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Salinity intrusion is a pressing issue in the coastal areas worldwide. It affects the natural environment and causes massive economic loss due to its impacts on the agricultural productivity and food safety. Here, we assessed the salinity intrusion in the Tra Vinh Province, in the Mekong Delta of Vietnam. Landsat 8 OLI image was utilized to derive indices for soil salinity estimate including the single bands, Vegetation Soil Salinity Index (VSSI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Salinity Index (NDSI). Statistical analysis between the electrical conductivity (EC1:5, dS/m) and the environmental indices derived from Landsat 8 OLI image was performed. Results indicated that spectral values of near-infrared (NIR) band and VSSI were better correlated with EC1:5 (r2 = 0.8 and r2 = 0.7, respectively) than the other indices. Comparative results show that soil salinity derived from Landsat 8 was consistent with in situ data with coefficient of determination, R2 = 0.89 and RMSE = 0.96 dS/m for NIR band and R2 = 0.77 and RMSE = 1.27 dS/m for VSSI index. Findings of this study demonstrate that Landsat 8 OLI images reveal a high potential for spatiotemporally monitoring the magnitude of soil salinity at the top soil layer. Outcomes of this study are useful for agricultural activities, planners, and farmers by mapping the soil salinity contamination for better selection of accomodating crop types to reduce economical loss in the context of climate change. Our proposed method that estimates soil salinity using satellite-derived variables can be potentially useful as a fast-approach to detect the soil salinity in the other regions with low cost and considerable accuracy.

BackgroundStudies of early childhood outcomes of mild hypoxic-ischemic encephalopathy (HIE) identified in the first 6 h of life are lacking.ObjectiveTo evaluate neurodevelopmental outcomes at 18–22 months of PRIME study.Study designMulticenter, prospective study of mild HIE defined as ≥1 abnormality using the modified Sarnat within 6 h of birth and not meeting cooling criteria. Primary outcome was disability with mild: Bayley III cognitive 70–84 or ≥85 and either Gross Motor Function Classification System (GMFCS) 1 or 2, seizures, or hearing deficit; moderate: cognitive 70–84 and either GMFCS 2, seizures, or hearing deficit; severe: cognitive <70, GMFCS 3–5.ResultsOf the 63 infants enrolled, 51 (81%) were evaluated at 19 ± 2 months and 43 (68%) completed Bayley III. Of the 43 infants, 7 (16%) were diagnosed with disability, including 1 cerebral palsy and 2 autism. Bayley scores < 85 in either cognition, motor, or language were detected in 17 (40%): 14 (32%) language, 7 (16%) cognitive, and 6 (14%) motor domain. Infants with disability had more abnormalities on discharge examination and brain MRI, with longer hospital stay (p < 0.001).ConclusionsIn this contemporary untreated cohort of mild HIE, disability occurred in 16% of infants at 18–22 months.

Many regions worldwide suffer from heavy air pollution caused by particulate matter (PM2.5) and nitrogen dioxide (NO2), resulting in a huge annual disease burden and significant welfare costs. Following the outbreak of the COVID-19 global pandemic, enforced curfews and restrictions on human mobility (so-called periods of ‘lockdown’) have become important measures to control the spread of the virus. This study aims to investigate the improvement in air quality following COVID-19 lockdown measures and the projected benefits for environmental health. China was chosen as a case study. The work projects annual premature deaths and welfare costs by integrating PM2.5 and NO2 pollutant measurements derived from satellite imagery (MODIS instruments on Terra and Aqua, and TROPOMI on Sentinel-5P) with census data archived by the Organization for Economic Co-operation and Development (OECD). A 91-day timeframe centred on the initial lockdown date of 23 January 2020 was investigated. To perform the projections, OECD data on five variables from 1990 to 2019 (mean population exposure to ambient PM2.5, premature deaths, welfare costs, gross domestic product and population) were used as training data to run the Autoregressive Integrated Moving Average (ARIMA) and multiple regression models. The analysis of the satellite imagery revealed that across the regions of Beijing, Hebei, Shandong, Henan, Xi’an, Shanghai and Hubei, the average concentrations of PM2.5 decreased by 6.2, 30.7, 14.1, 20.7, 29.3, 5.5 and 17.3%, while the NO2 decreased by 45.5, 54.7, 60.5, 58.7, 63.6, 50.5 and 66.5%, respectively, during the period of lockdown restrictions in 2020, as compared with the equivalent period in 2019. Such improvements in air quality were found to be beneficial, reducing in 2020 both the number of premature deaths by approximately 97,390 and welfare costs by over USD 74 billion.

Hanoi City of Vietnam changes quickly, especially after its state implemented its Master Plan 2030 for the city’s sustainable development in 2011. Then, a number of environmental issues are brought up in response to the master plan’s implementation. Among the issues, the Urban Heat Island (UHI) effect that tends to cause negative impacts on people’s heath becomes one major problem for exploitation to seek for mitigation solutions. In this paper, we investigate the land surface thermal signatures among different land-use types in Hanoi. The surface UHI (SUHI) that characterizes the consequences of the UHI effect is also studied and quantified. Note that our SUHI is defined as the magnitude of temperature differentials between any two land-use types (a more general way than that typically proposed in the literature), including urban and suburban. Relationships between main land-use types in terms of composition, percentage coverage, surface temperature, and SUHI in inner Hanoi in the recent two years 2016 and 2017, were proposed and examined. High correlations were found between the percentage coverage of the land-use types and the land surface temperature (LST). Then, a regression model for estimating the intensity of SUHI from the Landsat 8 imagery was derived, through analyzing the correlation between land-use composition and LST for the year 2017. The model was validated successfully for the prediction of the SUHI for another hot day in 2016. For example, the transformation of a chosen area of 161 ha (1.61 km2) from vegetation to built-up between two years, 2016 and 2017, can result in enhanced thermal contrast by 3.3 °C. The function of the vegetation to lower the LST in a hot environment is evident. The results of this study suggest that the newly developed model provides an opportunity for urban planners and designers to develop measures for adjusting the LST, and for mitigating the consequent effects of UHIs by managing the land use composition and percentage coverage of the individual land-use type.

In international trade, exporters prefer to receive payments as quickly as possible, and importers want to make payments as late as possible. In this respect, the payment field, an essential condition for trade transactions, also represents the positions of exporters and importers conflict. In addition, there are many cases in which various variables must be considered rather than only one specific variable representatively affecting payment, particularly in the case of import-export Small and Medium-Sized Enterprises (SMEs) from emerging countries. A selection of proper payment methods can be categorized as a Multi-Criteria Decision-Making (MCDM) issue. Therefore, this study aims to propose a novel and efficient Spherical Fuzzy Weighted Aggregated Sum Product Assessment based Entropy Objective Weighting method (SF-EW and WASPAS-SF) to evaluate international payment methods with uncertain information. First, SF-EW model is applied to determine the relative weights of critical factors. Second, international payment method alternatives are prioritized by the WASPAS-SF approach. Five essential factors for four international payment methods are proposed based on experts’ opinions and the existing literature. A real-world case study from Vietnamese import-export SMEs is presented to validate the applicability of the proposed framework. The results indicated that “Characteristics of payment method (PA)” had the most significant impact on international payment method selection. In comparison, “Letters of Credit (L/C)” was the most reliable payment method with the highest ranking available to international traders. Furthermore, a sensitivity analysis was performed to examine the validity and robustness of the proposed decision support model. Consequently, this study could contribute to international payment services and in the context of globalization and international trade.

The structural knowledge of membrane proteins (MPs) is crucial for the structure‐based drug design. The stabilization of MPs during extraction processes is essential for structural and functional maintenance. In this regard, detergents are used to achieve extractions of MPs in their functional form. Based on previous work showing the importance of adjacent dicarboxylate groups for the detergency properties, the synthesis of a new generation of detergents bearing more dicarboxylate groups is reported. The molecular structure of the new generation is characterized by the presence of four chemical entities: a DOTA or NOTA scaffold, three or four pairs of carboxylates, a fatty acid, and PEG chains. The preliminary biochemical evaluation reveals promising features of this novel generation of surfactants for the aqueous extraction of MPs. A novel generation of NOTA and DOTA derivatives is designed and synthesized as potential surfactants for the extraction and stabilization of membrane proteins in aqueous solution.

The government of Vietnam has selected shrimp production and exports as the pillars of rural economic development. The targets set depend on high yields through production intensification. International and national public research communities have raised production intensification concerns related to environmental and climate change challenges, such as saltwater intrusion, water pollution, disease outbreaks, mangrove destruction, and natural resource degradation. Social snags such as user right conflicts of water resources, food safety problems, tariff barriers, and attempts to taint the industry’s image by competitors also plague the industry. These give rise to the problem of certification and questions about the influence of standards on the small-scale farming sustainability in a competitive global environment. The questions asked are, how can one bring together small-scale shrimp farmers to comply with international standards? Can small-scale shrimp farming co-exist with super-intensive producers to bring about a sustainable and competitive industry? A proposed model to horizontally organize the limited resource farmers into cooperatives to vertically integrate with large-scale firms producing shrimp using super-intensive production methods shows small-scale farmers adopting super-intensive production methods that can generate higher yields, income, profits, and is more environmentally friendly and requires less water and land. The capital requirements are high for limited resource farmers. However, with the interest showed by banks in financing models that are appropriate for small-scale farms integrated with larger firms engaged in super-intensive production systems, along with government assistance, these small-scale shrimp producing units can attain higher levels of sustainability than the open, less intensive production systems.

The unprecedented coronavirus pandemic (COVID-19) is fluctuating worldwide. Since the COVID-19 epidemic has a negative impact on all countries and has become a significant threat, it is necessary to determine the most effective strategy for governments by considering a variety of criteria; however, few studies in the literature can assist governments in this topic. Selective governmental intervention during the COVID-19 outbreak is considered a Multi-Criteria Decision-Making (MCDM) problem under a vague and uncertain environment when governments and medical communities adjust their priorities in response to rising issues and the efficacy of interventions applied in various nations. In this study, a novel hybrid Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Fuzzy Weighted Aggregated Sum Product Assessment (WASPAS-F) model is proposed to help stakeholders such as governors and policymakers to prioritize governmental interventions for dealing with the COVID-19 outbreak. The SF-AHP is implemented to measure the significance of the criteria, while the WASPAS-F approach is deployed to rank intervention alternatives. An empirical case study is conducted in Vietnam. From the SF-AHP findings, the criteria of “effectiveness in preventing the spread of COVID-19”, “ease of implementation”, and “high acceptability to citizens” were recognized as the most important criteria. As for the ranking of strategies, “vaccinations”, “enhanced control of the country’s health resources”, “common health testing”, “formation of an emergency response team”, and “quarantining patients and those suspected of infection” are the top five strategies. Aside from that, the robustness of the approach was tested by performing a comparative analysis. The results illustrate that the applied methods reach the general best strategy rankings. The applied methodology and its analysis will provide insight to authorities for fighting against the severe pandemic in the long run. It may aid in solving many complicated challenges in government strategy selection and assessment. It is also a flexible design model for considering the evaluation criteria. Finally, this research provides valuable guidance for policymakers in other nations.

Islamabad is essentially the only well-planned city in Pakistan, but groundwater depletion has become a serious issue there because of the rapid increase in population, poor water management, and deforestation. The current water demand of the city is about 220 million gallons per day, with the Capital Development Authority (CDA) providing up to 70 million gallons per day. The need for water is mostly fulfilled through groundwater sources, such as water bores and commercial tube wells. Hence, identifying recharge sites for natural aquifers is a significant component of groundwater required to overcome the water crisis. Therefore, this study aims to identify potential sites for natural aquifer recharge by using analytical hierarchy process (AHP), weighted linear combination (WLC), and fuzzy logic methods. To achieve the stated objective, seven local influencing factors including soil, slope, water table, population density, land use land cover (LULC), drainage density, and elevation have been utilized in this study. AHP was utilized for the evaluation of the relative importance of the above-mentioned factors, while fuzzy logic was applied for the standardization of these factors. Finally, the AHP-WLC and fuzzy logic approaches were used to merge factor maps in order to identify suitable sites for natural aquifer recharge in Islamabad City. Two different suitability maps were constructed from both techniques, and on each of the resulting maps, the subregions were categorized into five classes: not suitable, less suitable, moderate, suitable, and most suitable. Based on the AHP-WLC results, 5% of the whole study area is deemed most suitable for natural aquifer recharge (NAR), whereas from the fuzzy logic results, 10% of the study area is marked as most suitable. In contrast, 37% and 32% of the whole study area were identified as suitable by the AHP-WLC and fuzzy logic methods, respectively. While both techniques can obtain satisfactory outcomes, the suitability map from fuzzy logic has produced more precise results. Hence, we propose to CDA-Islamabad here different sites for recharge wells based on the results of fuzzy logic. As recommended by this study, to date CDA has constructed twelve recharge wells.

The consequences for agricultural production are several: impaired plant uptake of water and essential nutrients, negative effects on crop growth and development, higher weed competition, lower soil microbial activity, and overall crop productivity reduction. According to the National Center for Hydro-meteorological Forecasting, Vietnam Ministry of Natural Resources and Environment, the severity of saline intrusion in the Mekong Delta is expected to increase in the dry season of 2023, further threatening rice supply in the foreseeable future. 3. A climate variation toward drier and warmer conditions is predicted (BSh, hot semi-arid climate). [...]the process of saltwater intrusion is expected to worsen. Here, climate change could lead to higher temperatures with hot summers, shifting to a hot semi-arid climate zone (BSh). [...]it could experience an intensification in the frequency of heat waves, with potential impacts on agriculture.