Doctor of Philosophy

dissertationThe RNA world hypothesis about the origin of life enjoys wide acceptance. The fact that RNA is capable of catalyzing a wide range of chemical reactions supports a RNA-based primitive metabolism. Redox reactions are very important to metabolism, and at the present time, protein enzymes need the assistance of redox coenzymes such as flavin and nicotinamide to promote these processes. In our current work, we investigate the potential role of 8-oxopurine nucleosides including 8-oxo-7,8-dihydroguanosine (OG) and ribofuranosyl uric acid (RU) as primordial redox coenzymes that could help RNA in redox reactions to support primitive metabolism. More specifically, we propose that 8-oxopurine nucleosides could function as primitive flavins in repairing cyclobutane pyrimidine dimers (CPD) that are photodamaged lesions of nucleic acids and are currently repaired by a flavin-dependent photolyase enzyme. In support of this, we incorporated OG proximal to a CPD in double-stranded oligonucleotides and investigated the repair of the CPD when OG is selectively photoexcited. Our results showed that OG is able to mediate the CPD repair following a flavin-type mechansim. The repair efficiency is dependent upon base pair context as well as the 5' vs. 3' orientation and the strand location. The photorepair activity of OG can operate on versatile environments including directly stacking on to a CPD in the same strand and base pairing with one or the other bases of these lesions

BARTPhoBEiT: Pre-trained Sequence-to-Sequence and Image Transformers Models for Vietnamese Visual Question Answering

Visual Question Answering (VQA) is an intricate and demanding task that integrates natural language processing (NLP) and computer vision (CV), capturing the interest of researchers. The English language, renowned for its wealth of resources, has witnessed notable advancements in both datasets and models designed for VQA. However, there is a lack of models that target specific countries such as Vietnam. To address this limitation, we introduce a transformer-based Vietnamese model named BARTPhoBEiT. This model includes pre-trained Sequence-to-Sequence and bidirectional encoder representation from Image Transformers in Vietnamese and evaluates Vietnamese VQA datasets. Experimental results demonstrate that our proposed model outperforms the strong baseline and improves the state-of-the-art in six metrics: Accuracy, Precision, Recall, F1-score, WUPS 0.0, and WUPS 0.9

Numerical evaluation of periodic transverse vibration of elastic connecting rods in a six-link mechanism

Application of the substructure method and d'Alembert's principle to deriving the differential equation of motion of a six-link mechanism with two elastic connecting rods is presented. In the case of stationary motion, the generalized Ritz's method has been applied to obtain system of linear differential equations with periodic coefficients. We have written computer programs to check conditions of dynamic stability and to find periodic solutions of the obtained equations. Numerical examples are given and from which the effect of elastic factors on articulation reactions is evaluated

Numerische Berechnung der dynamischen Stabilitätsbedingungen und der periodischen Schwingungen in Kurvengetrieben mit elastischer Stößelstange

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Antibacterial and Antioxidant Activity of Rhodomyrtus Tomentosa and Cinnamomum Zeylanicum Crude Extracts

The aim of this study was to investigate the extraction method for R. tomentosa and C. zeylanicum leaves and the evaluation of antibacterial and antioxidant activities of crude extracts. The results of the study showed that the active ingredients of crude extracts were clearly separated by Thin-layer chromatography and the presence of rhodomyrtone in R. tomentosa crude extract and cinnamaldehyde in C. zeylanicum crude extract. R. tomentosa crude extract was antibacterial activity against Staphylococcus aureus with 13.1 mm of inhibition zone, but is not effective against Salmonella Typhimurium. C. zeylanicum leaf extract did not show antibacterial activity on both S. aureus and S. Typhimurium. At a dilution of 1/2 of the R. tomentosa crude extract can completely inhibit S. aureus growth. This study also indicated the presence of antioxidant compounds such as flavonoids, tannins, phenols and terpenoids in C. zeylanicum and R. tomentosa crude extracts. The results showed that R. tomentosa and C. zeylanicum crude extracts should be used as a biotherapy alternative to antibiotic therapy. However, further study would be needed to investigate the antibacterial activity of crude extracts in vivo

ViCLEVR: A Visual Reasoning Dataset and Hybrid Multimodal Fusion Model for Visual Question Answering in Vietnamese

In recent years, Visual Question Answering (VQA) has gained significant attention for its diverse applications, including intelligent car assistance, aiding visually impaired individuals, and document image information retrieval using natural language queries. VQA requires effective integration of information from questions and images to generate accurate answers. Neural models for VQA have made remarkable progress on large-scale datasets, with a primary focus on resource-rich languages like English. To address this, we introduce the ViCLEVR dataset, a pioneering collection for evaluating various visual reasoning capabilities in Vietnamese while mitigating biases. The dataset comprises over 26,000 images and 30,000 question-answer pairs (QAs), each question annotated to specify the type of reasoning involved. Leveraging this dataset, we conduct a comprehensive analysis of contemporary visual reasoning systems, offering valuable insights into their strengths and limitations. Furthermore, we present PhoVIT, a comprehensive multimodal fusion that identifies objects in images based on questions. The architecture effectively employs transformers to enable simultaneous reasoning over textual and visual data, merging both modalities at an early model stage. The experimental findings demonstrate that our proposed model achieves state-of-the-art performance across four evaluation metrics. The accompanying code and dataset have been made publicly accessible at \url{https://github.com/kvt0012/ViCLEVR}. This provision seeks to stimulate advancements within the research community, fostering the development of more multimodal fusion algorithms, specifically tailored to address the nuances of low-resource languages, exemplified by Vietnamese.Comment: A pre-print version and submitted to journa

Replay detection and multi-stream synchronization in CS:GO game streams using content-based Image retrieval and Image signature matching

In GameStory: The 2019 Video Game Analytics Challenge, two main tasks are nominated to solve in the challenge, which are replay detection - multi-stream synchronization, and game story summarization. In this paper, we propose a data-driven based approach to solve the first task: replay detection - multi-stream synchronization. Our solution aims to determine the replays which lie between two logo-transitional endpoints and synchronize them with their sources by extracting frames from videos, then applying image processing and retrieval remedies. In detail, we use the Bag of Visual Words approach to detect the logo-transitional endpoints, which contains multiple replays in between, then employ an Image Signature Matching algorithm for multi-stream synchronization and replay boundaries refinement. The best configuration of our proposed solution manages to achieve the second-highest scores in all evaluation metrics of the challenge