Shan Gao, Bin Wang, Xinjie Yao and Quan Yuan
This paper aims to characterize the surface film formed on Alloys 800 and 690 in chloride and thiosulfate-containing solution at 300°C.
Abstract
Purpose
This paper aims to characterize the surface film formed on Alloys 800 and 690 in chloride and thiosulfate-containing solution at 300°C.
Design/methodology/approach
Alloy 800 and 690 were immersed in chloride and thiosulfate-containing solution at 300°C up to five days, and then the surface film was analyzed by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM) and energy dispersive X-ray spectrometers (EDX).
Findings
Through static immersion experiments in a high-temperature and high-pressure water environment, the alloy samples covered by surface film after five days of immersion were obtained. The morphology of the surface film was characterized at both horizontal and cross-sectional scales using SEM and focused ion beam-TEM techniques. It was observed that due to the influence of the quartz lining, the surface film primarily exhibited a bilayered structure. The first layer contained a significant amount of SiO2, with a higher content of metal hydroxides compared to metal oxides. The second layer was predominantly composed of Fe, Ni and Cr, with a higher content of metal oxides compared to metal hydroxides.
Originality/value
The results showed that the materials of the lining of the autoclave could significantly influence the film composition of the tested material, which should be paid attention when analyzing the corrosion mechanism at high temperature.
The purpose of this research is to examine generative artificial intelligence (AI) user continuance intention based on the stimulus-organism-response model.
Abstract
Purpose
The purpose of this research is to examine generative artificial intelligence (AI) user continuance intention based on the stimulus-organism-response model.
Design/methodology/approach
We adopted a mixed method of structural equation modeling and fuzzy-set qualitative comparative analysis to conduct data analysis.
Findings
The results found that generative AI content quality (perceived personalization, perceived accuracy and perceived credibility) and system quality (perceived interactivity, perceived anthropomorphism and perceived intelligence) affect sense of empowerment and satisfaction, both of which further determine continuance intention.
Originality/value
Extant research has identified the effect of flow, trust and parasocial interaction on generative AI user continuance, but it has seldom disclosed the internal decisional process of generative AI user continuance intention. This research tries to fill this gap, and the results enrich the extant research on generative AI user continuance.
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Hongdong Guo, Yehong Liu, Xinjie Shi and Kevin Z. Chen
The purpose of this study is to investigate e-commerce as a new means to ensure that the urban demand for food can be met during the coronavirus disease 2019 (COVID-19) outbreak…
Abstract
Purpose
The purpose of this study is to investigate e-commerce as a new means to ensure that the urban demand for food can be met during the coronavirus disease 2019 (COVID-19) outbreak. Because a number of COVID-19 e-commerce models have emerged, this paper discusses whether and (if so) why and how e-commerce can ensure the food supply for urban residents if social distancing becomes a norm and the transport and logistics systems are hindered.
Design/methodology/approach
This study used qualitative research methods following the lack of empirical data. The authors referred to relevant literature, statistical data and official reports and comprehensively described the importance of e-commerce in ensuring the safety of food supply to Chinese urban residents under the impact of the epidemic. Corresponding to the traditional case study, this study presented a Chinese case on ensuring food supply through e-commerce during an epidemic.
Findings
The authors found that three e-commerce models played a substantial role in preventing the spread of the epidemic and ensuring the food supply for urban residents. The nationwide e-commerce platforms under market leadership played their roles by relying on the sound infrastructure of large cities and its logistics system was vulnerable to the epidemic. In the worst-affected areas, particularly in closed and isolated communities, the local e-commerce model was the primary model, supplemented by the unofficial e-commerce model based on social relations. Through online booking, centralized procurement and community distribution, the risk of cross infection could be effectively reduced and the food demand could be effectively satisfied. The theoretical explanation further verifies that, apart from e-commerce, a governance system that integrates the government, e-commerce platform, community streets and the unofficial guanxi also impels the success of these models.
Originality/value
Lessons from China are drawn for other countries struggling to deliver food to those in need under COVID-19. The study not only provides a solution that will ensure constant food supply to urban residents under the COVID-19 epidemic but also provides some reference for the maintenance of the food system of urban residents under the impact of a globalization-related crisis in future.
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Wenbo Ma, Kai Li, Wei-Fong Pan and Xinjie Wang
The purpose of this paper is to construct an index for systemic risk in China.
Abstract
Purpose
The purpose of this paper is to construct an index for systemic risk in China.
Design/methodology/approach
This paper develops a systemic risk index for China (SRIC) using textual information from 26 leading newspapers in China. Our index measures the systematic risk from 21 topics relating to China’s economy and provides narratives of the sources of systemic risk.
Findings
SRIC effectively predicts changes in GDP, aggregate financing to the real economy and the purchasing managers’ index. Moreover, SRIC explains several other commonly used macroeconomic indicators. Our risk measure provides a helpful monitoring tool for policymakers to manage systemic risk.
Originality/value
The paper construct an index of systemic risk based on the information extracted from newspaper articles. This approach is new to the literature.
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Xinxing Yin, Juan Chen, Wenxin Yu, Yuan Huang, Wenxiang Wei, Xinjie Xiang and Hao Yan
This study aims to improve the complexity of chaotic systems and the security accuracy of information encrypted transmission. Applying five-dimensional memristive Hopfield neural…
Abstract
Purpose
This study aims to improve the complexity of chaotic systems and the security accuracy of information encrypted transmission. Applying five-dimensional memristive Hopfield neural network (5D-HNN) to secure communication will greatly improve the confidentiality of signal transmission and greatly enhance the anticracking ability of the system.
Design/methodology/approach
Chaos masking: Chaos masking is the process of superimposing a message signal directly into a chaotic signal and masking the signal using the randomness of the chaotic output. Synchronous coupling: The coupled synchronization method first replicates the drive system to get the response system, and then adds the appropriate coupling term between the drive The synchronization error and the coupling term of the system will eventually converge to zero with time. The synchronization error and coupling term of the system will eventually converge to zero over time.
Findings
A 5D memristive neural network is obtained based on the original four-dimensional memristive neural network through the feedback control method. The system has five equations and contains infinite balance points. Compared with other systems, the 5D-HNN has rich dynamic behaviors, and the most unique feature is that it has multistable characteristics. First, its dissipation property, equilibrium point stability, bifurcation graph and Lyapunov exponent spectrum are analyzed to verify its chaotic state, and the system characteristics are more complex. Different dynamic characteristics can be obtained by adjusting the parameter k.
Originality/value
A new 5D memristive HNN is proposed and used in the secure communication
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Keywords
Chenyang Song, Jianxuan Wu and Haibin Wu
This study aims to address the issue that existing methods for limb action recognition typically assume a fixed wearing orientation of inertial sensors, which is not the case in…
Abstract
Purpose
This study aims to address the issue that existing methods for limb action recognition typically assume a fixed wearing orientation of inertial sensors, which is not the case in real-world human-robot interaction due to variations in how operators wear it, installation errors, and sensor movement during operation.
Design/methodology/approach
To address the resulting decrease in recognition accuracy, this paper introduced a data transformation algorithm that integrated the Euclidean norm with singular value decomposition. This algorithm effectively mitigates the impact of orientation errors on data collected by inertial sensors. To further enhance recognition accuracy, this paper proposed a method for extracting features that incorporate both time-domain and time-frequency domain features, markedly improving the algorithm’s robustness. This paper used five classifiers to conduct comparative experiments on action recognition. Finally, this paper built an experimental human-robot interaction platform.
Findings
The experimental results demonstrate that the proposed method achieved an average action recognition accuracy of 96.4%, conclusively proving its effectiveness. This approach allows for the recognition of data from sensors placed in any orientation, using only training samples conducted at an orientation.
Originality/value
This study addresses the challenge of reduced accuracy in limb action recognition caused by sensor misorientation. The human-robot interaction system developed in this paper was experimentally verified to effectively and efficiently guide the industrial robot to perform tasks based on the operator’s limb actions.
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Lingyun Cao, Shuaibin Ren, ZhengHao Zhou, Xuening Fei and Changliang Huang
This study aims to fabricate a cool phthalocyanine green/TiO2 composite pigment (PGT) with high near-infrared (NIR) reflectance, good color performance and good heat-shielding…
Abstract
Purpose
This study aims to fabricate a cool phthalocyanine green/TiO2 composite pigment (PGT) with high near-infrared (NIR) reflectance, good color performance and good heat-shielding performance under sunlight and infrared irradiation.
Design/methodology/approach
With the help of anionic and cationic polyelectrolytes, the PGT composite pigment was prepared using a layer-by-layer assembly method under wet ball milling. Based on the light reflectance properties and color performance tested by ultraviolet-visible-NIR spectrophotometer and colorimeter, the preparation conditions were optimized and the properties of PGT pigment with different assembly layers (PGT-1, PGT-3, PGT-5 and PGT-7) were compared. In addition, their heat-shielding performance was evaluated and compared by temperature rise value for their coating under sunlight and infrared irradiation.
Findings
The PGT pigment had a core/shell structure, and the PG thickness increased with the self-assembly layers, which made the PGT-3 and PGT-7 pigment show higher color purity and saturation than PGT-1 pigment. In addition, the PGT-3 and PGT-7 pigment showed 11%–16% lower light reflectance in the visible region. However, their light reflectance in the NIR region was similar. Under infrared irradiation the PGT-5 and PGT-7 pigment coating showed 1.1°C–3.4°C and 1.3°C–4.7°C lower temperature rise value than PGT-1 pigment coating and physical mixture pigment coating, respectively. And under sunlight the PGT-3 pigment coating showed 1.5–2.6°C lower temperature rise value than the physical mixture pigment coating.
Originality/value
The layer-by-layer assembling makes the core/shell PGT composite pigment possess low visible light reflectance, high NIR reflectance and good heat-shielding performance.