Stability of Doubly-Charged Negative Ions of Atoms in the Density-Functional Theory

A Watson sphere removed to infinity is used to calculate, doubly charged negative ions of the atoms B, C, N, O, Al, Si, P, and S by the electron-correlation and self-interaction corrected generalized exchange local-spin-den- sity functional theory. These second electron affinities are compared to other theoretical calculations and show the doubly charged negative ions of these atoms to be unstable even when the Watson sphere radius is made infinite by an algebraic equation, but less unstable than in ionic crystals

Exploring Chinese College Students’ Motivations to Participate in Cross-Border E-Commerce Skill Training

This paper examines college students’ motivations to participate in cross-border e-commerce skill training. The study conducted a semi-structured interview with participants of cross-border e-commerce workshops at Huaihua University using the ARCS motivation model. According to the findings, relevance and attention motivational components significantly attract students to the cross-border e-commerce skill training program. In contrast, confidence and satisfaction motivational components act as supportive motivators to persuade students to participate in the training program. Students’ knowledge of cross-border e-commerce platforms impacts their interest and attention to cross-border e-commerce workshops and their confidence and satisfaction with their learning process. It is recommended that the design of the university’s cross-border e-commerce skill training program should be optimized. Doing so is expected to maximize students’ motivations to participate in cross-border e-commerce skill training by promoting knowledge of cross-border e-commerce platforms to students of different levels

Identifying Undergraduates’ Learning Needs in Cross-Border E-Commerce Professional Training

Cross-border e-commerce (CBEC) professional training programs jointly organized by enterprises and universities effectively reduce the CBEC talent supply-demand gap in China. Without understanding students’ learning needs, it’s hard to activate students’ motivations to participate in these programs. This study investigates undergraduates’ learning demands for knowledge and skills from the CBEC professional training program. A survey based on China CBEC Professionals Standards was conducted among four CBEC-related majors at Huaihua University located at an international inland port city of Huaihua in Central China. It was found that undergraduates of different grades and majors differed in their learning demands for CBEC knowledge topics and skills. Majors, rates, CBEC-related experience and CBEC knowledge levels could affect undergraduates’ CBEC learning needs. These results suggested that universities and enterprises should jointly design a differentiated curriculum for the specific learning demands of students in different CBEC-related majors and grades. The findings of this study have provided references for Huaihua University and other universities in China to optimize curriculums for CBEC professional training programs. The study also significantly motivates students to participate in CBEC training programs

Direct Learning-Based Deep Spiking Neural Networks: A Review

The spiking neural network (SNN), as a promising brain-inspired computational model with binary spike information transmission mechanism, rich spatially-temporal dynamics, and event-driven characteristics, has received extensive attention. However, its intricately discontinuous spike mechanism brings difficulty to the optimization of the deep SNN. Since the surrogate gradient method can greatly mitigate the optimization difficulty and shows great potential in directly training deep SNNs, a variety of direct learning-based deep SNN works have been proposed and achieved satisfying progress in recent years. In this paper, we present a comprehensive survey of these direct learning-based deep SNN works, mainly categorized into accuracy improvement methods, efficiency improvement methods, and temporal dynamics utilization methods. In addition, we also divide these categorizations into finer granularities further to better organize and introduce them. Finally, the challenges and trends that may be faced in future research are prospected.Comment: Accepted by Frontiers in Neuroscienc

Chinese Language Teacher Professional Growth: A Case Study

Chinese language teachers grow with certain characteristics in their professional development. Knowing these characteristics can reveal a teacher’s developmental needs which can inform the teachers and the teacher development facilitators. This case study examines the professional development of one Chinese language teacher that works in a high school in the United States. The Five-Stage Theory is employed to direct the examination of the teacher’s growing path. Findings cover the challenges, efforts to cope with the changes, successes, and failures

MaturePred: Efficient Identification of MicroRNAs within Novel Plant Pre-miRNAs

MicroRNAs (miRNAs) are a set of short (19∼24 nt) non-coding RNAs that play significant roles as posttranscriptional regulators in animals and plants. The ab initio prediction methods show excellent performance for discovering new pre-miRNAs. While most of these methods can distinguish real pre-miRNAs from pseudo pre-miRNAs, few can predict the positions of miRNAs. Among the existing methods that can also predict the miRNA positions, most of them are designed for mammalian miRNAs, including human and mouse. Minority of methods can predict the positions of plant miRNAs. Accurate prediction of the miRNA positions remains a challenge, especially for plant miRNAs. This motivates us to develop MaturePred, a machine learning method based on support vector machine, to predict the positions of plant miRNAs for the new plant pre-miRNA candidates.A miRNA:miRNA* duplex is regarded as a whole to capture the binding characteristics of miRNAs. We extract the position-specific features, the energy related features, the structure related features, and stability related features from real/pseudo miRNA:miRNA* duplexes. A set of informative features are selected to improve the prediction accuracy. Two-stage sample selection algorithm is proposed to combat the serious imbalance problem between real and pseudo miRNA:miRNA* duplexes. The prediction method, MaturePred, can accurately predict plant miRNAs and achieve higher prediction accuracy compared with the existing methods. Further, we trained a prediction model with animal data to predict animal miRNAs. The model also achieves higher prediction performance. It further confirms the efficiency of our miRNA prediction method.The superior performance of the proposed prediction model can be attributed to the extracted features of plant miRNAs and miRNA*s, the selected training dataset, and the carefully selected features. The web service of MaturePred, the training datasets, the testing datasets, and the selected features are freely available at http://nclab.hit.edu.cn/maturepred/

Hanban Teachers’ Culture Shock and Adaptation in the U.S.: A Mixed Method Study

When entering into the United States, Hanban teachers will face a totally different cultural environment. The different culture may lead to culture shock. This research, by employing mixed methods, investigated the culture shock the Hanban teachers in the United States have experienced. By looking at the teachers’ personal characteristics and the happenings to the teachers in the culture shock period, it also identified the main factors that significantly predict the culture shock. In addition, practical ways were suggested to help the teachers cope with cultural shock effectively. Keywords: Hanban teachers, culture shock, predictive factors, culture adaptatio

Hanban Teachers’ Culture Shock and Adaptation in the U.S.: A Mixed Method Study

When entering into the United States, Hanban teachers will face a totally different cultural environment. The different culture may lead to culture shock. This research, by employing mixed methods, investigated the culture shock the Hanban teachers in the United States have experienced. By looking at the teachers’ personal characteristics and the happenings to the teachers in the culture shock period, it also identified the main factors that significantly predict the culture shock. In addition, practical ways were suggested to help the teachers cope with cultural shock effectively. Keywords: Hanban teachers, culture shock, predictive factors, culture adaptatio

Spiking PointNet: Spiking Neural Networks for Point Clouds

Recently, Spiking Neural Networks (SNNs), enjoying extreme energy efficiency, have drawn much research attention on 2D visual recognition and shown gradually increasing application potential. However, it still remains underexplored whether SNNs can be generalized to 3D recognition. To this end, we present Spiking PointNet in the paper, the first spiking neural model for efficient deep learning on point clouds. We discover that the two huge obstacles limiting the application of SNNs in point clouds are: the intrinsic optimization obstacle of SNNs that impedes the training of a big spiking model with large time steps, and the expensive memory and computation cost of PointNet that makes training a big spiking point model unrealistic. To solve the problems simultaneously, we present a trained-less but learning-more paradigm for Spiking PointNet with theoretical justifications and in-depth experimental analysis. In specific, our Spiking PointNet is trained with only a single time step but can obtain better performance with multiple time steps inference, compared to the one trained directly with multiple time steps. We conduct various experiments on ModelNet10, ModelNet40 to demonstrate the effectiveness of Spiking PointNet. Notably, our Spiking PointNet even can outperform its ANN counterpart, which is rare in the SNN field thus providing a potential research direction for the following work. Moreover, Spiking PointNet shows impressive speedup and storage saving in the training phase.Comment: Accepted by NeurIP