Influence of Coping Style on Life Satisfaction Among Vietnamese Undergraduates of Psychology, Mediated by Stress, Anxiety, and Depression

This study investigated (1) the direct influence of coping style on life satisfaction; (2) the indirect influences of coping style on life satisfaction, being mediated by depression, anxiety, and stress; and (3) gender differences in coping style, life satisfaction, depression, anxiety, and stress on a sample of 510 Vietnamese undergraduates of psychology in Ho Chi Minh city. Vietnamese-translated versions of the Coping Inventory for Stressful Situations (CISS), Depression, Anxiety, and Stress Scale (DASS), Satisfaction with Life Scale (SWLS) and a researcherconstructed demographic questionnaire were employed for data collection. Reliability test, the t-test, and multiple regression analysis were used in data analysis. Results revealed that problem-focused coping and avoidance-focused coping were positively related to life satisfaction while emotion-focused coping was found to be negatively correlated with life satisfaction. Furthermore, problem-focused coping was found to be negatively correlated with depression, anxiety, and stress, whereas emotion-focused coping was found to be positively correlated with the three emotive variables. Avoidance-focused coping was negatively correlated with depression. In terms of testing indirect relationship hypothesis, the regression analysis showed that there was an indirect influence of emotion-focused coping and voidance-focused coping on Vietnamese psychology undergraduate students’ life satisfaction, being mediated by their reported level of depression. Additionally, no significant gender differences were found in problem-focused coping, depression, anxiety, stress, and life satisfaction. In contrast, there were significant gender differences in emotionfocused coping and avoidance-focused coping such that Vietnamese female students of psychology tended to employ emotion-focused coping and avoidance-focused coping more than their male counterparts

Evaluating structural safety of trusses using Machine Learning

In this paper, a machine learning-based framework is developed to quickly evaluate the structural safety of trusses. Three numerical examples of a 10-bar truss, a 25-bar truss, and a 47-bar truss are used to illustrate the proposed framework. Firstly, several truss cases with different cross-sectional areas are generated by employing the Latin Hypercube Sampling method. Stresses inside truss members as well as displacements of nodes are determined through finite element analyses and obtained values are compared with design constraints. According to the constraint verification, the safety state is assigned as safe or unsafe. Members’ sectional areas and the safety state are stored as the inputs and outputs of the training dataset, respectively. Three popular machine learning classifiers including Support Vector Machine, Deep Neural Network, and Adaptive Boosting are used for evaluating the safety of structures. The comparison is conducted based on two metrics: the accuracy and the area under the ROC curve. For the two first examples, three classifiers get more than 90% of accuracy. For the 47-bar truss, the accuracies of the Support Vector Machine model and the Deep Neural Network model are lower than 70% but the Adaptive Boosting model still retains the high accuracy of approximately 98%. In terms of the area under the ROC curve, the comparative results are similar. Overall, the Adaptive Boosting model outperforms the remaining models. In addition, an investigation is carried out to show the influence of the parameters on the performance of the Adaptive Boosting model

Imagined Communities and Identities in English as a Foreign Language (EFL) Learning: A Literature Review

Imagined community and identity have been recognized as critical aspects in English language learning. Imagined community refers to the ideal community that learners wish to get engaged in, while imagined identity refers to the ideal self that language learners wish to become in the future. However, there is a scant research on these two notions in relation to English as a foreign language (EFL) learning. To that end, this paper aims to present the literature review of the contemporary theories on imagined communities and identities in EFL learning. It first discusses the imagined communities regarding the functions, community of practice, notions of imagined communities and concepts of imagined EFL classroom communities. It then scrutinizes imagined identities in terms of poststructuralists’ theory, English language learners’ identities, notion of imagined identity and EFL learners’ imagined identity. This paper is hoped to provide a timely and needed conceptual framework for other relevant constructs (e.g., English language learning investment) in English language learning

Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique

Transmission towers are tall structures used to support overhead power lines. They play an important role in the electrical grids. There are several types of transmission towers in which lattice towers are the most common type. Designing steel lattice transmission towers is a challenging task for structural engineers due to a large number of members. Therefore, discovering effective ways to design lattice towers has attracted the interest of researchers. This paper presents a method that integrates Differential Evolution (DE), a powerful optimization algorithm, and a machine learning classification model to minimize the weight of steel lattice towers. A classification model based on the Adaptive Boosting algorithm is developed in order to eliminate unpromising candidates during the optimization process. A feature handling technique is also introduced to improve the model quality. An illustrated example of a 160-bar tower is conducted to demonstrate the efficiency of the proposed method. The results show that the application of the Adaptive Boosting model saves about 38% of the structural analyses. As a result, the proposed method is 1.5 times faster than the original DE algorithm. In comparison with other algorithms, the proposed method obtains the same optimal weight with the least number of structural analyses

Evaluation of dietary carbohydrate and rosmarinic acid on intestinal expression of glucose transporters and digestive enzymes

Dissertação de mestrado em Biotechnology and Bioentrepreneurship in Medicinal and Aromatic Plant (MBBPAMThe impact of dietary habits on human health is well known and diet plays a significant role in chronic and age related diseases. This study had the following objectives: (1) to characterize the effects of different types of dietary carbohydrate on the expression of the digestive enzyme sucrose-isomaltase (SI) and of the glucose transporters SGLT1 and GLUT2 (sodium dependent transporter and facilitated diffusion, respectively) in intestinal epithelial cells, and (2) describe the effects of the phytochemical agent RA on the modulation of these processes. Carbohydrate digestion and absorption by the intestine determine the rise in glucose levels of the blood after a meal and in diabetic patients these processes are increased which contributes to the hyperglycemia that characterizes the disease. Other dietary constituents, namely phytochemicals, may have a beneficial effect in this scenario by decreasing carbohydrate digestion and/or intestinal glucose uptake. This study shows that when carbohydrates are removed from the diet there is a marked decrease in SI, SGLT1 and GLUT2 not only at the apical membrane of enterocytes but also in enterocyte whole cell homogenates. Upon reintroduction of diets rich in carbohydrate (glucose or amylopectin) for 7 or 14 days, there is a marked increase in the enterocyte expression of the three proteins. The effects are more pronounced in the glucose diet which suggests a decisive role for luminal glucose on the adaptive response to increasing dietary carbohydrates. The phytochemical RA demonstrated to decrease the extent of the adaptive increase in the digestive enzyme as well as in the glucose transporters revealing its potential as a regulator of intestinal glucose absorption. This work is collaboration with Dr. Simon Lee of the University of Macau, China.Os efeitos da alimentação têm grande impacto sobre a saúde humana. Este trabalho tinha como objectivos (1) caracterizar os efeitos de diferentes fontes de hidratos de carbono na dieta de ratos sobre a expressão de enzimas digestivas e transportadores de glucose no epitélio intestinal (2) descrever os efeitos do agente fitoquímico RA na modulação destes processos. Como é sabido, a digestão e absorção de hidratos de carbono pelo intestino são processos que determinam a subida de glucose no plasma associado à dieta e podem, em doentes diabéticos por exemplo, estar aumentados o que agrava a hiperglicemia presente nestes doentes. Outros constituintes da dieta, nomeadamente agentes fitoquímicos, podem intervir beneficamente neste processo diminuindo a velocidade de digestão dos hidratos de carbono complexos e/ou eficiência do transporte de glucose para a circulação através de efeitos não só na actividade de enzimas digestivas mas também na expressão de transportadores de glucose na membrana apical de enterócitos. Assim, este estudo mostra que quando se retiram os hidratos de carbono da dieta de ratos previamente alimentados com uma dieta normal (contendo amido) os níveis da enzima sacarose-isomaltase e dos transportadores de glucose SGLT1 (sodium dependent glucose transporter 1) e do GLUT2 (difusão facilitada) baixam muito significativamente não só na membrana apical de enterócitos (BMM) como também nos extractos celulares totais de mucosa intestinal. Ao reintroduzir dietas isocalóricas ricas em hidratos de carbono de diferentes tipos – glucose ou amilopectina – por 7 ou 14 dias produzem adaptações ao nível da enzima e das proteínas transportadoras cuja expressão aumenta. Estes efeitos são mais pronunciados no caso da dieta com glucose (do que na dieta contendo amilopectina) o que indica um papel determinante da glucose lumenal livre na estimulaçãp destes mecanismos adaptativos. Os resultados confirmam ainda que a regulação do transporte da glucose e da sacarose-isomaltase parecem estar associados. O agente fitoquímico testado (RA) demonstrou ter potencial para conter estas respostas adaptativas ao aumento de glucose livre no lúmen do intestino o que revela que poderá ser útil no controle da glicemia. Este trabalho é o resultado de uma colaboração com o Doutor Simon Lee da Universidade de Macau, China

(The) New regional context of post cold war East Asia and implications for Vietnam

Thesis(Master) --KDI School:Master of Public Policy,2004masterpublishedby Vu Anh Tran

License Plate Recognition Based On Multi-Angle View Model

In the realm of research, the detection/recognition of text within images/videos captured by cameras constitutes a highly challenging problem for researchers. Despite certain advancements achieving high accuracy, current methods still require substantial improvements to be applicable in practical scenarios. Diverging from text detection in images/videos, this paper addresses the issue of text detection within license plates by amalgamating multiple frames of distinct perspectives. For each viewpoint, the proposed method extracts descriptive features characterizing the text components of the license plate, specifically corner points and area. Concretely, we present three viewpoints: view-1, view-2, and view-3, to identify the nearest neighboring components facilitating the restoration of text components from the same license plate line based on estimations of similarity levels and distance metrics. Subsequently, we employ the CnOCR method for text recognition within license plates. Experimental results on the self-collected dataset (PTITPlates), comprising pairs of images in various scenarios, and the publicly available Stanford Cars Dataset, demonstrate the superiority of the proposed method over existing approaches

A Review of Challenges and Opportunities in BIM Adoption for Construction Project Management

This research investigates the transformative impact of Building Information Modeling (BIM) on construction project management, highlighting its potential to enhance traditional processes through digital innovation. As the construction industry evolves amidst global economic integration and heightened competition, the demand for quality, efficiency, and sustainability escalates, presenting new challenges for project managers. Traditional management practices, while foundational, lack the dynamism and integrative capabilities offered by BIM technology. BIM emerges as a revolutionary paradigm, facilitating a shared digital environment that promotes precision, efficiency, and improved collaboration across the project lifecycle. By integrating BIM with artificial intelligence (AI), this study explores novel synergies that further refine project management methodologies, addressing complex challenges in the design, execution, and maintenance phases. The research employs a comprehensive review of existing literature, case studies, and practical applications to assess the effectiveness of BIM in various project management contexts. The findings reveal that while BIM significantly enhances project outcomes, its adoption faces technological, organizational, and cultural barriers. This necessitates a comprehensive strategy encompassing innovation, education, and policy reform to unlock its full potential. The study underscores the critical role of BIM in driving the future of construction project management, advocating for a collaborative effort among industry stakeholders to foster a conducive environment for BIM adoption and leverage its benefits for sustainable development in the construction sector

Automatic mapping of statechart into verilog

Master'sMASTER OF SCIENC