sWOM and Online Shopping within a Disease Menace: The Case of Vietnam

Although electronic word-of-mouth via social networking sites (or sWOM) greatly induced online shopping, its importance in shopping decisions during the coronavirus disease (COVID-19) pandemic has not been holistically considered. Based on the necessity of sWOM, uses and gratifications theory (UGT), and health belief theory (HBT), this study frames a consumer shopping tendency model toward sWOM in the context of the pandemic. A web-based survey was designed to collect data from 403 respondents who are inclined to patronize e-stores during the pandemic. Next, the measurement model is examined using a two-step method of structural equation modeling. The findings specify that sWOM is an influential communication mode for online shopping in the pandemic. sWOM is of primary importance to information quality. Moreover, utilitarian value, social value, perceived threat, and self-efficacy toward shopping tendency are significantly motivated by sWOM. Lastly, information quality, utilitarian value, social value, and perceived threat are major predictors of shopping tendency during Covid-19. Finally, theoretical and practical implications are discussed

An Intelligent Position-Tracking Controller for Constrained Robotic Manipulators Using Advanced Neural Networks

Nowadays, robots have become a key labor force in industrial manufacturing, exploring missions as well as high-tech service activities. Possessing intelligent robots for such the work is an understandable reason. Adoptions of neural networks for excellent control accuracies of robotic control systems that are restricted in physical constraints are practical challenges. This chapter presents an intelligent control method for position tracking control problems of robotic manipulators with output constraints. The constrained control objectives are transformed to be free variables. A simple yet effective driving control rule is then designed to force the new control objective to a vicinity around zeros. To suppress unexpected systematic dynamics for outstanding control performances, a new neural network is employed with a fast-learning law. A nonlinear disturbance observer is then used to estimate the neural estimation error to result in an asymptotic control outcome. Robustness of the closed loop system is guaranteed by the Lyapunov theory. Effectiveness and feasibility of the advanced control method are validated by comparative simulation

An integrated intelligent nonlinear control method for a pneumatic artificial muscle

This paper proposes an advanced position-tracking control approach, referred to as an integrated intelligent nonlinear controller, for a pneumatic artificial muscle (PAM) system. Due to the existence of uncertain, unknown, and nonlinear terms in the system dynamics, it is difficult to derive an exact mathematical model with robust control performance. To overcome this problem, the main contributions of this paper are as follows. To actively represent the behavior of the PAM system using a grey-box model, neural networks are employed as equivalent internal dynamics of the system model and optimized online by a Lyapunov-based method. To realize the control objective by effectively compensating for the estimation error, an advanced robust controller is developed from the integration of the designed networks, and improvement of the sliding mode and backstepping techniques. The convergences of both the developed model and the closed-loop control system are guaranteed by Lyapunov functions. As a result, the overall control approach is capable of ensuring the system's performance with fast response, high accuracy, and robustness. Real-time experiments are carried out in a PAM system under different conditions to validate the effectiveness of the proposed method

Closed Shop or Collaborative Hub? An Analysis of the Partners' Importance in CANZUK Countries' Research Collaborations

Collaborative partners are important in international research collaboration. The research collaborations between four CANZUK countries (Canada, Australia, New Zealand and the United Kingdom) are examined to see whether their research connections are different from the research relationships with other countries. This paper measures the affinity index values and analyses the development of research collaborations among CANZUK countries with those between the CANZUK and other countries. The whole counting method and the fractional counting method are applied in this study to compare the differences in the results. The findings show that although the affinity index values of CANZUK countries were decreasing over time, the importance of CANZUK partners to CANZUK countries has likely increased over time at the expense of the other partners' importance. The study also shows the minor differences in results obtained by applying two different counting methods. These differences can be explained by the nature of the counting methods, and the choice to use either one of these two counting methods should be considered in other international research collaboration studies.Peer Reviewe

Optimization of Rough Self-Propelled Rotary Turning Parameters in terms of Total Energy Consumption and Surface Roughness

The self-propelled rotary tool turning (SPRT) process is an economic and effective solution for machining difficult-to-cut materials. This work optimized SPRT parameters, including the inclination angle (A), depth of cut (D), feed rate (f), and turning speed (V) to decrease the total energy consumption (TE) and surface roughness (SR). The turning experiments of the hardened AISI 4150 steel were executed to obtain the experimental data, while the regression method was applied to develop the TE and SR correlations. The entropy method and quantum-behaved particle swarm optimization (QPSO) were utilized to select the weights and optimal factors. The results indicated that the optimal A, D, f, and V were 34 deg., 0.40 mm, 0.47 mm/rev., and 177 m/min, respectively, while the TE and SR were saved by 9.7% and 35.4%, respectively. The f and V were found to be the most effective parameters, followed by the D and A. The outcomes provide valuable data to determine optimal SPRT factors for minimizing energy consumption and maximizing machining quality.The optimizing technique could be applied to solve other issues for different SPRT operations

DEVELOPMENT AND EVALUATION OF ORAL SUSTAINED-RELEASE RANITIDINE DELIVERY SYSTEM BASED ON BACTERIAL NANOCELLULOSE MATERIAL PRODUCED BY KOMAGATAEIBACTER XYLINUS

Objective: The short biological half-life (2-3 h) and low bioavailability (50 %) of ranitidine (RAN) following oral administration favor the development of a controlled release system. This study was aimed to develop and in vitro evaluate oral sustained-release RAN delivery system based on the bacterial nanocellulose material (BNM) produced by Komagataeibacter xylinus (K. xylinus) from selected culture media. Methods: BNMs are biosynthesized by K. xylinus in the standard medium (SM) and coconut water (CW). RAN was loaded in BNMs by the absorption method. The structural and physicochemical properties of BNMs and BNMs-RAN were evaluated via swelling behavior, FTIR, and FESEM techniques. Moreover, the effect of BNMs on RAN release profile and release kinetics was analyzed and evaluated. Results: The amount of loaded RAN or entrapment efficacy for BNM-CW is higher than for BNM-SM. The BNM-SM-RAN and BNM-CW-RAN exhibited a decreased initial burst release system followed by a prolonged RAN release up to 24 h in relation to the commercial tablets containing RAN. The RAN release from these formulations was found higher in the SGF medium than that of in SIF medium. RAN released from these formulations was found to follow the Korsmeyer-Peppas model and diffusion sustained drug release mechanism. The sustained release of RAN from BNM-SM-RAN was slower than for RAN from BNM-CW-RAN, but the mechanism of sustained RAN release was the same. Conclusion: Oral sustained-release RAN delivery system based on BNMs was successfully prepared and evaluated for various in vitro parameters. The biopolymers like BNM-SM and BNM-CW could be utilized to develop oral sustained RAN release dosage form

Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics

In this work, the surface roughness (SR), surface hardness (SH), and the thickness of the affected layer (TL) of the multi-roller flat burnishing process are optimized.The parameter inputs are the tool rotational speed (S), burnishing depth (D), and feed rate (f). The flat burnishing tool having three rollers was utilized to facilitate burnishing trials. The Kriging models of performances are proposed regarding inputs.The CRITIC method and Crow Search Algorithm (CSA) were employed to select weights and optimality. The optimizing outcomes indicated that the optimal values of the S, f, and D were 912 rpm, 150 mm/min, and 0.12 mm, respectively. The improvements in the SR, SH, and TL were 33.3%, 26.9%, and 48.6%, respectively. The SR was primarily influenced by the f, followed by the D and S, respectively. The SH and TL were primarily influenced by the D, followed by the S and f, respectively. The optimal data could be applied to the practical multi-roller burnishing process to improve surface properties for flat surfaces. The Kriging models and CSA could be efficiently utilized to solve complex issues for burnishing operations and other machining processes