Commercially available and inexpensive lithium tert -butoxide ( t BuOLi) acts as a good precatalyst for the hydroboration of esters, lactones, and epoxides using pinacolborane as a borylation agent. Functional groups such as cyano-, nitro-, amino-, vinyl, and alkynyl are unaffected under the presented hydroboration process, representing high chemoselectivity. This transformation has also been effectively applied to the synthesis of key intermediates of Erlotinib and Cinacalcet. Preliminary investigations of the mechanism show that the hydroboration proceeds through the in situ formed BH 3 species.

The homoleptic lanthanide complex Sm[N(TMS)2]3 is an efficient rare-earth catalyst for the hydroboration of alkynes to the corresponding alkenylboron compounds. Practical applications were demonstrated in a gram-scale synthesis and further...

Lithium-promoted hydroboration of alkynes and alkenes using commercially available hexamethyldisilazane lithium as a precatalyst and HBpin as a hydride source has been developed. This method will be appealing for organic synthesis because of its remarkable substrate tolerance and good yields. Mechanistic studies revealed that the hydroboration proceeds through the in situ-formed BH3 species, which acts to drive the turnover of the hydroboration of alkynes and alkenes.

To address the problems appearing in multi-view three-dimensional (3D) reconstruction, such as the improvement of the accuracy and completeness of the 3D reconstructed images, a two-stage multi-level depth network is proposed. In the stage 1 of the proposed network, several convolutional block attention modules (CBAMs) are applied in the lateral connections of the feature pyramid network (FPN). This is targeted to enhance the spatial and channel relativity of the different hierarchical feature maps so as to bring more semantic information. In the stage 2, the obtained multi-scale feature maps in the stage 1 are tackled by a set of cascaded processing procedures, such as adaptive propagation, single-trees transform, and matching cost computation. As a result, a depth map could be generated and then be further refined in the processing. Comparing with other state-of-the-art methods, the subjective and objective experiments based on the DTU dataset show that our method performs better result in completeness meanwhile maintaining a considerable overall metric. The investigation of applying the proposed method for reconstructing agricultural crop images was carried out, which is based on a set of self-collected images. The experiment shows that a suitable human visual perception for the images could be obtained.

No abstract