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In Industry 4.0, technology and innovation constitute a driver for enhancing firms’ performance, particularly for small and medium-sized enterprises (SMEs). Our study aims to examine whether that statement is correct for SMEs in a developing country. We developed a generic model and employed multiple regression techniques, including ordinary least-squares, robust standard errors and weighted least squares, to test this hypothesis and address heteroskedasticity. Using a micro-level dataset including 11,630 SMEs in Vietnam’s logistics sector, an emerging logistics market in a developing country, our results reveals that the effects of technology on firm performance may differ depending on particular metrics of this performance. Furthermore, not all forms of innovation significantly affect SME performance. Control variables such as “firm’s age”, “firm’s size”, “state ownership”, “education of the manager” and “foreign activities” also play a significant role in SME performance, underscoring the importance of both internal capabilities and external technological elements.

In this paper, we propose an optimal algorithm for the convex minimax. This is an extension of the Nestrerov algorithm, which allows step size parameters to be non-constant and determined automatically during algorithm execution. We present the algorithm and prove the convergence of this algorithm with the optimal order. To calculate the gradient mapping, we apply the external point penalty function method. We then propose a method of determining the parameters in the algorithm automatically. The proposed new algorithm, which is integrated with the method of calculating gradient mapping and automatic parameter determination, is detailed in Algorithm 6.1. Finally, we applied the new algorithm to solve some specific examples and compared it with Nesterov's algorithm.

In this paper, we propose a generalized Nesterov algorithm for the constrained optimization problems on a closed convex set. We prove the convergence as well as the convergence rate of the proposed algorithm. First, we present a new algorithm based on the generalization of Nesterov’s algorithm. Then, we prove the convergence as well as the convergence rate of the new algorithm. With a specific choice of parameters, the new algorithm becomes Nesterov’s algorithm. Therefore, the convergence as well as the convergence rate of Nesterov’s algorithm are also followed. We illustrate the effectiveness of the new algorithm as well as compare it with Nesterov’s algorithm and the gradient descent algorithm through a specific example.

Supercritical carbon dioxide (SCCO2) is a non-toxic and environmentally friendly fluid and has been used in polymerization reactions, processing, foaming, and plasticizing of polymers. Exploring the behavior and data of SCCO2 sorption and dissolution in polymers provides essential information for polymer applications. This study investigated the sorption and diffusion of SCCO2 into polyetherimide (PEI). The sorption and desorption processes of SCCO2 in PEI samples were measured in the temperature range from 40 to 60 °C, the pressure range from 20 to 40 MPa, and the sorption time from 0.25 to 52 h. This study used the ex situ gravimetric method under different operating conditions and applied the Fickian diffusion model to determine the mass diffusivity of SCCO2 during sorption and desorption processes into and out of PEI. The equilibrium mass gain fraction of SCCO2 into PEI was reported from 9.0 wt% (at 60 °C and 20 MPa) to 12.8 wt% (at 40 °C and 40 MPa). The sorption amount increased with the increasing SCCO2 pressure and decreased with the increasing SCCO2 temperature. This study showed the crossover phenomenon of equilibrium mass gain fraction isotherms with respect to SCCO2 density. Changes in the sorption mechanism in PEI were observed when the SCCO2 density was at approximately 840 kg/m3. This study qualitatively performed FTIR analysis during the SCCO2 desorption process. A CO2 antisymmetric stretching mode was observed near a wavenumber of 2340 cm−1. A comparison of loss modulus measurements of pure and SCCO2-treated PEI specimens showed the shifting of loss maxima. This result showed that the plasticization of PEI was achieved through the sorption process of SCCO2.

The demand for Tra fish (Pangasius hypophthalmus) fillets is increasing every year which also increases the number of fish meat byproducts. Approximately 10% of P. hypophthalmus meat is discarded after the production of fish fillets. This study aimed to develop fish balls from the fishmeat byproduct of P. hypophthalmus fillet then investigated the effect of cooking methods and preservation time on the alteration of its texture, brightness, and total bacterial count (TBC). The raw material, minced byproduct and fish balls were analyzed for pH, protein, fat, and moisture contents. The protein content in Tra fish reached 7.35% and increased to 37.14% after the completion of the processing stages for the finished product. Blanching for 4 minutes at 90°C and steaming for 4 minutes at 100°C resulted in good texture and brightness of fish balls. However, a more effective reduction in total bacterial count was observed during the blanching process. Fish balls were preserved by freezing at -40 °C for 42 days and still maintained stable brightness. However, TBC increased significantly after 7 days, and conversely for the texture of fish balls. A finding on the stability of texture and TBC of fish balls when continued preservation from 7 to 42 days. The utilization and use of by-products from the fish fillet processing industry contribute to improving the economic value of the aquaculture industry.

Background and Objectives: Drug resistant epilepsy (DRE) is a major hurdle in epilepsy, which hinders clinical care, patients’ management and treatment outcomes. DRE may partially result from genetic variants that alter proteins responsible for drug targets and drug transporters in the brain. We aimed to examine the relationship between SCN1A, GABRA1 and ABCB1 polymorphism and drug response in epilepsy children in Vietnam. Materials and Methods: In total, 213 children diagnosed with epilepsy were recruited in this study (101 were drug responsive and 112 were drug resistant). Sanger sequencing had been performed in order to detect six single nucleotide polymorphisms (SNPs) belonging to SCN1A (rs2298771, rs3812718, rs10188577), GABRA1 (rs2279020) and ABCB1 (rs1128503, rs1045642) in study group. The link between SNPs and drug response status was examined by the Chi-squared test or the Fisher’s exact test. Results: Among six investigated SNPs, two SNPs showed significant difference between the responsive and the resistant group. Among those, heterozygous genotype of SCN1A rs2298771 (AG) were at higher frequency in the resistant patients compared with responsive patients, playing as risk factor of refractory epilepsy. Conversely, the heterozygous genotype of SCN1A rs3812718 (CT) was significantly lower in the resistant compared with the responsive group. No significant association was found between the remaining four SNPs and drug response. Conclusions: Our study demonstrated a significant association between the SCN1A genetic polymorphism which increased risk of drug-resistant epilepsy in Vietnamese epileptic children. This important finding further supports the underlying molecular mechanisms of SCN1A genetic variants in the pathogenesis of drug-resistant epilepsy in children.

Forecasting is a crucial part of supply chain management. Accurate forecasts have a strong influence on supply chain performance. Many forecasting methods have been developed and adapted in various domains and industries. However, none are perfect in all contexts due to the data's characteristics and the methods' strength. Hence, we propose a new ARIMAX‐LSTM hybrid forecasting model that integrates ARIMAX and LSTM models to improve the ability to capture different combinations of linear and nonlinear patterns in time series. Our proposed model is validated in a case study of coffee demand in Vietnam. The case study results show that our proposed model outperforms the well‐known single and current hybrid models regarding performance measures and degree of association. Moreover, to prove the model's robustness, we test and compare our proposed model to the previous study for Thailand's agricultural products (pineapple, corn, and cassava). Computational results demonstrate that our hybrid model is superior in the majority of experiments. It has a strong capability of predicting complex time series data. Furthermore, our proposed method increases forecasting accuracy and enhances supply chain performance (measured by the bullwhip effect; net‐stock amplification, and transportation cost. [ABSTRACT FROM AUTHOR]

The present study attempts to investigate the effects of time and temperature during blanching on the changes in physicochemical properties such as texture, brightness, and total bacterial count (TBC). The content of protein, fat, moisture, and pH of input materials (Tra fish) after the processing stages was also investigated. The product was preserved by freezing at -40 °C for 42 days and applied blanching/steaming conditions. The results showed that the blanching method is recommended for the product cooked stage at 90 °C for 4 min. After 42 days stored in frozen condition. TBC has been on an increasing trend and the structure has not changed significantly.

Vegetables have been shown to be able to provide nutrients, including vitamins, minerals and especially fiber, and release toxins that arise during the digestion of food. As a result, the importance of vegetables has been increasingly emphasized in the human diet. In this study, Kohlrabi, a vitamin C-rich vegetable, was used for lactic fermentation. The whole process was optimized by varying a wide range of parameters including concentrations of salt solution and pH value on the growth of lactic acid bacteria, product texture and sensory characteristics. Current results revealed the optimal conditions for the fermentation process are as follows: NaCl solution used of 3.5%, initial pH 4.2, and MnCl2 with a concentration of 30 mM. The obtained Kohlrabi pickle products exhibited acceptable quality and good sensory scores after 2 days. Elevated temperature was also found to be associated with loss of hardness, quality loss and longer fermentation time. Optimized Kohlrabi pickling process will contribute to diversifying pickled vegetable products to avoid the defects caused by improper processing.

Mango purée is a byproduct of the current production processes (such as freeze-drying, dehydration) after the product shaping stage or grades II and III mangoes. Currently, fruit bar is a convenient and highly nutritious snack made from fruit. The objective of this study is to utilize mango byproduct in order to develop a fruit bar processing technology, which is based on evaluating the quality (color, break force, vitamin C content, and sensory) when varying the pH of mango purée and the concentration of added pectin. Additionally, total soluble solids (TSS) after blending at 80°C were also investigated. The increase in pH, pectin concentration of mango purée, and TSS after blending showed that vitamin C content in fruit bars tended to decrease. TSS results revealed that at TSS=63°Bx, pH 3.3, and a pectin concentration of 1.3%, the product received a high rating of 6.3. Additionally, the vitamin C content of the product reached 7.82 mg/100 gDW. The results of this study are expected on the diversification of products from mango. Solving the situation that grades II and III mangoes are difficult to be commercialized and making the most of the byproduct mango flesh after certain production processes.