Clouds have a huge impact on the energy balance, climate and weather of the earth. Cloud types have different cloud radiation effects, which is an important indicator of cloud radiation effects. Therefore, determining the type of cloud is of great significance in meteorology. In this paper, the Convolutional neural network with Squeeze & Excitation Networks (SENet) are mainly used to solve this probelm. CNN can automatically learn the filters that need to be manually set before, and can learn complex edge, spatial and texture information in the image which are difficult for traditional methods to learn and extract. Moerover, a website and a deep learning framework are established to showcase the results of this article and to further develop our models and methods through open source methods.

Intervertebral disc degeneration (IDD), which is distinguished by a variety of pathologic alterations, is the major cause of low back pain (LBP). Nonetheless, preventative measures or therapies that may delay IDD are scarcely available. In this study, we sought to identify new diagnostic biological markers for IDD. In this first-of-a-kind study combining machine learning, stem cell treatment samples and single-cell sequencing data were collected. Differentially expressed genes (DEGs) were detected from the treatment group and clusters. To filter potential markers, support vector machine analysis and LASSO were performed. LAPTM5 was found to be the hub gene for IDD. In addition, the results of single-cell sequencing demonstrated the critical function of stem cells in IDD. Finally, we found that aging is significantly associated with the rate of stem cells. In general, our results may offer fresh insights that may be used in the investigation of innovative markers for diagnosing IDD. The critical genes identified by the machine learning algorithm could provide new perspectives on IDD.

Aim. This study aimed to investigate the potential of Liu’s Zhenggudan No. 2 Formula (LZF2) in inducing osteogenic differentiation of human umbilical cord blood mesenchymal stem cells (hUCB-MSCs) and treating osteoporosis (OP), thereby providing new methods and ideas for the treatment of OP by traditional Chinese medicine. Methods. Forty sample rats were equally divided into five groups: high-concentration LZF2, low-concentration LZF2, the Eucommia ulmoides (EU) group, the classical osteogenesis induction (COI) group, and the blank control group. Eight rats in each group were routinely housed for 7 days. Subsequently, to induce hUCB-MSCs, drug-containing serum was extracted from the abdominal aorta of rats to prepare the osteogenic induction solution. In addition, alkaline phosphatase (ALP) activity and osteocalcin (OCN) content assays, and alizarin red staining were performed on days 3, 6, 9, and 12 after culture. Results. After induction of hUCB-MSCs, ALP activity and OCN content increased significantly in the high-concentration LZF2 group. Alizarin red staining also depicted numerous orange-red calcified nodules in rats in the high-concentration LZF2 group. Conclusion. High concentration of LZF2 can facilitate the differentiation of hUCB-MSCs to promote osteogenesis.