Factors Affecting the Creativity of Young Lecturers

Purpose: The study was conducted to determine the factors affecting the creative capacity of young lecturers in the Vietnamese higher education system.   Theoretical framework: Creativity is the creation of new and helpful ideas in the field of science, art, business, and everyday activities (Amabile, 1996; Amabile, 1997). According to Woodman et al. (1993), creativity is the creation of new products, services, ideas, procedures, or processes that are useful and valuable. Kreitner & Kinicki (2004) argued that creativity is defined as the process of using imagination and skills to develop a new, unique idea, product, or process. Creativity is a difficult concept to define, researchers do not fully agree with any single definition (DiLiello & Houghton, 2006).   Design/methodology/approach: An official survey was conducted from March to April 2022. The selected subjects are young lecturers (under 40 years old) working at 15 universities in the higher education system in Vietnam. The number of survey questionnaires achieved was 328, and applying structural equation modeling (SEM) to test the research hypotheses.   Findings: The research has pointed out four factors that have positive impacts on the creative capacity of young lecturers, including intrinsic motivation, creative self-efficacy, thinking style, and the support environment. Among these, intrinsic motivation is the factor that has the most influence on the creative ability of young lecturers.   Research, Practical & Social implications: Several managerial implications are proposed to promote the creativity of young lecturers. Firstly, universities should have policies to encourage young lecturers to accept challenges and come up with new ideas. Secondly, universities should build a system to receive, evaluate, support, and provide practical suggestions for creative ideas from young lecturers. Thirdly, universities should develop a policy of recognizing and rewarding their efforts.   Originality/value: In general, the study has achieved the set goals. The study has demonstrated four factors affecting the creative capacity of young lecturers in the higher education system in Vietnam. All these factors have a positive impact on creative capacity

Standard gradient models and crack simulation

The standard gradient models have been intensively studied in the literature, cf. Fremond (1985) or Gurtin (1991) for various applications in plasticity, damage mechanics and phase change analysis. The governing equations for a solid have been introduced essentially from an extended version of the virtual equation. It is shown here first that these equations can also be derived from the formalism of energy and dissipation potentials and appear as a generalized Biot equation for the solid. In this spirit, the governing equations for higher gradient models can be straightforwardly given. The interest of gradient models is then discussed in the context of damage mechanics and crack simulation. The phenomenon of strain localization in a time-dependent or time-independent process of damage is explored as a convenient numerical method to simulate the propagation of cracks, in relation with some recent works of theliterature, cf. Bourdin Marigo [3], Lorentz al  [5], Henry al [12]

Knowledge Creation And Green Entrepreneurship: A Study Of Two Vietnamese Green Firms

This paper aims to advance the understanding and practice of knowledge-based management in Vietnam by studying two Vietnamese agricultural companies. It provides illustrative examples of how knowledge-based management, pursuing a vision that fosters creativity and innovation by employees, could ultimately fulfil the profitability objective of the business and at the same time add value to the community’s quality of life. Using the SECI model as the parameter for analysis, we found that knowledge creation processes were affected by a combination of leadership, teamwork and Ba, corporate culture, and human resource management. Our conclusion emphasises the need for future research to further examine the practice of knowledge-based management in cross-industry segments in Vietnam and in other countries with similar conditions

OMG U got flu? Analysis of shared health messages for bio-surveillance

Background: Micro-blogging services such as Twitter offer the potential to crowdsource epidemics in real-time. However, Twitter posts ('tweets') are often ambiguous and reactive to media trends. In order to ground user messages in epidemic response we focused on tracking reports of self-protective behaviour such as avoiding public gatherings or increased sanitation as the basis for further risk analysis. Results: We created guidelines for tagging self protective behaviour based on Jones and Salath\'e (2009)'s behaviour response survey. Applying the guidelines to a corpus of 5283 Twitter messages related to influenza like illness showed a high level of inter-annotator agreement (kappa 0.86). We employed supervised learning using unigrams, bigrams and regular expressions as features with two supervised classifiers (SVM and Naive Bayes) to classify tweets into 4 self-reported protective behaviour categories plus a self-reported diagnosis. In addition to classification performance we report moderately strong Spearman's Rho correlation by comparing classifier output against WHO/NREVSS laboratory data for A(H1N1) in the USA during the 2009-2010 influenza season. Conclusions: The study adds to evidence supporting a high degree of correlation between pre-diagnostic social media signals and diagnostic influenza case data, pointing the way towards low cost sensor networks. We believe that the signals we have modelled may be applicable to a wide range of diseases

AN INVESTIGATION INTO ASSESSMENT CRITERIA OF THE CONTENT CONTEXT AND FORMS OF EXTRACURRICULAR SPORTS ACTIVITIES FOR STUDENTS AT SECONDARY SCHOOLS IN TAY NINH PROVINCE, VIETNAM

After using the conventional scientific research methods, observing the steps of document synthesis, interviewing, and checking the reliability of the questionnaire through Cronbach's Alpha, the paper has come up with five quantitative assessment criteria and eight qualitative assessment questions of the content and forms of extracurricular sports activities for students at secondary schools in Tay Ninh province. This research has contributed to renewing the content and forms of extracurricular sports activities for students at secondary school.  Article visualizations

Conservation of Natural and Cultural Heritage in the Huong Son Complex of Natural Beauty and Historical Monuments, Northern Vietnam

The Huong Son Complex has long been recognised as an important sacred landscape in Vietnam due to its spiritual and cultural values. The area also retains many aesthetic and biological values. Unfortunately, its cultural and natural treasures are currently at risk due to anthropogenic impacts, mainly associated with increased spiritual tourist activities. Some urgent solutions have been implemented, but they give priority to protecting cultural values and sometimes conflict with nature conservation efforts. This problem was encountered during our recent bat conservation research in Huong Son. Our preliminary findings revealed symbiotic relationships between natural and cultural heritage in Huong Son; thus, linking nature and culture in conservation planning and management is critical for the sustainable development of the site. However, the application of this approach in Huong Son, and other sacred places in Vietnam, is challenged by gaps in basic research and the inadequate attention of local stakeholders

THE CONTENT AND METHODS OF CONDUCTING EXTRA-CURRICULAR SPORTS FOR LOWER SECONDARY SCHOOL STUDENTS IN TAY NINH PROVINCE, VIETNAM

The paper aims to provide a comprehensive, scientific and thorough description of the content and methods of how extra-curricular sports activities are conducted for lower secondary school students in Tay Ninh province. To investigate the dependable data, the research employed a range of trustworthy approaches including document synthesizing, interviewing the students and PE teachers in some lower secondary schools, and evaluating the gathered data. The results indicate that the most popular sports among the PE teachers and students are football, badminton, and volleyball which are mostly organized in group, class, and club practice, without an instructor. About the practice durations, it generally ranges from thirty minutes to two hours, equating to two or three sessions at school. Moreover, these activities usually take place in school, and it is mainly held in the afternoon or after theoretical learning.   Article visualizations

THE DIVERSITY OF YELLOW CAMELLIAS IN THE CENTRAL HIGHLANDS, VIETNAM

The Central Highlands (Tây Nguyên) is a center of yellow camellia diversity in Vietnam and the world. The Central Highlands contains 18 of Vietnam’s yellow camellia species, accounting for 37% of yellow camellia species in Vietnam and 28% of yellow camellia species worldwide. Moreover, all 18 yellow camellia species in the Central Highlands are endemic to Vietnam. The camellias of the Central Highlands belong to nine sections, accounting for 75% of the world. The yellow colors occur in three groups: pale yellow, yellow, and yellow with compound colors. The yellow camellia distribution is dispersed at 500–1600 m elevation in evergreen broadleaf forests and mixed wood-bamboo forests

Sparsity exploitation via discovering graphical models in multi-variate time-series forecasting

Graph neural networks (GNNs) have been widely applied in multi-variate time-series forecasting (MTSF) tasks because of their capability in capturing the correlations among different time-series. These graph-based learning approaches improve the forecasting performance by discovering and understanding the underlying graph structures, which represent the data correlation. When the explicit prior graph structures are not available, most existing works cannot guarantee the sparsity of the generated graphs that make the overall model computational expensive and less interpretable. In this work, we propose a decoupled training method, which includes a graph generating module and a GNNs forecasting module. First, we use Graphical Lasso (or GraphLASSO) to directly exploit the sparsity pattern from data to build graph structures in both static and time-varying cases. Second, we fit these graph structures and the input data into a Graph Convolutional Recurrent Network (GCRN) to train a forecasting model. The experimental results on three real-world datasets show that our novel approach has competitive performance against existing state-of-the-art forecasting algorithms while providing sparse, meaningful and explainable graph structures and reducing training time by approximately 40%. Our PyTorch implementation is publicly available at https://github.com/HySonLab/GraphLASS