Abstract Fruit peels can be valorized as a source of cutin-rich materials with useful functional properties. This study compared cutin-rich extracts (CREs) from tomato, watermelon, honeydew, and papaya peels obtained through alkaline hydrolysis. The extracts were characterized for extraction yield, structure, thermal stability, water sorption, hydrophobicity, total phenolic content, and antioxidant activity. CRE properties varied among the fruit sources. FTIR spectra showed functional groups associated with cutin in all samples. Tomato CRE had the lowest water sorption and better thermal stability, whereas watermelon CRE showed similar hydrophobicity and higher antioxidant activity. Watermelon CRE recorded the highest total phenolic content (71.23 ± 0.91 mg GAE/g), DPPH radical scavenging activity (19.41 ± 0.80%), and ABTS radical scavenging activity (88.64 ± 0.17%). The results show that fruit peel source affects CRE properties and supports their potential as sustainable bio-based materials for applications in packaging, coatings, and other material systems.

Abstract Pineapple pomace is an abundant processing residue with potential for conversion into compact pellets suitable for handling, storage and downstream utilization. This study investigated the effect of ball-milling duration on the morphology and densification of pineapple pomace pellets. The milling duration was varied to 0, 30, 60, and 90 min, and the samples were then compacted into pellets. The resulting pellets were characterized for thickness, density, Shore D hardness, surface morphology and color. Increasing milling duration reduced pellet thickness and increased pellet density by approximately 30% and 13%, respectively. Pellet hardness also increased with milling duration, indicating greater resistance to surface indentation. Surface morphology revealed progressive surface smoothing with increasing milling duration. Color analysis showed that increased milling durations improved the pellet color uniformity. These findings demonstrate that ball milling is an effective mechanical pretreatment approach for improving the densification of agricultural biomass residues.

Abstract Efficient allocation of lecturers to courses is essential for maintaining teaching standards and lecturer satisfaction within higher education. Although the traditional Hungarian Method has frequently been applied in earlier research, its modified version (MHM) has yet to be extensively examined in the context of competency-based lecturer assignments. This study introduces an optimized model for assigning lecturers to courses at UiTM Seremban, embedding multidimensional competency factors into enhanced mathematical formulation. As an applied optimization approach, this study integrates lecturers’ knowledge, skills, and teaching motivation into the MHM framework to maximize overall competency scores in course assignments. Competency data were collected through an online survey from Mathematics lecturers at UiTM Seremban, serving as the core empirical input for the optimization model. MATLAB’s intlinprog solver was utilized to execute the model, promoting a well-balanced and effective teaching assignment structure where lecturers are allocated up to three courses based on their optimal competency profiles. The results highlight the high effectiveness of this applied MHM framework in aligning course assignments with lecturers’ precise expertise, effectively minimizing academic mismatches and improving overall education quality. This study contributes to the field of educational optimization by demonstrating a novel application of the MHM framework, offering a highly structured and scalable approach to enhance academic performance and faculty resource management.

Abstract The retail sector plays a significant role in Malaysia’s economic development, contributing to employment creation, consumer spending and overall business growth. As competition within the sector intensifies, it becomes important for the firms to utilize their resources efficiently to survive in this industry. This study evaluates the operational efficiency of seven selected retail companies in Malaysia using Data Envelopment Analysis (DEA) method. The research aims to measure efficiency levels and identify benchmark firms that utilize their resources effectively. The companies were analyzed based on input variables which are total assets, number of employees, number of stores and total liabilities while the output variables are revenue and net profit. There are two objectives to be achieved in this study. The first one is to measure the efficiency of performance for selected Malaysian retail companies and rank them. The second objective is to determine the most effective strategy to maximize the level of efficiency of the selected Malaysian retail companies. The DEA model was implemented using QM for Windows software which was used to calculate the efficiency score. Six companies recorded relatively high efficiency scores while one company recorded low efficiency level for less than 90%. For the less efficient company, the improvement strategies are proposed based on dual weight and reference sets from the efficient companies. The recommendations include adjustments in input usage and enhancements in output performance. For instance, optimizing asset utilization, increasing both revenue and net profit. In general, the findings of this study provide a basic framework for retail companies to enhance operational efficiency and improve the performance of their firms.