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The lives and learning experiences of high school students are increasingly intertwined with online activities. With the global trend of Education 4.0, equipping students with digital skills is essential, including the capacity for online social-emotional skills. Someone with social-emotional skills knows how to turn social media into a useful tool, providing opportunities for personal development. This study focuses on developing social-emotional competence for high school students in the context of the Education 4.0 trend. The project has developed a learning program consisting of 6 common social-emotional skill themes for both virtual and real environments and implemented a test on 34 students. Using experimental evaluation methods, classroom observation, and quantitative methods were employed to assess the effectiveness of the program. The results indicate a significant improvement in students' social-emotional competence, with an average score post-experiment of 3.7397. Our experimental model also achieved 63.6% of CASEL criteria for organizing social-emotional competence. Therefore, the study has strengthened the findings and achievements in the development of social-emotional competence training in the fields of educational psychology in Vietnam.

Sloshing is the term for the liquid’s internal movement, which is often undesirable in technological processes. This paper aims to provide a solution for suppressing sloshing liquid in a moving cylindrical container. To prevent the negative impact of the sloshing problem, our approach is a combination of generating a desired path, robust control, and output constraints. To begin with, this research introduces a discrete model derived from a nonlinear equivalent mass-spring-damper system. Subsequently, after establishing the flatness of the approximate nonlinear model, we introduce rest-to-rest and time-optimal trajectory planning. We overcome the unmeasurable state variable and disturbance with the Linear Extended State Observer (LESO) algorithm. In addition, to address the challenge of tracking the orbital path, we suggest a control technique Terminal Sliding Mode Control (TSMC), which is well-known for its fast convergence while ensuring global stability. Moreover, to meet the constraints of a practical system, the control barrier function is applied. Lastly, the effectiveness of this control methodology is validated by comprehensive numerical simulations.

This research is dedicated to exploring the photoprotective qualities of extracts from 10 different herbal plants to identify natural ultraviolet (UV) filtering agents suitable for use in cosmetics. The study pinpointed specific plant parts that showed promising photoprotective capabilities, including the fruits of Gardenia jasminoides L., the flowers of Chrysanthemum morifolium Ramat., as well as the leaves of Camellia sinensis L. and Moringa oleifera L. Among these, G. jasminoides extracts stood out for their superior photoprotection. Specifically, G. jasminoides led with an impressive in vitro SPF of 40.8 ± 0.2, with C. morifolium, C. sinensis, and M. oleifera trailing closely. Hence, the extracts were added to the base of the lotion cream to evaluate the stability and photoprotective activity. Additionally, even though natural extracts cannot completely replace conventional UV filters, they have substantially decreased the reliance on physical or chemical UV filters. Thus, this study provides a strong foundation for natural antioxidants' status and potential use for UV filtration.

Abstract Objective Most current wound size measurement devices or applications require manual wound tracing and reference markers. Chronic wound care usually relies on patients or caregivers who might have difficulties using these devices. Considering a more human-centered design, we propose an automatic wound size measurement system by combining three deep learning (DL) models and using fingernails as a reference. Materials and methods DL models (Mask R-CNN, Yolov5, U-net) were trained and tested using photographs of chronic wounds and fingernails. Nail width was obtained through using Mask R-CNN, Yolov5 to crop the wound from the background, and U-net to calculate the wound area. The system’s effectiveness and accuracy were evaluated with 248 images, and users’ experience analysis was conducted with 30 participants. Results Individual model training achieved a 0.939 Pearson correlation coefficient (PCC) for nail-width measurement. Yolov5 had the highest mean average precision (0.822) with an Intersection-over-Union threshold of 0.5. U-net achieved a mean pixel accuracy of 0.9523. The proposed system recognized 100% of fingernails and 97.76% of wounds in the test datasets. PCCs for converting nail width to measured and default widths were 0.875 and 0.759, respectively. Most inexperienced caregivers consider convenience is the most important factor when using a size-measuring tool. Our proposed system yielded 90% satisfaction in the convenience aspect as well as the overall evaluation. Conclusion The proposed system performs fast and easy-to-use wound size measurement with acceptable precision. Its novelty not only allows for conveniences and easy accessibility in homecare settings and for inexperienced caregivers; but also facilitates clinical treatments and documentation, and supports telemedicine.

Abstract Introduction Guided surgery for immediate anterior implants aims to reduce the time required for aesthetic and functional immediate loading. However, the limited surface area of anterior teeth for guide stabilization may affect the accuracy of implant positioning. This in vitro study evaluated the effect of the number of supporting teeth on the accuracy of immediate implants in the maxillary central incisor region. Methods 28 replica implants were inserted into 28 upper jaw models, simulating immediate post-extraction sockets of tooth 11. Based on the number of supporting teeth, the implants were categorized into G1 (four adjacent teeth) and G2 (six adjacent teeth). The planned and actual implant positions were compared using the evaluation module of the implant planning software. Angular and 3D deviations were measured as the primary outcomes. Statistical analysis was performed using the two-sample t-test, with p-values less than 0.05 defined as statistically significant. Results Between group G1 and G2, angular deviation was measured at 4.63 ± 0.71° and 3.59 ± 0.97°, respectively, while the implant apex 3D deviation was 2.08 ± 0.21 mm for G1 and 1.40 ± 0.27 mm for G2. These differences were statistically significant (p = 0.003 and p

Two new zinc(II) complexes, triethylammonium dichlorido[2-(4-nitrophenyl)-4-phenylquinolin-8-olato]zinc(II), (C6H16N){Zn(C21H13N2O3)Cl2] (ZnOQ), and bis(triethylammonium) {2,2′-[1,4-phenylenebis(nitrilomethylidyne)]diphenolato}bis[dichloridozinc(II)], (C6H16N)2[Zn2(C20H14N2O2)Cl4] (ZnBS), were synthesized and their structures were determined using ESI–MS spectrometry, 1H NMR spectroscopy, and single-crystal X-ray diffraction. The results showed that the ligands 2-(4-nitrophenyl)-4-phenylquinolin-8-ol (HOQ) and N,N′-bis(2-hydroxybenzylidene)benzene-1,4-diamine (H2BS) were deprotonated by triethyl-amine, forming the counter-ion Et3NH+, which interacts via an N—H...O hydrogen bond with the ligand. The ZnII atoms have a distorted trigonal–pyramidal (ZnOQ) and distorted tetrahedral (ZnBS) geometries with a coordination number of four, coordinating with the ligands via N and O atoms. The N atoms coordinating with ZnII correspond to the heterocyclic nitrogen for the HOQ ligand, while for the H2BS ligand, it is the nitrogen of the imine (CH=N). The crystal packing of ZnOQ is characterized by C—H...π interactions, while that of ZnBS by C—H...Cl interactions. The emission spectra showed that ZnBS complex exhibits green fluorescence in the solid state with a small band-gap energy, and the ZnOQ complex does exhibit non-fluorescence.

Local energy networks, known as microgrids, can operate independently or in conjunction with the main grid, offering numerous benefits such as enhanced reliability, sustainability, and efficiency. This study focuses on analyzing the factors that influence energy performance in East-West microgrids, which have the unique advantage of capturing solar radiation from both directions, maximizing energy production throughout the day. A predictive pipeline was also developed to assess the performance of various machine learning models in forecasting energy output. Key input data for the models included solar radiation levels, photovoltaic (DC) energy, and the losses incurred during the conversion from DC to AC energy. One of the study’s significant findings was that the east side of the microgrid received higher radiation and experienced fewer losses compared to the west side, illustrating the importance of orientation for efficiency. Another noteworthy result was the predicted total energy supplied to the grid, valued at €15,423. This demonstrates that the optimized energy generation not only meets grid demand but also generates economic value by enabling the sale of excess energy back to the grid. The machine learning models—Random Forest, Extreme Gradient Boosting, and Recurrent Neural Networks—showed superior performance in energy prediction, with mean squared errors of 0.000318, 0.000104, and 0.000081, respectively. The research concludes that East-West microgrids have substantial potential to generate significant energy and economic benefits. The developed energy prediction pipeline can serve as a useful tool for optimizing microgrid operations and improving their integration with the main grid.

Community-oriented education has witnessed an increasing interest in online service-learning opportunities. Digital Learning Companion is an online service-learning project supported by Taiwan's Ministry of Education to give students experiential learning opportunities and practice social responsibility. As part of the initiative, 189 local and international students served as tutors for remote children. A mixed-methods design, including pre- and post-questionnaires and sharing videos, was employed to evaluate its effects on service-learning outcomes. The results revealed that all tutors improved personal competence, interpersonal relationships, and charitable responsibility. However, no significant difference was found in social justice responsibility. Furthermore, significant differences between the international and local tutors were noted in outcomes regarding personal competence, interpersonal relationships, and charitable responsibility, with the mean scores of the international group higher than those of the local one. Conversely, no significant difference was found in social justice responsibility with respect to nationality. The findings highlight the benefits to tutors with respect to personal and interpersonal development and support the implementation of similar service-learning projects.

An augmented reality (AR)-integrated gamification learning approach in an electronics course was developed in this study to help students better understand the concepts while simultaneously increasing their motivation. An experimental study was conducted to examine the effectiveness of the AR-integrated gamification approach on students' learning outcomes and motivation. A total of 29 vocational high school students was divided into two groups. The experimental group experienced AR-integrated gamification while the control group adopted conventional gamification. The results indicated that students in the AR-integrated gamification approach outperformed the conventional gamification group in the psychomotor learning outcomes, but no significant difference was found in cognitive and affective domains between the two groups. Concerning learning motivation, the experimental group only performed better intrinsic goal orientation than the control group while the other categories of motivation were insignificant. To compare the pretest and posttest in each group, the experimental group gained higher posttest scores in all domains of learning outcomes than the pretest scores after the intervention, but the control group only improved cognitive and psychomotor domains. Regarding learning motivation, the proposed approach pointed out the better posttest scores in all components compared to the pretest scores in the experimental group while only the posttest scores of extrinsic goal orientation, task value, and control beliefs about learning were higher than the pretest scores in the control group. The practical implications and recommendations for future work are presented.

Engineering drawing is valuable in capturing geometric features, conveying engineering ideas, and creating a blueprint of the intended product. Engineering students usually perform orthographic projections, imagining a 3D situation and sketching its 2D representation. That requires imagination and mental visualization, determined by the learner's spatial ability. This study proposes the infusion of an AR stereogram mobile application into an engineering drawing course to establish how it influences learning outcomes among students with different spatial abilities. The quantitative experimental study involved two mechanical engineering classes in northern Taiwan, N = 69 first-year vocational high schoolers. Statistical analysis revealed that the experimental group with high spatial ability recorded better results and excellent drawing skills. Bloom's taxonomy categorization reported that spatial ability influenced "understanding" and "applying" levels, with the strongest effect on "understanding." Although no significant interaction existed, learning outcomes were highly affected by spatial ability in "understanding" and "applying" levels and AR in the overall performance. The findings and discussions show AR holds great potential to enhance students' spatial ability for real-time visualization and enables better concept comprehension by improving their understanding of engineering topics. Future studies should consider these implications in creating effective and immersive learning environments for different courses in engineering education.

This paper investigates enhancing the operation characteristics and reducing pollutants of a simulated biogas (65 % CH4 and 35 % CO2) engine by the implementation of HHO gas. The simulation results showed that the appearance of HHO as an additive in charged air will shorten the ignition delay and combustion duration. HHO combustion lasts 40°, shorter than 44.5° without HHO. The RoHR peaks at 41.68 J/deg at 375 deg CA with HHO, compared to 34.52 J/deg without it. The maximum pressure rise is 1.90 bar/deg for gasoline, 0.97 bar/deg for simulated biogas, and 1.08 bar/deg for HHO-enriched biogas. The peak cylinder pressure was slightly raised from 42.12 bar to 45.73 bar with HHO aid. A system for supplying HHO to the intake manifold of the test engine was devised in a pilot model to conduct experiments. In comparison to the original gasoline engine, the average brake power of the biogas-fueled engine degraded by 39.1 % under full throttle conditions. The coefficient of variation of speed (COVspeed) under idling conditions increased from 0.31 % for gasoline to 1.58 % for the simulated biogas engine. However, as a small volume of HHO was presented in charge air, the biogas-fueled engine's performance and fuel economy improved by 7.86 % and 4.5 % at full-throttle conditions. Engine stability enhanced significantly as the COVspeed reduced from 1.58 % to 0.47 % with the HHO additive. The engine's exhaust emissions changed remarkably when operating with the HHO additive. Specifically, CO was reduced by 20.2 % on average at fully operated throttles and 6.5 % to 19.4 % at a constant speed of 4200 rpm; HC was moderately decreased 14.2 % on average at full throttle conditions and by 18.6 % on average at a constant speed of 4200 rpm; NOx emissions increased marginally from 9.4 % to 33.4 % at full throttle conditions and an average increase of 35.5 % at a constant speed of 4200 rpm.

Smart wearable devices that harvest energy from ambient sources, such as body heat, are gaining significant attention due to their potential in diverse applications. Thermoelectric (TE) materials, which convert thermal energy to electrical power, are critical for these devices, yet achieving both high TE performance and mechanical flexibility remains a significant challenge. Here, we investigate the TE properties of the penta-InP 5 monolayer, a novel two-dimensional material, using first-principles calculations integrated with machine learning potentials. We show that penta-InP 5 achieves a remarkable figure of merit, with values of 0.51 and 0.42 for hole and electron doping, respectively, at room temperature. Additionally, the material demonstrates remarkable mechanical properties, with an in-plane stiffness of 52 N/m and a fracture strain of 23% for the uniaxial strain. These findings suggest that penta-InP 5 is a promising candidate for flexible, high-performance TE applications, advancing the potential of wearable energy-harvesting devices. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore the ability of the combination of Theory of Reasoned Action (TRA) and Information Adoption Model (IAM); to predict and explain how Firm-Generated Content (FGC) and User-Generated Content (UGC) influence the intention to use telehealth services in Vietnam. A total of 751 citizens participated in this study based on the non-probability convenience sampling method. They completed the survey questionnaires, which consisted of 31 items rated on a 5-point Likert scale. The authors analyzed the quantitative data by using structural equation modeling. The results from SEM demonstrated the positive relationships in the proposed research model. This study adds to existing research on how FGC and UGC affect citizen intentions, particularly within the healthcare industry. Based on the study findings, the authors propose several recommendations for the application of FGC and UGC in telehealth services offered by hospitals and healthcare facilities.

Introduction. In recent years, unmanned aerial vehicles (UAVs) have been a rapidly advancing field. In all areas of UAV application, positioning accuracy is of particular importance. For outdoor environments, satellite navigation systems (such as GPS) are always the method of choice. However, for indoor environments, GPS signal weakening becomes a serious obstacle for determining the UAV location. A number of studies have been carried out to develop various indoor positioning technologies that meet the criteria of compactness and light weight, thus suitable for small aircrafts, including optical flows, inertial measurement systems, ultrasound, etc. However, there is a lack of comparative studies reviewing indoor positioning technologies for autonomous UAVs. The existing reviews fail to provide a comprehensive assessment of such technologies and their operational principles according to the main criteria. In this connection, this paper aims to review modern indoor positioning technologies and their operational principles, conducting evaluation according to such criteria as accuracy, operating range, cost. The assessment of promising machine vision-based technologies is carried out.Aim. To classify modern indoor navigation technologies for UAVs; to assess the technologies under consideration according to various criteria.Materials and methods. The current technologies for UAV indoor positioning were classified by the signal type used for connection and their capability to process information without external signals. The technologies were assessed according to the following criteria: accuracy, operating range, cost, as well as their advantages and disadvantages.Results. А classification and evaluation table of UAV indoor positioning technologies is proposed; a review of the current developments in the field is given.Conclusion. A review of UAV indoor positioning technologies has been carried out. In addition, the prospects of machine vision-based technologies are outlined.

Abstract Background The mortality risk of co-infections/secondary infections (CoI/ScI) is under-reported in patients with non-critical COVID-19, leading to the under-management of CoI/ScI and publication bias in the medical literature. We aimed to investigate the association between CoI/ScI and mortality in patients hospitalised with mild-to-severe COVID-19. Methods We conducted a retrospective cohort study at a COVID-19 treatment hospital in Vietnam and collected all eligible medical records, with CoI/ScI status as the exposure (non-CoI/ScI and CoI/ScI, with the latter including nature of pathogen [bacterial, fungal, or bacterial + fungal] and multidrug-resistance pathogen [no MDRp or ≥ 1 MDRp]). The outcome was all-cause mortality, defined as in-hospital death by all causes or being discharged under critical illness. We used time-dependent analysis to report rates of mortality with 95% confidence intervals (95% CI, Poisson regression) and hazard ratios (HR) with 95% CI (Cox proportional hazards regression with Holm’s method for multiplicity control). Results We followed 1466 patients (median age 61, 56.4% being female) for a median of 9 days. We recorded 387 (26.4%) deaths (95/144 [66.0%] in the CoI/ScI group and 292/1322 [22.1%] in the non-CoI/ScI group). Adjusted mortality rates (per 100 person-days) of the CoI/ScI (6.4, 95% CI 5.3 to 7.8), including bacterial (8.0, 95% CI 7.2 to 8.9), no MDRp (5.9, 95% CI 4.8 to 7.4), and ≥ 1 MDRp (9.0, 95% CI 8.2 to 10.0) groups were higher than that of the non-CoI/ScI group (2.0, 95% CI 1.8 to 2.2). These corresponded to higher risks of mortality in the overall CoI/ScI (HR 3.27, 95% CI 2.58 to 4.13, adjusted p

The landscapes in the Hinh River Basin are crucial and highly sensitive to climate change for the coastal province of Phu Yen and the entire south-central coastal region of Vietnam, offering vital environmental services to its downstream areas. Hinh River Basin has a rich system of rivers and streams and abundant surface water resources. However, it remains one of the region's top localities at risk and a very vulnerable region. This study aims to evaluate the changes in landscape (LC) over 10 years (2010-2023) and predict LC over the next six years using machine-learning (ML) algorithms on Google Earth Engine. To achieve these study goals, we establish: (i) potential environmental fragility (PEF) levels based on: terrain slope; geological domains; river hierarchy; percentage of sand in soil; annual mean precipitations; and (ii) emergent environmental fragility (EEF) levels through the addition of LC parameter to model. The methodology includes integrating the Analytic Hierarchy Process (AHP) into a Geographic Information System (GIS). Results show that three LC types (water, annual industrial crop, forest) are related to extremely high EEF. The predictive model suggests that, by 2030, the forest and annual industrial crop LCs in the study area will increase by around 20%. The analysis results show that there has been an increase in the area of planted forests, which can confirm the futher effectiveness of agricultural, forestry, afforestation and forest protection programmes in the study area (Plan for the implementation of forestry development strategy for the period 2021-2030, with a vision to 2050, Phu Yen Province, No 126/KH-UBND 13/7/2021; and Decision on the approval of the project for planting 15 million trees in Phu Yen Province for the period 2021-2025, No 1646/QĐ-UBND 16/11/2021).

Abstract Utilizing steel slag aggregate (SA) as a substitute for river sand in 3D concrete printing (3DCP) has emerged as a new technique as natural resources become increasingly scarce. This study investigates the feasibility of using steel slag (SS) as fine aggregate for 3DCP. Ninety mixtures with varying steel slag aggregate-to-cement ratios (SA/C), water-to-cement ratios (W/C), and silica fume (SF) contents were designed to study the workability and compressive strength of the 3D-printed concrete. Additionally, the actual components were printed to evaluate the printability of these mixtures. The experimental results indicate that it is feasible to fully employ SA in concrete for 3D printing. Mixtures with slump values ranging from 40 to 80 mm and slump flow values varying from 190 to 210 mm are recommended for 3D printing. The optimal mix is determined to have SA/C and W/C ratios of 1.0 and 0.51, respectively, and an SF content of 10% by cement weight. A statistical approach was utilized to construct the prediction models for slump and slump flow. Moreover, to predict the plastic failure of the 3D-printed concrete structure, the modified prediction model with an SA roughness coefficient of 4 was found to fit well with the experimental data. This research provides new insights into using eco-friendly materials for 3D concrete printing.

Infectious bursal disease is a highly contagious and economically devastating disease in the poultry industry worldwide caused by Infectious bursal disease virus (IBDV). However, the data on epidemiological and molecular characteristics of the IBDV outbreak in broiler flocks in the Mekong Delta of Vietnam is unclear. Herein, the epidemiological data of IBDV–positive flocks over a period of 2015–2018 were recorded and the hypervariable region of the VP2 gene of IBDV was amplified to analyze the local phylogeny. The current investigation showed that the overall morbidity and mortality rates of IBDV–positive flocks were 45% and 4.81%, respectively. The IBDV–positive birds occurred clinical signs and macroscopic findings involved with the very virulent (vv) IBDV outbreak. Epidemiological results revealed that IBDV was frequently infected in broiler flocks at 12–42 days, and birds belonging to Tau Vang and Binh Dinh breeds were more sensitive to IBDV. Also, the morbidity rate of IBDV was dramatically decreased in the open farming system. Flocks with complete vaccination significantly dropped morbidity in comparison with other groups. Regarding phylogenetic analysis, all identified IBDV sequences clustered in the same branch of vv phenotype and closely homology with prior strains circulated in Vietnam and other countries. These findings first indicated the epidemiological characteristics of the IBDV–positive broiler flocks in the Mekong Delta and highlighted the IBDV strain circulating in this region.

Background The identification of idiopathic inflammatory myopathies (IIMs) requires a comprehensive analysis involving clinical manifestations and histological findings. This study aims to provide insights into the histopathological and immunohistochemical aspects of IIMs. Methods This retrospective case series involved 56 patients diagnosed with IIMs at the Department of Pathology, University of Medicine and Pharmacy at Ho Chi Minh City, from 2019 to 2023. The histology and immunohistochemical expression of HLA-ABC, HLA-DR, C5b-9, Mx1/2/3, and p62 were detected. Results We examined six categories of inflammatory myopathy, including immunemediated necrotizing myopathy (58.9%), dermatomyositis (DM; 23.2%), overlap myositis (8.9%), antisynthetase syndrome (5.4%), inclusion body myositis (IBM; 1.8%), and polymyositis (1.8%). The average age of the patients was 49.7 ± 16.1 years, with a female-to-male ratio of 3:1. Inflammatory cell infiltration in the endomysium was present in 62.5% of cases, perifascicular atrophy was found in 17.8%, and fiber necrosis was observed in 42 cases (75.0%). Rimmed vacuoles were present in 100% of cases in the IBM group. Immunohistochemistry showed the following positivity rates: HLA-ABC (89.2%), HLA-DR (19.6%), C5b-9 (57.1%), and Mx1/2/3 (10.7%). Mx1/2/3 expression was high in DM cases. p62 vacuole deposits were noted in the IBM case. The combination of membrane attack complex and major histocompatibility complex I helped detect IIMs in 96% of cases. Conclusions The diagnosis of IIMs and their subtypes should be based on clinical features and histopathological characteristics. Immunohistochemistry plays a crucial role in the diagnosis and differentiation of these subgroups.

Background: Intestinal parasitic infections (IPIs) remain a significant public health challenge and a neglected disease in many parts of Asia, contributing to morbidity and mortality, particularly in vulnerable populations. Despite the potential of vaccines to reduce the burden of these neglected IPIs, little is known about the public's willingness to be vaccinated against these infections. Objective: This study aimed to assess the general population's knowledge, symptom experiences, and willingness to vaccinate against IPIs across six countries: Malaysia, Vietnam, India, Pakistan, and China. Materials and methods: A cross-sectional online survey was conducted between June and December 2023 across six countries in Asia region. Participants completed a self-administered online questionnaire that assessed demographic information, knowledge of IPIs, symptom experiences, and willingness to receive a vaccine against IPIs for themselves and their children. Univariate and multivariable logistic analyses were performed to determine the factors related to vaccination the willingness. Results: A total of 5470 complete responses were received. The highest proportion of individuals willing to receive the vaccine was in India (86.1 %), followed by China (80.8 %) and Pakistan (75 %), with Vietnam having the lowest proportion at 50.1 %. For child vaccination, China had the highest willingness (83.3 %). A higher knowledge score was significantly associated with increased willingness to be vaccinated [adjusted odds ratio (aOR)= 1.91, 95 % CI: 1.70–2.15]. Additionally, a higher symptom experience score was significantly associated with greater vaccination willingness (aOR=1.71, 95 % CI: 1.50–1.94). Females residing in urban-suburban areas showed significantly higher vaccination intentions. The willingness to vaccinate children against IPIs closely mirrored the trends observed in self-vaccination willingness, with knowledge being the only factor significantly associated with the willingness to vaccinate children. Conclusion: The study underscores the importance of enhancing educational efforts regarding neglected IPIs and vaccination, particularly when vaccines are available and recommended.