EFL TERTIARY STUDENTS' PERCEPTION AND PRACTICE WITH LANGUAGE LEARNING BEYOND THE CLASSROOM: THE CASE OF VIETNAM

While language teaching is widely acknowledged as preparation for real-life language use, attention is still focused mainly on classroom-bounded learning. However, the development of technology allows language learners to extend their learning opportunities beyond the classroom. Using a mixed method design that included questionnaires and semi-structured interviews, this study aims to explore how Vietnamese EFL tertiary students perceive and utilize language learning beyond the classroom (LLBC) resources in learning English. This study finds that the students perceived well the feasibility of the LLBC, and believed in the benefits of LLBC resources and activities in improving pronunciation and vocabulary, listening, and speaking skills. In addition, the students are found also to try to develop strategies for making the most of individual LLBC resources and activities to improve their English proficiency. The study also provides implications for the teachers to prepare and equip themselves with the effective utilization of LLBC resources and activities to provide their students with helpful advice.  Article visualizations

VIETNAMESE EFL TEACHERS’ USE OF THE SET OF NEW ENGLISH TEXTBOOKS TIENG ANH 11 AS RESOURCES FOR ACHIEVEMENT TESTS

The paper reported on part of a study investigating Vietnamese upper secondary school EFL teachers’ use of the set of new English textbooks Tieng Anh 11 as resources for achievement tests. To carry out this research, both qualitative and quantitative approaches including questionnaires and interviews were used to collect the data from research participants at some upper secondary schools in Quang Tri Province, Vietnam. The findings of the study showed the teachers’ practices in using the set of new English textbooks Tieng Anh 11 for achievement tests. They reported adapting the exercises and activities, following the teaching procedures, and referring to the book maps in the set of new English textbooks Tieng Anh 11 to organize revision, design one-period tests and semester exams. Especially, using the accompanying workbooks to revise what students learned accounted for the highest rate. Besides, major challenges of the upper-secondary school teachers in using this set are also uncovered through the results. The teachers mostly have difficulties in finding the relevant materials matching the prescribed test formats as well as the required language competence in the set of new English textbooks Tieng Anh 11, lacking the test formats and scoring criteria associated with achievement tests. From the research findings, some implications were suggested for teachers’ flexibility in teaching and test preparation processes, and for improving the set of new English textbooks Tieng Anh 11. Article visualizations

AN INVESTIGATION INTO QUANG TRI PRIMARY SCHOOL ENGLISH LANGUAGE TEACHER’S PERSPECTIVE OF ICT INTEGRATION DURING THE COVID-19 PANDEMIC

With the transition from face-to-face classes to online classes during Covid-19 epidemic, teachers in Quang Tri have no choice but to integrate ICT into their teaching. At this time ICT has become the most essential tool in educational settings and the subject of many researchers. This study aims to investigate how English teachers perceived ICT integration in terms of the benefits, difficulties as well as challenges of incorporating ICT. The study adopted both quantitative and qualitative methods of data collection, i.e., questionnaires and interviews. The findings revealed that the majority of English teachers had a positive perception of integrating ICT due to its effectiveness. However, it was also reported that lack of technical support from schools, and limited knowledge and training in ICT discouraged teachers from using ICT. The study offers useful implications for teachers to integrate ICT in teaching English during the pandemic time.  Article visualizations

VulCurator: A Vulnerability-Fixing Commit Detector

Open-source software (OSS) vulnerability management process is important nowadays, as the number of discovered OSS vulnerabilities is increasing over time. Monitoring vulnerability-fixing commits is a part of the standard process to prevent vulnerability exploitation. Manually detecting vulnerability-fixing commits is, however, time consuming due to the possibly large number of commits to review. Recently, many techniques have been proposed to automatically detect vulnerability-fixing commits using machine learning. These solutions either: (1) did not use deep learning, or (2) use deep learning on only limited sources of information. This paper proposes VulCurator, a tool that leverages deep learning on richer sources of information, including commit messages, code changes and issue reports for vulnerability-fixing commit classifica- tion. Our experimental results show that VulCurator outperforms the state-of-the-art baselines up to 16.1% in terms of F1-score. VulCurator tool is publicly available at https://github.com/ntgiang71096/VFDetector and https://zenodo.org/record/7034132#.Yw3MN-xBzDI, with a demo video at https://youtu.be/uMlFmWSJYOE.Comment: accepted to ESEC/FSE 2022, Tool Demos Trac

AutoPruner: Transformer-Based Call Graph Pruning

Constructing a static call graph requires trade-offs between soundness and precision. Program analysis techniques for constructing call graphs are unfortunately usually imprecise. To address this problem, researchers have recently proposed call graph pruning empowered by machine learning to post-process call graphs constructed by static analysis. A machine learning model is built to capture information from the call graph by extracting structural features for use in a random forest classifier. It then removes edges that are predicted to be false positives. Despite the improvements shown by machine learning models, they are still limited as they do not consider the source code semantics and thus often are not able to effectively distinguish true and false positives. In this paper, we present a novel call graph pruning technique, AutoPruner, for eliminating false positives in call graphs via both statistical semantic and structural analysis. Given a call graph constructed by traditional static analysis tools, AutoPruner takes a Transformer-based approach to capture the semantic relationships between the caller and callee functions associated with each edge in the call graph. To do so, AutoPruner fine-tunes a model of code that was pre-trained on a large corpus to represent source code based on descriptions of its semantics. Next, the model is used to extract semantic features from the functions related to each edge in the call graph. AutoPruner uses these semantic features together with the structural features extracted from the call graph to classify each edge via a feed-forward neural network. Our empirical evaluation on a benchmark dataset of real-world programs shows that AutoPruner outperforms the state-of-the-art baselines, improving on F-measure by up to 13% in identifying false-positive edges in a static call graph.Comment: Accepted to ESEC/FSE 2022, Research Trac

Insights into the Carbon chemistry of Mon R2

Aiming to learn about the chemistry of the dense PDR around the ultracompact (UC) HII region in Mon R2, we have observed a series of mm-wavelength transitions of C3H2 and C2H. In addition, we have traced the distribution of other molecules, such as H13CO+, SiO, HCO, and HC3N. These data, together with the reactive ions recently detected, have been considered to determine the physical conditions and to model the PDR chemistry. We then identified two kind of molecules. The first group, formed by the reactive ions (CO+, HOC+) and small hydrocarbons (C2H, C3H2), traces the surface layers of the PDR and is presumably exposed to a high UV field (hence we called it as "high UV", or HUV). HUV species is expected to dominate for visual absorptions 2 < Av < 5 mag. A second group (less exposed to the UV field, and hence called "low UV", or LUV) includes HCO and SiO, and is mainly present at the edges of the PDR (Av > 5 mag). While the abundances of the HUV molecules can be explained by gas phase models, this is not the case for the studied LUV ones. Although some efficient gas-phase reactions might be lacking, grain chemistry sounds like a probable mechanism able to explain the observed enhancement of HCO and SiO. Within this scenario, the interaction of UV photons with grains produces an important effect on the molecular gas chemistry and constitutes the first evidence of an ionization front created by the UC HII region carving its host molecular cloud. The physical conditions and kinematics of the gas layer which surrounds the UC HII region were derived from the HUV molecules. Molecular hydrogen densities > 4 10^6 cm^(-3) are required to reproduce the observations. Such high densities suggest that the HII region could be pressure-confined by the surrounding high density molecular gas.Comment: 32 pages, 8 figures. Accepted by Astrophysical Journa

Multi-Granularity Detector for Vulnerability Fixes

With the increasing reliance on Open Source Software, users are exposed to third-party library vulnerabilities. Software Composition Analysis (SCA) tools have been created to alert users of such vulnerabilities. SCA requires the identification of vulnerability-fixing commits. Prior works have proposed methods that can automatically identify such vulnerability-fixing commits. However, identifying such commits is highly challenging, as only a very small minority of commits are vulnerability fixing. Moreover, code changes can be noisy and difficult to analyze. We observe that noise can occur at different levels of detail, making it challenging to detect vulnerability fixes accurately. To address these challenges and boost the effectiveness of prior works, we propose MiDas (Multi-Granularity Detector for Vulnerability Fixes). Unique from prior works, Midas constructs different neural networks for each level of code change granularity, corresponding to commit-level, file-level, hunk-level, and line-level, following their natural organization. It then utilizes an ensemble model that combines all base models to generate the final prediction. This design allows MiDas to better handle the noisy and highly imbalanced nature of vulnerability-fixing commit data. Additionally, to reduce the human effort required to inspect code changes, we have designed an effort-aware adjustment for Midas's outputs based on commit length. The evaluation results demonstrate that MiDas outperforms the current state-of-the-art baseline in terms of AUC by 4.9% and 13.7% on Java and Python-based datasets, respectively. Furthermore, in terms of two effort-aware metrics, EffortCost@L and Popt@L, MiDas also outperforms the state-of-the-art baseline, achieving improvements of up to 28.2% and 15.9% on Java, and 60% and 51.4% on Python, respectively

CN and HCN in Dense Interstellar Clouds

We present a theoretical investigation of CN and HCN molecule formation in dense interstellar clouds. We study the gas-phase CN and HCN production efficiencies from the outer photon-dominated regions (PDRs) into the opaque cosmic-ray dominated cores. We calculate the equilibrium densities of CN and HCN, and of the associated species C+, C, and CO, as functions of the far-ultraviolet (FUV) optical depth. We consider isothermal gas at 50 K, with hydrogen particle densities from 10^2 to 10^6 cm^-3. We study clouds that are exposed to FUV fields with intensities 20 to 2*10^5 times the mean interstellar FUV intensity. We assume cosmic-ray H2 ionization rates ranging from 5*10^-17 s^-1, to an enhanced value of 5*10^-16 s^-1. We also examine the sensitivity of the density profiles to the gas-phase sulfur abundance.Comment: Accepted for publication in ApJ, 33 pages, 8 figure

GLYCOSIDES ISOLATED FROM THE AERIAL PARTS OF Premna integrifolia L. GROWING IN THAI BINH

From the aerial parts of Premna integrifolia L., three glycosides acteoside (1), premnaodoroside A (2), and premnaodoroside B (3) were isolated. Their chemical structures were elucidated by means of ESI-MS, 1H-NMR, 13C-NMR, HSQC, HMBC spectra and in comparison with the previous literature. To our best knowledge, this is the first report of 1 and 3 from P. integrifolia