Exposure to L2 online text on lexical and reading growth

With the fast-paced development of technology in today’s society, there has been emerging a shift from paper-based reading to digital online reading. While the benefits of exposure to print have been well-established in previous studies, how online reading may impact individuals’ literacy development is largely underexplored. The current study investigated if the amount of English reading experience on the Internet could predict EFL students’ lexical knowledge and reading comprehension ability. Participants were ninety-seven Vietnamese undergraduate students who were administered a website checklist and a vocabulary size test. Their reading comprehension scores were also collected as measures of their reading abilities. Descriptive statistics, hierarchical linear regression and structural equation modelling were utilized for data analysis. The results indicated that exposure to L2 online text was a significant predictor of the participants’ vocabulary size as well as their reading comprehension growth during a course of two years. Pedagogical implications are discussed

Recent Advances in Graph Partitioning

We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions

Deep learning application for real-time prediction of COVID-19 outbreak with susceptible-infected-recovered-deceased model

Due to the complex nature of a pandemic such as COVID-19, forecasting how it would behave is difficult, but it is indeed of utmost necessity. Furthermore, adapting predictive models to different data sets obtained from different countries and areas is necessary, as it can provide a wider view of the global pandemic situation and more information on how models can be improved. Therefore, we combine here the long-short-term memory (LSTM) model and the traditional susceptible-infected-recovered-deceased (SIRD) model for the COVID-19 prediction task in Ho Chi Minh City, Vietnam. In particular, LSTM shows its strength in processing and making accurate numerical predictions on a large set of historical input. Following the SIRD model, the whole population is divided into 4 states (S), (I), (R), and (D), and the changes from one state to another are governed by a parameter set. By assessing the numerical output and the corresponding parameter set, we could reveal more insights about the root causes of the changes. The predictive model updates every 10 days to produce an output that is closest to reality. In general, such a combination delivers transparent, accurate, and up-to-date predictions for human experts, which is important for research on COVID-19

Development of an Affimer-antibody combined immunological diagnosis kit for glypican-3

Glypican-3 (GPC3) is a promising new marker for hepatocellular carcinoma, but the reported values for serum GPC3 differ markedly between currently available kits. Here we isolated Affimer non-antibody binding proteins against GPC3 by phage display and developed a new sandwich chemiluminescence immunoassay (CLIA) combining an Affimer with a monoclonal antibody (Affimer-MAb CLIA). The proposed CLIA assay demonstrated a wide linear range  0.03–600 ng/mL) with a good linear correlation coefficient (0.9999), a high detection limitation (0.03 ng/mL) and specificity (0–0.002%) for detection of GPC3. The accuracy, hook effect and stability were demonstrated to be satisfactory. The mean level of GPC3 in serum was higher (>8.5 fold, P < 0.001) in hepatocellular carcinoma patients compared to healthy and other liver disease individuals. A poor correlation (correlation coefficients ranged from −0.286 to 0.478) was observed through pairwise comparison within different kits. However, only this newly developed CLIA test showed high specificity and correlated with the “gold standard” GPC3-immunohistochemistry. This study indicates that Affimer-MAb CLIA can be used to generate a sensitive immunodiagnostic kit, which offers the potential for a highly specific clinically-relevant detection system

Parallel Control-volume Method Based on Compact Local Integrated RBFs for the Solution of Fluid Flow Problems

In this paper, a high performance computing method based on the Integrated Radial Basis Function (IRBF), Control Volume (CV) and Domain Decomposition technique for solving Partial Differential Equations is presented. The goal is to develop an efficient parallel algorithm based on the Compact Local IRBF method using the CV approach, especially for problems with non-rectangular domain. The results showed that the goal is achieved as the computational efficiency is quite significant. For the case of square lid driven cavity problem with Renoylds number 100, super-linear speed-up is also achieved. The parallel algorithm is implemented in the Matlab environment using Parallel Computing Toolbox based on Distributed Computing Engine

Damage Identification of Functionally Graded Beams using Modal Flexibility Sensitivity-based Damage Index

Over the past decades, numerous damage diagnosis techniques based on modal flexibility have been studied and developed for various types of structures, but rarely for structures made of functionally graded (FG) materials. This paper aims to present the extensive applicability of a modal flexibility sensitivity-based damage index termed as MFBDI for damage identification of FG beams. The formulation of this damage index is based on the closed-form of modal flexibility sensitivity derived from the direct algebraic method. The applicability of the offered damage identification method is numerically demonstrated on a clamped-clamped FG beam and a two-span FG beam under (i) single and multiple damage cases, (ii) noise-polluted measurement data, and (iii) only the information of the first few incomplete modes. The identification results indicate that when the noise level added to the mode shape data is below 10%, the offered method can correctly localize the locations of damaged elements and approximately quantify their damage magnitudes in the FG beams. In addition, the influences of the number of used modes, damage magnitudes, and gradient index values are also investigated in the numerical simulations

Dispatching the problems in implementing mobile payment services from consumer attitude perspective

Due to the abundance of internet and e-commerce (electronic commerce), an excessive amount of data has been generated causing an overload of information to the current network infrastructure. As an attempt to solve this problem, there is a shift to mobile payment in the field of E-commerce. Thus, it is essential to study the adoption level of such service for global markets in general and the Vietnamese market in specific. In this paper, we study the consumers' attitude toward mobile payment, investigated with the theory of planned behavior (TPB) from three perspectives, namely the consumer innovativeness, perceived benefit, and perceived risk. Accordingly, there are six hypotheses proposed to study the consumers' attitude toward the service. Thanks to the structural equation modeling (SEM) method, a population of 250 Vietnamese mobile payment users was analyzed to confirm five out of the six hypotheses. It is drawn that the attitude toward the service is correlated positively with the innovativeness and the perceived benefit, while being correlated negatively with the perceived risk. Besides, the resulted model can elucidate approximately 49% the consumers' intention to reuse the mobile payment service

A mutant O-GlcNAcase enriches Drosophila developmental regulators

YesProtein O-GlcNAcylation is a reversible post-translational modification of serines/threonines on nucleocytoplasmic proteins. It is cycled by the enzymes O-GlcNAc transferase (OGT) and O-GlcNAc hydrolase (O-GlcNAcase or OGA). Genetic approaches in model organisms have revealed that protein O-GlcNAcylation is essential for early embryogenesis. Drosophila melanogaster OGT/supersex combs (sxc) is a polycomb gene, null mutants of which display homeotic transformations and die at the pharate adult stage. However, the identities of the O-GlcNAcylated proteins involved, and the underlying mechanisms linking these phenotypes to embryonic development, are poorly understood. Identification of O-GlcNAcylated proteins from biological samples is hampered by the low stoichiometry of this modification and limited enrichment tools. Using a catalytically inactive bacterial O-GlcNAcase mutant as a substrate trap, we have enriched the O-GlcNAc proteome of the developing Drosophila embryo, identifying, amongst others, known regulators of Hox genes as candidate conveyors of OGT function during embryonic development.Wellcome Trust Investigator Award (110061); MRC grant (MC_UU_12016/5); and Royal Society Research Grant

A High-order Coupled Compact Integrated RBF Approximation Based Domain Decomposition Algorithm for Second-order Differential Problems

This paper presents a high-order coupled compact integrated RBF (CC IRBF) approximation based domain decomposition (DD) algorithm for the discretisation of second-order differential problems. Several Schwarz DD algorithms, including one-level additive/ multiplicative and two-level additive/ multiplicative/ hybrid, are employed. The CCIRBF based DD algorithms are analysed with different mesh sizes, numbers of subdomains and overlap sizes for Poisson problems. Our convergence analysis shows that the CCIRBF two-level multiplicative version is the most effective algorithm among various schemes employed here. Especially, the present CCIRBF two-level method converges quite rapidly even when the domain is divided into many subdomains, which shows great promise for either serial or parallel computing. For practical tests, we then incorporate the CCIRBF into serial and parallel two-level multiplicative Schwarz. Several numerical examples, including those governed by Poisson and Navier-Stokes equations are analysed to demonstrate the accuracy and efficiency of the serial and parallel algorithms implemented with the CCIRBF. Numerical results show: (i) the CCIRBF-Serial and -Parallel algorithms have the capability to reach almost the same solution accuracy level of the CCIRBF-Single domain, which is ideal in terms of computational calculations; (ii) the CCIRBF-Serial and -Parallel algorithms are highly accurate in comparison with standard finite difference, compact finite difference and some other schemes; (iii) the proposed CCIRBF-Serial and -Parallel algorithms may be used as alternatives to solve large-size problems which the CCIRBF-Single domain may not be able to deal with. The ability of producing stable and highly accurate results of the proposed serial and parallel schemes is believed to be the contribution of the coarse mesh of the two-level domain decomposition and the CCIRBF approximation. It is noted that the focus of this paper is on the derivation of highly accurate serial and parallel algorithms for second-order differential problems. The scope of this work does not cover a thorough analysis of computational time

4th International Conference on Computational Methods (ICCM 2012)

Compact Local Integrated Radial Basis Function (CLIRBF) methods based on Cartesian grids can be effective numerical methods for solving Elliptic Partial Differential Equations (EPDEs) for fluid flow problems. The combination of the domain decomposition technique and function approximation using CLIRBF methods yields an effective coarse-grained parallel processing approach. This feature has enabled not only each sub-domain in the original analysis domain to be discretised by a separate CLIRBF Network but also Compact Local stencils to be independently treated. The present algorithm, namely parallel CLIRBF, achieves higher throughput in solving large scale problems by, firstly, parallel processing of sub-regions which comprise the original domain and, secondly, accelerating the convergence rate within each sub-region using groups of CLIRBF stencils in which function approximations are carried out by parallel processes. The procedure is illustrated with several numerical examples of EPDEs using Message Passing Interface (MPI) supported by MATLAB