Objective: This study aimed to examine the psychometric properties of the 21-item Depression, Anxiety, and Stress Scale (DASS-21) in a sample of Moroccan students. Method: A total of 208 Moroccan students participated in this study. The dimensionality of the DASS-21 scale was assessed using exploratory factor analysis. Construct validity was assessed using the Stress Perception (PSS-10), State Anxiety (SAI), and Depression (CESD-10) scales. Results: Correlation analyses between Depression, Anxiety, and Stress subscales showed significant results. The exploratory factor analysis results confirmed the DASS’s three-dimensional structure. Furthermore, correlation analyses revealed positive correlations between the DASS-18 sub-dimensions and the three scales for Stress (PSS-10), Anxiety (SAI), and Depression (CESD-10). Conclusion: In line with previous work, the results of this study suggest that the DASS-18 reflect adequate psychometric properties, making it an appropriate tool for use in the university context.

Employee retention promotes positivity in an organization and improves employers’ brand value. As the human resource department operates with the objective of improving employees’ contribution towards the organization, meaningful work is an important topic in the core areas of human resource development (HRD), such as employee involvement, motivation, and personal development. Not only salary, benefits, working environment, and status but also the factors that determine whether you enjoy going to work every day are whether you believe that your work makes a meaningful contribution. In HRD, meaningful work comes to the forefront through a connection with a high level of commitment. Thus, this study aims to establish the relationship between meaningful and purposeful jobs affecting employee retention and the mediating factors of person organization fit (POF) and person job fit (PJF). A cross-sectional study involving a survey methodology was used to collect data from 150 white-collar employees working in the IT, banking, textile, and multinational companies in Bangladesh. The results indicate that job meaningfulness has a positive relationship with employee retention (p-value = 0.031) and both the mediating factors of PJF (p-value = 0.040) and POF (p-value = 0.028). The results also indicate that while POF positively influences employee retention (p-value = 0.019), PJF has no significant influence on employee retention (p-value = 0.164). Thus, promoting employee job meaningfulness and purpose in the workplace may represent an opportunity for organizations to improve employee engagement and retention.

In 1859, the French invasion of Gia Dinh marked the beginning of their acquisition of Cochinchina. Shortly after their arrival, France brought printers on their ships, along with firearms and artillery. The printers were intended to quickly disseminate the policies of the invading army to the inhabitants of the occupied territory. At the end of 1861, the inaugural official newspaper in Cochinchina, ‘Le Bulletin officiel de l’expédition française de la Cochinchine’, had been published. The Royal Printing House (l’Imprimerie Impériale), the first printing facility in Cochinchina, was also established at the end of 1861 to accommodate printing tasks, particularly the production of gazettes. In 1873, various private printing houses emerged in Saigon-Cho Lon. Printing and publishing efforts gradually assimilated into the social fabric of Cochinchina after serving as a tool of the invaders. They transformed into political and cultural institutions within colonial society, notably in Saigon-Cho Lon. The progression of these activities during the process was observable, at least for those granted permission to participate. The requirements of the colonial environment and the vitality of the private sector fuelled these new activities, although the colonial authorities deemed it necessary to exert control over them. This article offers additional information on the printing and publishing activities in Saigon-Cho Lon, Vietnam, highlighting the accomplishments of some distinguished printers.

In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

This study investigates the performance assessment of methanol and water as working fluid in a solar-powered vapour absorption refrigeration system. This research clarifies the system’s performance across a spectrum of operating conditions. Furthermore, the HAP software was utilized to determine and scrutinize the cooling load, facilitating a comparative analysis between software-based results and theoretical calculations. To empirically substantiate the findings, this research investigates methanol-water as a superior refrigerant compared to traditional ammonia- water and LiBr-water systems. Through experimental analysis and its comparison with previous research, the methanol-water refrigeration system demonstrated higher cooling efficiency and better environmental compatibility. The system’s performance was evaluated under varying conditions, showing that methanol-water has a 1% higher coefficient of performance (COP) compared to ammonia-water systems, proving its superior effectiveness in solar-powered applications. This empirical model acts as a pivotal tool for understanding the dynamic relationship between methanol concentration (40%, 50%, 60%) and system performance. The results show that temperature of the evaporator (5–15 ℃), condenser (30 ℃–50 ℃), and absorber (25 ℃–50 ℃) are constant, the coefficient of performance (COP) increases with increase in generator temperature. Furthermore, increasing the evaporator temperature while keeping constant temperatures for the generator (70 ℃–100 ℃), condenser, and absorber improves the COP. The resulting data provides profound insights into optimizing refrigerant concentrations for improved efficiency.