Prevalence and risk factors associated with long COVID symptoms in children and adolescents in a southern province of Vietnam

Objective:To investigate the prevalence and risk factors associated with long COVID symptoms among children and adolescents who have recovered from COVID-19.Methods:This study applied a cross-sectional approach within community settings in a southern province of Vietnam.A structured questionnaire featuring socio-demographic information and common long COVID symptoms was employed.Phi correlation coefficients assessed associations among pairs of long COVID symptoms.Additionally,multivariable logistic regression models were performed to investigate the risk factors of long COVID in recovered COVID-19 children and adolescents.Results:Among 422 participants,39.3%reported long COVID symptoms,with a prevalence of 45.2%(SD=0.5)in children and 22.2%(SD=0.4)in adolescents.Common symptoms reported were cough 34.6%(SD=0.5),fatigue 20.6%(SD=0.4),shortness of breath 10.9%(SD=0.3),and lack of appetite 6.6%(SD=0.3).Concerning risk factors of long COVID,a higher risk was observed among demographic groups,including girls(OR 1.25,95%CI 1.15-1.37;P<0.001,reference:boys),children compared to adolescents(OR 1.24,95%CI 1.12-1.37;P<0.001),overweight individuals(OR 1.14,95%CI 1.02-1.27;P=0.018,reference:healthy weight),and participants without any COVID-19 vaccination(OR 1.36,95%CI 1.20-1.54;P<0.001),or have received only one single dose(OR 1.35,95%CI 1.10-1.64;P=0.004)compared to those who have received two doses.Besides,patients with a COVID-19 treatment duration exceeding two weeks also had a higher risk of long COVID(OR 1.32,95%CI 1.09-1.60;P=0.003)than those who recovered less than seven days.Conclusions:The insights from this study provide crucial guidance for predicting the factors associated with the occurrence of long COVID in pediatric patients,contributing to strategic interventions aimed at mitigating the long COVID risks among children and adolescents in Vietnam.

Exploring Mazu Worship at Fujian Assembly Hall in Hoi An,Vietnam

Hoi An Ancient Town in Vietnam is not only a UNESCO(United Nations Educational,Scientific,and Cultural Organization)World Heritage Site but also a convergence point of traditional and modern cultures.Throughout its historical transitions,the cultural heritage of Hoi An Ancient Town has been well preserved and developed,and the worship of Mazu,an essential component of Hoi An’s culture,is no exception.As far as is known,Hoi An in central Vietnam houses the most Mazu temples,including the Chung Wah Hall,the Guangzhou Assembly Hall,the Fujian Assembly Hall,the Teochew Assembly Hall,and the Hainan Assembly Hall,among others,with the Fujian Assembly Hall being the most vibrant center of Mazu worship.This study employs field surveys and literature research to explore the Mazu worship practices at the Fujian Assembly Hall in Hoi An,Quang Nam Province,Vietnam.

The Cult of Mazu in Hainan,China and Among Vietnamese Hainanese Diaspora:A Comparative Study of Mazu Culture

The cult of Mazu is a common folk belief in China and Vietnam.Originating from the Song and Yuan Dynasties,particularly during the Ming and Qing Dynasties,the cult of Mazu spread to Vietnam through maritime trade and migration from coastal regions of China.After centuries of integration and development,it evolved into its own cultural system of Mazu worship,becoming an important component of Vietnamese folk culture.Hainan,China,as a crucial supply station on the Maritime Silk Road,has close connections with the transmission of Mazu culture to Vietnam.This paper adopts field investigations and literature research methods to explore the Mazu worship and culture in Hainan,China,and the Qiongfu Assembly Halls in Vietnam.

Tuberculosis Diagnosis and Visualization with a Large Vietnamese X-Ray Image Dataset

Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse it.Significantly,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very difficult.The late detection of tuberculosis could lead to danger to patient health,even death.Vietnamis one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long time.Reality demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis system.In our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese patients.The chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning researchers.This paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image dataset.In detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a heat-map.To prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this research.To support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network model.The experiment results were evaluated regarding sensitivity,specificity,and accuracy.We achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over 0.9.Based on the X-ray image classification result,we visualize prediction results as heat-maps and also analyze them in comparison with annotated symptoms of radiologists.

Dry eye rate and its relationship with disease stage in patients with primary hypertension:a cross-sectional study in Vietnam

AIM:To determine the dry eye(DE)rate and its relationship with disease stage in patients with primary hypertension.METHODS:A cross-sectional study included 432 patients with primary hypertension(with an equal number of patients in each group:144 in stage Ⅰ,Ⅱ,and Ⅲ hypertension)and 144 healthy subjects as a control group.The Ocular Surface Disease Index(OSDI)and Schirmer Ⅰ test without anesthetics were conducted on all 576 subjects.Subjects with OSDI scores<13 and Schirmer Ⅰ values equal to or under 10 mm were diagnosed with DE.RESULTS:The ratio of DE in hypertension patients was higher than in the control group(41.7%versus 18.8%;P<0.001).The proportion of patients with DE increased gradually according to the hypertension stage:27.1% in stage Ⅰ,40.3% in stage Ⅱ,and 57.6% in stage Ⅲ,P<0.001.Age,duration of hypertension,plasma urea,creatinine,and high-sensitivity C-reactive protein(CRP-hs)levels in hypertension patients with DE were higher than those without DE,P<0.001.Advanced age,a long duration of hypertension,diabetes mellitus,elevated plasma creatinine,and CRP-hs levels were independent factors associated with DE in primary hypertension patients,P<0.001.CONCLUSION:DE is a common disorder associated with advanced age,a long duration of hypertension,diabetes mellitus,elevated plasma CRP-hs,and creatinine levels in patients with primary hypertension.

Building the ARIMA Model for Forecasting the Production of Vietnam’s Coffee Export

Coffee is a significant industry, accounting for 3% of Vietnam’s GDP, with annual export turnover consistently exceeding USD 3 billion. Despite global economic challenges affecting purchasing power at various times, Vietnam’s coffee exports in December 2023 continued to surge, reaching the highest level in the past 9 months at 190,000 tons, a 59.3% increase compared to November 2023, but still a slight 3.5% decrease from the same period last year. The export turnover reached USD 538 million, a 51% increase from November 2023 and a 26.4% increase from the same period last year. Therefore, forecasting the coffee export volume holds significant importance for coffee producers nationwide. This research employs the Box-Jenkins method to construct an ARIMA model for forecasting Vietnam’s coffee export volume based on annual data published by the General Statistics Office. Results indicate that among the models considered, the ARIMA(1, 1, 2) model is the most suitable. The study also provides short-term forecasts for Vietnam’s coffee export volume. However, the current model is limited to forecasting and is not yet optimized, as the assumed linearity in the model is a simplification.

Challenges of Vietnamese Agricultural Cooperatives in the 21st Century:The Link Between Efficiency and Legality

The article shows that the situation of agricultural cooperatives in the world in general and agricultural cooperatives in Vietnam in particular are facing certain challenges in the context of globalization in the 21st century.The article points out limitations on:the nature,principles of democratic member control and principles of surplus distribution of the International Cooperative Alliance,as well as Vietnamese law in cooperative management.

Prediction of Flash Flood Susceptibility of Hilly Terrain Using Deep Neural Network:A Case Study of Vietnam

Flash floods are one of the most dangerous natural disasters,especially in hilly terrain,causing loss of life,property,and infrastructures and sudden disruption of traffic.These types of floods are mostly associated with landslides and erosion of roads within a short time.Most of Vietnamis hilly and mountainous;thus,the problem due to flash flood is severe and requires systematic studies to correctly identify flood susceptible areas for proper landuse planning and traffic management.In this study,three Machine Learning(ML)methods namely Deep Learning Neural Network(DL),Correlation-based FeatureWeighted Naive Bayes(CFWNB),and Adaboost(AB-CFWNB)were used for the development of flash flood susceptibility maps for hilly road section(115 km length)of National Highway(NH)-6 inHoa Binh province,Vietnam.In the proposedmodels,88 past flash flood events were used together with 14 flash floods affecting topographical and geo-environmental factors.The performance of themodels was evaluated using standard statisticalmeasures including Receiver Operating Characteristic(ROC)Curve,Area Under Curve(AUC)and Root Mean Square Error(RMSE).The results revealed that all the models performed well(AUC>0.80)in predicting flash flood susceptibility zones,but the performance of the DL model is the best(AUC:0.972,RMSE:0.352).Therefore,the DL model can be applied to develop an accurate flash flood susceptibility map of hilly terrain which can be used for proper planning and designing of the highways and other infrastructure facilities besides landuse management of the area.

Detecting Tuberculosis from Vietnamese X-Ray Imaging Using Transfer Learning Approach

Deep learning created a sharp rise in the development of autonomous image recognition systems,especially in the case of the medical field.Among lung problems,tuberculosis,caused by a bacterium called Mycobacterium tuberculosis,is a dangerous disease because of its infection and damage.When an infected person coughs or sneezes,tiny droplets can bring pathogens to others through inhaling.Tuberculosis mainly damages the lungs,but it also affects any part of the body.Moreover,during the period of the COVID-19(coronavirus disease 2019)pandemic,the access to tuberculosis diagnosis and treatment has become more difficult,so early and simple detection of tuberculosis has been more and more important.In our study,we focused on tuberculosis diagnosis by using the chestX-ray image,the essential input for the radiologist’s profession,and researched the effectiveness of the transfer learning approach in the case study of Vietnamese chest X-ray images.We proposed four strategies to clarify our hypothesis in different ways of applying transfer learning and different training set types.We also prepared a Vietnamese X-ray image dataset with the support of the VRPACS team to provide the basis for training and testing deep learning models.Our experiments were carried out by applying three different architectures,Alexnet,Resnet,and Densenet,on international,Vietnamese,and combined X-ray image datasets.After training,all models were verified on a pure Vietnamese X-rays set.The results show that transfer learning is suitable in the case study of Vietnamese chest X-ray images with high evaluating metrics in terms of AUC(Area under the Receiver Operating Characteristic Curve),sensitivity,specificity,and accuracy.In the best strategy,most of the scores were more than 0.93,and all AUCs were more than 0.98.

Emotional Vietnamese Speech Synthesis Using Style-Transfer Learning

In recent years,speech synthesis systems have allowed for the produc-tion of very high-quality voices.Therefore,research in this domain is now turning to the problem of integrating emotions into speech.However,the method of con-structing a speech synthesizer for each emotion has some limitations.First,this method often requires an emotional-speech data set with many sentences.Such data sets are very time-intensive and labor-intensive to complete.Second,training each of these models requires computers with large computational capabilities and a lot of effort and time for model tuning.In addition,each model for each emotion failed to take advantage of data sets of other emotions.In this paper,we propose a new method to synthesize emotional speech in which the latent expressions of emotions are learned from a small data set of professional actors through a Flow-tron model.In addition,we provide a new method to build a speech corpus that is scalable and whose quality is easy to control.Next,to produce a high-quality speech synthesis model,we used this data set to train the Tacotron 2 model.We used it as a pre-trained model to train the Flowtron model.We applied this method to synthesize Vietnamese speech with sadness and happiness.Mean opi-nion score(MOS)assessment results show that MOS is 3.61 for sadness and 3.95 for happiness.In conclusion,the proposed method proves to be more effec-tive for a high degree of automation and fast emotional sentence generation,using a small emotional-speech data set.

Assessment of the Quality of Frozen-Thawed Semen or Epididymal Sperm in Three Native Vietnamese Pig Breeds

Our aim was to evaluate the quality of ejaculated and epididymal frozen-thawed pig sperm of endangered Vietnam native pig breeds. Ejaculated sperm was collected from live boars and epididymal sperm was collected from slaughtered boars of the MuongTe, Kieng Sat and Co BinhThuan breeds and frozen in 0.25 ml straws using a protocol established earlier for modern pig breeds. We evaluated the sperm quality after thawing in terms of motility and rates of viable and abnormal spermatozoa. Our results revealed that the sperm motility and rates of viable and abnormal frozen-thawed sperm were >30%, >44%, and <14%, respectively. The origin of sperm had an effect on the production of pig embryos in vitro. In the Co BinhThuan breed, ejaculated sperm generated higher cleavage, blastocyst and hatching rates than did the epididymal sperm (60.11% vs 56.02%, 17.23% vs 14.31%, 3.78% vs 2.34%, respectively, P < 0.05). Although no difference in cleavage rate, blastocyst formation rate and the average number of cells/blastocysts, the hatching blastocyst rate was different between the breeds (P > 0.05). In the Co BinhThuan breed, the rate of pregnancy of ejaculated groups was similar to that of the epididymal group. In conclusion, the ejaculated and epididymal sperm of native Vietnamese pigs were successfully frozen. We succeeded in creating embryos in vitro and pregnant pigs after artificial insemination from frozen-thawed semen in three native Vietnamese pig breeds for the first time. The use of the ejaculated sperm improved the production of native pig embryos in vitro efficiency.

A new species of Nanohyla(Anura:Microhylidae)from the lowland forests of southern Vietnam

DEAR EDITOR,We describe a new species of Nanohyla from the Song Hinh Protected Forest in Phu Yen Province,southern Vietnam,based on an integrative taxonomic approach.The new species represents a divergent lineage(16S rRNA gene uncorrected P-distance>5.3%),which clearly differs from any other Nanohyla species based on a series of morphological characters,most notably the presence of white spots on the top of its head.Morphologically,Nanohyla albopunctata sp.nov.is characterized by small body size(male snout-vent length(SVL)18.2-20.2 mm);moderately slender body habitus;rounded snout;distinct tympanum;rounded canthus rostralis;loreal region slightly concave;skin on dorsum tubercular,ventral surfaces smooth;mid-vertebral skin ridge and dorsomedial stripe absent;superciliary tubercles absent.

EFFECTS OF BIDEN’S VISIT TO VIETNAM For small and medium-sized countries,this period is one of both challenges and opportunities,which calls for increased caution

On September 10 after the G20 Summit in New Dehli,U.S.President Joe Biden traveled by Air Force One to Hanoi,Vietnam,for a state visit.There,he met with Nguyen Phu Trong,general secretary of the Communist Party of Vietnam(CPV)Central Committee,and other senior state leaders to exchange views on how to deepen cooperation between the two countries.

Nexus between CO2 Emissions and Economic Growth, Industrial Production, and Foreign Direct Investment in Vietnam: Symmetric ARDL Approach

Vietnam’s economy has been developing strongly in recent years;however, it is necessary to examine the impact of its economic activities on environmental quality. This study aims to evaluate the relationship between CO2 emissions and economic growth, industrial production, and foreign direct investment (FDI) in Vietnam. The ARDL estimation was used to process the dataset from World Bank. Results showed that economic growth, industrial production, and FDI have an impact on CO2 emissions in the long run in Vietnam. Granger Causality test also indicated that there is a causal relationship between economic growth, industrial production, and CO2 emissions in Vietnam from 1990 to 2018, at 5% statistical significance level. Proposed solutions to reduce CO2 emissions but still promote economic growth toward the green growth orientation and zero carbon target attainment are as follows: 1) reduce the use of fossil energy in industrial manufacturing and replace it by renewable energy sources;2) use modern technology for all production sectors in economy;and 3) develop a legal framework for FDI projects selection and choose foreign investors with modern and low carbon emission technology.

Assessing the Impact of Industrial Zones on the Environmental Pollution in Hai Phong’s Coastal Areas, Vietnam

Pollution in the coastal areas negatively affects biochemical indicators of seawater, human health and marine organisms. Hai Phong is a coastal city of Vietnam with the development of socio-economic activities, representing through an increasing number of industrial zones. This study is to evaluate the pollution of large industrial zones in Hai Phong city using numerical models. The numerical simulation (MIKE 21 SW, FM, ECO Lab) models were applied to simulate the wave propagation, hydraulic regime, water quality in coastal Hai Phong area. The MIKE 21 ECO Lab model was used to evaluate sources of waste from the large coastal industrial zones to some aquaculture zones. The calibration and validation results of wave propagation and the hydrodynamic models were resonably good, with Nash coefficient ranging from 0.65 to 0.90 and a percent bias (PBIAS) from 5.6% to 9.4%. The simulation results of water quality and concentration of pollutants (DO, BOD5, COD, TSS, Fe, and Coliform) in 2023 at the aquaculture locations show that the BOD5, COD, and TSS concentrations were higher than the allowable limits stated in the national technical regulation on surface water quality (QCVN 08:2023/BTNMT) and lower than the allowable limits stated in the national technical regulation on marine water quality (QCVN 10:2023/BTNMT). The outcomes of this study will provide more information to support managers to come up with a better socio-economic development plan for Hai Phong city to achieve sustainable development.

Genetic diversity and inferred ancestry of Asian lotus(Nelumbo nucifera) germplasms in Thailand and Vietnam

Tropical lotus(Nelumbo) is an important and unique ecological type of lotus germplasm.Understanding the genetic relationship and diversity of the tropical lotus is necessary for its sustainable conservation and utilization.Using 42 EST-SSR(expressed sequence tag-simple sequence repeats) and 30 SRAP(sequence-related amplified polymorphism) markers,we assessed the genetic diversity and inferred the ancestry of representative tropical lotus from Thailand and Vietnam.In total,164 and 41 polymorphic bands were detected in 69 accessions by 36 EST-SSR and seven SRAP makers,respectively.Higher genetic diversity was revealed in Thai lotus than in Vietnamese lotus.A Neighbor-Joining tree of five main clusters was constructed using combined EST-SSR and SRAP markers.Cluster Ⅰ included 17 accessions of Thai lotus;cluster Ⅱ contained three Thai accessions and 11 accessions from southern Vietnam;and cluster Ⅲ was constituted by 13 accessions of seed lotus.Consistent with the results from the NeighborJoining tree,the genetic structure analysis showed that the genetic background of most Thai and Vietnamese lotus was pure,as artificial breeding has been rare in both countries.Furthermore,these analyses indicate that Thai and Vietnamese lotus germplasms belong to two different gene pools or populations.Most lotus accessions are genetically related to geographical distribution patterns in Thailand or Vietnam.Our findings showed that the origin or genetic relationships of some unidentified lotus sources can be evaluated by comparing morphological characteristics and the data of molecular markers.In addition,these findings provide reliable information for the targeted conservation of tropical lotus and parent selection in breeding novel cultivars of lotus.

Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station;the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station;the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station;and the drought peak tends to decrease at 18 stations and increase at 1 station.

Conflict management styles of nurse managers and influencing factors in children’s hospital, Vietnam

Objective:This study aimed to describe the conflict management styles and identify factors affecting the conflict management styles of nurse managers.Materials and Methods:A cross-sectional study was conducted by interviewing nurse managers with a questionnaire,including the Rahim Organizational Conflict Inventory-II Form B,used to assess an individual’s approach to conflict management across five styles:cooperating,competing,compromising,obliging,and avoiding.Results:A total of 30 nurse managers participated in this study.The mean scores of the cooperating style were the highest at 4.3±0.4,followed by a compromising style at 3.4±0.5,an avoiding style at 3.1±0.6,an accommodating style at 2.9±0.7,and a competing style at 2.8±0.8(χ^(2)=66.624,P<0.001).The mean scores for avoiding style among bachelor’s degree nurse managers(3.2±0.6)were higher than those of master’s degree nurse managers(2.7±0.6)(P=0.036).Nurse managers over 40 years old,holding a managerial position for≥10 years,and frequent conflict handling rated higher mean scores for the cooperating style than their counterparts(P<0.05).Conclusion:The cooperating style was the most commonly used conflict management style among nurse managers.Factors affecting the conflict management style were age,education level,and experience in management and conflict handling.These findings are useful for developing interventions that enhance the competencies of nurse managers in conflict management.

Artificial Intelligence Technique in Hydrological Forecasts Supporting for Water Resources Management of a Large River Basin in Vietnam

Hydrological forecasting plays an important role in water resource management, supporting socio-economic development and managing water-related risks in river basins. There are many flow forecasting techniques that have been developed several centuries ago, ranging from physical models, physics-based models, conceptual models, and data-driven models. Recently, Artificial Intelligence (AI) has become an advanced technique applied as an effective data-driven model in hydrological forecasting. The main advantage of these models is that they give results with compatible accuracy, and require short computation time, thus increasing forecasting time and reducing human and financial effort. This study evaluates the applicability of machine learning and deep learning in Hanoi water level forecasting where it is controlled for flood management and water supply in the Red River Delta, Vietnam. Accordingly, SANN (machine learning algorithm) and LSTM (deep learning algorithm) were tested and compared with a Physics-Based Model (PBM) for the Red River Delta. The results show that SANN and LSTM give high accuracy. The R-squared coefficient is greater than 0.8, the mean squared error (MSE) is less than 20 cm, the correlation coefficient of the forecast hydrology is greater than 0.9 and the level of assurance of the forecast plan ranges from 80% to 90% in both cases. In addition, the calculation time is much reduced compared to the requirement of PBM, which is its limitation in hydrological forecasting for large river basins such as the Red River in Vietnam. Therefore, SANN and LSTM are expected to help increase lead time, thereby supporting water resource management for sustainable development and management of water-related risks in the Red River Delta.

Research on Technical Solutions to Renovate the Reinforced Concrete Constructions in Vietnam

During the use of constructions, they will be degraded. Due to the negative impact on structures such as increase in vertical load, horizontal windy load needs to evaluate the current state of the constructions before renovating, especially the current state of the main structural system whether necessary to carry out repair and reinforcement or not. In addition, the inspection of the current status constructions before renovating is also the legal basis for the granting of construction permits to renovate and repair degraded works. Reinforced concrete buildings in the coastal areas in Vietnam, in particular, are working in the marine environment leading to damage the reinforced concrete construction. It should be significantly noted. Although there have been legal documents related to the inspection of constructions issued in Vietnam, the detailed contents and procedures of institution for each type of construction have not been mentioned yet. Therefore, the topic research paper of “research on technical solutions to renovate constructions with reinforced concrete structures in Vietnam” is to improve the quality and efficiency of construction. This investigation in Vietnam is very essential. This study uses the method of surveying the current state of the construction works in use, using the experimental sampling method to analyze and evaluate the damage of the work, then propose typical solutions to repair construction. The purpose of this study is to provide a process to check the damage of the works, and to propose solutions to repair them. This work is very important and has practical significance, helping managers to maintain works better.