Eco-efficiency analysis of sustainability-certified coffee production in Vietnam

There is a belief that sustainability-certified coffee production helps increase economic benefits to farmers and reduces negative environmental impacts. However, the international empirical evidence is not conclusive. Also, there is a lack of empirical evidence for Vietnam - the world's second-largest coffee producing country. This paper provides the first empirical examination of the differences in eco-efficiency between conventional and sustainability-certified coffee-growing farms in Vietnam. Data of 726 farms in Vietnam over three crop years from 2012/13 to 2014/15 are analysed. Environmental pressures measured by the level of consumption of nitrogen, phosphorus, irrigation water, pesticides, herbicides, fungicides, and land are investigated in relation to the value-added of coffee production. Empirical results show that in each crop year, coffee farms could reduce environmental pressures by more than 50% while holding the value-added of outputs constant. On average, sustainability-certified farms are found to be more eco-efficient than conventional farms, but efficiency differences appear to converge over time. This convergence may be due to positive externalities of certification, less compliance to certification standards or the combination of these effects. Higher eco-efficiency levels are also correlated with farms located in higher elevation locations, having wind-break trees, and using drip or spray irrigation systems. These should be taken into account as policy options to sustain and improve the positive effects of certification in regard to both economic and environmental aspects, rather than rapid expansion of certified production. Further, one could incorporate ecological and environmental dimensions and welfare into eco-efficiency models and a stochastic production environment may be a useful modeling approach

Unveiling urban households’ livelihood vulnerability to climate change: An intersectional analysis of Hue City, Vietnam

This study applies the Livelihood Vulnerability Index within the IPCC vulnerability framework (LVI-IPCC) to assess the vulnerability of households to climate change in Hue City, Vietnam. The research then seeks to identify critical factors contributing to household vulnerability to climate change via a regression model, while concurrently conducting an intersectional analysis that considers gender, geographical location, and economic status. Using a cross-sectional data collection methodology, we surveyed 1080 households across 36 communes/wards in Hue City from October to December 2022 employing a semi-structured questionnaire. Our findings indicate that households situated on the periphery, particularly those recently incorporated, are at a higher risk of vulnerability to climate change and natural disasters. Poor households in peri-urban areas are the most susceptible to the impacts of environmental stressors. Furthermore, women are less adaptable than men, partly due to their limited decision-making power. Factors such as household head characteristics, degree of climate risk, food security, knowledge and skills, and social networks are identified as critical in contributing to vulnerability. Reconizing these, our study emphasizes the urgent need for integrated approaches to address multiple dimensions of vulnerability and climate change adaptation in Hue City and beyond. This includes investing in peri-urban areas, addressing poverty and inequality, promoting gender-sensitive approaches, and addressing the critical factors simultaneously to enhance the resilience of cities to climate change and natural disasters

An Application of the Super-SBM MAX and LTS(A,A,A) Models to Analyze the Business Performance of Hydropower Suppliers in Vietnam

As Vietnam continues to industrialize and modernize, such economic development and high-tech will require a major electrical energy source to operate the electrical equipment; hence, the hydropower plants are established and growing up to demand. Therefore, the purpose of this study is to evaluate the business performance of Vietnamese hydropower suppliers by integrating the LTS(A,A,A) model of the Additive Holt-winters method in Tableau and a super-slacks-based measure (super-SBM) max model in data envelopment analysis (DEA). The LTS(A,A,A) model is applied to forecast future valuation from 2022 to 2025 based on historical time series from 2012 to 2021. Next, with the actual and predicted data, the researcher uses the super-SBM max model to calculate the business performance of these hydropower suppliers from past to future. The empirical result reveals efficient and inefficient cases to explore which hydropower suppliers can achieve the business performance in their operational process. The position of hydropower suppliers in Vietnam from past to future time is determined particularly based on their scores every year. Further, the empirical result recommends a solution to deal with inefficient cases by deducting the input excesses and raising the output shortages based on the principle of the super-SBM Max model in DEA. The finding results create an overview of the operational process with the continuing variations in each period to equip hydropower suppliers in Vietnam which will determine their future and operational orientation

An Application of the Super-SBM MAX and LTS(A,A,A) Models to Analyze the Business Performance of Hydropower Suppliers in Vietnam

As Vietnam continues to industrialize and modernize, such economic development and high-tech will require a major electrical energy source to operate the electrical equipment; hence, the hydropower plants are established and growing up to demand. Therefore, the purpose of this study is to evaluate the business performance of Vietnamese hydropower suppliers by integrating the LTS(A,A,A) model of the Additive Holt-winters method in Tableau and a super-slacks-based measure (super-SBM) max model in data envelopment analysis (DEA). The LTS(A,A,A) model is applied to forecast future valuation from 2022 to 2025 based on historical time series from 2012 to 2021. Next, with the actual and predicted data, the researcher uses the super-SBM max model to calculate the business performance of these hydropower suppliers from past to future. The empirical result reveals efficient and inefficient cases to explore which hydropower suppliers can achieve the business performance in their operational process. The position of hydropower suppliers in Vietnam from past to future time is determined particularly based on their scores every year. Further, the empirical result recommends a solution to deal with inefficient cases by deducting the input excesses and raising the output shortages based on the principle of the super-SBM Max model in DEA. The finding results create an overview of the operational process with the continuing variations in each period to equip hydropower suppliers in Vietnam which will determine their future and operational orientation

Scale and scope economies in small household rice farming in Vietnam

The Vietnamese agricultural sector has experienced a dramatic structural change based on increased specialization in rice cultivation. However, small-scale rice-farmers have continued to grow multiple crops, especially in less developed provinces. While the literature advocates crop diversification for reasons of both economic and ecological sustainability, there lacks empirical evidence as to whether crop diversification brings efficiency and productivity gains to small farms. The present study is the first applications of the input-oriented stochastic distance function approach in estimating scale and scope economies using data of multi-crop farming households in Vietnam. We find strong evidence of product-specific economies of scale. Scope economies are also present for rice, vegetable, and other annual crop production. This suggests that crop diversification enhances efficiency and productivity. However, there still exists significant technical inefficiency in crop production, indicating opportunities to expand farm output at the existing level of inputs and technologies. More specifically, our empirical results indicate that it is desirable to expand vegetable and other annual crop production in mountainous areas while rice cultivation can be further expanded in delta and coastal regions.</p

BIẾN ĐỘNG GIÁ ĐẤT ĐÔ THỊ TRONG GIAI ĐOẠN 2017–2020: TRƯỜNG HỢP NGHIÊN CỨU TẠI THÀNH PHỐ ĐÀ NẴNG

This study aimed at clarifying the situation of the urban land use rights market in Da Nang city in the period of 2017–2020, as well as assessed the impact of the Covid-19 pandemic on the real estate market in Da Nang city. The research results have shown that, , the price of residential land in urban areas increased continuously from 2017 to 2019 and decreased when appearing the Covid-19 epidemic in 2020. The average rate of increasing prices in the period of 2017 – 2018 and 2018 – 2019 corresponded with 80%/year, and 50%/year. Since the period of 2019–2020, land prices have decreased markedly with -11%/year on average. In comparison with 2017, land price in 2020 increases from 100 to 160%, equivalent to an average of 25–40%/year. The magnitude of land price has a significant relationship with the rate of increasing price during the study period. Land plots have smaller or equal to 16 million VND/m2 price which have ahigher rate of increasing price than those priced greater than 16 million VND/m2. When the land market increases strongly, and signs of a “bubble”, the State's credit policy, and the supervision of the local government on real estate brokerage and trading activities are effective solutions to control the market.Bài báo này đã phân tích được diễn biến của thị trường quyền sử dụng đất ở đô thị trong giai đoạn 2017–2020 cũng như đánh giá tác động của dịch Covid-19 đến thị trường bất động sản trên địa bàn thành phố Đà Nẵng. Kết quả nghiên cứu đã cho thấy, giá đất ở tại đô thị có xu hướng tăng liên tục từ năm 2017 đến năm 2019 và giảm xuống vào năm 2020 khi dịch Covid-19 xuất hiện. Tỷ lệ tăng giá bình quân của giai đoạn 2017–2018 và 2018–2019 tương ứng với  80%/ năm và 50%/ năm.Từ giai đoạn 2019–2020, giá đất giảm rõ rệt với mức giảm bình quân khoảng -11%. So với năm 2017, giá đất năm 2020 tăng từ 100–160%, tương đương từ 25%–40%/năm. Độ lớn của giá đất có mối liên hệ rõ ràng với tỷ lệ tăng giá bình quân trong giai đoạn nghiên cứu. Những thửa đất có mức giá  16 triệu đồng/m2 có tỷ lệ tăng giá cao hơn rõ rệt so với những thửa có giá &gt; 16 triệu đồng/m2. Khi thị trường tăng mạnh và có dấu hiệu “bong bóng”, chính sách tín dụng của Nhà nước, sự giám sát chặt chẽ các hoạt động môi giới, kinh doanh bất động sản của chính quyền địa phương là giải pháp kiểm soát thị trường hiệu quả

Deep learning models for forecasting dengue fever based on climate data in Vietnam

BackgroundDengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam.ObjectiveThis study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change.MethodsConvolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).Results and discussionLSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features.ConclusionThis study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years

On the Inhibitability of Natural Products Isolated from Tetradium ruticarpum towards Tyrosine Phosphatase 1B (PTP1B) and α-Glucosidase (3W37): An In Vitro and In Silico Study

Folk experiences suggest natural products in Tetradium ruticarpum can be effective inhibitors towards diabetes-related enzymes. The compounds were experimentally isolated, structurally elucidated, and tested in vitro for their inhibition effects on tyrosine phosphatase 1B (PTP1B) and α-glucosidase (3W37). Density functional theory and molecular docking techniques were utilized as computational methods to predict the stability of the ligands and simulate interaction between the studied inhibitory agents and the targeted proteins. Structural elucidation identifies two natural products: 2-heptyl-1-methylquinolin-4-one (1) and 3-[4-(4-methylhydroxy-2-butenyloxy)-phenyl]-2-propenol (2). In vitro study shows that the compounds (1 and 2) possess high potentiality for the inhibition of PTP1B (IC50 values of 24.3 ± 0.8, and 47.7 ± 1.1 μM) and α-glucosidase (IC50 values of 92.1 ± 0.8, and 167.4 ± 0.4 μM). DS values and the number of interactions obtained from docking simulation highly correlate with the experimental results yielded. Furthermore, in-depth analyses of the structure–activity relationship suggest significant contributions of amino acids Arg254 and Arg676 to the conformational distortion of PTP1B and 3W37 structures overall, thus leading to the deterioration of their enzymatic activity observed in assay-based experiments. This study encourages further investigations either to develop appropriate alternatives for diabetes treatment or to verify the role of amino acids Arg254 and Arg676

Event-Based Surveillance at Community and Healthcare Facilities, Vietnam, 2016–2017

Surveillance and outbreak reporting systems in Vietnam required improvements to function effectively as early warning and response systems. Accordingly, the Ministry of Health of Vietnam, in collaboration with the US Centers for Disease Control and Prevention, launched a pilot project in 2016 focusing on community and hospital event–based surveillance. The pilot was implemented in 4 of Vietnam’s 63 provinces. The pilot demonstrated that event-based surveillance resulted in early detection and reporting of outbreaks, improved collaboration between the healthcare facilities and preventive sectors of the ministry, and increased community participation in surveillance and reporting

Kinetics of CD4+ T Helper and CD8+ Effector T Cell Responses in Acute Dengue Patients

Background: The protective or pathogenic role of T lymphocytes during the acute phase of dengue virus (DENV) infection has not been fully understood despite its importance in immunity and vaccine development. Objectives: This study aimed to clarify the kinetics of T lymphocyte subsets during the clinical course of acute dengue patients. Study design: In this hospital-based cohort study, 59 eligible Vietnamese dengue patients were recruited and admitted. They were investigated and monitored for T cell subsets and a panel of clinical and laboratory parameters every day until discharged and at post-discharge from the hospital. Results: We described for the first time the kinetics of T cell response during the clinical course of DENV infection. Severe cases showed significantly lower levels of effector CD8+ T cells compared to mild cases at day ?1 (p = 0.017) and day 0 (p = 0.033) of defervescence. After defervescence, these cell counts in severe cases increased rapidly to equalize with the levels of mild cases. Our results also showed a decline in total CD4+ T, Th1, Th1/17 cells during febrile phase of dengue patients compared to normal controls or convalescent phase. On the other hand, Th2 cells increased during DENV infection until convalescent phase. Cytokines such as interferon-γ, IL-12p70, IL-5, IL-23, IL-17A showed tendency to decrease on day 0 and 1 compared with convalescence and only IL-5 showed significance indicating the production during acute phase was not systemic.Conclusion: With a rigorous study design, we uncovered the kinetics of T cells in natural DENV infection. Decreased number of effector CD8+ T cells in the early phase of infection and subsequent increment after defervescence day probably associated with the T cell migration in DENV infection