Yong‐Ming Tang, Yun Chen, Wen‐Zhong Yang, Xiao‐Shuang Yin, Ying Liu and Jin‐Tang Wang
The aim of this paper is to investigate inhibition of copper corrosion by 3,5‐bis(2‐thienyl)‐4‐amino‐1,2,4‐triazole (2‐TAT) in 1 M HCl and 0.5 M H2SO4.
Abstract
Purpose
The aim of this paper is to investigate inhibition of copper corrosion by 3,5‐bis(2‐thienyl)‐4‐amino‐1,2,4‐triazole (2‐TAT) in 1 M HCl and 0.5 M H2SO4.
Design/methodology/approach
Potentiodynamic polarization curves and electrochemical impedance measurements were carried out on copper in 1 M HCl and 0.5 M H2SO4 containing various concentrations of 2‐TAT, and the effects of temperature were also investigated.
Findings
As an efficient inhibitor, 2‐TAT behaves better in 1 M HCl than in 0.5 M H2SO4. 2‐TAT can be classified as cathodic‐type corrosion inhibitor in 1 M HCl and acts as relatively mixed type in 0.5 M H2SO4. Activation energies in the presence and absence of 2‐TAT were obtained by measuring the temperature independence of corrosion current. Adsorption of the inhibitor on the copper surface was found to obey the Langmuir adsorption isotherm.
Practical implications
This inhibitor could have application in industries where hydrochloric acid solutions are used to remove scale and salts from copper surfaces and may render dismantling unnecessary.
Originality/value
The results from this paper showed that 2‐TAT could be considered as a suitable inhibitor for copper in acidic media.
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Jiaru Shao, Xueping Mo, Zijun Zheng and Yu Yang
This study aims to improve the survivability and maneuverability of the fighter,and study the stealth performance of fighter in the jet noise of aeroengine, it is of great…
Abstract
Purpose
This study aims to improve the survivability and maneuverability of the fighter,and study the stealth performance of fighter in the jet noise of aeroengine, it is of great significance to study the jet noise characteristics of double S-bend nozzles.
Design/methodology/approach
The multiparameter coupling and super-ellipse design methods are used to design the cross section of double S-bend nozzle. Taking unsteady flow information as the equivalent sound source, the noise signal at the far-field monitoring points were calculated with Ffowcs Williams–Hawkings (FW–H) method, and then, the sound source characteristics of the double S-bend nozzle are analyzed.
Findings
The results show that the internal flow of the S-bend nozzle with rectangular section is smoothed and the aerodynamic performance is better than super-ellipse section, the shear layer length of rectangular section is longer, the thickness is smaller and the mixing ability is stronger. The sound pressure level of the two S-bend nozzles decreases with the increase of the monitoring angle, and the sound pressure on the horizontal plane is greater than the vertical plane. In the direction of 40°–120°, the jet noise of rectangular nozzle is smaller, and the multiparameter coupled rectangular cross section structure is more applicable.
Practical implications
It is beneficial to reduce the jet noise of the engine tail nozzle and improve the stealth performance of the aircraft.
Originality/value
There is very little research on the jet noise characteristics of the double S-bend nozzle. The multiparameter coupling and the super-ellipse method are used to design the nozzle flow section to study the aerodynamic performance and jet noise characteristics of the double S-bend nozzle and to improve the acoustic stealth characteristics of the aircraft.
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Mohammed Sawkat Hossain and Maleka Sultana
As of now, the digitization of corporate finance presents a paradigm shift in business strategy, innovation, financing and managerial capability around the globe. However, the…
Abstract
Purpose
As of now, the digitization of corporate finance presents a paradigm shift in business strategy, innovation, financing and managerial capability around the globe. However, the prevailing finance scholarly works hardly document the impact of the digitalization of corporate finance on firm performance with global evidence and analysis. Hence, the contemporary debate on whether firm performance is genuinely stimulated because of the digitalization of corporate finance or not has been a pressing issue in the relevant literature. Therefore, the purpose of this study is to identify a data-driven, concise response to an unaddressed finance issue if the performance of high-digitalized firms (HDFs) outperforms that of their counterpart peers for wealth maximization.
Design/methodology/approach
The first stage test models examine the firm performance of relatively high-digitalized firms as opposed to low-digitalized firms based on the system GMM. The second stage test of the probabilistic (logit) model infers that the probability of being HDFs explores because of better performance. Then, the authors execute robust checks based on the different quantile regressions and Z-score-based system GMM. In addition, the authors recheck and present the test results of the fixed effect and random effect to capture time-invariant individual heterogeneity. Finally, the supplementary test findings of firms’ credit strength by using Altman five- and four-factor Z-score models are presented.
Findings
By using cross-country panel analysis as 15 years’ test bed for HDFs and low digitalized firms (LDFs), the test results indicate that the overall firm performance of a digitalized firm is significantly better than that of a non-digitalized firm. The global evidence documents that HDFs are exposed to higher values and are financially more persistent as compared to their counterparts. The finding is remarkably concomitant across several possible subsample analysis, such as country–industry–size–period analysis.
Practical implications
This study can be remarkably effective in encouraging managers, policymakers and investors to acknowledge the need for adopting the required digitalization. Overall, this original study addresses a core research gap in the corporate finance literature and remarkably provides further direction to rethink the assumptions of firm digitalization on additive value and thereby identify optimal decisions for wealth maximization. The findings also imply that investors require an additional risk premium if they invest in relatively LDFs, which have relatively lower market value and weaker firm performance.
Originality/value
From an investors point of view, the academic novelty contributes to an innovative and unsettled issue on the impact of digitization of corporate finance on firm performance because there is a new question of high or low digitization of corporate finance in the global market. Hence, this academic novelty contributes to sharing global evidence of the digitalization of corporate finance and its effect on firm performances. In addition, an intensive critical review analysis is conducted based on the most recent and relevant scholarly works published in the top-tier journals of finance and business stream to fix the hypothesis. Overall, this study addresses a core research gap in the corporate finance literature; notably provides further direction to rethink firm digitalization; and thereby identifies optimal decisions for shareholders’ wealth maximization.
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Mu Shengdong, Wang Fengyu, Xiong Zhengxian, Zhuang Xiao and Zhang Lunfeng
With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges to…
Abstract
Purpose
With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges to traditional routing protocols. The limitations of the existing routing protocols under the condition of rapid data growth are elaborated, and the routing problem is remodeled as a Markov decision process. this paper aims to solve the problem of high blocking probability due to the increase in data volume by combining deep reinforcement learning. Finally, the correctness of the proposed algorithm in this paper is verified by simulation.
Design/methodology/approach
The limitations of the existing routing protocols under the condition of rapid data growth are elaborated and the routing problem is remodeled as a Markov decision process. Based on this, a deep reinforcement learning method is used to select the next-hop router for each data transmission task, thereby minimizing the length of the data transmission path while avoiding data congestion.
Findings
Simulation results show that the proposed method can significantly reduce the probability of data congestion and increase network throughput.
Originality/value
This paper proposes an intelligent routing algorithm for the network congestion caused by the explosive growth of data volume in the future of the big data era. With the help of deep reinforcement learning, it is possible to dynamically select the transmission jump router according to the current network state, thereby reducing the probability of congestion and improving network throughput.