Does exchange rate policy matter for economic growth? Vietnam evidence from a co-integration approach

Both economic growth and exchange rate theories suggest that the exchange rate regime could have consequences for the medium-term growth of a country, directly, through its effects on the adjustment to shocks, and indirectly, through its impact on the important determinants of growth. It is, however, surprising that there was little empirical work investigating the indirect relationship between the exchange rate policy and economics growth in the case of a specific country. In a co-integration framework, our research attempts to fill the gap by econometrically investigating the possible impacts of exchange rate regime on economic growth through two main channels - Foreign direct investment (FDI) and Exports - in the case of Vietnam - a successful example of a transitional economy.Exports, Exchange Rate, FDI, Growth, Co-integration

Challenges in Employing BASEL II at Military Commercial Joint Stock Bank

This paper is conducted for examining the framework for risk management in the Basel II accord, the Basel II risk management model at the Military Commercial Joint Stock Bank. Data were collected from annual reports for the period from 2015 to 2017 of the Military Commercial Joint Stock Bank. The results show that the implementation of risk management under Basel II at Military Bank still faces many difficulties in the pressure of capital increase, database system, human resource quality, and cost of implementation. The study suggests some solutions for Military Bank to implement successfully Basel II, emphasizing the role of human resource quality, modernizing the data system and the specific mechanism for raising capital. The results of this research is a reference for Vietnamese commercial banks in identifying, controlling and responding various risks in banking activities in the context of Vietnam in particular and in emerging countries in general. Keywords: Basel II, Risk management, Military Ban

Primary Evaluation on Growth Performances of Stress Negative Piétrain Pigs Raised in Hai Phong Province of Vietnam

peer reviewedThe present study was carried out on 19 stress negative Piétrain pigs (Pietrain ReHal), consisting of 13 gilts and 6 young boars imported from Belgium, raised in the livestock farm of Dong Hiep (Hai Phong) in order to evaluate growth performances and their adaptability in the North of Vietnam. Results showed that the average body weight of the whole herd at 2, 4, 5.5, and 8.5 months old was 19.05, 51.05, 85.82, and 119.47 kg, respectively. During the growing periods, except the first stage, the male grew faster than the female and the pigs of the CT genotype grew faster than those of CC genotype although the difference was not significant (P>0.05). The average daily gain (ADG) was 528.56 grams for the whole herd. The ADG was higher for the male (546.48 grams) than for the female (520.29 grams), and its was higher for the CT than the CC, but the difference was not statistically significant (P>0.05). The feed conversion ratio (FCR) was 2.69 kg. The estimated lean percentage at 8.5 months old was 64.08%. The results indicate that Piétrain stress negative pigs could develop well on the farm conditions in Hai Phong, Vietnam

Catalytic Dye Oxidation over CeO2 Nanoparticles Supported on Regenerated Cellulose Membrane

A novel regenerated cellulose (RC) membrane containing cerium oxide (CeO2) nanoparticles is described in detail. In this work, CeO2 nanoparticles with high surface area and mesoporosity were prepared by a modified template-assisted precipitation method. Successful synthesis was achieved using cerium nitrate as a precursor, adjusting the final pH solution to around 11 by ammonium hydroxide and ethylene diamine, and annealing at 550 °C for 3 hours under a protective gas flow. This resulted in a surface area of 55.55 m².g–1 for the nanoparticles. The regenerated cellulose membrane containing CeO2 particles was synthesized by the novel and environmentally friendly method. The catalyst CeO2 and cellulose/CeO2 membrane were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Electron paramagnetic resonance (EPR), and Brunauer-Emmett-Teller (BET) measurements. The g-value of 2.276 has confirmed the presence of the surface superoxide species of CeO2 nanoparticles in EPR. The photocatalytic activity of the catalyst and the membrane containing the catalyst was evaluated through the degradation of methylene blue under visible light irradiation by UV-VIS measurements. The cellulose/CeO2 membrane degraded 80% of the methylene blue solution in 120 minutes, showing a better photocatalytic activity than the CeO2 catalyst, which degraded approximately 62% in the same period. It has been proven that the RC membrane is not only a good transparent supporting material but also a good adsorption for high-performance of CeO2 catalyst. Copyright © 2022 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

A nutrient method for cutivation of macroalgae Ulva papenfussii

Macroalgae species of the genus Ulva are widely distributed in the wild. Many species of this genus has been used as food as an attractive material for the study of materials, fuels, food etc.. In this paper, we are focusing on nutrient method for cultivation of Ulva papenfussii and A nutrient source for cultivation of U. papenfussii was also investigated with the perspective of utilizing the produced biomass for feed. U. papenfussii is fragmented into 1 × 1 cm size, then it keep in Ulva extract of 0.1 g/l concentrate for 7 days. Then continue to keep fragments in the following conditions: 20 ml/l of PES medium, 700 μmol photon/m2/s of light, 25oC of temperature, 3% of salinity, 28 days of time. Under this condition the productivity U. papenfussii was 17.8 g/l of weight and its growth rate was 4.3–6.5% day. Nutritional cultivation is successful for U. papenfussii speceies, which is of great importance to study the potential of producing seaweed varieties like blades for commercial application of seaweed species.

Impacts of κ- oligocarrageenan application on photosynthesis, nutrient uptake and bean yield of coffee (Coffea robusta)

κ-Oligocarrgeenan (OC) is well known as an effective and green plant growth promoter and elicitor. However, its effect on coffee plant has not been investigated so far. This study aimed to examine the impacts of OC on biophysical activity, vegetative growth and productivity of coffee plant (Coffea robusta). OC with average molecular weight (AMW) of 4.0 kDa was prepared by depolymerization of carrageenan using ascorbic acid. Field experiments were conducted by foliar spray four times per year at various OC concentrations (50, 100, 150, 200, and 250 ppm) for three years (2017-2019). The results showed that OC promoted growth of coffee plant in all tested concentrations, and an optimized concentration was found at 150 ppm which showed a significant increase compared to the control plant in total chlorophyll (24.79%), carotenoid (31.65%), uptakes of N (15.66%), P (15.81%), and K (22.25%) minerals in leaves, crop yield (19.80%) and bean size (13.10%). Therefore, OC is potentially promising to apply as a promoter to enhance yield of crops for sustainable coffee plantation

Fast and accurate prediction of temperature evolutions in additive manufacturing process using deep learning

Typical computer-based parameter optimization and uncertainty quantification of the additive manufacturing process usually requires significant computational cost for performing high-fidelity heat transfer finite element (FE) models with different process settings. This work develops a simple surrogate model using a feedforward neural network (FFNN) for a fast and accurate prediction of the temperature evolutions and the melting pool sizes in a metal bulk sample (3D horizontal layers) manufactured by the DED process. Our surrogate model is trained using high-fidelity data obtained from the FE model, which was validated by experiments. The temperature evolutions and the melting pool sizes predicted by the FFNN model exhibit accuracy of 99% and 98%, respectively, compared with the FE model for unseen process settings in the studied range. Moreover, to evaluate the importance of the input features and explain the achieved accuracy of the FFNN model, a sensitivity analysis (SA) is carried out using the SHapley Additive exPlanation (SHAP) method. The SA shows that the most critical enriched features impacting the predictive capability of the FFNN model are the vertical distance from the laser head position to the material point and the laser head position.VINIF.2020.DA15 EDPOMP projec

Uncertainty Quantification in the Directed Energy Deposition Process Using Deep Learning-Based Probabilistic Approach

peer reviewedThis study quantifies the effects of uncertainty raised from process parameters, material properties, and boundary conditions in the directed energy deposition (DED) process of M4 High-Speed Steel using deep learning (DL)-based probabilistic approach. A DL-based surrogate model is first constructed using the data obtained from a finite element (FE) model, which was validated against experiment. Then, sources of uncertainty are characterized by the probabilistic method and are propagated by the Monte-Carlo (MC) method. Lastly, the sensitivity analysis (SA) using the variance-based method is performed to identify the parameters inducing the most uncertainty to the melting pool depth. Using the DL-based surrogate model instead of solely FE model significantly reduces the computational time in the MC simulation. The results indicate that all sources of uncertainty contribute to a substantial variation on the final printed product quality. Moreover, we find that the laser power, the convection, the scanning speed, and the thermal conductivity contribute the most uncertainties on the melting pool depth based on the SA results. These findings can be used as insights for the process parameter optimization of the DED process.EDPOM

Healthy or Environmentally Friendly? Meat Consumption Practices of Green Consumers in Vietnam and Switzerland

High meat consumption is a phenomenon in both developed countries such as Switzerland and emerging countries such as Vietnam. This high meat consumption is associated with environmental, social, and health consequences. Drawing upon social practice theory, this study explores the influence of social practices on the meat consumption of green consumers, as a growing number of consumers in both countries want to eat healthy and sustainably but still have different needs and face different barriers. Data were collected from online group discussions. For green consumers, meat consumption was found to convey certain meanings and depends, among other things, on the information available. The consumption decision in Vietnam is strongly influenced by health and food safety, whereas negative environmental consequences are important in Switzerland. Social and cultural aspects also play a major part in the decision to eat or abstain from meat in both countries. Meat is a non-negotiable part of any special occasion meal in Vietnam and is often eaten at social gatherings in Switzerland. We argue that meat consumption is linked to social status in both countries, but family influence is stronger in Vietnam than in Switzerland. Interventions, such as policy measures that are adapted to regional, cultural, and consumer group specificities and focus on social practices rather than individual behavior, are a promising means to promote meat reduction