Domestic sewage has huge negative impacts on the marine environment. This paper discusses whether residents can accept the water-pricing policy that collects funds to improve sewage treatment technologies to reduce marine pollutants by raising water prices. First, the contingent valuation method is used to elicit residents’ acceptability of a water-price increase. Second, the contingent behavior method is applied to observe residents’ responses to the pricing policy. The results show that residents can accept an increase of 0.90 CNY/m3 in water price on average in Qingdao, China. We also find that people with low income show low acceptability of the water-pricing policy. Additionally, the water price plays a positive role in promoting residents’ willingness to reduce water use. The information transmission will encourage people to adopt water-saving behavior and strengthen the impact of the water-pricing policy on water-saving behavior. This paper provides important implications to establish a water-pricing policy to reduce the negative impacts of domestic sewage on the marine environment.
It is a key to open the text reading to use the spirit of "removing blindness" to guide the method of text reading. First of all, combining with the spirit of " removing blindness " put forward by Sun Shaozhen in "Min faction Chinese", this paper expounds the theoretical source of the text reading method from the perspective of aesthetics, philosophy and creation theory; Secondly, it points out that the key of Sun Shaozhen's theory of close reading is to remove the surface mask and find the concealment of artistic creation; Secondly, it points out that the key of Sun Shaozhen's theory of close reading is to remove the surface mask and find the concealment of artistic creation; Then it reveals that the core of the spirit of "removing blindness" is to grasp the breakthrough and prevent self blindness, authority blindness and trend blindness at all times. In the end, the application of comparative method and reductive method in text careful reading is illustrated from the practical level, which points out the direction for the practice of "removing blindness" spirit. Its purpose is to remind the reader not to be fooled by the selfpsychological layer, to avoid the circle of "multiple interpretation", or to be fooled by the popular or classical theory, so as to improve the quality of the Chinese text reading and to play the humanistic function of the Chinese education.
The Physics-Informed Neural Network (PINN) approach is a new and promising way to solve partial differential equations using deep learning. The L 2 Physics-Informed Loss is the de-facto standard in training Physics-Informed Neural Networks. In this paper, we challenge this common practice by investigating the relationship between the loss function and the approximation quality of the learned solution. In particular, we leverage the concept of stability in the literature of partial differential equation to study the asymptotic behavior of the learned solution as the loss approaches zero. With this concept, we study an important class of highdimensional non-linear PDEs in optimal control, the Hamilton-Jacobi-Bellman (HJB) Equation, and prove that for general L p Physics-Informed Loss, a wide class of HJB equation is stable only if p is sufficiently large. Therefore, the commonly used L 2 loss is not suitable for training PINN on those equations, while L ∞ loss is a better choice. Based on the theoretical insight, we develop a novel PINN training algorithm to minimize the L ∞ loss for HJB equations which is in a similar spirit to adversarial training. The effectiveness of the proposed algorithm is empirically demonstrated through experiments. * Equal contribution.Preprint. Under review.
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