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Analyzing marketing mix strategies and personal factors influencing BISI hybrid maize seed purchases: insights from agricultural development in Soppeng District, Indonesia
No full textAs a staple food and a key component of livestock feed, the growing demand for maize in Indonesia has spurred the expansion of hybrid maize cultivation. However, despite advancements in seed technology and government initiatives to boost maize production, farmers in rural areas continue to face obstacles in accessing high-quality seeds. This study explores the influence of the marketing mix—encompassing product, price, promotion, and distribution—alongside personal factors on farmers’ purchasing decisions for hybrid maize seeds in Soppeng District. Utilizing structural equation modeling (SEM) and survey data from 100 respondents, the findings indicate that product quality and price are the most critical determinants, with farmers prioritizing seed performance and affordability. Distribution also plays a vital role in rural areas, ensuring that farmers can readily access high-quality seeds. At the same time, personal factors such as farming experience and income significantly shape purchasing behavior. Notably, promotional efforts appear to have a limited impact, suggesting that traditional marketing approaches may not be the most effective in this context. Seed companies should focus on product development, refine pricing strategies, and strengthen distribution networks to enhance market penetration. In parallel, policymakers can facilitate access to agricultural credit, invest in rural infrastructure, and promote farmer education programs to improve purchasing power and awareness. Ultimately, adapting marketing strategies to align with local economic and cultural conditions can drive greater adoption of hybrid seeds, boost agricultural productivity, and contribute to the long-term sustainability of rural farming communities
Synthesis, characterization, and anti-breast cancer properties of Cu(II) complexes with Schiff base and azo dye ligands
Get PDFThis article focuses on the synthesis of three Schiff base ligands derived from 2-hydroxybenzaldehyde (B: BBr, BOCH3, BNO2) and three azo dye ligands derived from naphthol (A: ABr, AOCH3, ANO2), followed by the preparation of copper(II) complexes with these six ligands in a 1:2 (metal:ligand) ratio. The ligands and complexes were characterized by using1 H-NMR, 13 C-NMR, FTIR, UV-vis, and ESI-MS. Thermogravimetric and differential thermal analyses of the copper complexes indicated the absence of water molecules in the crystalline coordination, demonstrating high thermal stability. The findings confirmed the formation of square-planar copper complexes. The biological activity of the complexes was evaluated on breast cancer and healthy cells using the MTT assay at different concentrations. The IC50 analysis showed that CuABr, CuBBr, and CuAOCH3 had a significantly more substantial cytotoxic effect on cancer cells than on healthy cells. CuBOCH3 and CuBNO2 also exhibited notable selectivity toward cancer cells, whereas CuANO2 was more toxic to normal cells. These findings highlight the potential of CuABr, CuBBr, and CuAOCH3 as promising candidates for further development in targeted breast cancer therapy
Adopting strategies of mobile technology for assisted learning performance in higher education in China
Get PDFMobile technology, particularly mobile-assisted learning, has long been a rapidly growing and dynamic field. A prominent focus within this domain is the development and implementation of mobile learning applications and systems. The widespread adoption of mobile learning has led to the emergence of numerous applications, granting higher education students increased autonomy in leveraging mobile devices to support their academic performance. However, the abundance of available options has made the strategic selection and effective use of appropriate applications a pressing issue. This study employed a mixed-methods approach to investigate strategies for adopting mobile learning applications in Chinese higher education institutions—a context in which limited research has been conducted despite the ongoing technological transformation in mainland China. The findings revealed that academic major significantly influenced students’ learning performance supported by mobile applications, primarily due to differing academic demands [F(11, 289) = 1.788, p = .056, η² = 0.064]. Learners’ positive perceptions of mobile learning applications were found to be crucial to their assisted learning outcomes. Moreover, most students acknowledged the necessity of receiving guidance when selecting learning applications. Among the various forms of support examined, teacher recommendations were particularly valued. However, both in-class and out-of-class support remained insufficient. While online searches and social media offer some assistance, there is a strong preference among students for direct guidance from instructors. Furthermore, existing mobile learning applications do not fully meet the diverse needs of all learners. To address these challenges, this study proposes an eight-stage adoption strategy aimed at enhancing university students’ learning performance through more effective use of mobile applications
Bibliometric and visualized analysis of work engagement in business management
Get PDFWithin business management, the growing interest in work engagement stems from its recognised role in mitigating employee well-being, bolstering job satisfaction, and optimising organisational outcomes. This review comprehensively explores the knowledge structure of work engagement in business management, analysing 563 publications from the Scopus database spanning 2005 to 2023 through performance analysis, co-citation analysis, co-authorship analysis, keyword co-occurrence analysis, and content analysis. This review outlines prevailing trends and identifies influential scholars, articles, institutions, and leading countries. It il-luminates the current state of scientific collaboration, providing a rationale for developing countries to seek academic cooperation with developed countries. Additionally, it delves into six current themes and four future directions, providing a robust theoretical framework for future research endeavours
Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Get PDFImportance of the work: With the advancement of hyperspectral remote sensing technology, the potential of categorising frogeye leaf spot (FLS) of soybean has been examined. No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. The first step was to smooth out the data by applying a filtering technique called Savitzky-Golay to remove the spectrum noise. The ReliefF feature selection technique was used to determine the most influential wavelengths for the classification of FLS disease severity in soybean. Next, machine learning (ML) methods (i.e. decision tree, gradient boosting, random forest, stacking, and neural network) were used to classify FLS of soybean. This analysis' performance was evaluated using overall accuracy, F1, precision and the receiver operating characteristic curve metric. All of these steps were conducted using Orange data mining software. Results: Based on the findings, neural network scored the highest overall accuracy of 98.6% after conducting filtering technique. Furthermore, reliefF-Gradient boosting and random forest algorithms achieved promising overall accuracy of 97.4% and 96.9%, respectively after implementing filtering and feature selection techniques. Main finding: Due to the integration of workflow and the specially designed spectroscopic widget in Orange Data Mining Software, it is capable of processing hyperspectral reflectance data in order to determine the severity level of disease affecting crops
Insight into improved specificity and thermostability of Geobacillus zalihae T1 lipase by introducing novel molecular interactions via phenylalanin to cysteine substitution
No full textLipase specificity is a crucial requirement for industrial employment; however, tuning the lipase specificity in some cases can impair the structure and affect its stability. To enhance the T1 lipase specificity, we targeted the conserved bulky residue Phe180 in the lid domain to eliminate the impact of steric hindrance, as it constrains substrate accession to the enzyme active site and affects specificity. This residue was pre-substituted with a small side chain residue by utilizing DynaMut2 software to ensure that this substitution did not affect lipase stability. Phe180Cys was chosen because it exhibited a stabilizing effect by showing (ΔΔGStability) of 0.74 kcal/mol, which was subsequently substituted by the rational design approach. This variant has successfully exhibited specificity modification toward long fatty acid chains as a result of increasing the distance between the lid domain and catalytic site by 1.2 Å and the volume of active site by 190.2 Å3. In addition, this F180C variant exhibited an increase in the optimum temperature and thermal denaturation point to 75 °C and 78 °C, respectively, with an improvement in the lipase stability in the organic solvents. The analysis of the atomic interactions revealed a change in the whole H-bonds, S/π interactions, and salt bridge network. The biophysical study revealed changes in the secondary structure content compared with wt-T1. The MD simulation results displayed lower RMSD, gyration radius, and SASA values for the mutated lipase structure. In conclusion, comparative analysis of the atomic interactions resulting from structural modification can significantly elucidate the specificity and thermostability of enzymes of industrial relevance
National and regional effects of RCEP on trade: the application of the WITS-SMART tool with the focus on China
Get PDFThis paper investigates the effects of RCEP trade creation and trade diversion on China and its sectors, as well as the impact of imports and exports on provinces. The World Bank’s World Integrated Trade Solution Software for Market Analysis and Restrictions on Trade (WITS-SMART) tool with the 2020 data, alongside the OECD Inter-Country Input-Output (ICIO) tables and the Chinese Multi-Regional Input-Output (MRIO) tables based on the 2017 data under two scenarios. The results of the study indicate that trade growth with Japan and South Korea is significant, on the one hand, whereas the trade effects with the ASEAN nations and regions such as Australia and New Zealand are relatively low, on the other. The research emphasizes the disparities between various regions in China, demonstrating that the Eastern coastal provinces obtain more trade benefits than the Central and Western areas. The study highlights the importance of implementing the policies encouraging collaboration in high-growth sectors and developing tailored strategies for regional advancement
Recombinant Yebf-Cas9 fusion enzyme from thermophilic Geobacillus kaustophilus interaction with sgRNA by in silico method.
Get PDFGenetic engineering is a process that changes the structure of an organism by removing, inserting, or modifying its genetic material. Currently, the most widely used method in genetic engineering is CRISPR-Cas9, representing “Clustered Regularly Interspaced Short Palindromic Repeat-Associated Protein 9“. As an intracellular enzyme, the production of Cas9 is complex and costly due to the need for extraction and purification. In comparison, YebF is a protein that can be localized extracellularly. By fusing YebF with Cas9 (YebF-Cas9), it is possible to express and localize Cas9 extracellularly. This fusion potentially alters Cas9 ability to bind with sgRNA (single guide RNA). Therefore, this study aimed to explore the interaction between sgRNA and Cas9 from Geobacillus kaustophilus fused with YebF using in silico methods. In the in silico experiment, the molecular docking method was used to determine biomolecular interactions with variations in sgRNA, namely spacer 10, 20, 30 nt, repeat 16, 25, 36 nt, and tracrRNA 63, 98, 140 nt. The results showed that changes in the length of the spacer, repeat, and tracrRNA could affect the level of binding affinity formed in YebF-Cas9-sgRNA complex from Geobacillus kaustophilus. The optimal length of the molecular docking results in terms of affinity and position was in the variation of 30 nt spacer with 16 nt repeat and 98 nt tracrRNA, with the binding affinity of -419.24 kcal/mol
Synthesis of CuO nanoparticles using waste-derived bamboo cellulose for enhanced catalytic and antibacterial applications
Get PDFCopper oxide (CuO) nanoparticles were prepared using waste-derived cellulose from bamboo biomass as a functional additive. The cellulose, recovered from an alkaline dissolution process, enhanced the dispersion and structural integrity of CuO nanoparticles (NPs). The CuO prepared in the presence of waste cellulose (CuO-C) exhibited a specific surface area of 32 m²/g, compared to 7 m²/g for pure CuO. Scanning electron microscopy (SEM) revealed a feather-like CuO structure influenced by the presence of the waste-derived cellulose matrix. The catalytic activity of CuO-C was tested through the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP), achieving complete conversion within 15 min. The synthesis cost of CuO-C was approximately RM 3.30 per gram. Antibacterial tests confirmed activity against both Staphylococcus aureus and Klebsiella pneumoniae. These findings demonstrate the feasibility of using a highly alkaline solution from the cellulose dissolution process to produce low-cost CuO with improved catalytic and antibacterial properties
Fostering academic engagement through soft skills and positive emotions: a sustainable development perspective on university education
Get PDFIntroduction: Soft skills, including curiosity, initiative, perseverance, social awareness, adaptability, and leadership, are increasingly recognized as essential for fostering positive emotions and academic engagement in higher education. However, the pathways linking these skills to academic engagement remain underexplored, especially within the Chinese university context. Methods: This study investigated the relationships among soft skills, positive emotions, and academic engagement among 335 undergraduate students (197 females, 58.8%) from four universities in China, across faculties of Education, Literature, and Management. Standardized questionnaires assessing soft skills, positive emotions, and academic engagement dimensions (absorption, dedication, and vigor) were administered. Data were analyzed using SPSS 26 and AMOS 24. Reliability was confirmed through Cronbach's alpha (≥0.70), and construct validity was evaluated via confirmatory factor analysis (CFA). Results: CFA indicated an acceptable to excellent fit for both individual scales and the overall measurement model (χ2/df = 1.887, RMSEA = 0.052, CFI = 0.928). Structural equation modeling (SEM) results supported hypothesized relationships, demonstrating that soft skills directly predicted academic engagement and indirectly predicted it through positive emotions. Positive emotions significantly mediated the relationship between soft skills and all dimensions of academic engagement (absorption, dedication, vigor). Discussion: These findings underscore the importance of developing soft skills and fostering positive emotional experiences to enhance academic engagement. Aligning with sustainable development-oriented educational reforms, the results suggest that comprehensive educational approaches promoting soft skills and emotional well-being can effectively support holistic student growth and sustainable academic success