The aim of the present study was to determine the effects of single and mixed infections of nematode (Meloidogyne javanica), fungus (Fusarium oxysporum) and bacterium (Xanthomonas axonopodis) on nodulation and pathological parameters of Bambara groundnut (Vigna subterrenea (L.) Verdc.) in field condition. Nematode infested field was used while other pathogens were obtained from diseased plants. The Randomized Complete Block Design (RCBD) was adopted in a 5 × 9 × 5 factorial design (5 blocks, 9 treatments and 5 replicates per treatments) resulting in 225 experimental units. In each experimental unit, three seeds were sown to a depth of 5cm and thinned to one plant per planting hole after germination at day 7. Treatments were inoculated into test plant following standard methods. As a result, the control treatment recorded the highest number of nodules (64.0 ± 6.91), followed by bacterium (45.2 ± 5.11) while N + F + B had the lowest number of root nodules (23.4 ± 2.42). Simultaneous treatment (N + F + B) gave the highest percentage reduction in nodulation (63.44%), followed by treatment N + F7 (56.25%). Fungus treatment recorded the highest mean wilted plants (3.8 + 0.20) followed by N + F7 treatment (3.40 + 0.40). Gall formation in the nematode treatment increased proportionately by 56.33% as the highest recorded, followed by treatment N + F7 with 50.0%. Treatment N + F7 had the highest reproduction factor (Rf) value of 9.30 followed by nematode (8.30), N + B7 (7.40), N + F + B (6.80) and N + F14 (6.50). Zero (0) Rf value was recorded in fungus, bacterium and control treatments. The observed differences in nodulation and pathological parameters among the treatments are significant (P < 0.05). The data provided in this work is important in the control of the three pathogens affecting the productivity of Bambara nut. Formulation of a single protectant should be designed to have potent effects on the three pathogens to achieve effective protection and good production of Bambara nut.

The Circular Economy (CE) concept has been recognized as the core strategy that can support sustainable business through technological innovation that enables CE transition by focusing on resource savings. This case study conducts research on business strategy in achieving CE transition in an agroindustry company, by performing SWOT analysis to assess internal and external factors. The SWOT model provides valuable results that an effective strategy could maximize strengths and opportunities, minimize weaknesses and threats in business by boosting circularity on business-critical factors. The CE adoption by agroindustry company mostly focuses on efficient organic waste management, energy-efficient production, and production process. This study case reveals that while technology plays a significant role in advancing CE, there is still a significant need to pay attention to the social aspect in supporting the creation of worker-owned cooperatives by creating space for employee involvement in finding innovations and adopting technology in business transition into CE process. Social innovation through the involvement of employees by sharing CE vision, synergizing and optimizing internal potential, and building up the green innovation culture has created an internal conducive climate to put CE principle into practice. Further result shows that a labor-intensive company’s business strategy prioritizes employment and job security over maximizing profits, which directly leads to the economic welfare and social protection of the business operation that makes an inclusive business.

In China, ideological and political education is currently the hot direction of teaching reform in various colleges and universities, yet the development of appropriate teaching evaluation methods needs to catch up. This study addresses the pressing need for a preliminary investigation into the complex relationships among ideological and political education, the students’ learning satisfaction and teaching quality. This research examines the influence of teaching and ideological and political education quality on students’ satisfactions by designing a set of scales, collecting about 3800 questionnaires. Utilizing Structural Equation Modeling (SEM) and qualitative interviews, this study reveals that the teaching quality directly affects students’ learning satisfaction and ideological and political education. Notably, ideological and political education can also affect students’ learning satisfaction. The findings underscore the importance of including ideological and political education assessments in evaluating courses. This research contributes to the ongoing dialogue on effective teaching evaluation methods in the context of evolving educational practices.

Modelling and simulation have now become standard methods that serve to cut the economic costs of R&D for novel advanced systems. This paper introduces the study of modelling and simulation of the infrared thermography process to detect defects in the hydroelectric penstock. A 3-D penstock model was built in ANSYS version 19.2.0. Flat bottom holes of different sizes and depths were created on the inner surface of the model as an optimal scenario to represent the subsurface defect in the penstock. The FEM was applied to mimic the heat transfer in the proposed model. The model’s outer surface was excited at multiple excitation frequencies by a sinusoidal heat flux, and the thermal response of the model was presented in the form of thermal images to show the temperature contrast due to the presence of defects. The harmonic approximation method was applied to calculate the phase angle, and its relationship with respect to defect depth and defect size was also studied. The results confirmed that the FEM model has led to a better understanding of lock-in infrared thermography and can be used to detect subsurface defects in the hydroelectric penstock.

This study aims to explore the design and application of a learning achievement evaluation model, in order to improve the quality of teaching in the field of education and promote student development. This article starts with the importance of constructing a learning effectiveness evaluation model, and then clarifies the basic concepts and related theories of learning effectiveness evaluation, providing theoretical support for subsequent model design. In the model design section of learning effectiveness evaluation, propose the model design principles, indicator selection, and construction process to ensure the accuracy and comparability of the evaluation model construction. In the application and evaluation section of the learning effectiveness evaluation model, the application and evaluation methods of the main models in practical teaching were explored. Finally, the issues that need to be noted in the design process of the evaluation model were proposed in order to design a more high-quality evaluation system and promote the improvement of education quality.

Data mining technology is a product of the development of the new era. Unlike other similar technologies, data mining technology is mainly committed to solving various application problems, and the main means of solving problems are to use big data technology and machine learning algorithms. Simply put, data mining technology is like panning for gold in the sand, searching for useful information among massive amounts of information. Data mining technology is widely applied in various fields, such as scientific research and business, and also has its shadow in the education industry. Currently, major universities are applying data mining technology to teaching quality evaluation. This article first explains the impact of data mining technology on the education industry, and then specifically discusses the application of data mining technology in the evaluation of teaching quality in universities.