Genetic engineering of rice for improved agronomic characteristics

This thesis describes the production of three populations of transgenic rice plants using particle bombardment method altered in two main traits: (1) polyamine content and (2) insect pest resistance. The expression of antisense heterologous oat arginine decarboxylase (ADC) cDNA in transgenic rice plants suppressed endogenous ADC enzyme activity, and decreased putrescine and spermidine levels in a tissue/organ dependent manner, with no concomitant changes in the expression of other polyamine biosynthetic genes. The second population of transgenic rice plants engineered with a homologous spermidine synthase (SpdSyn) transgene, and observed through two generations, showed increased expression of both endogenous and transgene mRNAs. However, no significant accumulation of spermidine level in transgenic rice plants when compared to wild type control plants was observed. Putrescine levels were significantly increased in these transgenic plants. The study suggested the possible presence of an inter-conversion process from spermidine to putrescine in transgenic plants, triggered by over-expression of SpdSyn mRNAs. Novel insect resistance gene constructs encoding fusion proteins, including (1) rice thioredoxin h fused with snowdrop lectin-GNA (TRX-GNA), (2) the first domain of Bt toxin gene-Cry 1 Ac fused with GNA (Ac-GNA) and (3) Cry 1 Ac fused with ricin B chain-RTB (Ac-RTB) were assembled. When expressed in transgenic plant, these fusion proteins displayed an additive effect as insect toxins by maintaining the functional properties of the individual proteins. Artificial diet bioassays against insect pests showed that using these fusion proteins could enhance toxicity, insecticidal spectrum and possibly durability of resistance to insect pests. Our results clearly showed that transgenic rice plants expressing these fusion protein genes are resistant to brown planthopper, an important insect pest in tropical rice growing areas. These rice plants behave as horizontally resistant cultivars that are suitable for integrated pest management (IPM) networks

TEACHERS’ PERCEPTIONS ABOUT TASK-BASED LANGUAGE TEACHING AND ITS IMPLEMENTATION

Task-based language teaching has been advocated as a potentially effective approach in teaching English as a foreign language (EFL) in Asian contexts, including Vietnam. However, little is known about perceptions of tasks used by teachers in actual classroom practices at tertiary education. This article therefore examines teachers’ perceptions about task-based language teaching and its implementation in EFL classes. Questionnaire and interviews were conducted to investigate the perceptions of sixty-eight university teachers in the Mekong Delta. The findings reveal positive perceptions and understanding of teachers towards task-based language teaching (TBLT). Implications for practical applications of TBLT are also presented.  Article visualizations

The Impacts of Task-Based Activities on Learners’ Grammatical Acquisition and Motivation at Dong Nai Technology University

The study aims to measure the effect of Task-based language teaching on grammatical achievement and the motivation of EFL learners at Dong Nai Technology University. The research will conduct a quick grammar test to administer 48 students at the school to achieve this goal. After sitting the test, the learners will undergo a 6-week course applying task-based language teaching. Before the treatment, one certified instructor-made grammar test about the learning units will be encompassed as the pre-test. Furthermore, a motivation questionnaire will be carried out in this group at the research's beginning and end. Afterward, the learners will learn through the treatment, which is learning through the implementation of Task-based language teaching. After six weeks of treatment, the group will take the same teacher-made grammar test as the post-test. After that, the writer will analyze the data through paired sample t-test. The results demonstrated a significant difference between the pre-test and post-test in the student’s performance on grammar acquisition and the enhancement in learners’ motivation. Based on the findings of this research, it is believed that task-based language teaching can be used in English classes to enhance learners’ grammar achievements and motivation among Vietnamese university learners

Finding optimal reactive power dispatch solutions by using a novel improved stochastic fractal search optimization algorithm

In this paper, a novel improved Stochastic Fractal Search optimization algorithm (ISFSOA) is proposed for finding effective solutions of a complex optimal reactive power dispatch (ORPD) problem with consideration of all constraints in transmission power network. Three different objectives consisting of total power loss (TPL), total voltage deviation (TVD) and voltage stabilization enhancement index are independently optimized by running the proposed ISFSOA and standard Stochastic Fractal Search optimization algorithm (SFSOA). The potential search of the proposed ISFSOA can be highly improved since diffusion process of SFSOA is modified. Compared to SFSOA, the proposed method can explore large search zones and exploit local search zones effectively based on the comparison of solution quality. One standard IEEE 30-bus system with three study cases is employed for testing the proposed method and compared to other so far applied methods. For each study case, the proposed method together with SFSOA are run fifty run and three main results consisting of the best, mean and standard deviation fitness function are compared. The indication is that the proposed method can find more promising solutions for the three cases and its search ability is always more stable than those of SFSOA. The comparison with other methods also give the same evaluation that the proposed method can be superior to almost all compared methods. As a result, it can conclude that the proposed modification is really appropriate for SFSOA in dealing with ORPD problem and the method can be used for other engineering optimization problems

Automated pupillometry and optic nerve sheath diameter ultrasound to define tuberculous meningitis disease severity and prognosis

Background: Tuberculous meningitis (TBM) causes high mortality and morbidity, in part due to raised intracranial pressure (ICP). Automated pupillometry (NPi) and optic nerve sheath diameter (ONSD) are both low-cost, easy-to-use and non-invasive techniques that correlate with ICP and neurological status. However, it is uncertain how to apply these techniques in the management of TBM. Methods: We conducted a pilot study enrolling 20 adults with TBM in the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam. Our objective was to investigate the relationships between baseline and serial measurements of NPi and ONSD and disease severity and outcome. Serial NPi and ONSD were performed for 30 days, at discharge, and at 3-months, with measurements correlated with clinical progression and outcomes. Results: ONSD and NPi measurements had an inverse relationship. Higher ONSD and lower NPi values were associated with lower Glasgow coma score. Baseline NPi was a strong predictor 3-month outcome (median NPi 4.55, interquartile range 4.35–4.65 for good outcomes versus 2.60, IQR 0.65–3.95 for poor outcomes, p = 0.002). Pupil inequality (NPi ≥0.7) was also strongly associated with poor 3-month outcomes (p = 0.006). Individual participants' serial NPi and ONSD were variable during initial treatment and correlated with clinical condition and outcome. Conclusion: Pupillometry and ONSD may be used to predict clinical deterioration and outcome from TBM. Future, larger studies are need explore the optimal timing of measurements and to define how they might be used to optimise treatments and improve outcomes from TBM

A Measure of Smoothness in Synthesized Speech

The articulators typically move smoothly during speech production. Therefore, speech features of natural speech are generally smooth. However, over-smoothness causes "muffleness" and, hence, reduction in ability to identify emotions/expressions/styles in synthesized speech that can affect the perception of naturalness in synthesized speech. In the literature, statistical variances of static spectral features have been used as a measure of smoothness in synthesized speech but they are not sufficient enough. This paper proposes another measure of smoothness that can be efficiently applied to evaluate the smoothness of synthesized speech. Experiments showed that the proposed measure is reliable and efficient to measure the smoothness of different kinds of synthesized speech

Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings

BackgroundThe purpose of this paper is to demonstrate a mechanism for deploying and validating an AI-based system for detecting abnormalities on chest X-ray scans at the Phu Tho General Hospital, Vietnam. We aim to investigate the performance of the system in real-world clinical settings and compare its effectiveness to the in-lab performance.MethodThe AI system was directly integrated into the Hospital's Picture Archiving and Communication System (PACS) after being trained on a fixed annotated dataset from other sources. The system's performance was prospectively measured by matching and comparing the AI results with the radiology reports of 6,285 chest X-ray examinations extracted from the Hospital Information System (HIS) over the last 2 months of 2020. The normal/abnormal status of a radiology report was determined by a set of rules and served as the ground truth.ResultsOur system achieves an F1 score—the harmonic average of the recall and the precision—of 0.653 (95% CI 0.635, 0.671) for detecting any abnormalities on chest X-rays. This corresponds to an accuracy of 79.6%, a sensitivity of 68.6%, and a specificity of 83.9%.ConclusionsComputer-Aided Diagnosis (CAD) systems for chest radiographs using artificial intelligence (AI) have recently shown great potential as a second opinion for radiologists. However, the performances of such systems were mostly evaluated on a fixed dataset in a retrospective manner and, thus, far from the real performances in clinical practice. Despite a significant drop from the in-lab performance, our result establishes a reasonable level of confidence in applying such a system in real-life situations

Investigation of cure and mechanical properties of deproteined natural rubber-g-poly(methyl methacrylate)

Investigation of cure and mechanical properties of graft copolymer of deproteinized natural rubber (DPNR) with methyl methacrylate (MMA) prepared by graft copolymerization in latex was presented in this work. It is determined that the increase in scorch time, cure time, hardness and tear strength of the graft copolymer were depended on monomer concentration. With the monomer concentration of 15 g/100 g rubber, the increase of hardness and tear strength are 68 % and 66 %, respectively, compared to DPNR. Besides, there are increasing trends of tensile strength and elongation at break. The optimum concentration of MMA monomer is found at 15 g/100 g-rubber. At this monomer concentration, the hardness and tear strength of the graft copolymer increased, whereas the elongation at break and the tensile strength decreased a bit compared to the natural rubber. Keywords. Natural rubber, polymethyl methacrylate, grafted copolymer, curing properties, mechanical properties

Effects of raw material types on the chemical composition of Trung du tea variety (Camellia sinensis var. sinensis)

peer reviewedThe chemical composition of the four raw material types of Trung du tea variety has been identified (a bud with three leaves, B type, C type and old tea leaves). The results indicated that the moisture content, soluble substance, total catechin content, cafein and total polyphenol content significantly varied with the raw material type. The younger the material is, the higher the levels of these components are, and vice versa. In the sample materials, the total polyphenol content ranges from 13.23% dry matter (DM) to 21.73% DM, cafein content from 2.06% DM to 4.68%DM, and the total catechin content from 10.80% DM to 15.93% DM. With regard to catechins, the following relationship was observed: EGCG>EGC>ECG>EC>C. Contents of EGCG and ECG increase from the old leaves to the bud with three leaves. In contrast, EGC content reduces from the old leaves to the bud with three leaves