Can Negative Travel Habits Hinder Positive Travel Behavioural Change under Beijing Vehicle Restrictions?

Given the rapid development of large cities, the residents faced with pressure both at work and in their personal lives tend to solidify their choice of transport modes and form personal travel habits, which in turn leads to higher requirements for urban traffic management. Based on the modified Theory of Planned Behaviour, the structural equation method is employed to explore people’s travel behaviour. It is found that policy attitude, perceived behaviour control, and subjective norms comprehensively affect the residents’ travel intentions under the Vehicle Restrictions in place in Beijing. The residents without private cars display a stronger intention to change their travel choices under the policies. When considering the mediating effect of travel habits between travel intention and travel choice, the impact of the restrictive policies is weakened. Compared with lower-income people, those with higher incomes demonstrate more stable travel habits in response to the effects of the restrictions. The higher the income, the greater the dependence on private cars exhibited by the residents. To summarize, people’s travel habits weaken to some extent the effects of the restrictive policies. Such policies should be created with the explicit aim of gradually changing the people’s habits.</p

Can Negative Travel Habits Hinder Positive Travel Behavioural Change under Beijing Vehicle Restrictions?

Given the rapid development of large cities, the residents faced with pressure both at work and in their personal lives tend to solidify their choice of transport modes and form personal travel habits, which in turn leads to higher requirements for urban traffic management. Based on the modified Theory of Planned Behaviour, the structural equation method is employed to explore people’s travel behaviour. It is found that policy attitude, perceived behaviour control, and subjective norms comprehensively affect the residents’ travel intentions under the Vehicle Restrictions in place in Beijing. The residents without private cars display a stronger intention to change their travel choices under the policies. When considering the mediating effect of travel habits between travel intention and travel choice, the impact of the restrictive policies is weakened. Compared with lower-income people, those with higher incomes demonstrate more stable travel habits in response to the effects of the restrictions. The higher the income, the greater the dependence on private cars exhibited by the residents. To summarize, people’s travel habits weaken to some extent the effects of the restrictive policies. Such policies should be created with the explicit aim of gradually changing the people’s habits.</p

Information transfer between stock market sectors: A comparison between the USA and China

Information diffusion within financial markets plays a crucial role in the process of price formation and the propagation of sentiment and risk. We perform a comparative analysis of information transfer between industry sectors of the Chinese and the USA stock markets, using daily sector indices for the period from 2000 to 2017. The information flow from one sector to another is measured by the transfer entropy of the daily returns of the two sector indices. We find that the most active sector in information exchange (i.e., the largest total information inflow and outflow) is the {\textit{non-bank financial}} sector in the Chinese market and the {\textit{technology}} sector in the USA market. This is consistent with the role of the non-bank sector in corporate financing in China and the impact of technological innovation in the USA. In each market, the most active sector is also the largest information sink that has the largest information inflow (i.e., inflow minus outflow). In contrast, we identify that the main information source is the {\textit{bank}} sector in the Chinese market and the {\textit{energy}} sector in the USA market. In the case of China, this is due to the importance of net bank lending as a signal of corporate activity and the role of energy pricing in affecting corporate profitability. There are sectors such as the {\textit{real estate}} sector that could be an information sink in one market but an information source in the other, showing the complex behavior of different markets. Overall, these findings show that stock markets are more synchronized, or ordered, during periods of turmoil than during periods of stability.Comment: 12 pages including 8 figure

An Implementation of Multimodal Fusion System for Intelligent Digital Human Generation

With the rapid development of artificial intelligence (AI), digital humans have attracted more and more attention and are expected to achieve a wide range of applications in several industries. Then, most of the existing digital humans still rely on manual modeling by designers, which is a cumbersome process and has a long development cycle. Therefore, facing the rise of digital humans, there is an urgent need for a digital human generation system combined with AI to improve development efficiency. In this paper, an implementation scheme of an intelligent digital human generation system with multimodal fusion is proposed. Specifically, text, speech and image are taken as inputs, and interactive speech is synthesized using large language model (LLM), voiceprint extraction, and text-to-speech conversion techniques. Then the input image is age-transformed and a suitable image is selected as the driving image. Then, the modification and generation of digital human video content is realized by digital human driving, novel view synthesis, and intelligent dressing techniques. Finally, we enhance the user experience through style transfer, super-resolution, and quality evaluation. Experimental results show that the system can effectively realize digital human generation. The related code is released at https://github.com/zyj-2000/CUMT_2D_PhotoSpeaker

Explaining the differences of gait patterns between high and low-mileage runners with machine learning

Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mileages. In recent years, machine learning algorithms have been used for pattern recognition and classification of gait features to emphasize the uniqueness of gait patterns. However, they all have a representative problem of being a black box that often lacks the interpretability of the predicted results of the classifier. Therefore, this study was conducted using a Deep Neural Network (DNN) model and Layer-wise Relevance Propagation (LRP) technology to investigate the differences in running gait patterns between higher-mileage runners and low-mileage runners. It was found that the ankle and knee provide considerable information to recognize gait features, especially in the sagittal and transverse planes. This may be the reason why high-mileage and low-mileage runners have different injury patterns due to their different gait patterns. The early stages of stance are very important in gait pattern recognition because the pattern contains effective information related to gait. The findings of the study noted that LRP completes a feasible interpretation of the predicted results of the model, thus providing more interesting insights and more effective information for analyzing gait patterns