The rare earth mining area in South China is the main production base of ionic rare earth in the world, which has brought inestimable economic value to the local area and even the whole nation. However, due to the lack of mining technology and excessive pursuit for economic profits, a series of environmental problems have arisen, which is a great threat to the ecosystem of the mining area. Taking Lingbei rare earth mining area in Ganzhou as an example, this paper discriminated and analyzed such aspects as the ecological source, ecological corridor and ecological nodes of the mining area based on the landscape ecological security pattern theory and the minimum cumulative resistance model (MCR) method, and constructed a landscape ecological security pattern of the mining area during the 2009, 2013 and 2018. The results show that: i) The patch area of the ecological source of rare earth mining area is small, mainly concentrated in the east and west sides of the mining area. ii) During the selected year, the ecological source area, ecological corridors, radiation channels and the number of ecological nodes in the rare earth mining area are increasing, indicating that the landscape ecological security of the rare earth mining area has been improved to some extent, but it remains necessary for relevant departments to make a optimized planning to further reconstruct the ecological security pattern of the rare earth mining area.

In contemporary English teaching in primary and secondary schools, good use of modern educational technology can greatly improve the efficiency of teachers' teaching and students' learning, especially during the epidemic period, the application of educational technology in teaching has become an indispensable topic. As the guider of students, teachers should have more mature modern education concepts, master various advanced teaching technologies, prevent the use of "formalism" in educational technology, and ensure that network resources can have a positive impact on students' learning efficiency and effect. This paper adopts the methods of field investigation, interview and literature analysis to investigate and study the current situation of the application of modern educational technology in English teaching in Jinhe Middle School in Genhe City, analyze the existing problems, and propose targeted solutions, in order to effectively apply modern educational technology in Jinhe Middle School and improve its English teaching efficiency and effect.

The size effect on the free vibration and bending of a curved FG micro/nanobeam is studied in this paper. Using the Hamilton principle the differential equations and boundary conditions is derived for a nonlocal Euler-Bernoulli curved micro/nanobeam.  The material properties vary through radius direction. Using the Navier approach an analytical solution for simply supported boundary conditions is obtained where the power index law of FGM, the curved micro/nanobeam opening angle, the effect of aspect ratio and nonlocal parameter on natural frequencies and the radial and tangential displacements were analyzed. It is concluded that increasing the curved micro/nanobeam opening angle results in decreasing and increasing the frequencies and displacements, respectively. To validate the natural frequencies of curved nanobeam, when the radius of it approaches to infinity, is compared with a straight FG nanobeam and showed a good agreement.

The objectives of this qualitative research are to study problems and factors promoting success in the career path of government officials in the Ministry of Higher Education, Science, Research, and Innovation (MHESI) in Thailand. The study also finds out career path model to opinions between executives and government officials. This qualitative employed in-depth interview and focus group discussion with executives, academics, and civil servants. It found that the problem was the planning and management of career path due to lacking of standard pattern. Also, it found that the model of career path provides practitioners with career advancement opportunities and job titles from the very beginning to the very top where they can advance and can plan their career progression. The model also provides an opportunity to explore officers’ competencies, aptitudes, and interests that are appropriate for any type of work in the organization and able to prepare them to perform the job, which will affect the success of civil servants’ work and human resource management to create career path and develop oneself to be able to compete for academic and professional excellence, as well as prepare the government officers for appropriate positions in the future.

Falling is one of the most critical outcomes of loss of consciousness during triage in emergency department (ED). It is an important sign requires an immediate medical intervention. This paper presents a computer vision-based fall detection model in ED. In this study, we hypothesis that the proposed vision-based triage fall detection model provides accuracy equal to traditional triage system (TTS) conducted by the nursing team. Thus, to build the proposed model, we use MoveNet, a pose estimation model that can identify joints related to falls, consisting of 17 key points. To test the hypothesis, we conducted two experiments: In the deep learning (DL) model we used the complete feature consisting of 17 keypoints which was passed to the triage fall detection model and was built using Artificial Neural Network (ANN). In the second model we use dimensionality reduction Feature-Reduction for Fall model (FRF), Random Forest (RF) feature selection analysis to filter the key points triage fall classifier. We tested the performance of the two models using a dataset consisting of many images for real-world scenarios classified into two classes: Fall and Not fall. We split the dataset into 80% for training and 20% for validation. The models in these experiments were trained to obtain the results and compare them with the reference model. To test the effectiveness of the model, a t-test was performed to evaluate the null hypothesis for both experiments. The results show FRF outperforms DL model, and FRF has same accuracy of TTS.