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Unmanned aerial vehicles (UAVs) have been widely deployed in many applications such as transportation, data collection, monitoring, or tracking objects. Nowadays, numerous missions require UAVs to operate in a large area or to complete missions in a stringent period of time. Using a single UAV may not meet theperformance requirements because of its small size and limited battery. In this situation, multiple Unmanned Aerial Vehicles (UAVs) have emerged as an effective measure that can address these limitations. A group ofUAVs cooperatively working together could offer a solution that is more efficient and economical than usinga powerful UAV alone. To better utilizing the multiple-UAVs system, control of formation UAVs is a critical challenge that needs to overcome. Therefore, formation control has become an active research topic that gains great attention from researchers. Extensive research efforts have been dedicated to studying the formation control problem with numerous control protocols which have been proposed. This paper reviews the profound studies on formation control in literature. Each approach is investigated based on different criteria, which highlights its distinct merits and demerits. The comparison is provided to facilitate the readers in their future researches in the field of formation control. Finally, some open challenges and research directions are also discussed.

Management of multidrug-resistant tuberculosis (MDR-TB) is a significant challenge to the global healthcare system due to the complexity and long duration of the MDR-TB treatment. This study analyzed the safety of patients on longer injectable-based MDR-TB treatment regimens using active pharmacovigilance data. We conducted an observational, prospective study based on active pharmacovigilance within the national TB program. A total of 659 MDR-TB patients were enrolled and followed up at 9 TB- hospitals in 9 provinces of all 3 regions in Vietnam between 2014 and 2016. Patients received a treatment regimen (standardized or individualized) based on their drug susceptibility test result and their treatment history. Baseline and follow-up information was collected at the start and during treatment. Adverse events (AE) were defined and classified as serious adverse events (SAEs) or otherwise. Multivariate Cox regression following the Iterative Bayesian Model Averaging algorithm was performed to identify factors associated with AE occurrence. Out of 659 patients assessed, 71.3% experienced at least one AE, and 17.5% suffered at least one SAE. The most common AEs were gastrointestinal disorders (38.5%), arthralgia (34.7%), and psychiatric disorders (30.0%). The proportion of patients with nephrotoxicity and hearing loss or vestibular disorders were 7.4% and 15.2%, respectively. 13.1% of patients required modifications or interruption of one or more drugs. In 77.7% of patients, treatment was completed successfully, while 9.3% lost to follow-up, in 3.0% treatment failed, and 7.4% died. Some significant risk factors for nephrotoxicity included diabetes mellitus (HR = 8.46 [1.91-37.42]), renal dysfunction (HR = 8.46 [1.91-37.42]), alcoholism (HR = 13.28 [5.04-34.99]), and a higher average daily dose of injectable drugs (HR = 1.28 [1.14-1.43]). While a majority of patients on the longer injectable-based regimens experienced non-serious AEs during MDR-TB treatment, one in six patients experienced at least an SAE. Active TB drug-safety monitoring is useful to understand the safety of MDR-TB treatment and explore the risk factors for toxicity. All-oral, shorter MDR-TB regimens might be able to reduce the inconvenience, discomfort, and toxicity of such regimens and increase adherence and likelihood of successful completion.

Advanced Persistent Threat (APT) attacks are causing a lot of damage to critical organizations and institutions. Therefore, early detection and warning of APT attack campaigns are very necessary today. In this paper, we propose a new approach for APT attack detection based on the combination of Feature Intelligent Extraction (FIE) and Representation Learning (RL) techniques. In particular, the proposed FIE technique is a combination of the Bidirectional Long Short-Term Memory (BiLSTM) deep learning network and the Attention network. The FIE combined model has the function of aggregating and extracting unusual behaviors of APT IPs in network traffic. The RL method proposed in this study aims to optimize classifying APT IPs and normal IPs based on two main techniques: rebalancing data and contrastive learning. Specifically, the rebalancing data method supports the training process by rebalancing the experimental dataset. And the contrastive learning method learns APT IP’s important features based on finding and pulling similar features together as well as pushing contrasting data points away. The combination of FIE and RL (abbreviated as the FIERL model) is a novel proposal and innovation and has not been proposed and published by any research. The experimental results in the paper have proved that the proposed method in the paper is correct and reasonable when it has shown superior efficiency compared to some other studies and approaches over 5% on all measurements.

There is a growing burden of hypertension (HTN) among adults living in rural Vietnam, which is associated with reduced health related quality of life (HRQoL). Few community-based interventions have, however, attempted to improve the quality of life in patients with uncontrolled HTN. This study aimed to examine the impact of a multi-component intervention on HRQoL in adults with uncontrolled HTN. This cluster-randomized controlled trial was conducted in sixteen communities (8 intervention and 8 comparison) living in a rural setting in Vietnam (2017-2022). Consenting adults with uncontrolled HTN were enrolled. The comparison arm received training sessions about HTN prevention and management and patient education materials. The intervention arm received information similar to the comparison group and three enhancement components, namely a storytelling intervention, home blood pressure (BP) self-monitoring, and expanded community health worker services. The primary outcome was the differential change in HRQoL over 12-month follow-up period, measured using the 12-Item Short Form Health Survey (SF-12), which generates a Physical Component Summary (PCS-12) and a Mental Component Summary (MCS-12). The total HRQoL score was calculated as the sum of PCS-12 and MCS-12, with higher scores indicating better HRQoL. A total of 671 patients were studied; their mean age was 66 years and 55% were women. At the 12-month follow-up, the intervention group showed a significant increase in their PCS-12 with a multivariable-adjusted difference of 4.2 points (95% CI: 2.0-6.4) compared with the control group. While the MCS-12 scores increased for both groups, their differential change over 12 months was not statistically significant (multivariable-adjusted difference: 1.4 points; 95% CI: -0.6; 3.5). Our results demonstrate that a multicomponent intervention effectively improved overall HRQoL with a significant impact on physical health-related HRQoL in individuals with uncontrolled HTN. ClinicalTrials.gov, Registration number: https://clinicaltrials.gov/study/NCT03590691, (registration date July 17, 2018).

Tuberculosis continues to be a global health challenge. In this report, active case finding was more than twice as likely as standard passive case finding to identify tuberculosis among household contacts of index patients with smear-positive disease.

Tuberculosis transmission continues to be a major public health challenge. In this cluster-randomized, controlled trial conducted in Vietnam, active community-wide screening for tuberculosis over 4 years is shown to decrease the prevalence of tuberculosis.

Flavonoids and stilbenoids, crucial secondary metabolites abundant in plants and fungi, display diverse biological and pharmaceutical activities, including potent antioxidant, anti-inflammatory, and antimicrobial effects. However, conventional production methods, such as chemical synthesis and plant extraction, face challenges in sustainability and yield. Hence, there is a notable shift towards biological production using microorganisms like Escherichia coli and yeast. Yet, the drawbacks of using E. coli and yeast as hosts for these compounds persist. For instance, yeast’s complex glycosylation profile can lead to intricate protein production scenarios, including hyperglycosylation issues. Consequently, Corynebacterium glutamicum emerges as a promising alternative, given its adaptability and recent advances in metabolic engineering. Although extensively used in biotechnological applications, the potential production of flavonoid and stilbenoid in engineered C. glutamicum remains largely untapped compared to E. coli. This review explores the potential of metabolic engineering in C. glutamicum for biosynthesis, highlighting its versatility as a cell factory and assessing optimization strategies for these pathways. Additionally, various metabolic engineering methods, including genomic editing and biosensors, and cofactor regeneration are evaluated, with a focus on C. glutamicum. Through comprehensive discussion, the review offers insights into future perspectives in production, aiding researchers and industry professionals in the field.

Hospital effluents represent an important source for the release of antibiotics and antibiotic resistant bacteria into the environment. This study aims to determine concentrations of various antibiotics in wastewater before and after wastewater treatment in a rural hospital (60 km from the center of Hanoi) and in an urban hospital (in the center of Hanoi) in Vietnam, and it aims to explore the relationship between antibiotic concentrations in wastewater before wastewater treatment and quantities of antibiotics used in the rural hospital, over a period of one year in 2013. Water samples were collected using continuous sampling for 24 h in the last week of every month. The data on quantities of antibiotics delivered to all inpatient wards were collected from the Pharmacy department in the rural hospital. Solid-phase extraction and high performance liquid chromatography-tandem mass spectrometry were used for chemical analysis. Significant concentrations of antibiotics were present in the wastewater both before and after wastewater treatment of both the rural and the urban hospital. Ciprofloxacin was detected at the highest concentrations in the rural hospital’s wastewater (before treatment: mean = 42.8 µg/L; after treatment: mean = 21.5 µg/L). Metronidazole was detected at the highest concentrations in the urban hospital’s wastewater (before treatment: mean = 36.5 µg/L; after treatment: mean = 14.8 µg/L). A significant correlation between antibiotic concentrations in wastewater before treatment and quantities of antibiotics used in the rural hospital was found for ciprofloxacin (r = 0.78; p = 0.01) and metronidazole (r = 0.99; p < 0.001).

The development of unmanned aerial vehicles (UAVs) has become a revolution in the fields of data collection, surveying, monitoring, and tracking objects in the field. Many control and navigation algorithms are experimented and deployed for UAVs, especially quadrotors. Recent numerous approaches are geared towards reducing the influence of external disturbances to enhance the performance of UAVs. Nevertheless, designing cutting-edge controllers following the requirements of the applications is still a huge challenge. Based on the operating characteristics and movement principle of a quadrotor, this work reviews potential control algorithms of the current researches in the field of the quadrotor flight controller. Besides, a comparison has been made to provide an overview of the advantages and disadvantages of the mentioned methods. At last, the challenges and future directions of the quadrotor flight controller are suggested.

This work aims to synthesize akaganeite nanoparticles (AKNPs) by using microwave and use them to adsorb Congo red dye (CR) from the aqueous solution. The AKNPs with an average particle size of about 50 nm in width and 100 nm in length could be fabricated in 20 min. The effects of pH, CR initial concentration, adsorption time, and adsorbent dosage on the adsorption process were investigated and the artificial neural network (ANN) was used to analyze the adsorption data. The various ANN structures were examined in training the data to find the optimal model. The structure with training function, TRAINLM; adaptation learning function, LARNGDM; transfer function, LOGSIG (in hidden layer) and PURELIN (in output layer); and 10 neutrons in hidden layer having the highest correlation ( R 2 = 0.996) and the lowest MSE (4.405) is the optimal ANN structure. The consistency between the experimental data and the data predicted by the ANN model showed that the behavior of the adsorption process of CR onto AKNPs under different conditions can be estimated by the ANN model. The adsorption kinetics was studied by fitting the data into pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models. The results showed that the adsorption kinetics obeyed the pseudo-second-order model and governed by several steps. The adsorption isotherms at the different temperatures were studied by fitting the data to Langmuir, Freundlich, and Temkin isotherm models. The R 2 obtained from the Langmuir model was above 0.9 and the highest value in three of four temperatures, suggesting that the adsorption isotherms were the best fit to the Langmuir model and the maximum adsorption capacity was estimated to be more than 150 mg/g. Thermodynamic studies suggested that the adsorption of CR onto AKNPs was a spontaneous and endothermic process and physicochemical adsorption. The obtained results indicated the potential application of microwave-synthesize AKNPs for removing organic dyes from aqueous solutions.