Numerical analysis of subsoil-reinforced concrete slab interaction

This article presents the numerical modeling of interaction between a reinforced concrete slab and subsoil using ABAQUS. Subsoil was simulated as both homogeneous half-space and inhomogeneous half-space. Reinforcement bars in the concrete slab were accurately modelled allowing capturing a precise deformation profile of the slab in interaction with subsoil. Input data for numerical analysis were adopted from a published work. Results of the study were verified on the basis of comparison with those of the previous study

Advances in Smart Technologies for Structural Health Monitoring of Cable-stayed Bridges

This study deals with the general problem of developing smart technologies for vibration and impedance-based structural health monitoring (SHM) of cable-stayed bridges. The following approaches are implemented to achieve the objective. Firstly, vibration- and impedance-based SHM methods suitable for cable-stayed bridge are briefly outlined. Secondly, smart sensors are designed for vibration- and impedance-based SHM. Thirdly, the practicality of the smart sensor system is evaluated on a real cable-stayed bridge, Hwamyung Bridge in Korea. The system's performance is experimentally analyzed under various cable forces and weather conditions. Finally, the experimental modal parameters are identified by numerical modal analyses of the target bridge. Also, its structural parameters are estimated from the vibration-based structural identification using experimental modal parameters

EFFECTIVE SOLUTIONS TO MEET STUDENTS' SATISFACTION FOR PHYSICAL EDUCATION ACTIVITIES AT HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION

Through the research, the topic has built four solutions to meet students' satisfaction with physical education (PE) activities at Ho Chi Minh City University of Technology and Education (HCMUTE). These include: strengthening movement activities, and extra-curricular activities; supplementing and updating documents and textbooks; improving teaching staff's qualifications, along with improving teaching, testing and evaluation methods; upgrading physical facilities for sports. After a period of application in practice, the solutions proposed by the topic have proven to be effective and meet the satisfaction of learners.  Article visualizations

Factors Affecting C02 Emission in Vietnam: a Panel Data Analysis

The purpose of this study is to investigate the major factors in the process of economic growth that influence the carbon dioxide (CO2) emission in Vietnam. An Autoregressive Distributed Lag (ARDL) model was used to evaluate the impact based on Environmental Kuznets curve (EKC) and Pollution haven hypothesis (PHH) in 1990–2011. The results indicate that the economic growth, energy consumption, financial development and trade openness  positively influence the CO2 emissions, whereas foreign direct investment has a negative impact in the short term. Coefficient of joining ASEAN is not statistically significant. The findings of this study also support the validity of EKC and PHH in the Vietnamese economy. Therefore, it is important to use green energy, examine requirements for foreign investment and adopt trade-related measures and policies to increase environmental protection

Some remarks on functional dependencies in relational datamodels

The concept of minimal family is introduced. We prove that this family and family of functional dependencies (FDs ) determine each other uniquely. A characterization of this family is presented. We show that there is no polynomial time algorithm finding a minimal family from a given relation scheme. We prove that the time complexity of finding a minimal family from a given relation is exponential in the number of attributes

Algorithmes pour le (dés)assemblage d'objets complexes et applications à la biologie structurale

La compréhension et la prédiction des relations structure-fonction de protéines par des approches in sillico représentent aujourd'hui un challenge. Malgré le développement récent de méthodes algorithmiques pour l'étude du mouvement et des interactions moléculaires, la flexibilité de macromolécules reste largement hors de portée des outils actuels de modélisation moléculaire. L'objectif de cette thèse est de développer une nouvelle approche basée sur des algorithmes de planification de mouvement issus de la robotique pour mieux traiter la flexibilité moléculaire dans l'étude des interactions protéiques. Nous avons étendu un algorithme récent d'exploration par échantillonnage aléatoire, ML-RRT pour le désassemblage d'objets articulés complexes. Cet algorithme repose sur la décomposition des paramètres de configuration en deux sous-ensembles actifs et passifs, qui sont traités de manière découplée. Les extensions proposées permettent de considérer plusieurs degrés de mobilité pour la partie passive, qui peut être poussée ou attirée par la partie active. Cet outil algorithmique a été appliqué avec succès pour l'étude des changements conformationnels de protéines induits lors de la diffusion d'un ligand. A partir de cette extension, nous avons développé une nouvelle méthode pour la résolution simultanée du séquençage et des mouvements de désassemblage entre plusieurs objets. La méthode, nommée Iterative-ML-RRT, calcule non seulement les trajectoires permettant d'extraire toutes les pièces d'un objet complexe assemblé, mais également l'ordre permettant le désassemblage. L'approche est générale et a été appliquée pour l'étude du processus de dissociation de complexes macromoléculaires en introduisant une fonction d'évaluation basée sur l'énergie d'interaction. Les résultats présentés dans cette thèse montrent non seulement l'efficacité mais aussi la généralité des algorithmes proposés. ABSTRACT : Understanding and predicting structure-function relationships in proteins with fully in silico approaches remain today a great challenge. Despite recent developments of computational methods for studying molecular motions and interactions, dealing with macromolecular flexibility largely remains out of reach of the existing molecular modeling tools. The aim of this thesis is to develop a novel approach based on motion planning algorithms originating from robotics to better deal with macromolecular flexibility in protein interaction studies. We have extended a recent sampling-based algorithm, ML-RRT, for (dis)-assembly path planning of complex articulated objects. This algorithm is based on a partition of the configuration parameters into active and passive subsets, which are then treated in a decoupled manner. The presented extensions permit to consider different levels of mobility for the passive parts that can be pushed or pulled by the motion of active parts. This algorithmic tool is successfully applied to study protein conformational changes induced by the diffusion of a ligand inside it. Building on the extension of ML-RRT, we have developed a novel method for simultaneously (dis)assembly sequencing and path planning. The new method, called Iterative-ML-RRT, computes not only the paths for extracting all the parts from a complex assembled object, but also the preferred order that the disassembly process has to follow. We have applied this general approach for studying disassembly pathways of macromolecular complexes considering a scoring function based on the interaction energy. The results described in this thesis prove not only the efficacy but also the generality of the proposed algorithm