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With the increasing scarcity of conventional energy and environmental degradation, countries around the world are increasing their investment in renewable energy development. In order to make a scientific investment evaluation of renewable energy projects, this paper examines the analysis and control of their financial data. The intelligent analysis system of financial data is constructed based on OLAP. Logistic regression model and decision tree algorithm model are selected as the operation algorithm of the system to complete the intelligent analysis of data. Combining random forest algorithm and autoregressive moving average model, under the guidance of Bagging idea, the financial status of renewable energy projects after investment is judged in order to achieve the purpose of dynamic control. According to the results of analysis and control of financial data of renewable energy projects, it is known that the correct probability of intelligent analysis of financial data reached 94.5%, 83.1%, and 92.7% for different sample sizes of data sets, respectively. There were significant improvements in the efficiency of capital usage and asset quality, with an increase in capital concentration of 30.42%, an increase in inventory turnover from 10.68% to 13.04%, and an increase in the recovery rate of overdue accounts receivable from 60.31% to 67.83%. It has been proven that the method can help investors to better utilize uncertainty to improve the investment value of project, providing investors with a new way of thinking about decision-making.

A sol–gel and phase separation method were employed to synthesize porous TiO2 coating materials, which were applied to two types of transparent substrates. The coating preparation process is simple, cost-effective, and allows for the adjustment of pore structures. The study investigated the impact of the microstructure, substrate, and UV light exposure on the hydrophilic properties of the TiO2 coating materials. The results indicate that the hydrophilicity of TiO2 coating materials prepared with resin as the substrate is inferior to that of similar coatings prepared with glass as the substrate. Furthermore, the hydrophilic performance of glass substrates coated with porous TiO2 is superior to those coated with dense TiO2. Glass substrates coated with porous TiO2 exhibit superhydrophilicity after 1 h of UV light exposure. The hydrophilic mechanism of the coating material surface was analyzed using surface energy theory, capillary theory, and photo-induced hydrophilic theory. [ABSTRACT FROM AUTHOR]

With the emergence of targeted inhibition strategies for Hedgehog signaling in cancer, multiple Hedgehog signaling pathway-related biomarkers have become the focus of research. SsGSEA algorithm was employed to analyze the Hedgehog pathway scores of samples in TCGA-HNSC dataset and divide them into two groups. Weighted co-expression network analysis was performed to identify modules strongly associated with the Hedgehog pathway. Differentially up-regulated genes in tumor samples in comparison to the normal ones were screened by Limma, in which genes belonging to modules strongly related to Hedgehog pathway were further filtered by LASSO reduction and multivariate Cox regression analysis to develop a model. ESTIMATE and CIBERSORT were served to characterize the tumor microenvironment (TME). TIDE assessed immunotherapy response. Hedgehog pathway activity was significantly higher in head and neck squamous cell carcinoma (HNSCC) tissues than in normal tissues and was correlated with HNSCC survival, glycan, cofactors and vitamins, drug metabolism, and matrix scores. Six genes (SLC2A3, EFNB2, OAF, COX4I2, MT2A and TXNRD1) were captured to form a Hedgehog associated 6-gene signature, and the resulting risk score was an independent indicator of HNSCC prognosis. It was significantly positively correlated with stromal score, metabolism, angiogenesis and inflammatory response. Patients in low-risk group with a low TIDE score had higher immunotherapy sensitivity relative to those in high-risk group. This study revealed novel findings of the Hedgehog pathway in HNSCC progression and opened up a Hedgehog pathology-related signature to help identify risk factors contributing to HNSCC progression and help predict immunotherapy outcomes. [ABSTRACT FROM AUTHOR]