Transforming Industrial Engineering Education: Introducing the CWILE Model for Work-Integrated Learning in the Digital Age

Thailand's industrial sector has made significant progress in adopting and implementing technology associated with Industry 4.0. As technology advances and industries become more digitally driven, a skilled and adaptable workforce becomes paramount. The responsibility for cultivating such human resources lies with educational institutions. They are the foundation for developing a workforce that can thrive in the digital age by staying responsive to industry trends, fostering business collaboration, and prioritising technical and soft skills. Work-integrated learning (WIL) is one of the educational programs that can help improve student skills by integrating the theoretical exploration of a particular subject with its practical implementation within a professional environment. The WIL program enables individuals to demonstrate competence, expertise, and the capacity to keep up with contemporary technologies. This paper proposes the new WIL model for the WIL program in the industrial engineering profession, known as the CWILE model. The study aims to identify and establish the benefits of the CWILE model. These benefits include enhanced skill development, improved readiness for industry demands, and a seamless transition from education to the workforce. The initial step in the research procedure involved collecting stakeholders' perspectives on the existing WIL program in the industrial engineering department of the engineering faculty at Rajamangala University of Technology Lanna (RMUTL), Thailand. Following stakeholder feedback, the CWILE model was developed and implemented with the participation of eighteen students in the WIL program. The effectiveness of the CWILE model was assessed through a comprehensive evaluation of student competencies: core competency, functional competency, and professional competency. The evaluations were conducted at three distinct intervals: before, during, and after instruction. This longitudinal assessment allows a nuanced understanding of how the WIL program influences student competencies. The results of this study show that the duration of attending the WIL program is positively correlated with an increase in all competencies

Mathematical Analysis of Non-Newtonian Blood Flow in Stenosis Narrow Arteries

The flow of blood in narrow arteries with bell-shaped mild stenosis is investigated that treats blood as non-Newtonian fluid by using the K-L model. When skin friction and resistance of blood flow are normalized with respect to non-Newtonian blood in normal artery, the results present the effect of stenosis length. When skin friction and resistance of blood flow are normalized with respect to Newtonian blood in stenosis artery, the results present the effect of non-Newtonian blood. The effect of stenosis length and effect of non-Newtonian fluid on skin friction are consistent with the Casson model in which the skin friction increases with the increase of ither stenosis length or the yield stress but the skin friction decreases with the increase of plasma viscosity coefficient. The effect of stenosis length and effect of non-Newtonian fluid on resistance of blood flow are contradictory. The resistance of blood flow (when normalized by non-Newtonian blood in normal artery) increases when either the plasma viscosity coefficient or the yield stress increases, but it decreases with the increase of stenosis length. The resistance of blood flow (when normalized by Newtonian blood in stenosis artery) decreases when either the plasma viscosity coefficient or the yield stress increases, but it decreases with the increase of stenosis length

Modeling the Spread of COVID-19 Using Nonautonomous Dynamical System with Simplex Algorithm-Based Optimization for Time-Varying Parameters

The SIRDV (Susceptible, Infected, Recovered, Death, Vaccinated) compartmental model along with time-varying parameters is used to model the spread of COVID-19 in the United States. Time-varying parameters account for changes in transmission rates, people’s behaviors, safety precautions, government regulations, the rate of vaccinations, and also the probabilities of recovery and death. By using a parameter estimation based on the simplex algorithm, the system of differential equations is able to match real COVID-19 data for infections, deaths, and vaccinations in the United States of America with relatively high precision. Autoregression is used to forecast parameters in order to forecast solutions. Van den Driessche’s next-generation approach for basic reproduction number agrees well across the entire time period. Analyses on sensitivity and elasticity are performed on the reproduction number with respect to transmission, exit, and natural death rates in order to observe the changes from a small change in parameter values. Model validation through the Akaike Information Criterion ensures that the model is suitable and optimal for modeling the spread of COVID-19

Enhancement of Cholinesterase Inhibition of Alpinia galanga (L.) Willd. Essential Oil by Microemulsions

This study aimed to investigate the chemical composition and reveal the selective inhibitory activity of Alpinia galanga (L.) Willd. essential oil (AGO) on acetylcholinesterase (AChE) compared to butyrylcholinesterase (BChE). The chemical composition of AGO was investigated by means of gas chromatography–mass spectrometry. Ellman’s method was used to determine the inhibitory activities against AChE and BChE. Microemulsion systems with desirable anticholinesterase effects were developed. Methyl cinnamate and 1,8-cineole were reported as the major component of AGO. The IC50 values of A. galanga oil against AChE and BChE were 24.6 ± 9.6 and 825.4 ± 340.1 µg/mL, respectively. The superior selectivity of AGO on AChE (34.8 ± 8.9) compared to galantamine hydrobromide (6.4 ± 1.5) suggested AGO to be an effective ingredient with fewer side effects for Alzheimer’s treatment. Interestingly, the microemulsion of AGO possessed significantly higher anticholinesterase activity than that of native oil alone. Therefore, microemulsion of AGO is a promising alternative approach for the treatment of Alzheimer’s disease

Optimisation of stability and charge transferability of ferrocene-encapsulated carbon nanotubes

<p>Ferrocene-encapsulated carbon nanotubes (Fc@CNTs) became promising nanocomposite materials for a wide range of applications due to their superior catalytic, mechanical and electronic properties. To open up new windows of applications, the highly stable and charge transferable encapsulation complexes are required. In this work, we designed the new encapsulation complexes formed from ferrocene derivatives (FcR, where R = –CHO, –CH₂OH, –CON₃ and -PCl₂) and single-walled carbon nanotubes (SWCNTs). The influence of diameter and chirality of the nanotubes on the stability, charge transferability and electronic properties of such complexes has been investigated using density functional theory. The calculations suggest that the encapsulation stability and charge transferability of the encapsulation complexes depend on the size and chirality of the nanotubes. FcR@SWCNTs are more stable than Fc@SWCNTs at the optimum tube diameter. The greatest charge transfer was observed for FcCH₂OH@SWCNTs and Fc@SWCNTs since the Fe d levels of FcCH₂OH and Fc are nearly equal and close to the Fermi energy level of the nanotubes. The obtained results pave the way to the design of new encapsulated ferrocene derivatives which can give rise to higher stability and charge transferability of the encapsulation complexes.</p