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This study aims to propose a novel acoustic metamaterial waveguide with active switchable channels by changing the magnetic field strength.

Based on the Bragg scattering mechanism and the force-magnetic coupling effect of magnetorheological elastomer (MRE), an acoustic metamaterial waveguide structure containing lead scatterers and an MRE/rubber matrix is constructed. By changing the external magnetic field strength, the bandgap of the acoustic metamaterial can be adjusted, and then the channels of the proposed acoustic metamaterial waveguide can be actively switched. The bandgap ranges of acoustic metamaterials containing scatterers with different sizes are different and by designing the size of the scatterers, an acoustic metamaterial waveguide can be formed. The design and control method of this study will be useful for the design of waveguides and active control of bandgaps.

The proposed switchable multi-channel waveguide and active control method can effectively control the elastic wave propagation, and the opening and closing of the channel are achieved.

This study provides a new control method for waveguides and expands the application range of MRE. The proposed design concept of adjustable waveguides can be extended for the design of waveguides, metamaterials and vibration reduction structures.

This article proposes a waveguide structure controlled by an external magnetic field in a non-contact manner based on the principle of Bragg scattering and the force-magnetic coupling effect. The model is established, and its feasibility is demonstrated through numerical simulations.

This paper aims to amplify the retrieval and utilization of historical newspapers through the application of semantic organization, all from the vantage point of a fine-grained knowledge element perspective. This endeavor seeks to unlock the latent value embedded within newspaper contents while simultaneously furnishing invaluable guidance within methodological paradigms for research in the humanities domain.

According to the semantic organization process and knowledge element concept, this study proposes a holistic framework, including four pivotal stages: knowledge element description, extraction, association and application. Initially, a semantic description model dedicated to knowledge elements is devised. Subsequently, harnessing the advanced deep learning techniques, the study delves into the realm of entity recognition and relationship extraction. These techniques are instrumental in identifying entities within the historical newspaper contents and capturing the interdependencies that exist among them. Finally, an online platform based on Flask is developed to enable the recognition of entities and relationships within historical newspapers.

This article utilized the Shengjing Times·Changchun Compilation as the datasets for describing, extracting, associating and applying newspapers contents. Regarding knowledge element extraction, the BERT + BS consistently outperforms Bi-LSTM, CRF++ and even BERT in terms of Recall and F1 scores, making it a favorable choice for entity recognition in this context. Particularly noteworthy is the Bi-LSTM-Pro model, which stands out with the highest scores across all metrics, notably achieving an exceptional F1 score in knowledge element relationship recognition.

Historical newspapers transcend their status as mere artifacts, evolving into invaluable reservoirs safeguarding the societal and historical memory. Through semantic organization from a fine-grained knowledge element perspective, it can facilitate semantic retrieval, semantic association, information visualization and knowledge discovery services for historical newspapers. In practice, it can empower researchers to unearth profound insights within the historical and cultural context, broadening the landscape of digital humanities research and practical applications.

This paper analyzes the connectedness with network among the major cryptocurrencies, the G7 stock indexes and the gold price over the coronavirus disease 2019 (COVID-19) pandemic period, in 2020.

This study used a multivariate approach proposed by Diebold and Yilmaz (2009, 2012 and 2014).

For a stock index portfolio, the results of static connectedness showed a higher independence between the stock markets during the COVID-19 crisis. It is worth noting that in general, cryptocurrencies are diversifiers for a stock index portfolio, which enable to reduce volatility especially in the crisis period. Dynamic connectedness results do not significantly differ from those of the static connectedness, the authors just mention that the Bitcoin Gold becomes a net receiver. The scope of connectedness was maintained after the shock for most of the cryptocurrencies, except for the Dash and the Bitcoin Gold, which joined a previous level. In fact, the Bitcoin has always been the biggest net transmitter of volatility connectedness or spillovers during the crisis period. Maker is the biggest net-receiver of volatility from the global system. As for gold, the authors notice that it has remained a net receiver with a significant increase in the network reception during the crisis period, which confirms its safe haven.

Overall, the authors conclude that connectedness is shown to be conditional on the extent of economic and financial uncertainties marked by the propagation of the coronavirus while the Bitcoin Gold and Litecoin are the least receivers, leading to the conclusion that they can be diversifiers.

本文分析於2020年2019冠狀病毒病肆虐期間、主要的加密貨幣、七國集團 (G7) 股價指數與黃金價格三者之間在網絡上的連通性。

分析使用迪博爾德和耶爾馬茲 (Diebold and Yilmaz (2009, 2012, 2014)) 提出的多變量分析法。

就一個股票指數投資組合而言,靜態連結的結果顯示、在2019冠狀病毒病肆虐期間,股票市場之間有更高的獨立性。值得我們注意的是:一般來說,加密貨幣在股票指數投資組合起著多元化投資作用,這可減低不穩定性,尤其是在危機時期。動態連結的結果與靜態連結的結果沒有顯著的分別。我們剛提到、比特幣黃金已成為純接收者。除了處於先前水平的達世幣和比特幣黃金外,就大部分的加密貨幣而言,連通的範圍在衝擊後都得以維持。事實上,在這危機時期,比特幣一直是波動性連結或溢出的最大淨傳播者。掛單者 (Maker) 是從全球系統中出現的最大波動淨接收者。至於黃金,我們注意到在危機時期、它仍然是在網絡接收方面擁有顯著增長的淨接收者,這確認其為安全的避難所。

總的來說,我們的結論是:連通性被確認為取決於標誌著受廣泛傳播的冠狀病毒影響下的經濟和金融欠缺穩定的程度,而比特幣黃金和萊特幣則是最小的接收者,這帶出一個結論、就是:比特幣黃金和萊特幣、可以成為多元化投資項目。

Blockchain technology has created possibilities for environmental supply chain sustainability and climate protection. However, because of its early development stage, users tend to resist the adoption of this new technology. The purpose of this study is to investigate the effects of resistance on blockchain adoption intentions in the context of the foodservice industry. This study further explores if public pressures and climate change awareness could possibly weaken the negative relationships between blockchain resistance and adoption intentions.

Data were collected from managers and full-time employees in the foodservice industry, using an online research panel survey. A structural equation model was developed and tested to examine the hypothesized relationships. Additionally, a multi-group analysis was performed to test the moderating roles of public pressures and climate change awareness.

The findings from this study confirmed that foodservice employees’ characteristics, including traditional barriers, and blockchain technology factors, like perceived risk, are both significant in forming resistance to blockchain. This study also demonstrated the significant roles of internal and external stakeholders in weakening the negative associations between blockchain resistance and adoption intentions.

This study recommends that foodservice companies address how to reduce their employees’ negative perceptions about changes imposed by blockchain adoption. This study also suggests the joint consideration of the pressures from internal and external stakeholders to provide continued insights into developing environmental practices for the foodservice industry.

This study extends the theoretical underpinning of the innovation resistance theory by incorporating the stakeholder theory as a strong foundation for understanding how external pressures and internal awareness may influence foodservice employees’ responses to the implementation of blockchain technology to mitigate climate change.