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The influence of Michigan leadership behaviors in organizational variables has been conducted in the Western context. However, limited studies have been conducted in the Vietnam context, particularly in the primary school sector. This study aims to examine the impact of Michigan leadership behaviors on organizational citizenship behaviors (OCBs) in Vietnamese primary schools. In addition, this research aims to challenge the mediating role of organizational justice (OJ) and person-organization fit (POF) in the relationship between Michigan leadership behaviors and OCBs. A total of 282 responses were collected from various primary schools in Vietnam. Exploratory factor analysis, confirmatory factor analysis, and linear regression analysis were used to answer the research question. Findings partially supported our hypotheses as two Michigan leadership dimensions significantly influence OCBs, and OJ mediates the relationship between relationship-oriented leadership behavior (ROL) and OCBs. This study opens the main gaps in the current leadership studies, including the influence of Michigan leadership behaviors on OCB, its role in promoting OJ, and the underlying mechanism through which Michigan leadership behaviors contribute to OCB with the mediation of OJ.

Abstract In the era of industry 4.0 and the widespread use of digital devices, the number of cyber attacks poses an escalating and diverse threat, jeopardizing users' online activities. Intrusion detection systems (IDS) emerge as pivotal solutions, playing a crucial role in detecting anomalous signals within network systems. To counter novel attack patterns, IDS systems require periodic rule updates for effective identification of unusual signals. Typically, these policies are updated based on rule‐based or deep learning algorithms to enhance detection performance. However, the insufficient number of labeled samples remains a challenge for real‐world deployment. In this article, an automated labeling method is presented that has shown high effectiveness, requiring minimal hardware resources, and applicable to IDS systems. Additionally, the approach utilizes transfer learning combined with attention mechanisms to boost the efficiency of abnormal signal detection. The results from the approach are compared with those of a reference model, illustrating an overall improvement of nearly 10% in our model's performance compared to the reference model. This underscores the effectiveness of automating rule adjustments for IDS, contributing significantly to reducing associated financial costs. The research addresses the challenges in deploying IDS in real‐world scenarios and provides a valuable contribution to enhancing cyber threat detection capabilities. A preprint has previously been published [11].

Abstract Exposure to ionizing radiation can induce genetic aberrations via unrepaired DNA strand breaks. To investigate quantitatively the dose–effect relationship at the molecular level, we irradiated dry pBR322 plasmid DNA with 3 MeV protons and assessed fragmentation yields at different radiation doses using long-read sequencing from Oxford Nanopore Technologies. This technology applied to a reference DNA model revealed dose-dependent fragmentation, as evidenced by read length distributions, showing no discernible radiation sensitivity in specific genetic sequences. In addition, we propose a method for directly measuring the single-strand break (SSB) yield. Furthermore, through a comparative study with a collection of previous works on dry DNA irradiation, we show that the irradiation protocol leads to biases in the definition of ionizing sources. We support this scenario by discussing the size distributions of nanopore sequencing reads in the light of Geant4 and Geant4-DNA simulation toolkit predictions. We show that integrating long-read sequencing technologies with advanced Monte Carlo simulations paves a promising path toward advancing our comprehension and prediction of radiation-induced DNA fragmentation.

Abstract Background Breastfeeding is the biological norm for feeding infants and young children. When mothers’ breastmilk is unavailable, donor human milk (DHM) from a human milk bank (HMB) becomes the next option for small vulnerable newborns. A comprehensive cost analysis is essential for understanding the investments needed to establish, operate, and scale up HMBs. This study aims to estimate and analyze such costs at the first facility established in Vietnam. Methods An activity-based costing ingredients (ABC-I) approach was employed, with the cost perspective from service provision agencies (specifically, the project conducted at Da Nang Hospital for Women and Children and Development Partners). Estimated financial costs, based on actual expenditures, were measured in 2023 local currency and then converted to 2023 US dollars (USD). We examined three scenarios: 1) direct start-up costs + indirect start-up costs + implementation costs, 2) direct start-up costs + implementation costs, and 3) capital costs + implementation costs over the 6.5 years of operation. Results The total start-up cost was USD 616,263, with total expenditure on direct activities at USD 228,131 and indirect activities at USD 388,132. Investment in equipment accounted for the largest proportion (USD 84,213). The monthly costs of Da Nang HMB were USD 25,217, 14,565, and 9,326, corresponding to scenarios 1, 2, and 3, respectively. Over HMB's 6.5 years of operation, on average, the unit costs were USD 166, USD 96, and USD 62 for DHM received and USD 201, USD 116, and USD 74 for pasteurized DHM meeting specified criteria in the corresponding scenarios. Unit costs were highest in the initial six months, decreased, and reached their lowest levels after a year. Then, the unit costs experienced an increase in late 2020 and early 2021. Conclusion Although the unit cost of DHM in Da Nang HMB is comparable to that in certain neighboring countries, intentional measures to reduce disposal rates, improve HMB efficiency, motivate more community-based donors, and establish an HMB service network should be implemented to lower costs.

Motors play a crucial role in production systems. However, not everything always goes smoothly, and motor failures are one of the common challenges in the production process. Misalignment of the drive shaft is a frequent motor fault caused by improper installation or damage to machine components. This study proposes the design of a monitoring and fault diagnosis model for DC motors, which includes: (i) a PID controller for motor speed control; (ii) a vibration signal acquisition unit; and (iii) a motor monitoring unit via Blynk and signal processing for fault diagnosis. In the model, motor faults are classified using a convolutional neural network (CNN) based on analog signals that have been transformed to the frequency domain and denoised. Experimental results demonstrate that classification using the convolutional neural network is highly accurate and stable.

Abstract Antimicrobial resistance (AMR) poses a serious threat to the clinical management of typhoid fever. AMR in Salmonella Typhi (S. Typhi) is commonly associated with the H58 lineage, a lineage that arose comparatively recently before becoming globally disseminated. To better understand when and how H58 emerged and became dominant, we performed detailed phylogenetic analyses on contemporary genome sequences from S. Typhi isolated in the period spanning the emergence. Our dataset, which contains the earliest described H58 S. Typhi organism, indicates that ancestral H58 organisms were already multi-drug resistant (MDR). These organisms emerged spontaneously in India in 1987 and became radially distributed throughout South Asia and then globally in the ensuing years. These early organisms were associated with a single long branch, possessing mutations associated with increased bile tolerance, suggesting that the first H58 organism was generated during chronic carriage. The subsequent use of fluoroquinolones led to several independent mutations in gyrA. The ability of H58 to acquire and maintain AMR genes continues to pose a threat, as extensively drug-resistant (XDR; MDR plus resistance to ciprofloxacin and third generation cephalosporins) variants, have emerged recently in this lineage. Understanding where and how H58 S. Typhi originated and became successful is key to understand how AMR drives successful lineages of bacterial pathogens. Additionally, these data can inform optimal targeting of typhoid conjugate vaccines (TCVs) for reducing the potential for emergence and the impact of new drug-resistant variants. Emphasis should also be placed upon the prospective identification and treatment of chronic carriers to prevent the emergence of new drug resistant variants with the ability to spread efficiently.

In Vietnam's rapidly expanding e-commerce landscape, there is a critical need for advanced tools that can effectively analyze customer feedback to boost satisfaction and loyalty. This paper introduces a two-step predictive framework merging deep learning and traditional machine learning to analyze Vietnamese e-commerce reviews. Utilizing a dataset of 10,021 reviews on Tiki, Shopee, Sendo, and Hasaki between 2015 and 2023, the framework first employs fine-tuned deep learning models like BERT and Bi-GRU to extract aspect-based sentiments from reviews, tailored for the nuances of the Vietnamese language. Subsequently, machine learning algorithms like XGBoost predict customer satisfaction by integrating sentiment analysis with e-commerce data such as product prices. Results show BERT and Bi-GRU yield over 70% sentiment accuracy, while XGBoost achieves 80%+ satisfaction prediction accuracy. This framework offers a potent solution for discerning customer sentiments and enhancing satisfaction in Vietnam's dynamic e-commerce landscape.

In this study, various environmentally friendly approaches such as microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE) and enzyme-ultrasound assisted extraction (EUAE) were investigated to simultaneously separate polysaccharides and polyphenols from mangosteen fruit peels (MPs). The yield of polysaccharides (PSY) and total phenolic content (TPC) were computed to compare the efficiency among methods. The chemical structure through Fourier-transform infrared (FTIR) spectrophotometry of the extracted polysaccharides as well as the antioxidant properties of the phenolic extracts were also determined. The result reveals that EUAE at the optimal condition (enzyme content of 6.6 U/g, enzymatic incubation time of 60 min, pH of 5.0 and ultrasonic duration of 30 min) provided much higher PSY (32.65%) and TPC of (107.8 mg gallic acid/ g of dry weight of sample) than MAE and UAE. The FTIR spectrum of the EUAE polysaccharides were remarkably distinct with those of MAE and UAE ones, indicating the differences in chemistry of the polysaccharides to be extracted. The findings of the study indicate that the polysaccharides and polyphenols from MPs by EUAE treatment can be used as natural ingredients in pharmaceutical and functional food formulations.

The Russian economic space is characterised by a significant differentiation in the levels of socio-economic development of the country's various regions, which manifests itself in natural, territorial, socio-cultural, economic, political and other aspects. The results of socio-economic differentiation are unique regional socio-economic systems, which necessitates the formation of individual approaches to managing their development. Therefore, management decisions made at the federal centre, as well as by regional authorities, affect the activities of economic entities in the regions and the population's level of well-being in different ways. Social security is an integral element of the high quality of life of the population and is largely the basis for improving the economic status of the region, increasing the value of human capital. Thus, it is necessary to develop methods and tools for ensuring the social safe development of regional socio-economic systems, considering the specific characteristics of each region. From these perspectives, we can discuss the stability and social performance of the regional economy. Despite a broad scientific background, the factors contributing to the development and the results of regional socio-economic systems, considering the need for social security, have not been examined. The present research aims to fill this gap by developing a management model for the social and safe development of Russia's regions, using the city of St Petersburg as the case study.

This paper provides a novel and applicable work that builds a real system for disinfecting the air and surfaces of the environment in a hospital room, with a non-contact measurement system for supporting contagious disease treatments in hospitals. The system is built on an intelligent mobile robot system that operates autonomously in a simulated real treatment room. The research team uses a new positioning algorithm. It is a combination of data from the Lidar sensor, encoder, and Extended Kalman filter. The program that applies segmentation and image feature extraction algorithms is developed to meet requirements of real-time environment mapping in the room. Control algorithms for moving and avoiding obstacles are also proposed. Next, techniques for collecting health data including patient identification, body temperature, and blood oxygen index via wireless sensor network are also mentioned in the article. Analysis and experimental results show qualified outcomes and promise. The main contribution of the paper can be listed as follows. • Design and build a new CEE-IMR, an intelligent mobile robot that can regconize patients, guide and lead them walking in hospitals, especially keep a safe distance avoiding contagious deseases. • A novel framework for controlling the robot is proposed. The robot can move flexible, avoid obstacles, etc. based on advanced control algorithms. A new control mechanism is also proposed. • Methods of collecting data and processing medical data to support either patients or doctors to improve the effecency in hospitals in contagious disease management.

Abstract This study aims to investigate the effect of organically modified zirconium dioxide nanoparticles (m-Zr[O.sub.2] NPs) on the mechanical properties, morphology, and weather stability of fluoroethylene/vinyl ether copolymer (FEVE). To [...]

The concept of graduate employability has gained great prominence in international education. However, there still exists a gap in sexual orientation discrimination in graduate employability among transgender and queer (TQ) international students. In our qualitative study investigating graduate employability of transgender and queer students graduating from Australian and Canadian institutions, we have interviewed 14 international graduates with transgender and queer identity regarding their perceptions of sexual orientation and recruitment discrimination at the workplaces. Utilizing intersectionality as a conceptual framework, we have studied employability-related problems that these marginalized students with their foreigner identities have experienced in the labor market. The findings will be around the social, cultural, and political impacts of Canadian and Australian working and recruitment environments on the varying extent of discrimination, namely local attitudes toward queer and transgender international graduates, the manifestation of antidiscrimination laws, and the extent to which employers value stereotypically male heterosexual personality traits. [The page range cited on the .pdf (p152-) is incorrect. The correct page range is p153-160.]

Accurate and robust pedestrian detection is fundamental for indoor robotic systems to navigate safely and seamlessly alongside humans in spatially constrained, unpredictable indoor environments. This paper presents a novel method, IRBGHR-PIXOR, a detection framework specifically engineered for pedestrian perception in indoor mobile robots. This novel approach employs an enhanced adaptation of the cutting-edge PIXOR model, integrating two pivotal augmentations: a remodeled convolutional backbone leveraging Inverted Residual Blocks (IRB) in unison with Gaussian Heatmap Regression (GHR), as well as a Modified Focal Loss (MFL) function to tackle data imbalance issues. The IRB component notably bolsters the network’s aptitude for processing intricate spatial representations generated from sparse 3D LiDAR scans. Meanwhile, integrating GHR further elevates accuracy by enabling precise localization of pedestrian subjects. This is achieved by modeling the probability distribution and predicting the central location of individuals in the point cloud data. Extensively evaluated on the large-scale JRDB dataset comprising intense scans from 16-beam Velodyne LiDAR sensors, IRBGHR-PIXOR accomplishes exceptional results, attaining 97.17% Average Precision (AP) at the 0.5 IOU threshold. Notably, this level of accuracy is achieved without significantly increasing model complexity. By enhancing algorithms to overcome challenges in confined indoor environments, this research paves the way for safe and effective deployment of autonomous technologies once encumbered by perceptual limitations in human-centered spaces. Nonetheless, evaluating performance in diverse edge cases and integration with complementary sensory cues promise continued progress. The developments contribute towards the vital capacity of reliable dynamic perception for next-generation robotic systems coexisting in human-centric environments.

The growth of last-mile delivery in developing countries is featuring the important contribution of crowdshippers. Therefore, exploring the factors affecting the intentions to stay in jobs of the crowdshippers is of great significance to maintain and sustainably develop the last-mile delivery service. Based on the Social Exchange Theory, we hypothesize that benefits (economic benefits, professional reputation, and job autonomy) and costs (risks and stress at work) have an effect on crowdshippers’ intentions to continue participating in last-mile delivery service in Vietnam. We also look for differences in motivations to stay in job between full-time and part-time workers. Survey data from 428 crowdshippers were analyzed using SmartPLS. The research findings indicate that economic benefits and work autonomy (benefits) have positive influences on intention to continue participating in crowd logistics, while risks and job stress (cost) have negative effects on the intention of crowsdhippers to continue their work. In addition, research findings also uncover that differences in motivation (perception of benefits and costs) to stay in job between full-time and part-time workers also affect their intentions. Although reputation did not show a significant impact on the crowdshippers’ intentions to continue participating in crowd logistics, it was discovered that reputation has a positive effect on full-time crowdshippers’ intentions to continue working. Based on the findings of this study, we recommend that businesses increase benefits and reduce costs in job to sustain and increase the continued participation in last-mile delivery.

Transmembrane protein 119 (TMEM119) is a recently identified microglia marker that is not expressed by other immune cells. Using CRISPR/Cas9 technology, we introduced enhanced green fluorescence protein (EGFP), into the H9 WA-09 human embryonic stem cell line, directly before the TMEM119 stop codon. Sanger sequencing confirmed successful insertion of the EGFP sequence. The newly created cell line expressed a normal morphology and karyotype, several pluripotency markers, and the ability to differentiate into all three germ layers. H9-TMEM119-EGFP can be used to provide a deeper understanding of the role of TMEM119 in microglia by monitoring its expression under different experimental conditions.

This study presents an analysis based on data collected via questionnaire, surveying Gen Z customers using food delivery applications in Vietnam. The purpose of the original research was to investigate factors influencing Gen Z customers' decision to continue using the applications. The data set presented in this paper includes 361 valid responses that were collected by convenience sampling method from Hanoi and Hochiminh City, which are the two most potential regions of e-commerce transactions in Vietnam. After being collected, sorted, and filtered, the data was calculated by SPSS 22 and AMOS 23 software to extract descriptive analysis, Cronbach's Alpha, and confirmatory factor analysis (CFA). The calculation results indicated that this data set ensures reliability, convergent, and discriminant validity, which can serve as a good reference for future studies.

Hand-raising gesture is one of the most popular signs of communication, whose frequency is related to the classroom’s atmosphere, the attractiveness of the subject, and the level of interactions between students and teachers. However, automatic hand-raising gesture detection and recognition remains still a challenging problem mainly due to low hand resolution, hand occlusion, various backgrounds, and viewpoint changes. While majority of the existing methods focus on static hand-raising posture detection, in this paper, we propose a framework for dynamic hand gesture recognition from classroom videos consisting of two main stages: hand posture detection and dynamic hand gesture recognition. In hand posture detection stage, we extend the previous work by adding relative position-aware in non-local network. After detecting the hand-raising posture on static pixels, which in turn accelerates the performance images, at the dynamic hand gesture recognition stage, we incorporate object detection and tracking to associate the hand-raising detection results at consecutive frames to supplement the missing detection due to the occlusion issue and obtain hand-raising gesture recognition at the event level. The experimental results show that the proposed method outperforms three benchmark models for static hand posture detection that are Faster-RCNN, Libra-RCNN, and Libra-RCNN+RDA on our dataset with the gains obtained for mAP being 7.68%, 5.76%, and 0.35% higher, respectively. In terms of event-level recognition results, the proposed method achieves the value of frame-wise accuracy, temporal_IoU, F1-score@0.3, and Levenshtein-score are 90.0%, 84.4%, 83.2%, and 84.3%, respectively. The code and dataset used in the paper will be made publicity available for research community.

Background: Appendiceal neuroendocrine tumors (NETs) rank as the third most frequent neoplasm affecting the appendix, originating from enterochromaffin cells. This study aims to evaluate the influence of various prognostic factors on the mortality rates of patients diagnosed with NETs of the appendix. Methods: Conducted retrospectively, the study involved 3346 patients, utilizing data sourced from the Surveillance, Epidemiology, and End Results (SEER) database. Our analysis centered on investigating demographic characteristics, clinical features, overall mortality (OM), and cancer-specific mortality (CSM) among the cohort. Variables showing a p-value < 0.1 in the univariate Cox regression were incorporated into the multivariate Cox regression analysis. A Hazard Ratio (HR) > 1 indicated an unfavorable prognosis. Results: In the multivariate analysis, higher OM and CSM were observed in males, older age groups, tumors with distant metastasis, poorly differentiated tumors, and those who underwent chemotherapy. Non-Hispanic Black individuals showed elevated mortality rates. Conclusion: Delayed diagnosis may contribute to the increased mortality in this community. Improved access to healthcare and treatment is crucial for addressing these disparities. Larger prospective studies are needed to pinpoint the underlying causes of elevated mortality in non-Hispanic Black populations, and randomized controlled trials (RCTs) are warranted to evaluate therapies for advanced-stage appendix NETs.

There is a growing recognition globally that care regarding lactation following a perinatal death needs to potentially offer the opportunity for maternal donation. This article discusses this experience and perspectives from a human milk bank (HMB) in Vietnam. This is a descriptive exploratory case study that has a long tradition in both the social and health sciences. Triangulated data collection involved a review of video data, interview data with the donor, and data review for the Da Nang HMB, a Center for Excellence in Breastfeeding. We found that although it is common for mothers in Vietnam to donate breastmilk to HMBs, it is less common for this to occur following perinatal loss. We offer a descriptive case study of the maternal loss of twins and a subsequent choice to donate for approximately 1 month to the Da Nang HMB, the first HMB in Vietnam. We discuss four reasons derived from this case regarding donation following perinatal loss. (1) A strong motivation to donate breastmilk when aware of the service, (2) donating breastmilk helped her deal with grief, (3) family members supported her through this tough time and supported her decision, and (4) health staff supported her decision. While human milk sharing (e.g., wet nursing) has been practiced in Vietnam, breastmilk donation from bereaved mothers has neither been discussed nor well-researched. Because maternal grief is complex and individual, deciding to donate breastmilk is a personal decision that needs to be supported, without creating guilt for those who do not wish to donate.

Summary: SCN2A protein-truncating variants (PTV) can result in neurological disorders such as autism spectrum disorder and intellectual disability, but they are less likely to cause epilepsy in comparison to missense variants. While in vitro studies showed PTV reduce action potential firing, consequences at in vivo network level remain elusive. Here, we generated a mouse model of Scn2a insufficiency using antisense oligonucleotides (Scn2a ASO mice), which recapitulated key clinical feature of SCN2A PTV disorders. Simultaneous two-photon Ca2+ imaging and electrocorticography (ECoG) in awake mice showed that spontaneous Ca2+ transients in somatosensory cortical neurons, as well as their pairwise co-activities were generally decreased in Scn2a ASO mice during spontaneous awake state and induced seizure state. The reduction of neuronal activities and paired co-activity are mechanisms associated with motor, social and cognitive deficits observed in our mouse model of severe Scn2a insufficiency, indicating these are likely mechanisms driving SCN2A PTV pathology.

BackgroundDonor human milk (DHM) is essential to the operation of human milk banks (HMB). This study examined characteristics and factors associated with higher volumes of DHM donation at the first HMB in Vietnam.MethodData from an online HMB monitoring system collected between February 2017 and July 2022 included demographic characteristics, child information, the timing of donation, and the volume of DHM. Higher volume is defined as equal to or greater than the median DHM volume per donor of 14.4 liters (L). Potential contributors to higher DHM volume were examined using the chi-square test in univariate and multivariable logistic regression analysis.ResultsDuring the 5.5-year operation, this HMB recruited 517 donors with an average age of 28.6 years. Approximately 60.9% of donors had a college or higher degree and 97.3% gave birth in Da Nang city. Of these donors, the prevalence of cesarean birth was 48.2%, preterm births was 40.2%, and 27.9% had babies with a birth weight of less than 1,500 g. There was a similar proportion of donors between the hospital (48.2%) and community (51.8%). On average, hospital donors started their donations 15 days after birth when their newborns were 33.9 weeks corrected age compared to 63 days and 47.7 weeks among community-based donors. The overall median volume of DHM per donor was 14.4 L over a period of 46 days. The amount and duration were higher in community-based donors (17.5 L in 72 days, 300 ml/day) than those in the hospital (8.4 L in 30 days, 258 ml/day). More than 37% of donors contacted the HMB themselves; the remainder were introduced by health professionals. Factors associated with higher volumes of DHM included higher education (OR: 1.77; 95% CI: 1.09, 2.87), having a full-term newborn (OR: 2.46; 95% CI: 1.46, 4.13), and community-based donors (OR: 2.15; 95% CI: 1.22, 3.78).ConclusionsMothers with higher education and from the community donate more breastmilk over a longer duration than those with lower education and from the hospital. Breastfeeding protection, promotion, and support should be offered to all mothers with specialized breastfeeding support for mothers of preterm and sick infants. This will ensure mothers have sufficient breastmilk for their newborns and potentially surplus breastmilk for donation.

Background: Routine placement of a drain for complicated appendicitis is one of the approaches to reduce postoperative complication. In a resource-limited hospital where radiologist-directed monitoring is not feasible, drainage is beneficial for complication follow-up. Nevertheless, emerging studies indicated drainage did not significantly impact on amelioration of patients’ outcomes. This study aimed to compare the postoperative results of pediatric patients with or without drainage after laparoscopic appendectomy for complicated appendicitis at a rural children's hospital. Methods: We performed a quasi-randomized recruitment of pediatric patients who underwent laparoscopic treatment for complicated appendicitis with or without drainage. Several parameters, including operative time, lengths of stay, complication rate, duration of antibiotic administration, and hospital charges were monitored for assessment. Results: From 05/2020 to 05/2022, there were 184 cases of recruited pediatric patients who underwent laparoscopic appendectomy for complicated appendicitis, with 91 patients in drain-placing group (49.5%). Demographic baseline and pre-surgery symptoms did not indicate any differences between two groups. Data of postoperative complications including intra-abdominal abscesses and wound infections showed no significance in discrepancy. Notably, patients of drainage group experienced longer length of stay than non-drainage group, with average of 8.5 days and 7.5 days, respectively (p

Plant segmentation is a critical task in precision agriculture as related to crop management and weed treatment. Plants can exhibit very large scale changes, which presents great challenge for accurate crop/weed segmentation. Recent works have shown that multi-scale features are useful to segment objects with different scales. In this work, we propose a Dense Multi-scale Convolutional Network (DMSCN) for pixel-wise crop/weed segmentation. Our network has an encoder-decoder structure. The encoder comprises of a Dense Convolutional Network (DCN) and a Dense Multi-Scale Atrous Pooling (DMSAP) module. DCN is composed of standard and atrous convolutions with dense connections. The architecture of DCN allows the encoder to increase the density of feature maps while avoiding signal decimation due to the dimension reduction. The proposed DMSAP connects a set of standard and atrous convolutional layers with different dilation rates in a densely cascaded manner. DMSAP is able to capture features with dense scale sampling and large receptive field. A simple yet effective decoder is used to refine the segmentation results by combining high and low-level features of the encoder. Extensive experiments are performed on four crop/weed datasets. One of these datasets was collected and annotated by us. We conduct an ablation study to show the advantages of different modules of DMSCN. The comparative study demonstrates the advantages of our model compared with the previous methods in terms of accuracy and complexity.

A robust mechanical parameter estimation together with adaptive speed control algorithms for permanent magnet synchronous motor (PMSM) drive systems based on the dual adaptive sliding-mode method is proposed in this paper. First, a robust adaptive sliding mode mechanical observer (RASM) and mechanical parameter identification (MPI) are proposed to eliminate system parameter errors in the first rotation. Based on RASM-MPI, the correct mechanical parameters are estimated from the system disturbance value. Then, an adaptive sliding-mode speed control (ASMSC) is applied to reduce the chattering inherent in the control signal and improve the convergence time to reach the sliding-mode surface. From the second rotation, the RASM identifies unknown external load torque and provides feed-forward compensation for the ASMSC to improve the speed control of the PMSM. All the proposed methods are applied to an industrial motor drive. The experimental results verified that the proposed scheme can estimate system parameters accurately within a short time. In addition, the speed controller can run stably, and with less error.

In this work, we study the ability to use hand gestures for human-machine interaction from wrist-worn sensors. Towards this goal, we design a wrist-worn prototype to capture RGB video stream of hand gestures. Then we built a new wrist-worn gesture dataset (named WiGes) with various subjects in interaction with home appliances in different environments. To the best of our knowledge, this is the first benchmark released for studying hand gestures from a wrist-worn camera. We then evaluate various CNN models for vision-based recognition. Furthermore, we deeply analyze the models that produce the best trade-off between accuracy, memory requirement, and computational cost. We point out that among studied architectures, MoviNet produces the highest accuracy. Then, we introduce a new MoviNet-based two-stream architecture that takes both RGB and optical flow into account. Our proposed architecture increases the Top-1 accuracy by 1.36% and 3.67% according to two evaluation protocols. Our dataset, baselines, and proposed model analysis give instructive recommendations for human-machine interaction using hand-held devices.

This study aims to examine the impact of brand image on public university links in the context of autonomy in Vietnam. Using quantitative research methods through exploratory factor analysis (EFA) and Structural Equation Modeling (SEM), the survey data included 631 samples of managers, experts, and scientists at public universities divided by different disciplines. The results of the study showed that the brand image has both a direct and indirect impact on public university links in the context of autonomy through intermediate elements of trust and commitment in the relationship between universities. In addition, trust has also been shown to have a direct impact on commitment in the relationship between public universities in Vietnam in the context of autonomy. In the context of research in Vietnam, the findings of this study have shown both theoretical and practical contributions and will be an important basis for further research.

To provide reliable position control for a permanent-magnet synchronous motor (PMSM) under conditions of lumped disturbances such as external load torque fluctuation and system parameter variation, an adaptive backstepping sliding-mode control (ABSMC) with a nonlinear disturbance observer (NDO) is proposed. An ABSMC is a non-cascade technique that employs a position-current single-loop control structure rather than a conventional cascade control structure for vector control of the PMSM. This method uses Lyapunov theory to design a control law that ensures the motor position reaches a desired value in a finite period of time and consequently achieves a rapid transient response. The proposed ABSMC incorporates adaptive convergence gain to avoid a large overshoot under point-to-point position command. The NDO with nonlinear observer gain is proposed to estimate unknown disturbances and provide feed-forward compensation for the ABSMC, improving robustness and reducing steady-state position error. The proposed methods are applied to an industrial motor drive to confirm their validity in real-world operating environments.

University autonomy is a necessary condition for the implementation of advanced university governance methods to improve and enhance the quality of training. This study aims to examine the influence of factors on linkage between public universities in the context of university autonomy in Vietnam. Using quantitative research methods, through multiplicative model analysis, with a scale of 528 samples being managers, experts, scientists at public universities which are then divided by different sectors. The results show that there are 5 factors that favorably influence the linkage between public universities in the context of autonomy with the order of influence defined as: Information sharing; Goal consensus; Financial resources; University brand values; Commitment. Based on the research findings, the authors propose a number of recommendations to strengthen the linkages between public universities in the context of university autonomy in Vietnam.

Abstract Vietnam has high rates of antibiotic use and resistance. Measuring resistance in commensal bacteria could provide an objective indicator for evaluating the impact of interventions to reduce antibiotic use and resistance. This study aimed to evaluate the feasibility, acceptability, and bacterial recovery for different sampling strategies. We conducted a cross-sectional mixed methods study in a rural community in Ha Nam Province, northern Vietnam, and collected structured interviews, samples, and in-depth interviews from households. Out of 389 households invited, 324 participated (83%), representing 1502 individuals. Samples were collected from these individuals (1498 stool, 1002 self-administered nasal swabs, and 496 HW-administered nasopharyngeal swabs). Pneumococci were recovered from 11.1% (128/1149) of the total population and 26.2% (48/183) of those under 5-years. Recovery was higher for health-worker (HW)-administered swabs (13.7%, 48/350) than self-administered swabs (10.0%, 80/799) (OR 2.06, 95% CI 1.07–3.96). Cost per swab was cheaper for self-administered ($7.26) than HW-administered ($8.63) swabs, but the overall cost for 100 positive samples was higher ($7260 and $6300 respectively). Qualitative interviews revealed that HW-administered nasopharyngeal swabs took longer to collect, caused more discomfort, and were more difficult to take from children. Factors affecting participation included sense of contribution, perceived trade-offs between benefits and effort, and peer influence. Reluctance was related to stool sampling and negative perceptions of research. This study provides important evidence for planning community-based carriage studies, including cost, logistics, and acceptability. Self-administered swabs had lower recovery, and though cheaper and quicker, this would translate to higher costs for large population-based studies. Recovery might be improved by swab-type, transport medium, and better cold-chain to lab.

Seasonal changes in freshwater phytoplankton assemblages at Tuyen Lam Reservoir in the Central Highlands of Vietnam were classified into 23 functional groups based on physiological, morphological, and ecological characteristics. A total of 168 species were recorded during 10 surveys from 2015 to 2019 at 7 sampling sites, with Chlorophyta dominating in number of species. Phytoplankton abundance varied from 0.18×105 to 21.2×105 cells/L during the study period, mainly due to cyanobacteria. Seven of the 23 functional groups were considered to be dominant (relative density > 5%). The dominant functional groups were groups M and G in the dry season and groups M, G, P, and E in the rainy season. Group M (Microcystis aeruginosa) was the most common in both seasons, while group P (Closterium, Staurastrum, Aulacoseira), group E (Dinobryon, Synura), and group G (Sphaerocystis, Eudorina) were more common in the rainy season. The Shannon diversity index (H¢) showed that phytoplankton communities were relatively diverse and that most of the study sites were lightly polluted. However, the ecological status has deteriorated at some locations due to the overgrowth of group M, leading to eutrophication in this reservoir. This study highlights the usefulness of functional groups in the study of seasonal changes in phytoplankton dynamics. Functional groups are applied for the first time at Tuyen Lam Reservoir and can be used to predict early-stage cyanobacterial blooms in future studies.

Workplace incivility (WI) is defined as low-intensity negative behaviors in the workplace. While this topic is common in a Western context, limited research has been conducted in the Asian context, particularly in China and Vietnam. This research aims to investigate a cross-cultural study about WI, to focus on the linkage between demographic variables and WI. The research sample comprised 598 voluntary working adults in China and Vietnam. The data were calculated using descriptive statistics and paired t -tests in SPSS. The result indicated that Chinese and Vietnamese experienced the same incivility behaviors at works. In addition, males experienced more WI than females. This research is a pioneer cross-cultural study about WI in the Asian context, which investigates the influence of demographic variables on WI in Chinese and Vietnamese working adults. Although this study attempts to conduct a cross-cultural study, its limitation is that the sample size is modest and random. This study also expresses some solutions to eliminate incivility behaviors in the workplace.

Probiotics have been popularly used in livestock production as an alternative to antibiotics. This study aimed to investigate the microbiological quality and phenotypic and genotypic antimicrobial resistance of bacteria in probiotic products sold for food animals. A total of 45 probiotic products were examined for the number of viable cells, species, and antimicrobial susceptibility; the contamination of Escherichia coli and Salmonella; and the presence of 112 genes encoding resistance to clinically important antimicrobials and transferability of AMR determinants. The results showed that 29 of 45 products (64.4%) were incorrectly labeled in either number of viable cells or bacterial species. None of the tested products were contaminated with E. coli and Salmonella. A total of 33 out of 64 bacterial isolates (51.6%) exhibited resistance to at least one antimicrobial agent. Of the 45 products tested, 16 (35.5%) carried AMR genes. Almost all AMR genes detected in probiotic products were not correlated to the AMR phenotype of probiotic strains formulated in the products. Three streptomycin-resistant Lactobacillus isolates could horizontally transfer their AMR determinants. The findings demonstrated that the probiotic products could serve as reservoirs for the spread of AMR genes and may not yield benefits to animals as claimed. The need for the adequate quality control of probiotic products is highlighted.

The purpose of the study was to examine the occurrence of metritis on reproduction of beef cows. A total of 2,962 cows were examined, and samples were collected from those displaying clinical symptoms of bovine metritis for bacterial analysis. Bacterial species identification was performed using culture and PCR techniques. The findings revealed that bovine metritis affected 5.5% of the reproductive cow population with the presence of Streptococcus spp., Staphylococcus aureus, Escherichia coli, and Salmonella spp. at the rates of 87.7%, 61.1%, 59.9% and 17.3%, respectively. The results also demonstrated that Streptococcus spp. was the most prevalent group, while Salmonella spp. had the lowest prevalence across different breeds and litters. However, in the Limousin crossbred cows, the infection rate of E. coli surpassed that of the other bacteria and a significantly higher infection rate for E. coli was observed in litter 4 and litter ≥6 compared to the others. The disk diffusion method was utilized to assess antibiotic resistance patterns of the isolated bacteria. Among the bacteria, marbofloxacin exhibited the lowest prevalence of antibiotic resistance (16.9%), while doxycycline had the highest prevalence (82.2%). All cows recovered from the disease within 3-5 days of treatment, and all of them resumed estrus in the subsequent reproductive cycle. The pregnancy rate ranged from 66.7% to 80.0% for the first insemination in the next reproductive cycle.

Gamified online quizzes have gained popularity for their potential in enhancing student learning motivations, creating engaging lessons, and improving learning outcomes. Yet, its application and effectiveness in support of student vocabulary learning have only been explored in synchronous learning setting. This study, hence, extended the exploration by examining the implementation of gamified vocabulary learning in an asynchronous mode and analyzing the impacts on students’ learning outcomes in class. The study was carried out for 10 weeks, involving 300 2nd year students at a Thai university. The instrument and measure comprised 500 English academic words made into 10 vocabulary sets on Quizizz.com, and 10 in-class vocabulary tests. The findings of the study revealed that students’ vocabulary learning practice in asynchronous mode had positive correlations with and could significantly predict their in-class vocabulary results. Female students outperformed male students; nonetheless, there was no significant difference across academic majors.

Phytoplankton communities can be classified into different groups based on physiological, morphological, and ecological functions. In this study, the responses of phytoplankton functional groups (PFGs) to physicochemical variables and hydraulic regimes were investigated and used as ecological indicators in the Tri An Reservoir (TAR), a eutrophic tropical floodplain reservoir located in southern Vietnam. Altogether, 148 phytoplankton taxa were identified and assigned to 16 PFGs; the four predominant PFG groups were M (Microcystis spp.), MP (filamentous cyanobacteria: Oscillatoria spp., and some other diatoms: Gomphonema angustatum, Navicula sp.), J (green algae: Coelastrum spp., Cosmarium spp., Pediastrum spp., Scenedesmus spp., Staurastrum spp., Tetradesmus spp., Tetraëdron spp., and Xanthidium spp.), and P (Closterium spp., Aulacoseira granulata, Fragilaria spp., Pinnularia spp., and Desmidium baileyi). The average PFG biovolume ranged from 79.6 ± 20.2 to 230.1 ± 69.1 mg/L with M being the dominant group. The trophic state index (TSI) indicated that the water condition was light-eutrophic to hyper-eutrophic. It was found that the large water level fluctuation resulted in seasonal nutrient dynamics, with higher nutrient concentrations and higher turbidity during the low water level period and vice versa. The redundancy analysis (RDA) indicated that the nutrient concentrations, water level fluctuation, and mixing regimes were critical factors in the PFG selection in the TAR. Therefore, we assumed that water level fluctuation management coupled with biological competition have the potential to control toxic cyanobacteria in the TAR. In conclusion, the PFGs are suitable for examining the effects of environmental conditions on phytoplankton dynamics in tropical floodplain reservoirs, but their sensitivity to long-term changes in water quality and eutrophication requires further investigation. HIGHLIGHTS Phytoplankton functional groups (PFGs) in relation to the ecological conditions in a tropical floodplain reservoir were investigated.; The trophic state index (TSI) ranged from light-eutrophic to hyper-eutrophic conditions.; Sixteen PFGs were found with the dominant group being M (Microcystis spp.).; Nutrient concentrations, water level fluctuation, and mixing regimes are critical factors in selecting PFGs in the TAR.;

This paper proposes a new online auto-tuning method to improve the accuracy and reduce the tuning time of permanent magnet synchronous motor (PMSM) drives. Under varying loads, the ability to tune the controllers of PMSM drives using optimal tuning time is crucial. However, direct tuning of controller parameters using estimated parameters or conventional particle swarm optimization (PSO) methods do not satisfy the performance criteria. To solve this problem, the new method combining mechanical parameter estimation (MPE) and multi-layer particle swarm optimization (MLPSO) with K-means clustering (KMC) and an adaptive learning strategy (ALS) is proposed. First, the combination of an MPE method with a lookup table (LUT) for initial parameter selection is introduced to reduce the iteration time. Then, the MLPSO-KMCALS method is proposed as an improvement over the conventional PSO method by increasing the number of layers, grouping the swarm into several subswarms, and using the ALS for each particle to increase the population diversity and optimize the controller parameters within the shortest possible amount of time. Finally, a disturbance load torque observer is applied to compensate for the effect of external disturbances after tuning. The effectiveness of the proposed method is validated through experiments conducted under practical conditions.

BackgroundGlobally, almost 15 million infants are born prematurely each year, disproportionately affecting low and middle-income countries. In the absence of mother's milk, the World Health Organization recommends using donor human milk (DHM) due to its protective effect against necrotizing enterocolitis, a life-threatening intestinal disorder. The use of DHM is increasing globally, with many low and middle-income countries integrating donor milk banks into their public health strategies to reduce neonatal mortality, yet very little is known about the nutritional composition of DHM. Additional knowledge gaps include how DHM composition is influenced by milk banking practices, and whether preterm nutrient recommendations are achieved when DHM is used with commercially available fortifiers.MethodsWe designed a multi-site study with eight geographically diverse milk bank partners in high, middle, and low-income settings that will examine and compare a broad range of nutrients and bioactive factors in human milk from 600 approved milk bank donors around the world to create comprehensive, geographically diverse nutrient profiles for DHM. We will then simulate the random pooling of 2 to 10 donors to evaluate the impact of pooling as a potential strategy for milk banks to manage nutrient variability in DHM. Finally, we will evaluate whether commercially available fortifiers meet nutrient recommendations when used with DHM.DiscussionWe expect that results from this study will improve nutritional care globally for the growing number of preterm infants who receive donor human milk.

With a young population structure, young consumers in Vietnam have been becoming a driving force and a major purchasing power behind the economic development. While ethical issues associated with consumerism have been a topic of discussion in the society, young consumers have stepped up to the plate by showing a positive support for being ethical consumers. It is still unclear, however, whether they are willing to actualize their perspective, as the alleged attitude—behavior gap is still commonplace. This research attempted to examine the influence of socialization agents and environmental concern on the ethically minded consumer behavior (EMCB) of young consumers by drawing on the socialization framework. The context of this research is Generation Z in Vietnam, the generation who has been growing up with technology but has been received lack investigation. With a sampling of 230 young consumers based in Ho Chi Minh City, results demonstrate that intimate relationships have a significant impact on young consumers’ behavior towards dimensions of EMCB. In particular, family and peers exert substantial effect on young consumers’ tendency to pay more for an ethical product as well as to purchase eco-friendly goods. Media, on the contrary, is not a significant determinant.

Background and objectivesObesity is a global epidemic which increases the risk of the metabolic syndrome. Cathelicidin (LL-37 and mCRAMP) is an antimicrobial peptide with an unknown role in obesity. We hypothesize that cathelicidin expression correlates with obesity and modulates fat mass and hepatic steatosis.Materials and methodsMale C57BL/6 J mice were fed a high-fat diet. Streptozotocin was injected into mice to induce diabetes. Experimental groups were injected with cathelicidin and CD36 overexpressing lentiviruses. Human mesenteric fat adipocytes, mouse 3T3-L1 differentiated adipocytes and human HepG2 hepatocytes were used in the in vitro experiments. Cathelicidin levels in non-diabetic, prediabetic and type II diabetic patients were measured by enzyme-linked immunosorbent assay.ResultsLentiviral cathelicidin overexpression reduced hepatic steatosis and decreased the fat mass of high-fat diet-treated diabetic mice. Cathelicidin overexpression reduced mesenteric fat and hepatic fatty acid translocase (CD36) expression that was reversed by lentiviral CD36 overexpression. Exposure of adipocytes and hepatocytes to cathelicidin significantly inhibited CD36 expression and reduced lipid accumulation. Serum cathelicidin protein levels were significantly increased in non-diabetic and prediabetic patients with obesity, compared with non-diabetic patients with normal body mass index (BMI) values. Prediabetic patients had lower serum cathelicidin protein levels than non-diabetic subjects.ConclusionsCathelicidin inhibits the CD36 fat receptor and lipid accumulation in adipocytes and hepatocytes, leading to a reduction of fat mass and hepatic steatosis in vivo. Circulating cathelicidin levels are associated with increased BMI. Our results demonstrate that cathelicidin modulates the development of obesity.

RNA viral infections, including those caused by respiratory syncytial virus (RSV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and Venezuelan Equine encephalitis virus (VEEV), pose a major global health challenge. Here, we report the synthesis and screening of a series of pyrrolo[2,3-b]pyridines targeting RSV, SARS-CoV-2 and/or VEEV. From this campaign, a series of lead compounds was generated that demonstrated antiviral activity in the low single-digit micromolar range against the various viruses and did not show cytotoxicity. These findings highlight the potential of 3-alkynyl-5-aryl-7-aza-indoles as a promising chemotype for the development of broad-spectrum antiviral agents.

The prevalence of early and exclusive breastfeeding in Vietnam remains sub-optimal. The objective of this study was to determine factors associated with early initiation of breastfeeding (EIBF) and exclusive breastfeeding for the first 3 days after birth (EBF3D). We conducted a population-based, cross-sectional survey of 726 mothers with children aged 0–11 months in two provinces and one municipality from May to July 2020. Multinomial logistic regression was used to examine factors associated with EIBF and EBF3D. The prevalence of EIBF was 39.7% and EBF3D 18.0%. The EIBF prevalence is positively associated with immediate and uninterrupted skin-to-skin contact (SSC) for 10–29 min (aOR: 2.55; 95% CI: 1.49, 4.37), 30–59 min (aOR: 4.15; 95% CI: 2.08, 8.27), 60–80 min (aOR: 4.35; 95% CI: 1.50, 12.6), or ≥90 min (aOR: 5.87; 95% CI: 3.14, 10.98). EIBF was negatively associated with cesarean birth (aOR: 0.24; 95% CI: 0.11, 0.51), bringing infant formula to the birth facility (aOR: 0.49; 95% CI: 0.30, 0.78), purchased it after arrival (aOR: 0.37; 95% CI: 0.24, 0.60), or did both (aOR: 0.43; 95% CI: 0.21, 0.89). EBF3D was negatively associated with cesarean section birth (aOR: 0.15; 95% CI: 0.06, 0.39), vaginal birth with episiotomy (aOR: 0.40; 95% CI: 0.18, 0.88), bringing formula to the maternity facility (aOR: 0.03; 95% CI: 0.01, 0.07), purchased it after arrival (aOR: 0.02; 95% CI: 0.01, 0.06) or did both (aOR: 0.04; 95% CI: 0.02, 0.10). Receiving counseling from any source was not significantly associated with early breastfeeding practices. Policy and health service delivery interventions should be directed at eliminating infant formula from birthing environments, reducing unnecessary cesarean sections and episiotomies, providing immediate and uninterrupted SSC for all births, and improving breastfeeding counseling and support.