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This paper aims to design a deep reinforcement learning (DRL)-based variable impedance control policy that supports stability analysis for robot force tracking in complex geometric environments.

The DRL-based variable impedance controller explores and pre-learns the optimal policy for impedance parameter tuning in simulation scenarios with randomly generated workpieces. The trained results are then used as feedforward inputs to improve the force-tracking performance of the robot during contact. Based on Lyapunov’s theory, the stability of the proposed control policy is analysed to illustrate the interpretability of the results.

Simulations and experiments are performed on different types of complex environments. The results show that the proposed method is not only theoretically feasible but also has better force-tracking effects in practice.

Compared with most other DRL-based control policies, the proposed method possesses stability and interpretability, effectively avoids the overfitting phenomenon and thus has better simulation-to-real deployment results.

This study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain.

A bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain.

The system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype.

Solve the problem of information island in automobile supply chain.

This study aims to investigate the effect of powder recycling on the microstructure of plasma-sprayed Ni625-WC composite coating and to verify the feasibility of Ni625-WC powder recycling by comparing the corrosion resistance of the coatings in high-temperature and pressure CO₂ environment.

Recycling powder is an efficient way to improve the utilization rate of metal powder during plasma spraying. The plasma-sprayed Ni625-WC composite coatings with original powder (OC) and recovered powder (RC) were analytically compared by using scanning electron microscope (SEM) equipped with an energy-dispersive spectroscopy, X-ray diffractometer, and X-ray photoelectron spectroscopy. The corrosion resistance of the Ni625-WC composite coatings was characterized in a self-designed high-temperature and pressure autoclave by an electrochemical workstation.

The results showed that there is massive M₂₃C₆ in OC and acicular M₂₃C₆ in RC. The WC particles in RC are more uniformly distributed, and the area ratios of WC particles to Inconel 625 matrix are 2.37% higher than OC. RC showed high corrosion resistance, and the recycling of Ni625-WC powder is feasible.

The feasibility of Ni625-WC powder recycling was verified from the microstructure evolution and electrochemical behavior of the coatings.

This study aimed to examine the impact of learning organization (LO) on job satisfaction and individual performance in Vietnamese enterprises. The study further explores the mediating effect of job satisfaction on the relationship between learning organization and employee performance.

Data were collected from 653 employees from various types of organizations in Vietnam. Structural equation modeling was implemented to test the hypotheses.

The results revealed that the proposed research model was supported. Results indicated that LOs positively influenced employees’ job satisfaction and the broader range of their individual performance. In addition, employees’ job satisfaction motivated them to achieve higher performance levels. The study also found a mediating effect of job satisfaction on the relationship between LO and employee performance. The results underscore the importance of implementing an LO culture for individual outcomes such as job satisfaction and employee performance in the Vietnamese cultural context, which is based on socialism and Confucianism.

To the best of the authors’ knowledge, this is the first study to examine the relationships among LO, job satisfaction and individual employee performance in the Vietnamese context. The results offer a deeper understanding of the LO concept in the Vietnamese cultural context and highlight the cultural impact on the LO concept and its effects. The results suggest how the LO concept is applied in the Vietnamese context.

This research tests how the social context of meals influences the sense of responsibility for serving healthy meals and food choices, taking into account the role of gender.

An online between-subject scenario experiment was conducted with parents of young children (under 12 years old) in Flanders, Belgium (N = 288, 67.4% women). Participants envisioned serving and consuming food in three social contexts: alone, with core family members, or with peers.

The social context in which meals take place significantly influences participants’ sense of responsibility for serving healthy meals, which influences their food choices. Moreover, the influence of the social context varies by gender. Women feel more responsible for serving healthy meals than men when eating alone or among core family members. Men feel more responsible for serving healthy meals when eating with others, irrespective of whether these others are core family members or peers, than when eating alone.

One’s sense of responsibility serves as a significant positive determinant in making healthy food choices. However, this sense is context dependent. In a family context, and irrespective of gender, sense of responsibility correlates only weakly to moderately with the perceived healthfulness of food choices. Consequently, the question arises as to whether emphasizing responsibility is the most effective strategy for promoting healthy food choices.

This paper provides new insights into how the social context shapes parents’ sense of responsibility for serving healthy meals and how this, in turn, affects food choices.

The purpose of this research is to investigate how WeChat official account marketing activities influence consumer brand loyalty through instrument- and emotion-based paths (i.e. cognitive and affective brand trust) and how these paths operate depending on consumer shopping motivation.

We tested hypotheses using structural equation modeling with a three-wave online survey of two-week intervals administered to 179 individuals who follow the WeChat official account of a yoga gym brand.

WeChat official account marketing activities are positively related to cognitive and affective brand trust. Affective trust mediated the relationship between WeChat official account marketing activities and brand loyalty, and hedonic motivation moderated this relationship.

Our research extends the current knowledge by articulating that the influence of WeChat official account marketing activities on brand loyalty is mediated by affective brand trust, and hedonic motivation as a key contingency affects this mediation effect.

With increasing demands for competitiveness, demand fulfilment and cost efficiency, the need to optimise workforce planning in logistics has become crucial. This applies not only to external customer demands, but also to internal customers, i.e. production. For this reason, the purpose of this paper is to develop a simulative, data-driven model that predicts the internal shopfloor material logistics demands.

It is a hybrid approach that includes both deterministic and probabilistic components and is an alternative to advanced but data and knowledge-dependent machine learning algorithms. Inductive, self-developed procedures, heuristic calculation rules and consideration of real-world factors form the basis of the prediction of the number of picks. The number of picks predicted in the first step forms the basis for deriving the number of employees required in the second step, and thus the basis for optimised workforce planning. The developed approach was then validated in a case study in a real company.

The results show that the model significantly optimises not only the planning efficiency, but also the forecasting effectiveness through better decision making in demand prediction and workforce planning in internal shopfloor material logistics compared to the status quo on a weekly basis (95.5% accuracy in the case study). This improved decision making leads to increased efficiency throughout the intralogistics/production system.

A structured approach is described for systematically predicting the number of internal picks, which is highly relevant in practice and cannot be found in the existing literature (from the data model to the calculation rules, including statistical influencing factors, to the prediction). In terms of future research, the model has the potential to be used and validated in additional companies.

Considering behavior-based pricing strategy, we explore the choice of instant logistics service model and pricing strategy of Quick-commerce channel.

We adopt the Hotelling framework to develop a two-period game in which two horizontally differentiated suppliers sell repetitively purchased products through a traditional e-commerce channel and an instant e-commerce channel in two periods.

The results show that: (1) when consumer’s mismatch cost and instant logistics cost coefficient are moderate or relatively high or low, platform-operated logistics (PL) is more beneficial to traditional supplier and traditional e-platform, while Q-commerce platform may prefer self-operated logistics. However, for Q-commerce suppliers, as his/her instant logistics cost coefficient increases, he/she tends to prefer PL. (2) If the instant logistics cost coefficient is moderate, traditional suppliers may always earn more than Q-commerce suppliers in both models, despite the higher commission rate of traditional e-platform. (3) When the instant logistics cost coefficient for Q-commerce suppliers is low, traditional suppliers should significantly reduce price for new customers under PL.

Our research constructs a competition between traditional and quick commerce channels, using game theory methods to examine the impact of different instant logistics models on the dynamic pricing strategies, profitability and instant logistics efficiency of these two online channels.

In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and scientific progress. The intermediate aim of the work was to present the calibration of the model with respect to the gold nanorods experiment. The purpose of this work is to study the effect of initial concentration of E. coli bacteria, the design of the chamber and the laser power on heat transfer and inactivation of E. coli bacteria.

Using the CFD simulation, the work combines three main concepts. 1. The conversion of laser light to heat has been described by a combination of three distinctive approximations: a- Discrete particle integration to take into account every nanoparticle within the system, b- Rayleigh-Drude approximation to determine the scattering and extinction coefficients and c- Lambert–Beer–Bourger law to describe the decrease in laser intensity across the AuNPs. 2. The contribution of the presence of E. coli bacteria to the thermal and fluid-dynamic fields in the microdevice was modeled by single-phase approach by determining the effective thermophysical properties of the water-bacteria mixture. 3. An approach based on a temperature threshold attained at which bacteria will be inactivated, has been used to predict bacterial response to temperature increases.

The comparison of the thermal fields and temporal temperature changes obtained by the CFD simulation with those obtained experimentally confirms the accuracy of the light-heat conversion model derived from the aforementioned approximations. The results show a linear relationship between maximum temperature and variation in laser power over the range studied, which is in line with previous experimental results. It was also found that the temperature inside the microchamber can exceed 55 °C only when a laser power higher than 0.8 W is used, so bacterial inactivation begins.

The experimental data allows to determinate the concentration of nanoparticles. This parameter is introduced into the mathematical model obtaining the same number of AuNPs. However, this assumption introduces a certain simplification, as in the mathematical model the distribution of nanoparticles is uniform.

This work is directly connected to the use of gold nanoparticles for energy conversion, as well as the field of bacterial inactivation in microfluidic systems such as lab-on-a-chip. Presented mathematical and numerical models can be extended to the entire spectrum of wavelengths with particular use of white light in the inactivation of bacteria.

This work represents a significant advancement in the field, as to the best of the authors’ knowledge, it is the first to employ a single-phase computational fluid dynamics (CFD) approach specifically combined with the thermal inactivation of bacteria. Moreover, this research pioneers the use of a numerical simulation to analyze the temperature threshold of photothermal inactivation of E. coli mediated by gold nanorods (AuNRs). The integration of these methodologies offers a new perspective on optimizing bacterial inactivation techniques, making this study a valuable contribution to both computational modeling and biomedical applications.

After completion of the case study, the students will be able to analyze the overall competitive environment for telecom sector in India with the use of Herfindahl–Hirschman index tool, execute the fundamental analysis of Jio Platforms Limited (JPL) company, understand the concept of net neutrality and its implications for India market, understand the concept of “Zero debt company” and its implication for companies and understand data privacy concerns.

In early September of 2020, Ashish Aggarwal, a businessman in the northern state of Punjab, India with his usual habit of turning the pages of newspaper on hand and sipping morning chai got excited while reading newspaper with recent investment of Meta Platforms via Facebook buying 9.99% stake in reliance JPL. He explored and saw the potential for small businesses to invest in this and earn money, as a finance-inclined individual Aggarwal thought why not invest and earn from this opportunity. So he started googling and saw all the reviews of analysts on investment site and investors predicted that the deal could be a game changer that would further transform the existing telecom and social media platforms in India. The deal would further open doors for a new market “JioMart” which could be a futuristic design for a “one-stop-shop for e-commerce, social media consumption, instant messaging, and also digital payments”. Mukesh Ambani’s intentions to make the company zero net debt company within next 18 months fascinated him too. All this made Aggarwal interested in investing in JPL on behalf of his company as this investment option was only for business investors. So he called his financial manager, Mr Anish Mahajan for discussing the issue and both started discussing what could be the future of investment, then he told Mahajan to do the complete analysis. Also, Aggarwal was perplexed about the impact that Meta’s investment in Jio would have on consumers, especially in India. How would the telecom regulatory authority in India view it? Aggarwal felt that how the telecommunication industry would plunge into disruption mode in future. What would be the competitors’ stance in India? Would it trigger other players for strategic alliances? Aggarwal was in a dilemma whether he should invest his money in JPL company or not with controversial discussion on net neutrality and data privacy concern?

This case study is suited to master degree programs.

Teaching notes are available for educators only.

CSS 1: Accounting and Finance.