result in potential signal distortion or signal leakage. To improve this, we propose a reconstructive filter, whose parameters are optimized by the signal-to-noise ratio. Subsequently, our optimal filter corresponding to the best signal-to-noise ratio (5.63) is used to estimate the mass changes (2002–2017) in Madagascar. Eventually, our results are compared with two reliable GRACE mascon products and other independent observations. Correspondingly, here are our major conclusions: (1) Compared with groundwater storage from the mascon products, our estimates have the highest Pearson correlation (0.5) with in situ observation and can detect the rapid increase of groundwater storage during the rainy season. (2) The Fourier spectrum analysis detects a ∼3.8-yr periodic signal in the terrestrial water storage changes in Madagascar, which is contributed from the interannual precipitation driven by climate factor (Indian Ocean Dipole) and the aliasing error for imperfect GRACE pre-process. Our work introduces an effective filter for processing GRACE Level-2 data and presents novel insights into mass changes in Madagascar.
In this study, we aim to estimate the mass changes in Panama using the Gravity Recovery and Climate Experiment level-2 products, which are formed as spherical harmonic coefficients and limited by stripe noise. The empirical de-striping method and the temporal filter achieved by empirical mode decomposition can be used to reveal the signals but are still limited in signal reservation and noise reduction. To this end, we put forward a novel efficient strategy that uses the variational mode decomposition algorithm to filter the time series of each SHC separately. Based on the two reliable mascon products and in situ short-term groundwater observations, various comparisons in spatial, spectral, and temporal domains are implemented. In addition, the SNR (signal-to-noise ratio) index and the three-cornered hat method are adopted for assessment. The main results and conclusions are as follows: 1) Our filter outperforms the two previous methods with the best SNR (2.14) and the lowest Panama regional uncertainty (70 mm) for all available months. 2) Our estimate of the basin groundwater storage is closest to one of the groundwater observations with the maximum correlation coefficient (0.72, p<0.05). This result suggests that our method seems to detect small-scale mass signals that are undetectable in the two mascon products. Our work provides a reference for studying the mass change of small-scale basins in low latitudes.
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