Nutrient losses from sloping farmland in karst areas lead to the decline in land productivity and nonpoint source pollution. A specially tailored steel channel with an adjustable slope and underground hole fissures was used to simulate the microenvironment of the "dual structure" of the surface and underground of sloping farmland in a karst area. The artificial rainfall simulation method was used to explore the surface and underground runoff characteristics and nutrient losses from sloping farmland under different rainfall intensities. The effect (...) of rainfall intensity on the nutrient loss of farmland on karst sloping land was clarified. The results showed that the surface was the main route of runoff and nutrient loss during the rainy season on sloping farmland in karst areas. The influence of rainfall intensity on the nutrients in surface runoff was more substantial than that on underground runoff nutrients. Nutrient loss was more likely to occur underground than on the surface. The losses of total nitrogen, total phosphorus, and total potassium in surface and underground runoff initially increased and then gradually stabilized with the extension of rainfall duration and increased with increasing rainfall intensity and the amount of nutrient runoff. The output of nutrients through surface runoff accounted for a high proportion of the total, and underground runoff was responsible for a low proportion. Although the amount of nutrients output by underground runoff was small, it could directly cause groundwater pollution. The research results provide a theoretical reference for controlling land source pollution from sloping farming in karst areas. (shrink)

The issue of how to identify the liability of subjects after a traffic accident takes place remains a puzzle regarding the SAE classification system. The SAE system is not good at dealing with the problem of responsibility evaluation; therefore, building a new classification system for self-driving cars from the perspective of the subject's liability is a possible way to solve this problem. This new system divides automated driving into three levels: i) assisted driving based on the will of drivers, ii) (...) automated driving based on the will of the manufacturers, and iii) fully automated driving based on social will. The corresponding responsible subjects for level one, level two, and level three are the drivers, the manufacturers, and society, respectively. (shrink)

The feeling brings the "Hard Problem" to philosophy of mind. Does the subjective feeling have a non-ignorable impact on Intelligence? If so, can the feeling be realized in Artificial Intelligence (AI)? To discuss the problems, we have to figure out what the feeling means, by giving a clear definition. In this paper, we primarily give some mainstream perspectives on the topic of the mind, especially the topic of the feeling (or qualia, subjective experience, etc.). Then, a definition of the feeling (...) is proposed through a thought experiment, the "semi-transparent room". The feeling, roughly to say, is defined as "a tendency of changing input representations by representing its inner state". Also, a formalized definition is given. The definition does not help to verify "having the feeling", but it helps to provide evidence. Based on the definition, we think these are the hard problems of intelligence — whether the "innate" feeling plays an important role in Intelligence, whether the difference between the "simulated" feeling and the "innate" feeling will have a significant influence on Artificial General Intelligence (AGI), and, if so, where the "innate" feeling comes from and how to make an artificial agent possess it. (shrink)