On the basis of relativistic density functional theory calculations, homo- and heterovalent binuclear uranium complexes of a polypyrrolic macrocycle in a U-O-U bridging fashion have been investigated. These complexes show a variety of oxidation states for uranium ranging from III to VI, which have been confirmed by the calculated electron-spin density on each metal center. An equatorially 5-fold uranyl coordination mode is suitable for hexavalent uranium complexes, while silylation of the uranyl oxo is favored by pentavalent uranium. Uranyl oxo ligands are not required anymore for the coordination environment of tetra- and trivalent uranium because of their replacement by strong donors such as tetrahydrofuran and iodine. Optimization of binuclear U(VI)-U(III) complexes with various coordinating modes of U(III), donor numbers, and donor types reveals that 0.5-1.0 electron has been transferred from U(III) to U(VI). Consequently, U(V)-U(IV) complexes are more favorable. Electronic structures and formation reactions of several representative uranium complexes were calculated. For example, a 5f-based σ(U-U) bonding orbital is found in the diuranium(IV) complex, rationalizing the fact that it shows the shortest U-U distance (3.82 Å) among the studied binuclear complexes.
Due to the increased frequency and intensity of forest damage caused by diseases and pests, effective methods are needed to accurately monitor the damage degree. Unmanned aerial vehicle (UAV)-based hyperspectral imaging is an effective technique for forest health surveying and monitoring. In this study, a framework is proposed for identifying the severity of damage caused by Tomicus spp. (the pine shoot beetle, PSB) to Yunnan pine (Pinus yunnanensis Franch) using UAV-based hyperspectral images. Four sample plots were set up in Shilin, Yunnan Province, China. A total of 80 trees were investigated, and their hyperspectral data were recorded. The spectral data were subjected to a one-way ANOVA. Two sensitive bands and one sensitive parameter were selected using Pearson correlation analysis and stepwise discriminant analysis to establish a diagnostic model of the damage degree. A discriminant rule was established to identify the degree of damage based on the median value between different degrees of damage. The diagnostic model with R690 and R798 as variables had the highest accuracy (R2 = 0.854, RMSE = 0.427), and the test accuracy of the discriminant rule was 87.50%. The results are important for forest damage caused by the PSB.
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