Miracle-dz/UniFAR-FTUs huggingface dataset:
THE RELATIONSHIP BETWEEN LEARNING STRATEGY USE IN ENGLISH AND MOTIVATION OF STUDENTS AT A COLLEAGUE IN CAN THO CITY, VIETNAM

Among the many factors that increase students’ achievement in the mastery of foreign languages, including English, are motivation and use of language learning strategies. Previous studies by a range of researchers have identified these two elements as the most important in obtaining success in language learning. This study carried out on 152 university students, roughly equal in gender, studying at a university in Can Tho, Vietnam, sought to discover the relationships between these two factors within the Vietnamese language learning context. In particular, the study sought to 1) discover which of two types of motivation, intrinsic and extrinsic, is most prevalent among the students studied; 2) their use of language learning strategies; 3) reveals the relationship between students' motivation and use of language learning strategies; and 4) describe the differences in their use of language learning strategies based on whether their motivation was high, medium or low. Research instruments included Schmidt et al.'s Questionnaire on Motivation in Learning English, and Oxford's Strategy Inventory for Language Learning (both modified for the Vietnamese language learning context and translated into Vietnamese), plus an interview with 18 of the students to gain greater insight into the answers they gave on the questionnaires. Results were obtained using standard deviations and t-tests. They showed that Vietnamese university students are mainly extrinsically motivated; that all strategies were used at least at a medium level, amidst other fluctuations; and that those metacognitive strategies are most prevalent among medium and high motivated students but affective strategies are most common among low motivation students. Recommendations flowing from these results are that teachers should prioritize the formal teaching of learning strategies and should attempt to increase intrinsic motivation by putting greater emphasis on making language learning fun and relevant to the students' interests and passions. Article visualizations:
A RIGOROUS MODEL FOR ABSORPTION OF CARBON DIOXIDE INTO AQUEOUS N-METHYLDIETHANOLAMINE SOLUTION

ABSTRACT A rigorous model for absorption of carbon dioxide into aqueous N-methyldiethanolamine (MDEA) based on the assumption of reversible reactions and the simplified model with a pseudo-first order irreversible reaction hypothesis were employed to compare with experimental data. The experimental absorption rates were obtained from a characterized double stirred-cell absorber with a planar gas-liquid interface. It was demonstrated that the numerical solution of the rigorous model provides a better prediction for the absorption rate of carbon dioxide into aqueous MDEA solution than that of the simplified model. Only in the case of absorption experiments carried out at a low carbon dioxide partial pressure (p < 20 kpa) and low amine concentration (MDEAtotal < 1000 mol/m3), the assumption of pseudo-first order irreversible reaction is reasonable.
Mechanical buckling of nanocomposites: Experimental and numerical investigations

The proposed research explores Multi-Walled Carbon Nanotube’s (MWCNT’s) effect on the mechanical buckling behavior of glass fiber-enhanced thermosetting composites using UTM and the load vs displacement curve is plotted. Using the inflection point method, the critical buckling load is obtained from the load vs displacement curve for beams with three different volume fractions of MWCNT. The nonlinear finite element method is used to numerically obtain the load vs deflection curve and the numerical results are compared with the experimental results, and a close match is found with the experimental results. It is observed that the nonlinearity associated with the structure can significantly reduce the critical buckling load. The critical buckling load is found to increase and reported a 27.4% increase in buckling load with 0.3 wt. % of MWCNT which could be accounted for the increase in flexural modulus of the material.
Improving word vector model with part-of-speech and dependency grammar information

Part-of-speech (POS) and dependency grammar (DG) are the basic components of natural language processing. However, current word vector models have not made full use of both POS information and DG information, and hence the models’ performances are limited to some extent. The authors first put forward the concept of POS vector, and then, based on continuous bag-of-words (CBOW), constructed four models: CBOW + P, CBOW + PW, CBOW + G, and CBOW + G + P to incorporate POS information and DG information into word vectors. The CBOW + P and CBOW + PW models are based on POS tagging, the CBOW + G model is based on DG parsing, and the CBOW + G + P model is based on POS tagging and DG parsing. POS information is integrated into the training process of word vectors through the POS vector to solve the problem of the POS similarity being difficult to measure. The POS vector correlation coefficient and distance weighting function are used to train the POS vector as well as the word vector. DG information is used to correct the information loss caused by fixed context windows. Dependency relations weight is used to measure the difference of dependency relations. Experiments demonstrated the superior performance of their models while the time complexity is still kept the same as the base model of CBOW.
Nexus among Perceived Organizational Politics and Organizational Citizenship Behavior Under the lenses of Social Exchange Perceptions

Employee-organization relationship is most debatable and interested phenomena of organizational behavior research stream. This study aims to investigate the influence of perceived organizational politics on organizational citizenship behavior under the lenses of social exchange theory. This study also propose that perceptions of social exchange not only mitigate the influence of perceived organizational politics but also enhance employees’ voluntary efforts to engage in extra-role behaviors. Data was collected from the staff of SMEs operating in Lahore, Pakistan. Structured questionnaires were used to collect data from target respondents. Results revealed that perceived organizational politics do not directly have negative influence on organizational citizenship behavior. However, perceived organizational politics has effect on social exchange perceptions and social exchange perceptions have positive influence on citizenship behavior. Indirect relationship exists among POP and OCB which is fully mediated by social exchange perceptions.
Admission oxygen saturation and all-cause in-hospital mortality in acute myocardial infarction patients: data from the MIMIC-III database

Background Acute myocardial infarction (AMI) is mainly caused by a mismatch of blood oxygen supply and demand in the myocardium. However, several studies have suggested that excessively high or low arterial oxygen tension could have deleterious effects on the prognosis of AMI patients. Therefore, the relationship between blood oxygenation and clinical outcomes among AMI patients is unclear, and could be nonlinear. In the critical care setting, blood oxygen level is commonly measured continuously using pulse oximetry-derived oxygen saturation (SpO2). The present study aimed to determine the association between admission SpO2 levels and all-cause in-hospital mortality, and to elucidate the optimal SpO2 range with real-world data. Methods Patients diagnosed with AMI on admission in the Medical Information Mart for Intensive Care III (MIMIC-III) database were included. A generalized additive model (GAM) with loess smoothing functions was used to determine and visualize the nonlinear relationship between admission SpO2 levels within the first 24 hours after ICU admission and mortality. Moreover, the Cox regression model was constructed to confirm the association between SpO2 and mortality. Results We included 1,846 patients who fulfilled our inclusion criteria, among whom 587 (31.80%) died during hospitalization. The GAM showed that the relationship between admission SpO2 levels and all-cause in-hospital mortality among AMI patients was nonlinear, as a U-shaped curve was observed. In addition, the lowest mortality was observed for an SpO2 range of 94–96%. Adjusted multivariable Cox regression analysis confirmed that the admission SpO2 level of 94–96% was independently associated with decreased mortality compared to SpO2 levels <94% [hazard ratio (HR) 1.352; 95% confidence interval (CI): 1.048–1.715; P=0.028] and >96% (HR 1.315; 95% CI: 1.018–1.658; P=0.030). Conclusions The relationship between admission SpO2 levels and all-cause in-hospital mortality followed a U-shaped curve among patients with AMI. The optimal oxygen saturation range was identified as an SpO2 range of 94–96%, which was independently associated with increased survival in a large and heterogeneous cohort of AMI patients.
Dialogic education for classroom teaching: a critical review

Abstract Dialogic education has become increasingly appealing due to the recognized value of dialogue for the development of students’ thinking and knowledge. Yet, its appeal has not catalysed widespread adoption of dialogic education in classrooms due partly to teachers’ uncertainty over the conceptualization of dialogic education and the presence of several similar yet different models in the literature. The purpose of this paper is to critically review several well-known models of dialogic education to uncover some of their shared features as well as differences. Four dialogic education models, ‘dialogically organized instruction’, ‘Thinking Together’, ‘Accountable Talk’ and ‘dialogic teaching’, are reviewed, compared and critiqued. Based on the review, a framework of dialogic education that synthesizes the features of the four dialogic education models and hinges on four components – dialogic environment, teaching goal, classroom talk and dialogic moves – is proposed. This will hopefully help to equip and empower teachers to translate the theoretical principles of dialogic education into actual classroom practices.
Deep Convolutional Neural Networks for Emotion Recognition of Vietnamese

Human emotions play a very important role in communication. Emotional speech recognition research brings human–machine communication closer to human-to-human communication. This paper presents the evaluation using ANOVA and T-test for the Vietnamese emotional corpus and using deep convolutional neural networks to recognize four basic emotions of Vietnamese based on this corpus: neutrality, sadness, anger, and happiness. Five sets of characteristic parameters were used as inputs of the deep convolutional neural network in which the mel spectral images were taken and attention was paid to the fundamental frequency, F0, and its variants. Experiments were conducted for these five sets of parameters and for four cases, depending on dependent or independent content and dependent or independent speakers. On average, the maximum recognition accuracy achieved was 97.86% under speaker-dependent and content-dependent conditions. The results of the experiments also show that F0 and its variants contribute significantly to the increased accuracy of Vietnamese emotional recognition.
Forge-resistant radio-frequency identification tags for secure internet of things applications

Aim: Internet of Things (IoT) represents a key aspect within several application domains, and it enables growing opportunities for both organizations and end-users. Radio-frequency identification tags are probably the most relevant enabling solution for ubiquitous IoT systems and are often seen as a prerequisite for IoT itself. In this study, we analyzed one of the most promising radio-frequency identification tags to determine whether or not it represents a viable solution for secure IoT applications. Methods: The study was conducted relying on an Android OS application developed within our laboratories, which helped us to inspect the chip and describe its logical data structure. We studied the capabilities of the tag in relation to the application protocol data unit it supports, and we described the cryptographic protocols with which
A Thematic Analysis of Theses Made in the Field of Lifelong Learning with Pre-Service Teachers (2009-2020)

This study was conducted to examine the postgraduate theses made in the field of lifelong learning with pre-service teachers between 2009 and 2020 in terms of their thesis problem, research topic, conclusions and recommendations. The 23 postgraduate theses constituting the study sample were determined by means of criterion sampling method from the Higher Education Council’s thesis database. These theses were used as data collection tools and the study was designed as a qualitative study using the document review method. The data was analyzed using content analysis. The study revealed that a significant part of the theses consisted of subjects aimed at revealing the perceptions of lifelong learning tendencies-competencies and the relationships between lifelong learning and different variables. In addition, the postgraduate theses predominantly looked at the level of lifelong learning tendencies of the pre-service teachers and whether lifelong learning competencies-tendencies differed by gender, grade levels, departments, educational status of parents, academic achievement and socio-economic levels. As a result, it was revealed that the pre-service teachers' lifelong learning tendencies were high in most of the theses and that there was a significant difference in terms of lifelong learning competence by gender. Some suggestions were made based on these results.
Vehicle Positioning System using V2X that Combines V2V and V2I Communications

In this paper, we present a V2X (Vehicle to Everything) vehicle positioning system environment using V2V (Vehicle to Vehicle) and V2I (Vehicle to Infrastructure) communication server. With the growth of the 5G network technology, using V2X which exchanges information, connected car recently became an important area of research in autonomous driving. However, it takes too much risk to test autonomous driving in a real-world experiment and it also have difficulties such as road infrastructure or 5G communication system. Regrading autonomous driving research, we established V2X environment in a small RC car, similar to a vehicle environment. Our proposed Vehicle Positioning System environment uses a ceiling camera, V2V, and main server, V2I, which plays the same role as GPS and 5G in the real-world. Combining the V2I and V2V from the camera of each other car using Kalman Filter we present a vehicle positioning system.
An Early Flame Detection System Based on Image Block Threshold Selection Using Knowledge of Local and Global Feature Analysis

Fire is one of the mutable hazards that damage properties and destroy forests. Many researchers are involved in early warning systems, which considerably minimize the consequences of fire damage. However, many existing image-based fire detection systems can perform well in a particular field. A general framework is proposed in this paper which works on realistic conditions. This approach filters out image blocks based on thresholds of different temporal and spatial features, starting with dividing the image into blocks and extraction of flames blocks from image foreground and background, and candidates blocks are analyzed to identify local features of color, source immobility, and flame flickering. Each local feature filter resolves different false-positive fire cases. Filtered blocks are further analyzed by global analysis to extract flame texture and flame reflection in surrounding blocks. Sequences of successful detections are buffered by a decision alarm system to reduce errors due to external camera influences. Research algorithms have low computation time. Through a sequence of experiments, the result is consistent with the empirical evidence and shows that the detection rate of the proposed system exceeds previous studies and reduces false alarm rates under various environments.
Phytochemical Content and in Vitro Antioxidant, Antibacterial and Antitumor Activities of Phoenix Dactylifera Fruit Extract

Phoenix dactylifera fruits are important sources for carbohydrates, minerals, vitamins, phenols and flavonoids compounds, which are important for human health. The objective of study: To evaluate the chemical composition, minerals, phytochemical, antioxidant activity using [FRAP+ and DPPH+], and antibacterial properties against some bacterial strains, (E. coli, St. aureus, L. monocytogenes and B. subtillis), of Phoenix dactylifera fruits. In addition, cytotoxic study of plant fruit extracts on human cancer cell lines (MCF-7 and HCT-116). The phytochemical screening showed that the fruit extracts contain alkaloids, flavonoids, tannins, phenols, saponins, carbohydrates and except steroids. The Phoenix dactylifera fruits have the highest value of polyphenol and flavonoid content which were 181.27mg GAE/g and 31.09mg QE/g, respectively. The antioxidant activity was evaluated using the ferric reducing antioxidant power (FRAP) radical into 79.17 and 87.05%, at a concentration 16mg/ml of aqueous and methanolic extracts. DPPH assay revealed a good antioxidant activity of methanolic extract which was (IC50 0.45μg). Moreover, the methanolic extract of Phoenix dactylifera led to the highest growth inhibition (18.75, 20.5 and 17mm), against E. coli, L. monocytogenes and B. subtillis at a concentration 4mg/ml, respectively. While, the aqueous extract provided the medium percentage of growth inhibition (11.5, 9.75 and 12.5mm) against E. coli, St. aureus and B. subtillis at a concentration 4mg/ml, respectively. Moreover, the fruit extracts have a reasonable effect on breast and colon cancer cell lines inhibition when compared with Thymoquinone at a concentration 75μg/ml.
Implementation of HOG Feature Extraction with Tuned Parameters for Human Face Detection

Extracting and tracking face in image sequences is a required first step in many applications such as face recognition facial expression classification and face tracking, it is a challenging problem in computer vision field because of many factors that effects on the image, some of these factors are luminosity, different face colors, background patterns, face orientation and variability in size, shape, and expression. The objective of this paper is to Experiment wide range of parameters for HOG face detector and setting up the most suitable kernel for Support Vector Machine (SVM) and then, comparing this method with some well-known methods for face detection and identifying the most reliable one. The aim of this study is not providing the best face detector method rather than a try to find out the performance of HOG feature for detecting a face, experimenting different kernels and eventually finding the tuned parameters for HOG descriptors for detecting a face, in this study based on experimental results as shown in Table IV. The HOG + SVM scores the highest value of precision, accuracy, and sensitivity. As 0.8824, 0.9986 and 0.75 respectively compared to Viola-Jones method which scores 0.6512, 0.9973 and 0.7 finally skin color method which scores 0.3968, 0.9947 and 0.625.
Numerical Simulation of Fire Resistance Test for Gas Turbine Component Using Coupled CFD/FEM Approach

The article presents the implementation of CFD/FEM approach for real oil tank of the gas turbine engine for the purposes of prediction of the component behavior under the local impact of a burner jet. The model takes into account heat and mass transfer problems as well as strength problems that are solved using a one way coupled fluid-structure interaction method. Results of the blind test simulation are compared and show good agreement with available experimental data.
Analytical method development and validation for simultaneous estimation of Moxifloxacin Hydrochloride and Ketorolac Tromethamine by using RP-HPLC

The main objectives of the present research were to develop the new method for the simultaneous estimation and validation of Moxifloxacin HCl and Ketorolac Tromethamine in pure form and in pharmaceutical dosage form by RP-HPLC. The chromatogram of Moxifloxacin HCl and Ketorolac Tromethamine was developed through column (Inertsil ODS C18), UV detection at 304 nm at a flow rate of 1.0 ml/min with Buffer (pH 4.0):Acetonitrile:Methanol (50:30:20) V/V as mobile phase. The method was validated by various validation parameters such as accuracy, precision, linearity, specificity as per the ICH guidelines. A linearity range of Moxifloxacin HCl and Ketorolac Tromethamine was found to be 60 to 140 µg/ml and 48 to 112 µg/ml respectively. The retention time of Moxifloxacin HCl and Ketorolac Tromethamine was found to be 2.07 min and 4.06 min respectively. % RSD of retention time and peak areas obtained in system precision for Moxifloxacin HCl was 0.21 and 0.80 respectively and for Ketorolac Tromethamine were 0.90 and 1.06 respectively. The % recovery of standard Moxifloxacin HCl and Ketorolac Tromethamine was found to be 100.18 to 100.08% and 99.97 to 99.93% respectively. The % recovery of Moxifloxacin HCl and Ketorolac Tromethamine in dosage form was found to be 98.73 to 100.92% and 98.10 to 100.77% respectively. This method was simple, accurate, precise, and sensitive. Hence, the developed method was employed for the routine analysis of Tenofovir in the pharmaceutical dosage form.
Direct Determination of Creatinine in Urine and Analysis of Pure Aniline by Extractive Electrospray Ionization Mass Spectrometry

The direct mass spectrometric determination of highly concentrated analytes in human urine was demonstrated using extractive electrospray ionization without sample dilution or complex preparation. By increasing the distance between the extractive electrospray source and ion inlet of the mass spectrometer from 5 millimeters to 15 centimeters, the fraction of free analyte ions and charged microdroplets introduced into the mass spectrometer was substantially reduced. Consequently, detector saturation, instrument contamination, and space charge effects were greatly diminished for the analysis of highly concentrated samples. Under the optimized experimental conditions, pure aniline and creatinine (>1 millimolar) in human urine were directly characterized by extractive electrospray ionization without any pretreatment. The urinary creatinine concentrations from two adults were 424 ± 30 and 635 ± 32 micrograms per milliliter and were in good agreement with those obtained by a spectrophotometric method based on the Jaffe reaction. The results show that extractive electrospray ionization is suitable for the direct determination of highly concentrated analytes or even pure compounds, allowing rapid characterization of samples in the chemical industry and clinical studies.