THE EFFECT OF USING INSTRUCTIONAL RUBRICS ON EFL STUDENTS’ WRITING PERFORMANCE: A HIGH SCHOOL CASE IN THE MEKONG DELTA OF VIETNAM

Teaching EFL writing has been one of the most trending research fields recently. Among the techniques being tested, using instructional rubrics has drawn much attention from researchers and teachers. This study aimed to investigate the effectiveness of using rubrics in enhancing students’ writing skill and the students’ attitudes towards this technique. The study used the experimental research design. The participants were thirty English-majored eleventh-grade students (N=30) in a high school in Can Tho City, Viet Nam. The main research tools included two guiding rubrics, one writing pre-test, two writing post-tests, and a questionnaire. Holistic and analytic rubrics were used in the teaching of writing skill to the participants to help them understand the targets for learning and the standards of quality for their writing work.  Data from the pre- and post- writing tests indicated significant changes in students’ writing performance after using both holistic and analytic rubrics. Besides, the results of the questionnaire revealed learners’ positive perceptions of this technique. It could be suggested that high school teachers should take into account the use of rubrics in teaching writing for EFL students.  Article visualizations

Prenatal Exposure to Nitrates, Nitrites, and Nitrosatable Drugs and Preterm Births

Nitrosatable drugs react with nitrite in the stomach to form N-nitroso compounds, observed in animal models to result in adverse pregnancy outcomes such as birth defects and reduced fetal weight. Previous studies examining prenatal exposure to medications classified as nitrosatable have observed an increased risk of preterm delivery. Vitamin C is a known nitrosation inhibitor. Using data from mothers (controls) of babies without major birth defects from the National Birth Defects Prevention Study, we examined the relation between preterm births and: 1) prenatal nitrosatable drug usage; 2) dietary intake of nitrates/nitrites; 3) joint exposures to nitrosatable drugs and nitrate/nitrite intake; and 4) nitrosatable drugs and vitamin C intake among 496 case-mothers of preterm infants and 5398 control-mothers who delivered full term babies from 1997-2005. An increased risk of preterm births was observed with secondary amine exposure during the second (adjusted hazard ratio (aHR) 1.37, [95% confidence interval (CI) 1.05, 1.79]) and third (aHR 1.34, [95% CI 1.02, 1.76]) trimester. A protective effect was detected with high levels of plant nitrites (aHR 0.72, [95% CI 0.53, 0.97]). Exposure to secondary amines and high levels of nitrite were associated with preterm births, having an increased risk with first (aHR 1.84, [95% CI 1.14, 2.98]), second (aHR 1.89, [95% CI 1.17, 3.07]), and third (aHR 2.00, [95% CI 1.22, 3.29]) trimester exposure. Lower risk of moderately preterm births was observed with second trimester amide exposure in conjunction with higher levels of dietary vitamin C (aHR 1.14, [95% CI 0.66, 1.98]) compared to <85 mg/day (aHR 2.08, [95% CI 1.25, 3.47]). Prenatal exposure to nitrosatable drugs during the second and third trimester, particularly secondary amines, might increase risk of preterm delivery. In addition, nitrosatable drugs, especially secondary and tertiary amines, and higher levels of dietary nitrite (including animal, plant, and total) may increase risk of preterm births. However, dietary vitamin C intake ≥85 mg/day may attenuate the association between nitrosatable drug use during the second trimester and preterm and moderately preterm births. In this study population, daily vitamin C supplementation did not appear to confer the same benefits

Influence of the Capped Polymer on the Optical of ZnS:Cu Nanocrystalline Thin Films

The ZnS:Cu nanopowders were synthesized by the wet chemical method with Cu concentrations of 0.1, 0.15, 0.2, 0.3 and 0.4{\%}. The microstructure of samples was investigated by the X-ray diffraction (XRD) measurement. The results show that the prepared samples belong to the Wurtzite structure with the average particle size of about 3--7 nm. The highest luminescence intensity of ZnS:Cu nanopowders corresponds to sample with Cu concentration of 0.2{\%}. To investigate the effect of polyvinylacohol (PVA) on the structure of ZnS:Cu, we have prepared the polyvinylacohol (PVA)-capped ZnS:Cu thin films with a Cu concentration of 0.2{\%} by dip-coating method. The PVA did not affect the microstructure of ZnS nanomaterials. The optical properties of samples were studied by measuring the absorption and the photoluminescence spectra in the wavelength range from 300 nm to 900 nm at room temperature. The value of direct band gap is about 3.8 eV. The dependence of the photoluminescence (PL) spectra of samples on the exciting power density, their time-resolved-luminescence spectra were also investigated

implications for policy

Thesis(Master) --KDI School:Master of Public Policy,2006Outstandingmasterpublishedby Hieu Thi Minh Vuong

Essays On Explosive Time Series

In the first chapter of this thesis, we introduce and explore three prominent research areas related to explosive bubbles. We also establish the link between each chapter in the thesis and consequently, these strands of research. In Chapter 2, we introduce a novel test that builds upon the existing WLS-based test proposed by Harvey et al. (2019) to identify explosive bubbles in financial data with the presence of time-varying volatility. Our test outperforms both the conventional supremum bubble test of Phillips and Yu (2011) and Harvey et al. (2019)’s test. Our approach involves replacing the kernel-based volatility function estimator used by Harvey et al. (2019) with our own volatility estimator that is based on an iterative cumulative sum of squares algorithm. Similar to Harvey et al. (2019)’s test, we use the estimated volatility to calculate the WLS-based statistic and employ a wild-bootstrap procedure to control the size of the test and make it robust under various time-varying volatility patterns. We suggest using a union of rejections procedure when the volatility pattern is a late upward shift to capture the better power available from the two constituent tests for a given alternative. Chapter 3 introduces a backward supremum KPSS-based test, which extends the KPSS-based test of Evripidou et al. (2022) to detect short-lived co-explosive behaviour between a pair of asset prices at the end of the sample period. Finite sample simulations show that our test has well-controlled size under most volatility specifications and has higher power than Evripidou et al. (2022)’s test in detecting periods without co-bubbles. As with Evripidou et al. (2022)’s test, our proposed test still employs a wild bootstrap algorithm to deliver a robust test for heteroskedasticity and uses a long-run variance estimate to control the size of the test when serial correlation exists in innovations. By applying both single and double backward supremum tests to the same dataset as Evripidou et al. (2022), we show new findings of co-explosive bubbles in pairs of non-ferrous and precious metals in spot and futures markets. In Chapter 4, we compare the behaviour of common return predictability tests (i.e., IVX, Bonferroni-t, and Bonferroni-Q tests) during bubble periods. Overall, Monte Carlo simulations show that all three tests over-reject the null hypothesis of no predictability. In that regard, the Bonferroni-t test is the least oversized, while the IVX test is badly oversized across different bubble specifications. To conduct the simulations, we introduce a new data generating process that does not require a predetermined variable in the predictive model. Finally, by comparing results obtained from subsamples with and without bubbles, our empirical application shows the over-rejections of the tests to the null using the extended dataset from January 1927 to December 2021 containing 14 financial and macroeconomic predictors of Welch and Goyal (2008). The last chapter of this thesis provides concluding remarks on the significant findings and limitations, as well as presenting suggestions for future research directions

Improving Bayesian statistics understanding in the age of Big Data with the bayesvl R package

The exponential growth of social data both in volume and complexity has increasingly exposed many of the shortcomings of the conventional frequentist approach to statistics. The scientific community has called for careful usage of the approach and its inference. Meanwhile, the alternative method, Bayesian statistics, still faces considerable barriers toward a more widespread application. The bayesvl R package is an open program, designed for implementing Bayesian modeling and analysis using the Stan language’s no-U-turn (NUTS) sampler. The package combines the ability to construct Bayesian network models using directed acyclic graphs (DAGs), the Markov chain Monte Carlo (MCMC) simulation technique, and the graphic capability of the ggplot2 package. As a result, it can improve the user experience and intuitive understanding when constructing and analyzing Bayesian network models. A case example is offered to illustrate the usefulness of the package for Big Data analytics and cognitive computing

Neural network based patient recovery estimation of a PAM-based rehabilitation robot

Rehabilitation robots have shown a promise in aiding patient recovery by supporting them in repetitive, systematic training sessions. A critical factor in the success of such training is the patient’s recovery progress, which can guide suitable treatment plans and reduce recovery time. In this study, a neural network-based approach is proposed to estimate the patient’s recovery, which can aid in the development of an assist-as-needed training strategy for the gait training system. Experimental results show that the proposed method can accurately estimate the external torques generated by the patient to determine their recovery. The estimated patient recovery is used for an impedance control of a 2-DOF robotic orthosis powered by pneumatic artificial muscles, which improves the robot joint compliance coefficients and makes the patient more comfortable and confident during rehabilitation exercises

Complemented and uncomplemented subspaces of Banach spaces

"A natural process in examining properties of Banach spaces is to see if a Banach space can be decomposed into simpler Banach spaces; in other words, to see if a Banach space has complemented subspaces. This thesis concentrates on three main aspects of this problem: norm of projections of a Banach space onto its finite dimensional subspaces; a class of Banach spaces, each of which has a large number of infinite dimensional complemented subspaces; and methods of finding Banach spaces which have uncomplemented subspaces, where the subspaces and the quotient spaces are chosen as well-known classical sequence spaces (finding non-trivial twisted sums)." --Abstract.Master of Mathematical Science