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Most rapid prototyping (RP) relies on energy fields to handle materials, among which electricity has been much more utilized, resulting in distinctive responsiveness of non-linear, overshoot, variable inertia, etc. The purpose of this paper is to eliminate the drawbacks of array nozzle clogging, stringing, melt sagging, particularly in multi-material RP, by focusing on the electrothermal response so as to adaptively distribute thermal more accurate, rapid and balanced.

This paper presents an electrothermal response optimization method of nozzle structure for multi-material RP based on fuzzy adaptive control (FAC). The structural, physical and control model are successively logically built. The fractional order electrothermal model is identified by Riemann Liouville fractional differential equation, using the bisection method to approximate the physical model via least square method to minimize residual sum of squares. The FAC is thereafter implemented by defining fuzzy proportion integration differentiation control rules and fuzzy membership functions for fuzzy inference and defuzzification.

The transient thermodynamic and structural statics, as well as flow field analysis, are conducted. The response time, mean temperature difference and thermal deformation can be found using thermal-solid coupling finite element analysis. In physical experimental research, temperature change, together with material extrusion loading, were measured. Both numerical and physical studies have revealed findings that the electrothermal responsiveness varies with the three-dimensional structure, materials and energy sources, which can be optimized by FAC.

The proposed FAC provides an optimization method for extrusion-based multi-material RP between the balance of thermal response and energy efficiency through fulfilling potential of the hardware configuration. The originality may be widely adopted alongside increasing requirements on high quality and high efficiency RP.

A combination of highly conductive porous media and nanofluids is an efficient way for improving thermal performance of relevant applications. For precisely predicting the flow and thermal transport of nanofluids in porous media, the purpose of this paper is to explore the inter-phase coupling numerical methods.

Based on the lattice Boltzmann (LB) method, this study combines the convective flow, non-equilibrium thermal transport and phase interactions of nanofluids in porous matrix and proposes a new multi-phase LB model. The micro-scale momentum and heat interactions are especially analyzed for nanoparticles, base fluid and solid matrix. A set of three-phase LB equations for the flow/thermal coupling of base fluid, nanoparticles and solid matrix is established.

Distributions of nanoparticles, velocities for nanoparticles and the base fluid, temperatures for three phases and interaction forces are analyzed in detail. Influences of parameters on the nanofluid convection in the porous matrix are examined. Thermal resistance of nanofluid convective transport in porous structures are comprehensively discussed with the models of multi-phases. Results show that the Rayleigh number and the Darcy number have significant influences on the convective characteristics. The result with the three-phase model is mildly larger than that with the local thermal non-equilibrium model.

This paper first creates the multi-phase theoretical model for the complex coupling process of nanofluids in porous structures, which is useful for researchers and technicians in fields of thermal science and computational fluid dynamics.

As the limited energy of wireless sensor networks (WSNs), energy-efficient data-gathering algorithms are required. This paper proposes a compressive data-gathering algorithm based on double sparse structure dictionary learning (DSSDL). The purpose of this paper is to reduce the energy consumption of WSNs.

The historical data is used to construct a sparse representation base. In the dictionary-learning stage, the sparse representation matrix is decomposed into the product of double sparse matrices. Then, in the update stage of the dictionary, the sparse representation matrix is orthogonalized and unitized. The finally obtained double sparse structure dictionary is applied to the compressive data gathering in WSNs.

The dictionary obtained by the proposed algorithm has better sparse representation ability. The experimental results show that, the sparse representation error can be reduced by at least 3.6% compared with other dictionaries. In addition, the better sparse representation ability makes the WSNs achieve less measurement times under the same accuracy of data gathering, which means more energy saving. According to the results of simulation, the proposed algorithm can reduce the energy consumption by at least 2.7% compared with other compressive data-gathering methods under the same data-gathering accuracy.

In this paper, the double sparse structure dictionary is introduced into the compressive data-gathering algorithm in WSNs. The experimental results indicate that the proposed algorithm has good performance on energy consumption and sparse representation.

Human resource practices are transforming at a varying pace for different businesses to meet the increasingly intensified external challenges. The pursuit of innovation while balancing the tensions between flexibility and efficiency has become a core challenge for survival in this globally competitive era. The literature identifies ambidexterity as a realistic choice to manage these tensions during transformation towards diversified and innovative human resource practices. Based on social exchange theory (SET), this study explores the impact of ambidextrous human resource practices (AHRPs) on organization members' innovation performance while examining the mediating effect of psychological safety.

Data were collected for this cross-sectional study in three waves, and the final sample included 788 employees from 32 companies across different industries in China.

The results of data analysis indicate support for all the hypothesized relationships. AHRPs positively affect employee innovation performance; employee psychological safety mediates this relationship; inclusive leadership moderates the direct effect of AHRPs on employee psychological safety and the indirect effect of AHRPs on employee innovative performance through psychological safety. Theoretical and practical implications of the study are also presented.

This study examines AHRPs’ influence on employee innovation performance mediated by psychological safety and the moderating role of inclusive leadership in the above relationship to clarify the boundary conditions of AHRPs' effect on innovation performance.

This paper aims to investigate the corrosion rate, surface morphology and composition of corrosion products of 20# seamless steel in aqueous CO₂ solution under stratified gas-liquid two-phase flow condition. The development of a corrosion products layer has also been discussed.

The following methods were used: weight loss method, scanning electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction.

The corrosion rate curve presents an irregular zigzag change trend with a gradual increase in time. The peak value of the corrosion rate appears when the corrosion time is 4 h and 8 h. The corrosion products layer is composed of two sub-layers: the inner dense layer that is about 6 µm thick and the outer loose layer that is about 9 µm thick when the corrosion time is 8 h. The main corrosion product are FeCO₃ and Fe₂O₃.

The atomic ratio of Fe/C/O is relatively stable for the inner dense layer, but changes in thickness for the outer loose layer. There is a densification stage after a loose corrosion products layer forms, and it is periodic.

The study aims to scrutinize the concomitant associations between corporate social responsibility (CSR), perceived organizational support (POS), green transformational leadership (GTL) and organizational performance (OP). This paper aims to explore the role of intervening variable to measure the strength on the relationship between CSR and OP.

This research administered a survey through self-administered questionnaire among the staff-level employees of construction companies of Nepal. Fully filled 305 responses from the participants were analyzed using a structural equation model. The study used self-structured questionnaire as research tool and face-to-face meetings as data collection technique.

The research indicates that POS showed competitive partial mediation relation between CSR and OP. Besides, a novel exploration of the moderation effect of GTL displays a supportive role in harmonizing the CSR with organizational support to achieve better OP. This study enriches empirical evidence to understand the linkage between CSR and POS in staff-level employees in the construction area. Moreover, the research shed a light on GTL 's moderating influence on the mediated model of CSR, POS and OP.

Although the results of the study add to the current knowledge base, several limitations highlight avenues for future research. Future studies can explore the relationship in other study areas with added evidence on a similar result with different analysis patterns and study sample. The research model studied in the context of Nepal creating evidence as a representation for the developing countries.

The intervening role of POS and GTL gives new insight for the research-based organization based social behavior and performance

The purpose of this paper is to investigate remanufacturing operational strategies considering uncertain quality of end-of-life (EOL) products and differential consumers’ willingness-to-pay (WTP) for new products and provide suggestions on the remanufacturing mode selection for the original equipment manufacturer (OEM).

This study considers three remanufacturing modes, i.e. in-house, outsourcing and authorization modes. By establishing and comparing decision models of three modes from the perspectives of profit, consumer surplus and environment, the optimal remanufacturing mode is discussed.

The results suggest that if the OEM’s remanufacturing capability is high, the in-house mode brings to the highest environmental performance, OEM’s profit and consumer surplus. Otherwise, the outsourcing mode (authorization) is the best benefit to environment (consumers if the unit production cost of new products is not too high). As for the preference of two decision-makers to outsourcing and authorization modes, if the difference of consumers’ WTP for new products is low, the OEM prefers the outsourcing mode; otherwise, the OEM prefers the authorization mode. The preference of the third-party remanufacturer (TPR) to remanufacturing mode is affected by consumers’ WTP for remanufactured products, WTP difference for new products and remanufacturing quality level standard.

These results can provide operational insights into how to select remanufacturing mode when the quality of EOL products is uncertain and consumers’ WTP for new products is different under three remanufacturing modes.

This paper is among the first to investigate the joint effects of EOL products’ uncertain quality and differential consumers’ WTP for new products on the operational strategies and performance under different remanufacturing modes.

The purpose of this study is to present a system dynamic (SD)-based remanufacturing economic analysis model of used automobile engine under two recycling modes. The authors will compare the remanufacturing cost, sales profit and sales revenue from time and space dimensions incurred in different recycling modes in the long run.

The remanufacturing economic analysis model is based on SD methodology. The authors can simulate the relations of impact factors on automobile engine recycling and remanufacturing and further analyze and compare the cost, sales profit and sales revenue incurred in different recycling modes in the long term.

Sinotruk Steyr engine remanufacturing in Shandong province is taken as the research case subject. The revenue, cost and profit under the two recycling modes from 2015 to 2035 are analyzed and compared. The results show that different recycling modes have significant varying influence on the economy of engine remanufacturing.

This economic analysis model can provide a method reference to decide the recycling mode for auto components and other product remanufacturing. Moreover, this model can guide and support the sustainable development of remanufacturing industry.

This paper aims to explore the effect of fairness concerns on supply chain members' optimal decisions and profits, to compare their profits under different policies, and to investigate the impact of each policy on members, consumers, and the environment with fairness concerns.

Considering government policies and fairness concerns in recycling management, this paper develops five recycling and remanufacturing decision models (anarchy policy model, reward-penalty mechanism model, recycling investment subsidies model, government tax model, and fund subsidy system model). In each model, the manufacturer and the online platform form the Stackelberg game. This research further discusses comprehensive environmental benefits and consumer surplus under five scenarios.

First, the fairness concerns of the online platform inhibit the recovery rate and supply chain members' profit while increasing the platform's utility. Second, fairness concerns increase the profit gap between the manufacturer and online platform, and the higher the degree of fairness concerns, the greater the profit gap; however, the four policies reduce the profit gap. Finally, when there are fairness concerns, environmental taxes damage the interests of supply chain members and consumers, but are most beneficial to the environment; recycling investment subsidies are on the contrary; the fund subsidy system depends on the relative size of the treatment fund and the subsidy fund.

This paper provides useful insights on how to regulate government policy to improve supply chain management with fairness concerns.

Shadow banking has been evolving rapidly in China, with banks actively using wealth management products (WMPs) to evade regulatory restrictions. These products are the largest constituent of China's shadow banking sector. A large number of these products are off-balance-sheet and considered a substitute for bank deposits. China's banking sector, especially the small and medium-sized banks (SMBs), uses these products to avoid regulatory restrictions and sustainability risk in the deposit market.

This study empirically examined how banks in China, specifically SMBs, utilize these products on a short and long-run basis to manage and control their deposit levels. This study utilized a quarterly panel dataset from 2010 to 2019 for the top 30 Chinese banks, by first implementing a Panel ARDL-PMG model. For cross-sectional dependence, this study further executed a cross-sectional augmented autoregressive distributive lag model (CS-ARDL).

Under regulations avoidance theory, the findings revealed that WMPs and deposits have a stable long-run substitute relationship. Furthermore, the WMP–Deposit substitute relationship was only significant and consistent for SMBs, but not for large four banks. The findings further revealed that the WMP–Deposit substitute relationship existed, even after the removal of the deposit rate limit imposed by the People's Bank of China (PBOC) to control the deposit rates.

The individual bank-issued WMPs' amount data is not available in any database. Therefore, this study utilized the number of WMPs as a proxy for China's banking sector's exposure to the wealth management business.

This research helps policymakers to understand the Deposit–WMP relationship from the off-balance-sheet perspective. During the various stages of interest rate liberalization, banks were given more control to establish their deposit and loan interest rates. However, the deposit rates are still way below the WMP returns, making WMPs more competitive. This research suggests that policymakers should formulate a more balanced strategy regarding deposit rates and WMPs returns.

This study contributes to the existing literature on China's shadow banking by concentrating on the WMPs. This research represents one of the few studies that analyze regulatory arbitrage in terms of the WMP–Deposit relationship. Moreover, the implementation of CS-ARDL panel data models and multiple data sources makes this study's findings more reliable and significant.