EFL TEACHERS’ PERCEPTIONS AND THEIR REPORTED PRACTICES OF ENACTING THE COMMUNICATION AND CULTURE SECTION IN THE NEW ENGLISH TEXTBOOK

The development of globalization and integration requires a modern workforce with 21st-century skills, especially intercultural communicative competence (ICC). Thanks to the National Foreign Language 2020 project, the new English textbooks were introduced to Vietnamese students with the hope prepare them for ICC. Research on how EFL teachers explored the new teaching materials has been made, but previous findings show limitations on EFL teachers’ practices in the communication and culture section. Hence, this descriptive research was conducted to investigate EFL teachers’ perceptions and their reported practices of enacting this section. A mixed-method approach was employed to collect quantitative and qualitative data. Seventy-two EFL teachers in the Mekong Delta responded to the questionnaire and seven of them joined the semi-structured interviews. Results revealed various EFL teachers’ perceptions and high levels of agreement on their practices of four dimensions of ICC. The study also suggested further research should look into students’ perspectives.  Article visualizations

Determination of the content of major chemical components and bioactive compounds and antioxidant ability of Hong Quan (Flacourtia jangomas (Lour.) Raeusch) fruit cultivated in An Giang, Vietnam

Hong Quan (Flacourtia jangomas (Lour.) Raeusch) is a new fruit that has appeared recently and it is cultivated with other orchards or under forest canopy of Tri Ton and Tinh Bien district at An Giang province. Since this fruit has not been popularized in Vietnam, there is a shortage in research about chemical compositions of Hong Quan. Therefore, quantitative analysis of main chemical components, bioactive compounds and antioxidant activity of this kind of fruit need to be carried out to enhance its applications in food. Results showed that Hong Quan fruits contain 76.50% ± 2.56 of moisture, carbohydrate is 24.86% ± 1.54, protein is 9.19% ± 0.49, lipid is 0.68% ± 0.21, total sugar is 10,91% ± 0.88, ash is 1.05% ± 0.08, fiber is 8.39% ± 0.95 and vitamin C is 81.62 ± 3.99 mg/100g. The content of bioactive compounds such as carotenoids, phenolics, tannins, alkaloids, saponins and flavonoids were 9.87 ± 0.40 mg/100g, 456.32 ± 23.81 mgGAE/100g, 944.08 ± 26.31 mgTAE/100g, 586.68 ± 44.56 mgCE/100g, 20.87 ± 2.00 mgSE/100g and 65.95 ± 2.92 mgQE/100g fresh weight respectively. Moreover, antioxidant capacity of extract ethanol from fruit was high level as the free radical scavenging ability (DPPH) at 88.65% ± 1.23, the ability to reduce iron (FRAP) at 15.24 ± 0.26 mM FeSO4/100g and the antioxidant ability index (AAI) at 8.13 ± 0.82. Hong Quan fruit promisingly could be a good source of commercial processing products or cosmetic due to high level of nutrients and functional compounds

CÁC YẾU TỐ ẢNH HƯỞNG ĐẾN QUYẾT ĐỊNH ĐẶT PHÒNG TRỰC TUYẾN CỦA KHÁCH DU LỊCH TRÊN BOOKING.COM TẠI CÁC KHÁCH SẠN 4 SAO Ở THÀNH PHỐ HUẾ

This study aims to identify the factors influencing tourists' online booking decisions on Booking.com at 4-star hotels in Hue City and evaluate the importance of these factors. Data was collected from direct surveys of 175 domestic tourists who booked rooms at 4-star hotels in Hue City via Booking.com. A multiple regression model was used to analyze the factors affecting tourists' online booking decisions. The results indicate that booking decisions are influenced by six factors, including: products and services, pricing - promotions - other benefits, hotel images and information provided, change and cancellation policies, payment, and online reviews. Themost important factor influencing customers' booking decisions is online reviews. Consequently, several recommendations are proposed to assist 4-star hotels in Hue City in enhancing and developing their online business on Booking.com.Nghiên cứu này nhằm xác định các yếu tố ảnh hưởng đến quyết định đặt phòng trực tuyến của khách du lịch trên Booking.com tại các khách sạn 4 sao ở thành phố Huế và đánh giá mức độ quan trọng của các yếu tố. Số liệu được thu thập thông qua khảo sát trực tiếp 175 khách du lịch nội địa đã đặt phòng tại các khách sạn 4 sao ở thành phố Huế trên kênh Booking.com. Phương pháp phân tích hồi quy đa biến được sử dụng để xem xét các yếu tố ảnh hưởng đến quyết định đặt phòng trực tuyến của du khách. Kết quả cho thấy, quyết định đặt phòng chịu ảnh hưởng bởi sáu yếu tố, bao gồm: sản phẩm và dịch vụ, giá cả - khuyến mãi - lợi ích khác, hình ảnh và thông tin khách sạn cung cấp, chính sách thay đổi và hủy phòng, thanh toán và đánh giá trực tuyến. Yếu tố quan trọng nhất ảnh hưởng đến quyết định đặt phòng là đánh giá trực tuyến. Từ đó, một số khuyến nghị được đề xuất nhằm giúp các khách sạn 4 sao ở thành phố Huế cải thiện và phát triển kinh doanh trực tuyến trên Booking.com

A Novel Explainable Artificial Intelligence Model in Image Classification problem

In recent years, artificial intelligence is increasingly being applied widely in many different fields and has a profound and direct impact on human life. Following this is the need to understand the principles of the model making predictions. Since most of the current high-precision models are black boxes, neither the AI scientist nor the end-user deeply understands what's going on inside these models. Therefore, many algorithms are studied for the purpose of explaining AI models, especially those in the problem of image classification in the field of computer vision such as LIME, CAM, GradCAM. However, these algorithms still have limitations such as LIME's long execution time and CAM's confusing interpretation of concreteness and clarity. Therefore, in this paper, we propose a new method called Segmentation - Class Activation Mapping (SeCAM) that combines the advantages of these algorithms above, while at the same time overcoming their disadvantages. We tested this algorithm with various models, including ResNet50, Inception-v3, VGG16 from ImageNet Large Scale Visual Recognition Challenge (ILSVRC) data set. Outstanding results when the algorithm has met all the requirements for a specific explanation in a remarkably concise time.Comment: Published in the Proceedings of FAIC 202

Efek penambahan ekstrak daun mangga arumanis (Mangifera indica l.) pada antibiotik klindamisin dalam menghambat pertumbuhan bakteri Staphylococcus aureus

Staphylococcus aureus termasuk bakteri yang cukup sering dijumpai pada mulut, terutama pada kasus abses periodontal di mana perawatannya memerlukan pemakaian antibiotik. Tingginya angka resisten bakteri Staphylococcus aureus terhadap antibiotik menyebabkan banyaknya dicari pengobatan alternatif menggunakan herbal. Melihat efek penambahan ekstrak daun mangga arumanis (Mangifera indica L.) pada antibiotik klindamisin dalam menghambat pertumbuhan bakteri Staphylococcus aureus. Jenis dari penelitian ini adalah eksperimental laboratorium secara in vitro dengan 25 sampel. Konsentrasi ekstrak daun mangga yang digunakan 25%, 50%, 75%, 100% dan kelompok kontrol. Ekstrak dibuat dengan teknik maserasi dan uji daya hambat dengan metode Kirbi bauer. Hasil dianalisis menggunakan statistik ANOVA, lalu dilanjutkan dengan Post Hoc LSD. Hasil penelitian ini menunjukkan bahwa penambahan ekstrak 50%, 75%, 100% meningkatkan daya hambat terhadap Staphylococcus aureus (p=0,000) dibandingkan kelompok kontrol. Semakin tinggi konsentrasi yang digunakan, maka semakin besar zona hambat yang terbentuk. Sedangkan penambahan ekstrak 25% tidak meningkatkan daya hambat (p=0,618) bila dibandingkan dengan kelompok kontrol. Penambahan ekstrak daun mangga arumanis dengan klindamisin dapat meningkatkan aktivitas antibakteri terhadap Staphylococcus aureus

G-CAME: Gaussian-Class Activation Mapping Explainer for Object Detectors

Nowadays, deep neural networks for object detection in images are very prevalent. However, due to the complexity of these networks, users find it hard to understand why these objects are detected by models. We proposed Gaussian Class Activation Mapping Explainer (G-CAME), which generates a saliency map as the explanation for object detection models. G-CAME can be considered a CAM-based method that uses the activation maps of selected layers combined with the Gaussian kernel to highlight the important regions in the image for the predicted box. Compared with other Region-based methods, G-CAME can transcend time constraints as it takes a very short time to explain an object. We also evaluated our method qualitatively and quantitatively with YOLOX on the MS-COCO 2017 dataset and guided to apply G-CAME into the two-stage Faster-RCNN model.Comment: 10 figure

Enhancing the Fairness and Performance of Edge Cameras with Explainable AI

The rising use of Artificial Intelligence (AI) in human detection on Edge camera systems has led to accurate but complex models, challenging to interpret and debug. Our research presents a diagnostic method using Explainable AI (XAI) for model debugging, with expert-driven problem identification and solution creation. Validated on the Bytetrack model in a real-world office Edge network, we found the training dataset as the main bias source and suggested model augmentation as a solution. Our approach helps identify model biases, essential for achieving fair and trustworthy models.Comment: IEEE ICCE 202

Miliutine A acid, a new cyclofarnesane sesquiterpene from the stems of <i>Miliusa velutina</i>

Six compounds were isolated from the ethyl acetate extract of the stems of Miliusa velutina, including miliutine A acid (1), a new cyclofarnesane sesquiterpenoid; miliutine B methyl ester (2), a cyclofarnesane sesquiterpenoid which was determined the absolute configuration for the first time and four known phenol derivatives (3–6). NMR spectroscopic and mass spectrometry were used for identifying relative configurations. The assignments of the absolute configurations were determined based on Electronic Circular Dichroism (ECD) and NOESY spectra analysis. All six compounds were screened for their in vitro cytotoxic activities against HepG2 cell line using the SRB assay and they showed weak or none activities.</p

LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks

LangXAI is a framework that integrates Explainable Artificial Intelligence (XAI) with advanced vision models to generate textual explanations for visual recognition tasks. Despite XAI advancements, an understanding gap persists for end-users with limited domain knowledge in artificial intelligence and computer vision. LangXAI addresses this by furnishing text-based explanations for classification, object detection, and semantic segmentation model outputs to end-users. Preliminary results demonstrate LangXAI's enhanced plausibility, with high BERTScore across tasks, fostering a more transparent and reliable AI framework on vision tasks for end-users

Preparation, Characterization, and Antibacterial Activity of Silver Nanoparticle-Decorated Ordered Mesoporous Carbon

In this study, Ordered Mesoporous Carbon (OMC) was prepared using resol as a carbon precursor and F127 as a soft template. Small-angle X-ray Diffraction (XRD), Transmission Electron Microscopy (TEM) images, and nitrogen adsorption and desorption isotherms revealed that OMC possessed ordered hexagonal mesostructures (p6m) with an ordered pore size of 3.2nm, a high specific surface area (SBET) of 539m2/g, and a large total pore volume (Vtotal) of 0.44cm3/g. Subsequently, silver nanoparticles synthesized from an aqueous AgNO3 solution using glucose as a reducing agent and starch as a stabilizing agent were decorated on OMC, producing Ag/OMC. XRD analysis revealed that the composite contained silver crystals. In addition, the content and size of silver nanoparticles in Ag/OMC were 0.71wt% (AAS) and around 25-50nm (TEM), respectively. Due to the surface cover of silver nanoparticles, SBET and Vtotal of Ag/OMC slightly decreased to 417m2/g and 0.38cm3/g, respectively. Both agar and broth dilution techniques were used to evaluate the antibacterial activity of the material against Staphylococcus aureus. Ag/OMC with a Minimum Inhibitory Concentration (MIC) of 25.0μg/mL is a potential candidate for use against Staphylococcus aureus