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Reference targets with stability, uniformity, and known reflectance on the Earth's surface, such as deserts, can be used for the absolute radiometric calibration of satellite sensors. A wide-angle hyperspectral reflectance model at the top of atmosphere (TOA) over such a reference target will expand the applicability of on-orbit calibration to different spectral bands and angles. To achieve the long-term, continuous, and high-precision absolute radiometric calibration of remote sensors, a wide-angle hyperspectral TOA reflectance model of the Libyan Desert was constructed based on spectral reflectance data, satellite overpass parameters, and atmospheric parameters from the Terra/Aqua and Earth Observation-1 (EO-1) satellites between 2003 and 2012. By means of angle fitting, viewing angle grouping, and spectral extension, the model is applicable for absolute radiometric calibration of the visible to short-wave infrared (SWIR) bands for sensors within viewing zenith angles of 65 degrees. To validate the accuracy and precision of the model, a total of 3120 long-term validations of model accuracy and 949 cross-validations with the Landsat 8 Operational Land Imager (OLI) and Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensors between 2013 and 2020 were conducted. The results show that the TOA reflectance calculated by the model had a standard deviation (SD) of relative differences below 1.9% and a root-mean-square error (RMSE) below 0.8% when compared with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 OLI. The SD of the relative differences and the RMSE were within 2.7% when predicting VIIRS data. [ABSTRACT FROM AUTHOR]

Soil salinization is a crucial type in the degradation of coastal land, but its spatial distribution and drivers have not been sufficiently explored especially at the depth scale owing to its multidimensional nature. In this study, we proposed a multi-depth soil salinity prediction model (0–10 cm, 10–20 cm, 20–40 cm, and 40–60 cm) fully using the advantages of satellite image data and field sampling to rapidly estimate the multi-depth soil salinity in the Yellow River Delta, China. Firstly, a multi-depth soil salinity predictive factor system was developed through correlation analysis of soil sample electrical conductivity with a series of remote-sensing parameters containing heat, moisture, salinity, vegetation indices, spectral value, and spatial location. Then, three machine learning methods including back propagation neural network (BPNN), support vector machine (SVM), and random forest (RF) were adopted to construct a coastal soil salinity inversion model. By using the best inversion model, we obtain the spatial distribution of soil salinity in the Yellow River Delta. The results show the following: (1) Environmental variables in this study are all effective variables for soil salinity prediction. The most sensitive indicators to multi-depth soil salinity are GDVI, ENDVI, SI-T, NDWI, and LST. (2) The RF model was chosen as the optimal approach for predicting and mapping soil salinity based on performance at four soil depths. (3) The soil salinity profiles exhibited intricate coexistence of two distinct types: surface aggregated and homogeneous. The former was dominant in the east, where salinity was higher. The central and southwestern parts were mostly homogeneous, with lower soil salinity. (4) The soil salinity throughout the four depths examined was found to be most elevated in saltern and bare land and lowest in wetland vegetation and farmland, according to land-cover type. This study proposed a remote sensing prediction method for salinization in multiple soil layers in the coastal plain, which could provide decision support for spatial monitoring of land salinization and achieving land degradation neutrality targets. [ABSTRACT FROM AUTHOR]

To provide carbon steel a long-term corrosion protection effect in NaCl solutions with different pH values, based on poly-acrylamide (PAM) and oleate imidazoline (OIM), a solid corrosion inhibitor with the properties of pH-controlled release was synthesized. SEM, FTIR and TGA results indicated that the OIM inhibitors were successfully loaded into PAM hydrogel with a high OIM encapsulation content (39.64 wt.%). The OIM release behavior from the hydrogel structure has two stages, quick release and sustained release. The pH of solutions could affect the initial release kinetics of OIM inhibitors and the diffusion path in the hydrogel structure. Weight loss measurement of L80 steel in different pH solutions with OIM@PAM proved the inhibitor responsive release mechanism and anticorrosion performance. The inhibition efficiency of OIM@PAM can maintain over 80% after long-term immersion in a harsh corrosive environment (pH 3), which is much higher than the inhibition efficiency of OIM@PAM in a moderate corrosive solution. [ABSTRACT FROM AUTHOR]

In this study, a column experiment was employed to evaluate the nuclide migration behavior in the surrounding rock medium of a near-surface disposal site in China and to investigate the advection–dispersion behavior of tritium (H-3) and plutonium-238 (Pu-238) in highly weathered argillaceous shale. A reasonable numerical model was selected to fit the experimental breakthrough curves (BTCs) and to obtain the relevant migration parameters. The results show the following: (1) the internal structure of the highly weathered argillaceous shale exhibited heterogeneity, and the nuclide migration BTC showed characteristics of a "curve peak moving forward" and a "tail curve trailing"; (2) compared with other models, the stream tube mode could better fit the BTCs and obtain the average dispersion coefficient , average distribution coefficient d>, and other parameters; (3) compared to the results of the batch experiment, the distribution coefficient Kd obtained from the column experiment was smaller than that obtained from the batch experiment, which is speculated to be due to the influence of contact time and the contact area between the nuclide and the medium. [ABSTRACT FROM AUTHOR]

The adsorption characteristics of corrosive anions (Cl−, HS−, S2−, HCO3− and CO32−) on TiO2 of TC4 titanium alloy in a NaCl solution containing H2S and CO2 were studied by density functional theory (DFT). The stable adsorption configuration of each corrosive species on the TiO2 (110) surface was obtained by geometric optimization, and the electronic structure and interface binding energy were calculated and analyzed. The results showed that the optimal adsorption positions of Cl−, HS−, S2−, HCO3− and CO32− on TiO2 (110) were all bridge positions. There was a strong charge interaction between the negatively charged Cl, S and O atoms in Cl−, HS−, S2−, HCO3− and CO32− and the positively charged Ti atoms of TiO2. The interface bonding was mainly caused by charge movement from around Ti atoms to around Cl, O, S atoms. The energy levels were mainly caused by the electron orbital hybridization of Cl-3p5, S-3p4, O-2p4 and Ti-3d2. All adsorption configurations were chemical adsorption. The order of influence of the five ions on the stability of TiO2 was S2− > CO32− > Cl− > HS− > HCO3−. Finally, a novel corrosion mechanism was proposed to illustrate the dynamic evolution processes of pits. [ABSTRACT FROM AUTHOR]

A hybrid polymer of SiO2@Tb3+(poly(ethylene terephthalate)-tetraglycol)3 phenanthroline (SiO2@Tb3+(PET–TEG)3Phen) was synthesized by mixing of inorganic SiO2 nanoparticles with polymeric segments of PET–TEG, whereas PET–TEG was achieved through multi-step functionalization strategy. Tb3+ ions and β-diketonate ligand Phen were added in resulting material. The experimental results demonstrated that it was well blended with PET as a robust additive, and not only promoted the crystallinity, but also possessed excellent luminescence properties. An investigation of the mechanism revealed that the SiO2 nanoparticles functioned as a crystallization promotor; the Tb3+ acted as the fluorescent centre; and the PET–TEG segments played the role of linker and buffer, providing better compatibility of PET matrix with the inorganic component. This work demonstrated that hybrid polymers are appealing as multifunctional additives in the polymer processing and polymer luminescence field. [ABSTRACT FROM AUTHOR]

Stonin 2 ( STON2 ), which functions in adjusting endocytotic complexes, is probably involved in the monitoring of the internalization of dopamine D2 receptors which have an inhibitory action of dopamine on tumor progression. However, its clinical significance in tumor progression and prognosis remains unclear. We explored the association between STON2 and the clinicopathological characteristics of epithelial ovarian cancer (EOC). The STON2 levels in ovarian cancer and normal cell lines and tissues were detected by real-time PCR and Western blot analyses. STON2 protein expression was also detected by an immunohistochemical analysis. The clinical significance of STON2 expression in ovarian cancer was statistically analyzed. STON2 significantly increased in the ovarian cancer cell lines and tissues compared to the normal ones. In the 89 EOC samples tested, STON2 expression was significantly correlated with intraperitoneal metastasis, intestinal metastasis, intraperitoneal recurrence, ascites containing tumor cells, and CA153 level. Moreover, patients with STON2 protein overexpression were more likely to exhibit platinum resistance and to have undergone neoadjuvant chemotherapy. Patients with high STON2 protein expression had a tendency to have a shorter overall survival and a poor prognosis. A multivariate analysis showed that STON2 was an independent prognostic predictor for EOC patients. In conclusion, STON2 plays an important role in the progression and prognosis of ovarian carcinoma, especially in platinum resistance, intraperitoneal metastasis, and recurrence. STON2 can be a novel antitumor drug target and biomarker which predicts an unfavorable prognosis for EOC patients.

Background: There is an abnormal expression of nuclear receptor subfamily 2 group F member 6 (NR2F6) in human cancers such as breast cancer, colon cancer, and acute myelogenous leukemia. However, its clinical significance in cervical cancer has not been established. We explored NR2F6 expression and its clinicopathological significance in early-stage cervical cancer., Methods: NR2F6 expression in cervical cancer cell lines and cervical cancer tissues was determined by Western blotting, real-time PCR, and immunochemistry (IHC). NR2F6 expression in 189 human early-stage cervical cancer tissue samples was evaluated using IHC. The relevance between NR2F6 expression and early-stage cervical cancer prognosis and clinicopathological features was determined., Results: There was marked NR2F6 mRNA and protein overexpression in the cervical cancer cells and clinical tissues compared with an immortalized squamous cell line and adjacent noncancerous cervical tissues, respectively. In the 189 cervical cancer samples, NR2F6 expression was positively related to International Federation of Gynecology and Obstetrics (FIGO) stage ( p = 0.006), squamous cell carcinoma antigen ( p = 0.006), vital status ( p < 0.001), tumor recurrence ( p = 0.001), chemotherapy ( p = 0.039), and lymph node metastasis ( p < 0.001). Overall and disease-free survival was shorter in patients with early-stage cervical cancer and higher NR2F6 levels than in patients with lower levels of NR2F6. Univariate and multivariate analysis determined that NR2F6 was an independent prognostic factor of survival in early-stage cervical cancer., Conclusions: Taken together, our findings suggest that high NR2F6 expression predicts pelvic lymph node metastasis, tumor recurrence and poor prognosis in early-stage cervical cancer. NR2F6 might be a novel prognostic biomarker and potential therapeutic target of cervical cancer., Competing Interests: The authors declare no conflict of interest.