In order to create the possibility of economic breakthrough development, remove economic institutional bottlenecks, release resources, and develop the economy quickly and sustainably in Vietnam in the coming time, it is impossible not to mention solutions to improve the quality, create breakthroughs in training and fostering talents. This is one of the important solutions in the context that the Party and State require the application and development of science and technology more and more extensively in all fields and all sectors in Vietnam. The article focuses on researching the the political basis, legal basis, and practical basis for training, fostering, attracting and employing talents in Vietnam. Meanwhile, statistics on undergraduate and postgraduate training in the period of 2016–2022, the training level of the workforce and the Global Talent Competitiveness Index show that Vietnam has not achieved many positive changes in training, fostering, attracting and employing talents as expected. The article is approached from many different aspects, including the perspective of leaders and managers at the head of state agencies, the perspective of businesses and the perspective of the university teaching staff and scientific research workers themselves. On that basis, the article points out the key contents that need addressing so as to build solutions to improve quality, create breakthroughs in training, fostering, attracting and employing talents in Vietnam in the context of international integration and science and technology development. The main contributions of the article focus on the identification of the concept of “talent”, the criteria for determining “talent” and the renewal of awareness of policies and laws on training, fostering, attracting, employing, introducing and recommending talents.

In wealthy nations, biofuel usage has grown in importance as a means of addressing climate change concerns, ensuring energy security, and promoting agricultural development. Because they understand the potential advantages of biofuel for rural development and job creation, governments have created policies and legislation to encourage the production of biofuel. However, the province of Limpopo hasn’t fully taken advantage of the potential to use biofuel production as a vehicle for job development, despite a higher demand for the fuel. There is currently a lack of understanding of the role of biofuel in promoting local development in developing regions. For this reason, this study made use of semi-structured interviews to explore how biofuel production can be used as an instrument for Local Economic Development (LED) in the Limpopo province of South Africa. The research investigated the determinants of empowerment that could impact the commercial feasibility of biofuel production in the province. It also identified the need for human resource development to get workers ready for jobs in Limpopo’s biofuel sector. The results showed that, provided certain conditions were met, the production of biofuel in Limpopo may be a useful instrument for creating local jobs. By highlighting the potential for job creation and the importance of human resource development, this research aims to facilitate evidence-based decision-making that can harness biofuel production for sustainable rural development in the region. The value of this study lies in its contribution to the understanding of biofuel’s role in LED, offering actionable insights for policymakers and stakeholders in Limpopo. 

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.

This research presents an in-depth examination of the emotional effects of synchronous hybrid education on undergraduate university students at a pioneering private institution in educational innovation. The study had encompassed all courses that were delivered in a synchronous hybrid format, covering 16 courses and involving 241 students. Each student had been observed and recorded on two separate class sessions, with each recording lasting approximately 30 min. This comprehensive data collection had resulted in 409 recordings, each approximately 30 min in duration, translating to nearly an hour of observation per student across the classes, totaling close to 205 h of recordings. These recordings were subsequently processed using neuroscience software tools for advanced statistical analysis, effectively serving as a comprehensive survey of courses within this modality. The primary focus of the research was on the emotions experienced during both face-to-face and online classes and their subsequent influence on student behavior and well-being. The findings reveal higher emotional time ratios for positive emotions such as joy and surprise in face-to-face students. Notably, both groups exhibited comparable ratios for negative emotions like anger and sadness. The research underscores the emotional advantages of face-to-face interactions, which elicit stronger emotions, in contrast to online students who often feel detached and isolated.

Aims of this study clarify the intrinsic value of Galileo’s law of inertia, which holds significance in the history of science, and the process through which such law of inertia was formed, for educational purposes, and explores a possible conversion of this intrinsic value into an environmental ethical value. The research methodology is to establish a value schema and, through its application, to explore the changes in the active intrinsic value principle of Galileo’s law of inertia based on the history of science. This study derived the following results: First, Galileo professed the value he assigned and discovered as a complete experience to support heliocentrism. Second, he realized his personal religious ideal, or in other words, the ideal of life as a whole. Third, the overall process is to feel a comprehensive and integral expansion of the self. Above all, it shows that the principle of active intrinsic value based on Galileo’s experimental activities has changed and expanded throughout the history of science. One internalizes one’s faith in accordance with the activity-centered value. Only when combined with aesthetic experience does education make one ethical. As general school education does not necessarily guarantee ethics, we must lead our values education toward ecocentric ethics education, which highlights beauty. It shows that these active intrinsic values also extend to ethical values.