Government-invested construction project (GICP) has a great significance to social and economic development but suffered many risks due to its large scale, huge investment, and long construction period. The risks in GICP are complex so as to lead the project to failure; it is extremely urgent to take the risk management of GICP. This study establishes a risk early-warning framework to help the managers to understand the risk threat in advance, which supports them to make proper management strategies for the risk control. The whole framework can be concluded as three parts: information collection, data processing, and result prediction. Firstly, the 16 risk factors of GICP are identified. To express the hesitance of human decision and reduce the information loss in quantification, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are used to collect the experts’ linguistic term and transform them into numerical value. And then, these inputs are simplified into five factors based on principal component analysis (PCA), decreasing the impact of redundancy to risk early-warning. Meanwhile, the warning level is divided based on K-means, which avoids the subjectivity of experience decision. Further, the backpropagation neural network optimized by the genetic algorithm (GA-BP) is used to complete the simulation of risk value. The 75 groups of questionnaire data are used to train the network and the 10 groups are used as test set. The validation of the proposed framework has been verified with an average relative error in 7.2% and the average absolute error in 3.91. Finally, corresponding suggestions to prevent and control the different risks in GICP are put forward.

Retrospectively analyze the reconstruction methods and surgical outcomes of patients with middle and lower face soft tissue defects treated at our hospital over the past 10 years. 200 patients with middle and lower face soft tissue defects were surgically reconstructed at our hospital. Medical charts were retrospectively reviewed and analyzed to abstract the pertinent information. The lesion was mainly at the eyelid, lips, chin and nasal-cheek region. There were 41 (63.08 %) men and 24 (36.92 %) women. In our study, male to female ratio = 1.7:1. We used direct closure for night patients, local flap for 141 patients, free flap for 38 patients, combined flap for 12 patients involving extensive mid face and lower face defects. Most patients had their tumor resected and reconstructed in single stage procedure mostly with local advancement flap, and no flap failure was presented post-operatively. Middle and lower face soft tissue defects can be successfully treated with local flap in a single stage approach and step-by-step approach.

Developing carbon finance is significant to a green-oriented transition of energy but suffering risks in China. This article aims to construct a framework for the risk identification, analysis, and solution of carbon finance development. It could help trading parties, third-party intermediaries, and government to understand the main obstacles to carbon finance and then take effective control measures. Firstly, 12 risk factors in policy, economy, environment, technology, and society five aspects are identified. Secondly, the risk analysis data is obtained through a comparison of the mutual influence degree of factors, where hesitant fuzzy linguistic term set is used to collect the initial information and triangular intuitionistic fuzzy number is employed to quantify the qualitative linguistics. Expanding the analysis into fuzzy environment can avoid the loss of decision information caused by traditional single real number evaluation. Thirdly, the improved decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling methods are combined to gain the risk analysis results. K-means is used to refine the influence relationship between factors in traditional DEMATEL to three categories: high effect, low effect, and no effect, which enhances applicability of the model in reality. Finally, corresponding improvement schemes and policy suggestions are proposed for each risk factor. The findings of research show that among the risks hindering carbon finance development: low carbon price, immature carbon abatement technology, lack of carbon financial products, and operational risk are the direct factors; adjustments in international climate policy is the fundamental factor .

China’s dual-carbon targets necessitate a transition toward a greener, safer, and more efficient energy system; however, substantial disparities persist across provinces. This study evaluates high-quality energy development across 30 Chinese provinces (2011–2022) under the dual-carbon agenda and identifies differentiated transition pathways. Using a PCA-TOPSIS framework with regional pattern classification, we find an “east-high, west-low, central-dip” spatial structure and a nationwide improvement trend over time. Beijing and Guangdong remain persistent leaders, whereas the central region is the primary weak link. Green energy and energy innovation are the strongest contributors to provincial performance, highlighting the importance of clean supply and technological capability. Policy implications emphasize differentiated approaches: strengthen innovation leadership in the east, accelerate structural upgrading and clean substitution in central and resource-dependent provinces, and improve infrastructure and market integration to unlock renewable advantages in the west.