The Guangdong-Macao Intensive Cooperation Zone in Hengqin (Intensive Cooperation Zone) has emerged as a pivotal economic hub, attracting Macao residents and enterprises. However, disparities in contract-related rules between the zone and Macao have led to legal challenges. This article delves into a comparative study of contract laws between the People’s Republic of China (PRC) and Macao. Analyzing key facets such as pacta sunt servanda, freedom of contract, principle of equity, contract form, principles of interpretation, and termination of contract, the study identifies nuanced differences. Recognizing the imperative of aligning contract laws for the Intensive Cooperation Zone’s development, the article advocates for a unified legal environment. To achieve this, the author proposes a model contract law that prioritises the United Nations Convention on Contracts for the International Sale of Goods (CISG) as the basis. Notably, Macao’s contract-related rules should govern aspects not covered by the CISG given the policy trend in the Intensive Cooperation Zone. The proposed model law serves as a foundation for legislative reform, aiming to address the existing disparities and promote the Intensive Cooperation Zone’s economic growth.
The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R2) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.
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