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River basins receive wastewater from socio-economic activities. In such a context, a comprehensive assessment and forecast of load-bearing capacity needs to be developed. This capacity depends on many complex factors, such as hydrology, hydraulics, and environment, leading to applying a modelling approach. This study aims to propose a hybrid modelling approach to evaluate and predict the river water environmental capacity (RWEC) in a basin. Big data technology with Python is applied to process modelling results and RWEC forecasts. The long short-term memory (LSTM) model predicts RWEC on each reach of the river channel network. The {RWECP, i, P = Nitrate, BOD, Phosphate, i = hourly} data set and related factors form a time series of data used for the LSTM forecasting model. Forecast results are evaluated through the root mean square error (RMSE) and mean absolute error (MAE). The results show that the average level over all 24 reaches for 7 forecast days: RMSENitrate = 22.16 (kg/day), RMSEBOD = 38.92 (kg/day), and RMSEPhosphate = 0.79 (kg/day). This is an acceptable result for a complex system and 7-day forecast. The results of the study help significantly with pollution control. HIGHLIGHTS Suggesting steps to determine river water environmental capacity (RWEC).; Building a forecasting model based on long short-term memory (LSTM) to predict RWEC.; Assessing and forecasting RWEC for the concrete basin.; Comparing forecast accuracy by standard metric RMSE and MAE.; Clarifying RWEC dependence on hydrodynamic and environmental factors.;

Ho Chi Minh City authorities are currently developing PM2.5 pollution control measures and implementing the Clean Air Plan (CAP) with a vision for 2030. This mission will be more convincing if the benefits from these control measures are argued. At the same time, decision-makers always need practical tools to perform assessments, compare different scenarios, quantify the impact of PM2.5 exposure and demonstrate the effectiveness of PM2.5 pollution reduction program. This study aims to present a modelling framework platform implemented in the Environment, Public Health, and Economic Benefit Management Support Integrated System (HEBIS) through a comparative analysis based on CAP's health benefit-to-control cost ratio. Moreover, implementing CAP measures also created net benefits as improvements in public health were generally much higher than technical costs. These results are the evidence to prioritize implementing different air pollution solutions from CAP. Furthermore, the HEBIS tool has provided a practical framework by which managers could further build appropriate policies to achieve multiple environmental, economic, and human health benefits.

River water environmental capacity (RWEC) is an essential indicator of sustainable development. However, there are several studies on the dependence of RWEC on hydrological and hydraulic factors, especially self-cleaning ability. This study aims to clarify the role of self-cleaning factors in RWEC formation in a specific river basin. The method used in this study employed a set of models, including hydrological and eco-hydrodynamic models, with an added set of water quality parameters. The proposed research framework was applied to a specific river basin for four selected pollutants: NH4+, NO3-, PO43-, and BOD. The results revealed that the self-cleaning factors contributed significantly to the increase in RWEC. Specifically, RWECNH4+ improved by 22.6 % in the wet season and 22.7 % in the dry season; RWECNO3- improved by 10.22 % and 13.08 % in the wet and dry seasons, respectively; RWECPO43- exhibited the most significant improvement (143 % and 73 %, respectively), RWECBOD in the dry season decreased slightly by about 9%, the wet season increased by 88.34%. Our results demonstrate the critical role of self-cleaning factors in improving the carrying capacity, leading to developing medium- and long-term plans to preserve ecosystems in river systems in different basins.

The Lower Mekong Delta region (LMD) accounts for 90% of Vietnam's rice exports; however, the air quality in the LMD is remarkably reduced by ground-level ozone (O3) pollution. This study aimed to quantify the relative yield and economic value losses in rice-growing crop seasons affected by ground-level O3 concentrations across the LMD. The results of this study can serve as a basis for extensive assessments for the following years and support environmental managers to propose control measures of O3 precursor emissions (NOx and VOCs) from man-made sectors, as well as build protective solutions for rice farming in LMD. Two ground-level O3 exposure metrics of M7 and AOT40 reflecting ground-level O3 pollution impacts, combined with the model of exposure-relative yield relationship (or surface O3-crop models), were used to assess losses of crop production (CPL) and economic cost losses (ECL) caused by rice crop yield reductions. For the M7 metric of ground-level O3 exposure, the average value was 14.746 ppbV, with levels ranging from 13.959 ppbV to 15.502 ppbV, and the affected area was spread across 1309.39 thousand hectares. The AOT40 exposure metric reached an average value of 11.490 ppbV, with a range of 0.000–31.665 ppbV. The highest exposure level was 17.503–31.653 ppbV, covering an area of 747.01 thousand hectares. The total CPL of the three rice crops over the LMD was 9593.52 tonnes (accounting for 0.039% of the total value of rice production in the region), with a total corresponding EPL of 62.405 billion VND (equivalent to 2761.01 thousand USD). The results are considered a baseline study to serve as a basis for extensive assessments for the following years and support for the environmental managers to propose control measures of O3 precursor emissions (NOx and VOCs) from man-made sectors as well as build protective solutions in rice farming in LMD shortly.

Helicobacter pylori (H. pylori) infection is prevalent and has a rapidly increasing antibiotic resistance rate in Vietnam. Reinfection is quite common, and gastric carcinoma remains one of the most common malignancies, which is not uncommon to develop after successful eradication. The purpose of this consensus is to provide updated recommendations on the management of H. pylori infection in the country. The consensus panel consisted of 32 experts from 14 major universities and institutions in Vietnam who were invited to review the evidence and develop the statements using the Delphi method. The process followed the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. The consensus level was defined as ≥80% for agreement on the proposed statements. Due to the limited availability of high-quality local evidence, this consensus was also based on high-quality evidence from international studies, especially those conducted in other populations in the Asia–Pacific region. The panel finally reached a consensus on 27 statements after two voting rounds, which consisted of four sections (1) indications for testing and selection of diagnostic tests (2), treatment regimens, (3) post-treatment confirmation of H. pylori status, and (4) reinfection prevention methods and follow-up after eradication. Important issues that require further evidence include studies on third-line regimens, strategies to prevent H. pylori reinfection, and post-eradication follow-up for precancerous gastric lesions. We hope this consensus will help guide the current clinical practice in Vietnam and promote multicenter studies in the country and international collaborations.

Access to quality veterinary antimicrobial products contributes to efficient treatment of diseases in Vietnamese livestock and to reducing antimicrobial resistance (AMR). Poor quality antimicrobial drugs can lead to treatment failure, potentially influencing the inappropriate use of antimicrobials products, including increasing the dose, combining drugs, or changing to a broader spectrum antimicrobial. The objective of the study was to determine the actual concentration of antimicrobial active ingredient (AAI) in commercially available veterinary antimicrobial products as an indicator of their quality. A total of 144 veterinary antimicrobial products were purchased from randomly selected veterinary drug stores in 34 districts in eight provinces. For the qualitative analysis, we observed criteria linked to form, colour, and labelling information according to the Department of Animal Health regulations. For the quantitative analysis, high-performance liquid chromatography was used to determine the actual concentration of AAI in each sample. Of the 144 samples, 131 (91%) met the national standard of quality of being within ±10% of the labelled concentration. Ten antimicrobials (6.9%) contained less than half of the labelled content concentrations. Veterinary antimicrobial product quality control is an important part of addressing AMR. To support the national action plan to lower AMR, a veterinary drug quality control program should be implemented at all stages of the supply chain to assure high quality drugs and effective treatment of sick animals.

Vietnam has a great demand for stone exploitation for the development of the country's infrastructure, reaching 181 million m3 in 2020. Mining activities are always accompanied by environmental pollution, negatively affecting public health. To accurately assess the level of pollution, as well as quantify the effect of air pollution on human health, a number of structures, methods, and models provide tools to assess the benefits of this control for public health and related economic values. However, there has been no research in Vietnam applied specifically to this type of stone exploitation. This study offers a model to evaluate the economic damage caused by dust exposure from activities related to quarrying, overcoming the lack of continuous monitoring data. The area selected for research is Binh Duong province, in the Ho Chi Minh megapolis, Vietnam, which has two construction quarries, Thuong Tan and Tan My, with a current annual production of approximately 4–5 million m3. The calculation results show that the damage to human health is estimated at approximately 9,643 billion dong a year, equivalent to 15.03 million USD. In addition, if the standard criteria are tightened, damage will continue to increase. This study also analyses some of the difficulties and limitations in the modelling process.

PM2.5 pollution exposure is the leading cause of disease burden globally, especially in low- and middle-income countries, including Vietnam. Therefore, economic damage in this context must be quantified. Long An province in the Southern Key Economic (SKE) region was selected as a research area. This study aimed to evaluate PM2.5-related human health effects causing early deaths attributable to respiratory, cardiovascular, and circulatory diseases in all ages and genders. Health end-points and health impact estimation, economic loss model, groups of PM2.5 concentration data, data of exposed population, data of baseline premature mortality rate, and data of health impact functions were used. Hourly PM2.5 concentration data sets were generated specifically using the coupled Weather Research and Forecasting Model (WRF)/Community Multiscale Air Quality Modelling System (CMAQ) models. Daily PM2.5 pollution levels considered mainly in the dry season (from January to April 2018) resulted in 12.9 (95% CI − 0.6; 18.7) all-cause premature deaths per 100,000 population, of which 7.8 (95% CI 1.1; 7.1), 1.5 (95% CI − 0.2; 3.1), and 3.6 (95% CI − 1.5; 8.5) were due to respiratory diseases (RDs; 60.54%), cardiovascular diseases (CVDs; 11.81%), and circulatory system diseases (CSDs; 27.65%) per 100,000 population, respectively. The total economic losses due to acute PM2.5 exposure-related premature mortality cases reached 62.0 (95% CI − 2.7; 89.6) billion VND, equivalent to 8.3 (95% CI − 0.4; 12.0) million USD. The study outcomes contributed remarkably to the generation and development of data sources for effectively managing ambient air quality in Long An. [ABSTRACT FROM AUTHOR]

Abstract Background Grazing exclusion is a practical approach to restore vegetation in degraded grasslands and enhance soil organic carbon (SOC) sequestration. However, the dynamics and drivers of SOC in grasslands after grazing exclusion have not been well documented, especially in ecosystems with cold climates. Methods Here, we established 14 paired treatments (grazing exclusion vs. free-grazing) along a 600-km transect in the northeastern zone of the Qinghai-Tibet Plateau. After six years, we analyzed vegetation biomass dynamics and measured the soil physicochemical properties and organic C concentration across three depths (0–10, 10–20, and 20–30 cm). Results Grazing exclusion significantly increased above- and belowground biomass (139.85% and 43.30%, respectively), pH (1.38%), total phosphorus (3.29%), nitrate nitrogen (18.03%), and ammonium nitrogen (17.81%), but significantly decreased soil bulk density (2.43%) and clay content (10.49%), particularly in 0–30 cm. Specifically, SOC concentrations positively responded to grazing exclusion (0–10 cm) in 9 of the 14 sites evaluated. The effects of grazing exclusion on SOC concentrations were significantly higher in areas with a mean annual temperature (MAT) below 0 °C compared to those in sites with a high MAT (> 0 °C). The SOC concentrations significantly correlated with the mean annual precipitation (MAP) in both treatments, but these correlations diminished with increasing soil depth. Ridge regression analysis showed that soil chemical properties (e.g., total nitrogen and phosphorus) positively influenced SOC accumulation, while MAT negatively influenced it after grazing exclusion. Path analysis further revealed that MAT indirectly regulated SOC dynamics via soil chemical properties. Conclusions Our study highlights that grazing exclusion results in an asynchronous SOC and plant biomass accumulation and may be more beneficial for SOC sequestration in Qinghai-Tibet Plateau grasslands with lower temperatures. Also, humid climates promote SOC concentration in alpine grasslands. These results could help develop management practices and policies that promote sustainable grassland management.

Abstract Study of the interaction between fault activation and mining stress evolution in the longwall working face is helpful to provide a targeted area for fault type heavy mine pressure disaster control. Combining theoretical analysis, physical and numerical simulation, the mechanical mechanism of fault activation is analyzed, the interaction law between mining stress and fault activation is studied, and the influence of fault dip angle on the evolution of fault activation and mining stress is discussed. The minimum critical dip angles α of normal and reverse fault activation are π/4 + φ/2 and π/4-φ/2, respectively. During the mining process, the activation position of the fault surface, the peak values of stress and displacement gradually increase and transfer from the high position of the fault to the low position, and the peak value of the advance abutment pressure reaches the maximum at the fault. The advancing distance of the working face required for fault activation gradually decreases with the decrease of the fault dip angle, and the peak elevation area of the working face gradually increases with the decrease of the fault dip angle. Combined with the on-site microseismic monitoring results, it can be seen that when the working face is about 20 m away from the fault, the stress and energy increase sharply, which is the main control area of the impact disaster.

Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025–2030. [ABSTRACT FROM AUTHOR]

Abstract Traditional vehicular edge computing research usually ignores the mobility of vehicles, the dynamic variability of the vehicular edge environment, the large amount of real‐time data required for vehicular edge computing, the limited resources of edge servers, and collaboration issues. In response to these challenges, this article proposes a vehicular edge computing optimization scheme based on the Lyapunov function and Deep Reinforcement Learning. In this solution, this article uses Digital Twin technology (DT) to simulate the vehicular edge environment. The edge server DT is used to simulate the vehicular edge environment under the edge server, and the base station DT is used to simulate the entire vehicular edge system environment. Based on the real‐time data obtained from DT simulation, this paper defines the Lyapunov function to simplify the migration cost of vehicle tasks between servers into a multi‐objective dynamic optimization problem. It solves the problem by applying the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. Experimental results show that compared with other algorithms, this scheme can effectively optimize the allocation and collaboration of vehicular edge computing resources and reduce the delay and energy consumption caused by vehicle task processing.

Abstract The geological phenomenon of igneous rock invading coal seam is widely distributed, which induces mining risk and affects efficient mining. The pre-splitting blasting method of igneous rock is feasible but difficult to implement accurately, resulting in unnecessary safety and environmental pollution risks. In this paper, the blasting model with penetrating structural plane and the multi-hole blasting model with different hole spacing were established based on the Riedel–Hiermaier–Thoma (RHT) damage constitutive to explore the stress wave propagation law under detonation. The damage cloud diagram and damage degree algorithm were used to quantitatively describe the spatio-temporal evolution of blasting damage. The results show that the explosion stress wave presents a significant reflection stretching effect under the action of the structural plane, which can effectively aggravate the presplitting blasting degree of the rock mass inside the structural plane. The damage range of rock mass is synchronously evolved with the change of blasting hole spacing. The blasting in the igneous rock intrusion area of the 21,914 working face is taken as an application example, and the damage degree of rock mass is reasonably evaluated by the box-counting dimension and K-means clustering method, which proves the effectiveness of the blasting scheme and provides reference value for the implementation of related blasting projects.