Research on Innovative Teaching Design of “Securities Investment” Based on BOPPPS Teaching Mode

With the continuous and rapid development of China’s capital market, the securities investment environment has undergone earth-shaking changes, which brings new challenges to the cultivation of college students’ financial literacy in securities investment. In the teaching design of the traditional course “Securities Investment” in colleges and universities, there is a problem that the curriculum design lags behind the needs of social development, which seriously affects the quality of talent training in securities investment. In view of the above problems, this paper proposes to use the BOPPPS teaching model to carry out the teaching design of “Securities Investment”, improve the teaching quality of the course, and hope to improve the financial literacy of college students in securities investment

Adjustment Strategy of Compulsory Education School Layout in Tibet: Taking Changdu Area as an Example

It is found through survey that students, parents and teachers in Changdu area of Tibet are ambivalent about school layout adjustment, as follows. Most of students prefer to attend a day school, while they don’t object boarding. More than half of parents support to integrate teaching sites, but more than one third of parents object. More than half of teachers are for boarding, but a lot of teachers’ attitude are noncommittal even explicitly opposed to the student boarding. Moreover, the factors such as the local terrain characteristics, traffic characteristics, the characteristics of production and life style, water and electricity in poor supply and teacher shortage restrict the compulsory education school layout adjustment. Therefore, the local government about school layout adjustment should adhere to the following strategies, such as scientific planning and sustainable development, collect most parents’ advices and suggestions, keep and restore the necessary teaching sites, set standards for school construction, strengthen teachers team construction and improve the quality of school education, more government spending and encourage various forms of running a school

Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation

Recent studies have witnessed that self-supervised methods based on view synthesis obtain clear progress on multi-view stereo (MVS). However, existing methods rely on the assumption that the corresponding points among different views share the same color, which may not always be true in practice. This may lead to unreliable self-supervised signal and harm the final reconstruction performance. To address the issue, we propose a framework integrated with more reliable supervision guided by semantic co-segmentation and data-augmentation. Specially, we excavate mutual semantic from multi-view images to guide the semantic consistency. And we devise effective data-augmentation mechanism which ensures the transformation robustness by treating the prediction of regular samples as pseudo ground truth to regularize the prediction of augmented samples. Experimental results on DTU dataset show that our proposed methods achieve the state-of-the-art performance among unsupervised methods, and even compete on par with supervised methods. Furthermore, extensive experiments on Tanks&Temples dataset demonstrate the effective generalization ability of the proposed method.Comment: This paper is accepted by AAAI-21 with a Distinguished Paper Awar

Analysis of the Role of General Practitioners Services in Rural Areas during the COVID-19 Epidemic

Since the outbreak of the COVID-19, various regions of China have been rapidly deployed under the leadership of the Central Committee of the Party to actively prevent and control the COVID-19. The rural areas of my country have weak links to the prevention and management of public health emergencies. Problems include lack of medical and health resources and farmers’ low awareness of epidemic prevention. Situations that correspond to the prevention and management of the COVID-19 are more serious. As the patient’s first contact and “gatekeeper” in the fight against the epidemic, the general practitioner is responsible for the “first visit-subsequent ongoing intervention”. This article is about the prevention and control of the COVID-19 epidemics and epidemic prevention in terms of dissemination of knowledge, informed crowd control, joint prevention and control, and standardized management of people. This is a summary of the efforts of general practitioners. Quarantine at home, interactive referrals to medical consortiums, special care for contracted families. The function during the management period aims to analyze the role played by general practitioners during the epidemic and to provide new ideas for the prevention and management of the epidemic. Provide more targeted general practitioner-style services in rural areas to promote the implementation and improvement of health and poverty alleviation. The health level of the rural population provides a theoretical standard

Self-organizing Brain Emotional Learning Controller Network for Intelligent Control System of Mobile Robots

The trajectory tracking ability of mobile robots suffers from uncertain disturbances. This paper proposes an adaptive control system consisting of a new type of self-organizing neural network controller for mobile robot control. The newly designed neural network contains the key mechanisms of a typical brain emotional learning controller network and a self-organizing radial basis function network. In this system, the input values are delivered to a sensory channel and an emotional channel; and the two channels interact with each other to generate the final outputs of the proposed network. The proposed network possesses the ability of online generation and elimination of fuzzy rules to achieve an optimal neural structure. The parameters of the proposed network are on-line tunable by the brain emotional learning rules and gradient descent method; in addition, the stability analysis theory is used to guarantee the convergence of the proposed controller. In the experimentation, a simulated mobile robot was applied to verify the feasibility and effectiveness of the proposed control system. The comparative study using the cutting-edge neural network-based control systems confirms the proposed network is capable of producing better control performances with high computational efficiency

Vehicle emission and atmospheric pollution in China: problems, progress, and prospects

China has been the largest vehicle market in the world since 2009. The stalemate between the rapid development of the vehicle industry and delayed vehicle emission control has become increasingly prominent. Vehicle emission has become a significant source of air pollution in China’s cities. Understanding the current barriers in the vehicle industry is necessary for the development of effective and sustainable measures and policy to manage vehicle-induced air pollution. This review provides insight into the circumstances and causes of vehicle-induced air pollution and outlines recent progress in policy-makers’ long-term strategies and regulations. The development of an integrated mechanism of social participation, technical revolution, and regulatory innovation in vehicles, fuel, and roads is suggested to break the stalemate between air pollution and the automobile boom in China; the implications of this review extend to other countries facing the similar atmospheric pollution problems