Weedy rice (Oryza sativa f. spontanea) poses significant challenges to rice production, reducing yield and commercial value. This study investigates the inhibitory effects of root, stem, and leaf extracts from cultivated rice OM5930 (60 days after sowing) on two weedy rice lines, WR19 (short awn) and WR20 (long awn). The objectives were to: (i) identify the most potent plant part for inhibition, (ii) determine the optimal treatment duration, and (iii) assess the resistance of the two weedy rice lines. Results demonstrated that extracts from all OM5930 plant parts suppressed seedling shoot and root growth in both weedy rice lines. Leaf extracts exhibited the strongest inhibition, achieving complete suppression (100%) at 0.3 g/mL across all time points (0, 48, and 96 hours). The 48-hour treatment showed the most stable inhibitory effect. Root and stem extracts displayed lower efficacy, reaching only 60–70% inhibition at the same concentration. WR20 was more susceptible than WR19, with a slight stimulation observed at lower concentrations (0.015 and 0.075 g/mL). The strong allelopathic potential of OM5930 leaf extracts suggests their application as an eco-friendly bioherbicide, reducing dependence on synthetic herbicides, minimizing production costs, and promoting sustainable rice cultivation.

The study involved 24 crossbred bucks (New Zealand White × Local) in a factorial design to assess the impact of semen collection frequency and age on semen quality. Two factors were considered: the age of the bucks (5-6 months for young and 9-10 months for mature) and the frequency of semen collection (daily (Fre-1), every three days (Fre-3), every five days (Fre-5), and weekly (Fre-7)). The study was conducted over 12 weeks. Results from the last 7 weeks indicated that weekly semen collection yielded the best outcomes, with a concentration of 346×10⁶ sperm/mL, 66.7% sperm motility, 70.5% membrane integrity, and 66.8% live sperm rate. Furthermore, semen volume and the number of motile sperm increased as the collection interval increased, with mature bucks (9-10 months) showing better semen characteristics than younger bucks. Younger bucks had smaller testicular dimensions than mature bucks. In conclusion, the optimal semen collection frequency for New Zealand White × Local crossbred bucks was once a week, and the recommended age for semen collection was 9-10 months.

The study investigated the impact of probiotics and vitamins (PV) on the reproductive performance and egg quality of Ac chickens' diet. The experiment was conducted using a completely random design with 250 hens, aged 40-50 weeks, housed in cages. There were 5 treatments, each with 5 repetitions, and 10 hens per repetition. The treatments corresponding to the diets were: Control (BD), C250 (BD + 250 mg PV/kg of feed), C500 (BD + 500 mg PV/kg of feed), C750 (BD + 750 mg PV/kg of feed), and C1000 (BD + 1000 mg PV/kg of feed). The results showed that the highest laying rate (39.2%), yolk index (0.45), albumen index (0.08) and yolk colour (7.6) were in C1000. Although the C750 indicated the lowest FCR (3.78), it had the greatest egg weight (36.4 g/egg) and Haugh unit (82.8). In conclusion, probiotics and vitamins at 1,000 mg/kg diet improved Ac chicken laying rate, FCR, and egg weight.

Diverse starch-based foods have been widely consumed. To keep the products in good quality, preservatives are added. Sodium benzoate is one of the most commonly used food preservatives for starch-based products. As an antimicrobial compound, high concentrations of sodium benzoate in water can pose risks to aquatic indigenous microbial communities. From wastewater samples of three rice noodle facilities, 27 sodium benzoate-degrading bacteria were isolated on minimal mineral medium supplemented with sodium benzoate (50 mg/L). Isolates SB2.1, SB2.2, SB2.4, SB3.10, and SB3.13 demonstrated their best sodium benzoate degradation efficacy in liquid minimal mineral medium containing 1,250, 2,500, and 5,000 mg/L sodium benzoate, quantitatively measured by the spectrophotometric method at 225 nm. Optimal degradation efficacy (>93%) at 1,250 mg/L sodium benzoate was observed when isolates SB2.1, SB2.2, SB2.4, and SB3.10 were grown in a minimal mineral medium at pH 7-9. Notably, SB3.10 exhibited chemotaxis towards sodium benzoate at 24 hours of incubation. Based on 16S-rRNA gene sequencing and biochemical characterization, SB3.10 was identified as Acinetobacter calcoaceticus SB3.10.

This study presents a comparative analysis of state-of-the-art deep learning models–EfficientNetB0, MobileNetV2, and ResNet101–for image classification and content-based retrieval in scientific publications. A dataset of 4,303 images from 11 categories was curated from the Can Tho University Journal of Science and enhanced through tailored data augmentation strategies. The models were fine-tuned using transfer learning with hyperparameters optimised via Grid Search. Features were extracted using GlobalAveragePooling2D, and cosine similarity was combined with the FAISS library for efficient similarity search. Experimental results demonstrate a clear performance-efficiency trade-off: ResNet101 achieved the highest classification accuracy, while EfficientNetB0 and MobileNetV2 offered significant advantages in inference speed. A user-friendly web interface was developed to support practical image retrieval applications. These findings highlight the potential of deep learning in enhancing the management and integrity of scientific image resources.

Human-action recognition aims to identify the actions performed by individuals. Due to the broad spectrum of human activities, action recognition covers a wide range. Among all, fall detection is a critical aspect of surveillance, particularly in environments where individuals are at risk. Throughout the years, several sensors, data types, and classification techniques have been investigated to address this issue. This paper proposes a lightweight fall-detection system that processes image sequences in real time. This system is deployed on an embedded device, specifically the Jetson Nano. Our goal is to construct a comprehensive dataset that accurately detects falls in various lighting conditions. The proposed system is constructed using YOLOv8n-pose, which has been trained to identify people using widely recognized dataset. Our methodology includes the design and implementation of YOLOv8n-pose, data collection, and rigorous testing to ensure the accuracy of real-time fall detection using a surveillance camera. The experimental results show that high detection over 90% accuracy and acceptable timing capabilities are achieved.

This literature review synthesises recent advancements and emerging trends in the field of project management, with a focus on the evolving impact of technology, leadership, and sustainability. Drawing on a wide range of scholarly articles and industry publications, the review explores the foundational principles of project management, such as risk management, leadership effectiveness, and project efficiency, while also highlighting the complexities of applying these practices across various sectors. The integration of cutting-edge technologies, such as artificial intelligence, data analytics, and hybrid methodologies, is identified as a key driver of change in project execution. Furthermore, the increasing emphasis on sustainability and ethics reflects a shift in the industry toward a broader definition of project success, beyond traditional financial outcomes. This review emphasizes the need for continuous adaptation in project management practices and calls for future research to refine leadership strategies, improve technology adoption, and develop more holistic frameworks for assessing project success. The findings underscore the importance of aligning traditional project management principles with the demands of an increasingly complex and fast-evolving global environment.

In this work, ZnAl2O4: Mn4+ phosphor is prepared by the sol-gel method. The phase structure was investigated by X-ray diffraction (XRD), and morphology and element composition were analysed by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), luminescent performance of the phosphor using photoluminescence (PL) spectra, and Raman spectroscopy. The obtained powder shows a red broad emission band peaking at 676 nm and 692 nm, corresponding to the energy transfer of electrons from 2Eg to 4A2g. The Mn4+ concentration is doped at 0.5 mol% into the ZnAl2O4 host lattice. After that, the powder annealed at 1200℃ for 4 hours in the air revealed an average crystallite size of about 52.833 nm and a high emission intensity with (x, y) CIE colour coordinates (0.2705, 0.2741). Therefore, ZnAl2O4: Mn4+ phosphor could be a promising material for solid-state lighting applications.

The survey of plant diversity and vegetation in the Vam Ho Bird Sanctuary and surrounding areas (Ba Tri and Binh Dai districts, Ben Tre province) was conducted in October 2024. The study aimed to build the plant diversity basics for investing and upgrading Vam Ho to the status of a Natural Heritage site. Using transect surveys and sampling, the study recorded 179 species belonging to 55 families of vascular plants. Among them, Azima sarmentosa, Oryza rufipogon, Psilotum nudum were listed in the Vietnam Red Book (2024), Avicennia marina var. rumphiana, Phoenix paludosa, Sonneratia ovata, Ceriops decandra were on the IUCN Red List (2025). In addition, a total of 158 out of 179 recorded species have had at least one of six main use groups: medicine, food, animal/poultry feed, ornamental plants, timber/charcoal/construction materials, and household items/handicrafts. The vegetation was divided into three types: the natural habitat in Vam Ho Bird Sanctuary, the Casuarina equisetifolia coastal plantation, and the estuarine-coastal mangrove forest. The establishment of the Natural Heritage Site will create positive conditions for the activities of habitat conservation and coastal protection, which help to reduce the pressure of environmental degradation on the Ba Lai estuary in the future.

This paper studied the diversity of phytoplankton species at 9 sampling points of aquaculture ponds in Dak Ha, Sa Thay and Kon Plong districts, Kon Tum province (now Quang Ngai province) in 2022–2023. The results recorded 7 phyla, 98 genera, and 142 species, of which 22 genera and 23 species of phytoplankton were present in all 3 sampling periods. The values of the biodiversity index (H’) and the diversity value index (Dv) at 9 sampling points ranged from 2.51–3.66 and 2.39–3.58, indicating that the diversity of phytoplankton in aquaculture ponds is high and very high, respectively. The regulation index (J) ranged from 0.95 to 0.99, indicating that phytoplankton species were evenly distributed at all studied sampling points. The similarity coefficient of species composition of phytoplankton populations at 9 sampling points ranged from 0.43 - 0.85. In water samples collected at 9 study locations, the number of phytoplankton species was negatively correlated with impedance. In particular, at the sampling locations, the main environmental factors such as suspended solids, salinity, and conductivity affecting the cell density of phytoplankton communities had a positive correlation and a negative correlation with impedance.

As English-medium instruction (EMI) programs have expanded rapidly in Vietnam as a result of educational globalisation, more research is needed in this field. This study aims to promote EMI lecturers’ professional development and enhance teaching quality by identifying the needs of content lecturers in Vietnamese higher education, in order to gain a more comprehensive insight into appropriate support and policy development. Data were collected via questionnaires distributed to EMI lecturers (n=33) and in-depth interviews with six participants. The findings show that EMI lecturers required professional development support, particularly in improving their pedagogical competencies and English language proficiency. They also expressed a desire for collaboration with colleagues. In addition, this study identified lecturers' specific needs for institutional support, with particular emphasis on teaching materials and resources. These insights contribute to the existing literature and provide helpful suggestions for supporting EMI lecturers in similar settings.

This study explores the factors influencing students' motivation for online learning at Can Tho University. The research examines five key factors: personal, lecturer-related, institutional, academic, and environmental aspects. A survey was conducted with 892 students across various academic disciplines. The study employed statistical analyses, including Cronbach’s Alpha reliability testing, exploratory factor analysis (EFA), and multiple regression analysis to determine the impact of these factors on students' motivation. The findings indicate that personal and lecturer-related factors have the most significant positive influence, highlighting the importance of self-discipline, time management, and lecturer support. Institutional factors also play a crucial role, particularly in terms of learning infrastructure and support services. However, environmental factors negatively affect motivation, such as poor internet connectivity, financial difficulties, and distractions, which hinder students’ engagement. Additionally, students with higher academic performance and greater online learning experience show stronger motivation. Differences across academic disciplines suggest the need for tailored teaching methods and institutional support. These findings provide insights into enhancing online learning motivation and contribute to policy recommendations improving the quality of online education at Can Tho University.

This study examined how gender and development (GAD) concepts and principles are incorporated into English 10 learning materials using a mixed-methods approach. The examination of lesson plans and self-learning modules through content analysis revealed biases supporting traditional gender roles, such as inadequate representation of women and showing stereotypical gender behaviours. Interviews with English 10 public teachers highlighted diverse strategies they employed, despite limited exposure to GAD concepts, suggesting a lack of comprehensive training in this area. However, teachers still endeavour to integrate these principles into their instruction to foster inclusivity, though challenges persist, such as biases influencing disciplinary measures. The findings of this study highlight the importance of challenging narrow views and promoting inclusive practices in educational materials. This study contributes to the ongoing efforts to promote gender equality and diversity in education highlighted in UNESCO’s Education for All initiative (2003), emphasizing the need for continuous awareness, sensitivity, and proactive integration of GAD principles in educational settings.

This meta-synthesis aimed to determine the technological landscape of English Language Teaching (ELT) in Asia over the past decade. Through meticulous screening of relevant studies, a thematic analysis of 14 qualitative and primary sources revealed a reliance on internet platforms, mobile devices, gadgets, and robots to facilitate effective English instruction. Yet, a critical evaluation of contemporaneity revealed deficiencies in ELT technologies, ranging from source unreliability to technological unfamiliarity, alongside notable strengths such as user-friendliness and timeliness of information. Addressing these shortcomings demands a concerted effort to equip students and educators with the requisite devices and training. Furthermore, fostering a conducive learning environment mandates tailored curriculum enhancements to bolster technical proficiency and the seamless integration of emerging technologies. Collaboration among parents, institutional leaders, and the educational community is paramount for navigating the adoption of new technologies, both within and beyond the traditional classroom. Delineating clear learning objectives, providing adequate skills training, and instituting appropriate curriculum changes are pivotal in harnessing the full potential of technology for English language learning.

This paper aimed to evaluate a parent-teacher partnership project implemented in one laboratory school in Metro Manila. Parent-teacher partnership is a collective effort by parents to work together for the benefit of learners. A project aims to address a particular problem and can be an intervention which ends once it has been implemented and regularly used. Participants are middle-income parents. Convenient sampling was used to identify the participants. After planning and designing a project in support of parent-teacher partnership, it was implemented to equip the parents with the necessary strategies to assist their children in flexible learning. After close collaboration with the parents, the researchers evaluated the project using a survey questionnaire. The results show that the objectives of the project were met, and the content was helpful in supporting parent-teacher partnerships. Also, relevant findings revealed that parents perceived the project as informative, as they gained strategies and tools to support their child's academic learning and were equipped with socio-emotional strategies to manage their child’s socio-emotional needs and to teach them how to navigate the educational technologies used in the school. The results of the study provided insights into revisiting policies to engage parents so they can develop...

The aim of this study was to investigate the antimicrobial activity against Staphylococcus aureus, Cutibacterium acnes, Escherichia coli, and Candida albicans of the ethanol extract and the n-hexane and ethyl acetate extract of the stingless bee Tetragonula sp. propolis. Additionally, the study also identified the stingless bee species based on morphological characteristics and Cytochrome c oxidase subunit I (COI) gene sequence. The antimicrobial activity of three stingless bee propolis extracts showed resistance against all three bacterial S. aureus, C. acnes, and E. coli. At a concentration of 1000 μg/mL, the ethanol extract exhibited the highest resistance, with C. acnes showing a zone of inhibition of 13.33 mm, while the inhibition zones were 11.33 mm for S. aureus and 10.33 mm for E. coli. The Minimum Inhibitory Concentration (MIC) for the three bacterial S. aureus, C. acnes, and E. coli were found to be 30, 50, and 50 μg/mL, respectively. The study identified the presence of polyphenols, flavonoids, aglycones, phenolics, and ketones quantified the total phenolic and flavonoid content, assessed the antibacterial activity of the propolis extract against the three pathogenic bacteria, and provided the foundation for further research.

The application of machine learning models in the analysis of helmet-related images has yielded remarkable results in identifying and classifying helmet-wearing behaviours. Previous research has employed several pretrained models to predict proper or improper helmet use, achieving high accuracy on the Helmet Wearing Image Dataset (2024), a newly introduced dataset designed to enhance classification capabilities. This study aims to improve prediction performance on helmet datasets by leveraging state-of-the-art deep learning models and ensemble techniques. Using ResNet-50, MobileNetV2, and EfficientNet-B0 models, the proposed EnsemHelmet Framework uses a soft voting ensemble to optimise the classification results, achieving an outstanding accuracy of 99.24% on the experimental dataset. The results demonstrate the potential of ensemble learning to achieve high performance. This study not only improves the accuracy of the helmet-wearing recognition system but also highlights the effectiveness of ensemble techniques in optimizing performance on real-world datasets.