A Study on the Willingness of Kindergarten Teachers to Continue With Their Educational Work as Well as Relevant Influencing Factors

Willingness to continue with their educational work represents the extent of attitude and willingness of preschool teachers to accept their occupation and be willing to continue with their work, which is not only concerned with the development of preschool teachers themselves, but also imposes a far-reaching influence on the stability of preschool teachers and the development of rural preschool education. This study explores the extent of rural kindergarten teachers’ willingness to continue with their educational work and their willingness to take teaching as a lifelong career, as well as influencing factors in respect thereof by means of literature analysis, questionnaire survey and interview. The research suggests that rural kindergarten teachers hold a relatively strong willingness to continue with their educational work, while their willingness to take teaching as a lifelong career is comparatively weak. Significant dimensional differences are observed in terms of age, teaching age, marital status and incorporation into the official staffing in respect of rural preschool teachers’ willingness to be devoted for a lifelong educational work, wherein it turns out that the older they are, the stronger their willingness to be engaged in a lifelong educational work is; the longer their teaching age is, the stronger their willingness to be engaged in a lifelong educational work is; married teachers are more willing to be engaged in a lifelong educational work than those who are merely in love or remain single; teachers unincorporated into the official staffing are more willing to be engaged in a lifelong educational work than those incorporated thereinto. The willingness of preschool teachers to continue to be engaged in the education sector is influenced by their own factors as well as external and objective factors. Finally, some suggestions are brought forward in this paper to address the above-mentioned problems: first of all, pre-service training is to be conducted to enhance professional self-identity; secondly, emphasis should be laid on humanistic care to increase job satisfaction; thirdly, welfare and treatment for teachers are to be elevated to reinforce professional attraction; and finally, more social support is to be given to gain respect and recognition towards preschool teachers

The Impact of Green Disclosure Nudging in Online Reuse Markets: Evidence from a Natural Experiment

As the environment continues to deteriorate, for managers, the means of shifting consumer behavior to green is urgently needed. Information disclosure as a tactic to promote green consumption has been widely studied, which typically stimulates demand for new green products through cost disclosure. In contrast, the impact of environmental benefit information disclosure on green consumption, especially on online reuse platforms, remains to be ascertained. In this study, we examine the economic effects of a green disclosure nudge through a natural experiment. Drawing on daily sales data, we find that the green disclosure nudge can stimulate consumer demand and generate economic benefits. We provide suggestive evidence that this positive effect stems from an increase in consumers’ perceptions of the functional and symbolic value of used products, respectively. In addition, exploratory analysis shows that the nudge may have potential social benefits. The findings provide practical and theoretical implications for promoting green consumption

Towards More Authentic Heritage Destination Experiences

Heritage destinations have a significant responsibility to visitors. In countries like China, where heritage plays a significant role in a person\u27s identity, such destinations offer visitors an opportunity to develop a deeper sense of self. For this reason, they need to be authentic, but so do the visitors. UCF Rosen College of Hospitality Management researcher Dr. Xiaoxiao Fu joined a team of experts based in China to identify how the perceived authenticity of two of China\u27s most revered heritage sites affects visitors\u27 personal sense of authenticity, their wellbeing, and how memorable they found their visits

A Miniature 3-DoF Flexible Parallel Robotic Wrist Using NiTi Wires for Gastrointestinal Endoscopic Surgery

Gastrointestinal endoscopic surgery (GES) has high requirements for instruments' size and distal dexterity, because of the narrow endoscopic channel and long, tortuous human gastrointestinal tract. This paper utilized Nickel-Titanium (NiTi) wires to develop a miniature 3-DoF (pitch-yaw-translation) flexible parallel robotic wrist (FPRW). Additionally, we assembled an electric knife on the wrist's connection interface and then teleoperated it to perform an endoscopic submucosal dissection (ESD) on porcine stomachs. The effective performance in each ESD workflow proves that the designed FPRW has sufficient workspace, high distal dexterity, and high positioning accuracy.Comment: IEEE International Conference on Robotics and Automation (ICRA) 2022 workshop: Frontiers of Endoluminal Intervention: Clinical opportunities and technical challenge

Point Contrastive Prediction with Semantic Clustering for Self-Supervised Learning on Point Cloud Videos

We propose a unified point cloud video self-supervised learning framework for object-centric and scene-centric data. Previous methods commonly conduct representation learning at the clip or frame level and cannot well capture fine-grained semantics. Instead of contrasting the representations of clips or frames, in this paper, we propose a unified self-supervised framework by conducting contrastive learning at the point level. Moreover, we introduce a new pretext task by achieving semantic alignment of superpoints, which further facilitates the representations to capture semantic cues at multiple scales. In addition, due to the high redundancy in the temporal dimension of dynamic point clouds, directly conducting contrastive learning at the point level usually leads to massive undesired negatives and insufficient modeling of positive representations. To remedy this, we propose a selection strategy to retain proper negatives and make use of high-similarity samples from other instances as positive supplements. Extensive experiments show that our method outperforms supervised counterparts on a wide range of downstream tasks and demonstrates the superior transferability of the learned representations.Comment: Accepted by ICCV 202

An Optimal Transmission Strategy for Joint Wireless Information and Energy Transfer in MIMO Relay Channels

An optimal resource allocation strategy for MIMO relay system is considered in simultaneous wireless information and energy transfer network, where two users with multiple antennas communicate with each other assisted by an energy harvesting MIMO relay that gathers energy from the received signal by applying time switching scheme and forwards the received signal by using the harvesting energy. It is focused on the precoder design and resource allocation strategies for the system to allocate the resources among the nodes in decode-and-forward (DF) mode. Specifically, optimal precoder design and energy transfer strategy in MIMO relay channel are firstly proposed. Then, we formulate the resource allocation optimization problem. The closed-form solutions for the time and power allocation are derived. It is revealed that the solution can flexibly allocate the resource for the MIMO relay channel to maximize the sum rate of the system. Simulation results demonstrated that the performance of the proposed algorithm outperforms the traditional fixed method

NeTO:Neural Reconstruction of Transparent Objects with Self-Occlusion Aware Refraction-Tracing

We present a novel method, called NeTO, for capturing 3D geometry of solid transparent objects from 2D images via volume rendering. Reconstructing transparent objects is a very challenging task, which is ill-suited for general-purpose reconstruction techniques due to the specular light transport phenomena. Although existing refraction-tracing based methods, designed specially for this task, achieve impressive results, they still suffer from unstable optimization and loss of fine details, since the explicit surface representation they adopted is difficult to be optimized, and the self-occlusion problem is ignored for refraction-tracing. In this paper, we propose to leverage implicit Signed Distance Function (SDF) as surface representation, and optimize the SDF field via volume rendering with a self-occlusion aware refractive ray tracing. The implicit representation enables our method to be capable of reconstructing high-quality reconstruction even with a limited set of images, and the self-occlusion aware strategy makes it possible for our method to accurately reconstruct the self-occluded regions. Experiments show that our method achieves faithful reconstruction results and outperforms prior works by a large margin. Visit our project page at \url{https://www.xxlong.site/NeTO/