Nowadays, small and medium-sized enterprises (SMEs) have become an essential part of the national economy. With the increasing number of such enterprises, how to evaluate their credit risk becomes a hot issue. Unlike big enterprises with massive data to analyse, it is hard to find enough primary information of SMEs to assess their financial status, which makes the credit risk evaluation result less accurate. Limited by the lack of primary data, how to infer SMEs’ credit risk from secondary data, such as information about their upstream, downstream, parent, and subsidiary enterprises, attracts big attention from industry and academy. Targeting on accurately evaluating the credit risk of the SME, in this study, we exploit the representative power of the information network on various kinds of SME entities and SME relationships to solve the problem. With that, a heterogeneous information network of SMEs is built to mine enterprise’s secondary information. Furthermore, a novel feature named meta-path feature is proposed to measure the credit risk, which makes us able to evaluate the financial status of SMEs from various perspectives. Experiments show that our proposed meta-path feature is effective to identify SMEs with credit risks.
Forest ecosystems are crucial to the survival and development of human societies. Urbanization is expected to impact forest landscape patterns and consequently the supply of forest ecosystem services. However, the specific ways by which such impacts manifest are unclear. Therefore, to discuss the relationship between them is of great significance for realizing regional sustainable development. Here, we quantitatively assess the intensity of forest ecosystem service functions and forest landscape patterns in Renqiu City of China’s Hebei Province in 2019 using ArcGIS and FRAGSTATS. We characterize the relationships between forest ecosystem service capacity and landscape patterns, and identify strategies for the spatial optimization of forests. We find that the ecosystem service intensity of forests are significantly correlated with their spatial distribution, forest area ratio, and landscape patterns. Specifically, the percentage of landscape (PLAND) index, landscape shape index (LSI), and contagion (CONTAG) index indices display second-order polynomial relationships with various forest ecosystem service functions, with critical values of 80, 5, and 70, respectively. We propose that forest ecosystem functions can be optimized by optimizing forest landscape patterns. Specifically, to maximize the function of forest ecosystem services, managers should consider the integrity of forest ecosystems, optimize their ability to self-succession, repair service functions of key nodes within forests, enhance forests’ structural stability, optimize forest quality and community structure, and strengthen the efficiency of functional transformation per unit area. Finally, we propose a strategy for the spatial optimization of forests in Renqiu to optimize their associated ecosystem services. This involves protecting important areas for forest ecosystems, rationally organizing different ecological patches such as forests and water bodies to maximize their functions, strengthening the connectivity of scattered forests, and supplementing woodland areas.
Background
Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder in women of childbearing age. Recent studies have shown that long non-coding RNA (lncRNA) played a vital role in the development of the PCOS. Competitive endogenous RNA (ceRNA), a novel interacting mechanism, in which lncRNA could interact with micro-RNAs (miRNA) and indirectly interact with mRNAs through competing interactions. However, the mechanism of ceRNA regulated by lncRNA in the PCOS was unclear.
Results
We constructed the global background network based on the assumed lncRNA-miRNA and miRNA-mRNA pairs, which were obtained from lncRNASNP, miRTarBase and StarBase database. Then we calculated differentially expressed genes of PCOS using the data of GSE95728. PCOS related lncRNA-mRNA network (PCLMN) was constructed by hypergeometric test, including 41 mRNA nodes, 41 lncRNA nodes and 203 edges. Topological analyses was performed to determine the crucial lncRNAs with the highest centroid. We further identified the subcellular localization, performed functional module analyses and identified putative transfer factors of the key lncRNAs. Functional enrichment analyses were performed by GO classification and KEGG pathway analyses. Finally, 3 key lncRNAs(LINC00667, H19, AC073172.1) and their ceRNA sub-networks, which were involved in NF-kB signaling pathway, inflammatory, apoptotic and immune-related processes, had been found as the potential PCOS related disease genes.
Conclusions
Based on the result above, we speculate that LINC00667, H19, AC073172.1 and their ceRNA sub-networks played an crucial role in PCOS. All these results can help us discover the molecular mechanism and offer new predictive biomarkers for PCOS.
In December 2019, Coronavirus Disease 2019 (COVID-19) was first detected in Hubei Province and spread rapidly around the world. Summarizing the development of COVID-19 and assessing the effect of control measures are very critical to China and other countries. A heatmap was used to find the highest concentration of the COVID-19 outbreak and the areas with initial imported cases. A logistic growth curve model was employed to compare the development of COVID-19 before and after the emergency response took effect. We found that the number of confirmed cases peaked 9-14 days after the first detection of an imported case, but there was a peak lag in the province where the outbreak was concentrated. The average growth rate of cumulative confirmed cases decreased by approximately 50% after the emergency response began. Areas with frequent population migration have a high risk of outbreak. The emergency response taken by the Chinese government was able to effectively control the COVID-19 outbreak. Our study provides references for other countries and regions to control the COVID-19 outbreak.
“Biao Hu” was one of the eight famous traditional crafts in the late Qing dynasty. It included decorating the interior of ancient buildings and making burial objects, including ceilings, walls and windows. It was popular in the structures of northern China in the early Qing dynasty. There was white and patterned wallpaper in the Forbidden City. The latter included traditional and rare patterns. Taking the wallpaper in Lodge of Bamboo Fragrance (Zhuxiang Guan) as an example, in this article, its structure and composition have been studied by morphological observation and spectroscopic analysis. The pigments and dye were analyzed by Raman spectroscopy and UPLC. Combined with an analysis of the patterned wallpaper in other buildings of the Forbidden City, traditional technology has been investigated.
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