This study explores the impact of online assessments on students’ academic performance and learning outcomes at the University of Technology in South Africa. The research problem addresses the effectiveness and challenges of digital assessment platforms in higher education (HE), particularly their influence on student engagement, feedback quality, and academic integrity. A qualitative case study approach was employed, involving semi-structured interviews with ten undergraduate and postgraduate students from diverse academic backgrounds. The findings reveal that while online assessments provide flexibility and immediate feedback, they also pose challenges related to technical issues, feedback delays, and concerns about long-term knowledge retention. The study highlights the necessity of aligning assessment strategies with constructivist learning principles to enhance critical thinking and student-centered learning. Implications for theory include strengthening the application of constructivist learning in digital environments, while practical recommendations focus on improving assessment design, institutional support, and feedback mechanisms. Policy adjustments should consider inclusive and equitable access to online assessments. Future research should further investigate the long-term impact of digital assessments on professional readiness. This study contributes to ongoing discussions on online education by offering a nuanced understanding of digital assessment challenges and opportunities in higher education.

The focus of the article is the evaluation of the interaction between regional state bodies and business structures in Kazakhstan, specifically in terms of the development of public-private partnerships. The purpose of the research is to enhance the understanding of the theoretical and practical aspects of the mechanism of interaction between the state and business structures. Through an examination of the various structural components of the partnership development strategy, the study aims to identify the elements of the mechanism for the implementation of the state and business development strategy. Additionally, the research seeks to establish the correlation between the outcomes of the joint entrepreneurship mechanism and the criteria used to evaluate the performance of regional state bodies. To assess the effectiveness of the interaction between business and government at the regional level in Kazakhstan, a survey-based evaluation was conducted to measure the satisfaction levels of public utilities, entrepreneurs, and businesses with the activities of local authorities. The survey also evaluated the degree of corruption among local authorities. A matrix of interaction between business and government was created, and various models and algorithms for the interaction between government representatives and business structures were studied. The research findings highlight the importance of enhancing the collaboration between the state and the business sector, promoting the implementation of public-private partnerships, and establishing social partnerships to cultivate mutually beneficial relationships.

With the increasing demand for sustainable energy, advanced characterization methods are becoming more and more important in the field of energy materials research. With the help of X-ray imaging technology, we can obtain the morphology, structure and stress change information of energy materials in real time from two-dimensional and three-dimensional perspectives. In addition, with the help of high penetration X-ray and high brightness synchrotron radiation source, in-situ experiments are designed to obtain the qualitative and quantitative change information of samples during the charge and discharge process. In this paper, X-ray imaging technology based on synchrotron and its related applications are reviewed. The applications of several main X-ray imaging technologies in the field of energy materials, including X-ray projection imaging, transmission X-ray microscopy, scanning transmission X-ray microscopy, X-ray fluorescence microscopy and coherent diffraction imaging, are discussed. The application prospects and development directions of X-ray imaging in the future are prospected.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO₂ in 2023 and 2059 tCO₂ in 2030.

Entrepreneurial self-efficacy has a predictive effect on entrepreneurial performance. The lithium-ion battery industry is the cornerstone of the emergency of the four emerging industries of “new energy”, “new materials”, “new technology” and “high-end manufacturing”. In the past, scholars have not considered the characteristics of entrepreneurs in their research on improving Chinese lithium-ion battery new venture growth. The personal characteristics of entrepreneurs have not received widespread attention from scholars. This article will start with the characteristics of entrepreneurs themselves and explore the path that entrepreneurs’ characteristics affect Chinese lithium battery new venture growth. This article builds a structural equation model to empirically analyze the relationship among variables. The data analysis results show that entrepreneurial self-efficacy significantly promotes the growth of new startups and entrepreneurial resilience plays a mediating role between the two. It cannot be concluded that entrepreneurial passion plays a positive moderation role between entrepreneurial self-efficacy and entrepreneurial resilience. Entrepreneurial passion also does not play a positive moderation effect between entrepreneurial self-efficacy and new venture growth. However, entrepreneurial passion plays a positive moderating role in the influence of entrepreneurial resilience on new venture growth. The findings of the study are beneficial for practitioners of Chinese lithium battery enterprises and will allow their strategies to promote sustainable new venture growth.