Non-noble metal single-atom catalysts prepared by wet chemical method and their applications in electrochemical water splitting

Water splitting by electrolysis is an appealing pathway for sustainable hydrogen production. The practical performance of water splitting is highly dependent on the efficiency of electrocatalysts, which can promote the anodic oxygen evolution reaction(OER) or cathodic hydrogen evolution reaction(HER). Downsizing the metal nanostructures to atomic level to construct single-atom catalysts(SACs) has attracted enormous attention due to its distinct advantages in maximizing the efficiency of metal atom utilization and enhancing activity over corresponding metal nanoparticles. Research on SACs towards electrochemical water splitting application is an emerging field and intensive investigations have been focused on their rational syntheses and applications in HER/OER. In this review, we focus on the wet chemical method developed to prepare non-noble metal based SACs with an emphasis on the synthetic strategies and structure-activity relationship between single metal atoms and catalytic activity. Finally, the challenges and future opportunities for application of single-atom catalysts in water splitting are briefly addressed.

Giant retroperitoneal malignant schwannoma:A case report and review of literature

The retroperitoneal malignant schwannoma is an extremely rare pathological entity and sparsely reported in the literature.We reported a case of a 56-year-old man who was admitted to our hospital for giant retroperitoneal malignant schwannoma with 40 cm in diameter.The case did not accompanied by neurofibromatosis.We used spiral CT 3D reconstruction to identify the characters of the tumor and the invasion to the peripheral organs before surgery.The patient has been survived for more than 8 years after radical surgery.Its clinical presentation, radiological, histopathological features, and radical surgery were retrospective analysis.

Influence of anchorage length and pretension on the working resistance of rock bolt based on its tensile characteristics

In coal mining roadway support design,the working resistance of the rock bolt is the key factor affecting its maximum support load.Effective improvement of the working resistance is of great significance to roadway support.Based on the rock bolt’s tensile characteristics and the mining roadway surrounding rock deformation,a mechanical model for calculating the working resistance of the rock bolt was established and solved.Taking the mining roadway of the 17102(3)working face at the Panji No.3 Coal Mine of China as a research site,with a quadrilateral section roadway,the influence of pretension and anchorage length on the working resistance of high-strength and ordinary rock bolts in the middle and corner of the roadway is studied.The results show that when the bolt is in the elastic stage,increasing the pretension and anchorage length can effectively improve the working resistance.When the bolt is in the yield and strain-strengthening stages,increasing the pretension and anchorage length cannot effectively improve the working resistance.The influence of pretension and anchorage length on the ordinary and high-strength bolts is similar.The ordinary bolt’s working resistance is approximately 25 kN less than that of the high-strength bolt.When pretension and anchorage length are considered separately,the best pretensions of the high-strength bolt in the middle of the roadway side and the roadway corner are 41.55 and 104.26 kN,respectively,and the best anchorage lengths are 1.54 and 2.12 m,respectively.The best anchorage length of the ordinary bolt is the same as that of the high-strength bolt,and the best pretension for the ordinary bolt in the middle of the roadway side and at the roadway corner is 33.51 and 85.12 kN,respectively.The research results can provide a theoretical basis for supporting the design of quadrilateral mining roadways.

Associating Preoperative MRI Features and Gene Expression Signatures of Early-stage Hepatocellular Carcinoma Patients using Machine Learning

Background and Aims:The relationship between quanti-tative magnetic resonance imaging(MRI)imaging features and gene-expression signatures associated with the recur-rence of hepatocellular carcinoma(HCC)is not well studied.Methods:In this study,we generated multivariable regres-sion models to explore the correlation between the preoper-ative MRI features and Golgi membrane protein 1(GOLM1),SET domain containing 7(SETD7),and Rho family GTPase 1(RND1)gene expression levels in a cohort study including 92 early-stage HCC patients.A total of 307 imaging features of tumor texture and shape were computed from T2-weighted MRI.The key MRI features were identified by performing a multi-step feature selection procedure including the cor-relation analysis and the application of RELIEFF algorithm.Afterward,regression models were generated using kernel-based support vector machines with 5-fold cross-validation.Results:The features computed from higher specificity MRI better described GOLM1 and RND1 gene-expression levels,while imaging features computed from lower specificity MRI data were more descriptive for the SETD7 gene.The GOLM1 regression model generated with three features demon-strated a moderate positive correlation(p<0.001),and the RND1 model developed with five variables was positively as-sociated(p<0.001)with gene expression levels.Moreover,RND1 regression model integrating four features was mod-erately correlated with expressed RND1 levels(p<0.001).Conclusions:The results demonstrated that MRI radiomics features could help quantify GOLM1,SETD7,and RND1 ex-pression levels noninvasively and predict the recurrence risk for early-stage HCC patients.