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The purpose of this paper is to compare the thermal resistances between optimized gallium- and water-based heat sinks to show which one is superior.

Taking the thermal resistances of heat sinks as the goal function, an optimization process is programmed based on the genetic algorithm. The optimal channel/fin widths and the corresponding thermal resistances of gallium- and water-based heat sinks are obtained and compared with/without a laminar flow constraint. The analytic model and CFD method are applied in different situations to ensure sufficient accuracy.

The results show that in the laminar regime, the thermal resistance of optimized gallium-based heat sink is lower than the water-based counterpart in most cases, but the latter becomes better if it is long enough or the channel is sufficient high. Without the laminar constraint, the thermal resistance of the optimized gallium-based heat sink can be decreased by 33-45 per cent compared with the water-based counterparts. It is interesting to find that when the heat sink is long or the channel height is short, the optimal geometry of gallium-based heat sink is a mini gap.

This paper demonstrates that the cooling performance of gallium-based heat sink can be significantly improved by optimization without the laminar flow constraint.

This study aims to investigate the effect of combined use of granular graphite and petroleum coke on the properties of copper-based friction materials and the friction and wear mechanisms.

Copper-based friction materials with different proportions of petroleum coke and granular graphite were prepared by using powder metallurgy. The friction surfaces were analyzed.

Changing the ratio of petroleum coke/granular graphite affects the formation of oxides and sulfides on the surface of the materials. Increasing the petroleum coke promotes the production of metal sulfide and sulfate in the friction materials and reduces coefficient of friction (COF) and wear. Increasing petroleum coke also increases the amount of carbonic oxide (CO) released during the braking process and promotes the reduction process of iron oxide on the friction surface.

The synergistic effect of carbon materials on copper-based friction materials was studied in terms of the tribological chemical reaction. This research provides useful information for the selection of carbon materials in friction materials.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2020-0075/

The purpose of this paper is to increase understanding of the real situation of Enterprise's Sustainable Innovation (ESI) in China.

First, the paper analyzes the practice of Chinese ESI in the past 30 years, and then reviews research results of the topic in China, by the authors and by other Chinese scholars. Finally, it provides the future prospects for ESI in China.

The practice of Chinese ESI started in 1978 when this country began reform, and two stages of Chinese ESI practice has been summarized. Otherwise, six major characteristics have been highlighted. China is one of the earliest countries that began to research on ESI and has achieved significant results since 1995. The paper summarizes major research findings of ESI in China, which can be divided into two categories. Especially, it stresses that one of the distinguishing achievements is research on mechanisms of ESI in China.

The research on ESI in China is initially implemented based on Chinese practice. So, future research may explore whether the research results could be suitable for abroad, or not.

This original paper analyzes ESI practice and research findings in China, and may have value in helping people to understand ESI's real situation.

The simulation of the fluid–solid interaction (FSI) problem is important for both academic studies and engineering applications. However, the numerical approach for simulating the FSI problems is a great challenge owing to the large discrepancy of material properties and inconsistent description of grid motion between the fluid and solid domains. The difficulties will be further increased if there are multiple materials in the fluid region. In these complicated applications, interface reconstruction, multi-material advection and FSI must be all taken into account. This paper aims to present an effective integrated work of multi-material arbitrary Lagrangian Eulerian (MMALE) method, finite element (FE) method and the continuum analogy method to simulate the complex FSI problems involving multi-material flow. The coupled method is used to simulate the three-dimensional CONT test and the blast-plate interaction. The numerical results show good agreement with the benchmark and the experiment data, which indicates that the presented method is effective for solving the complicated FSI problems.

MMALE and FE methods are used to simulate fluid and solid regions, respectively. The interfacial nodes of fluid and solid are required to be coincident in the whole simulation so the interacted force can be easily and accurately calculated. To this end, the continuum analogy method is used in the rezoning phase.

The coupled method is used to simulate the three-dimensional CONT test and the blast-plate interaction. The numerical results show good agreement with the benchmark and the experiment data, which indicates that the presented method is effective for solving the complicated FSI problems.

To the best of the authors’ knowledge, this is the first time that the ALE method, moment of fluid interface reconstruction method, continuum analogy method and the FE method are combined to solve complicated practical problems.

This study examines the impact of corporate performance and corporate size on corporate environmental information disclosure of A-share listed enterprises in Shanghai and Shenzhen during the period 2008–2017. In this study, corporate size (size) is represented by total assets, and corporate performance (Jzc) is represented by return on net assets. Environmental information disclosure quality (EID) is measured by the Environmental Information Disclosure Index (EIDI). Non-balanced panel data models are used. In order to eliminate the influence of unobservable factors during the sample period, year fixed effects and industry fixed effects are included. The results show that corporate size and performance both promote the improvement of EID quality. Measures such as improving corporate management efficiency and setting clear environmental performance indicators can help improve corporate competitiveness and core values, thus providing important support for improving EID quality. Future research is recommended to focus on the influence of internal corporate characteristics such as corporate nature (state-owned or not), equity structure, and executive background on EID quality.

The purpose of this paper is to give broad‐spectrum analysis of general system theory, including the researching approach – dynamic structure approach, the study on general object system by broad‐spectrum analysis, and the study of general cognitive system by broad‐spectrum analysis, etc.

The theoretical basis of broad‐spectrum analysis is dynamic structuralism, which, therefore, leads to the fact that its methodology is dynamic structural methodology, including that from the perspective of generalized structure, that from the dynamic perspective (the fluxional viewpoint of structure and the transforming viewpoint of structure).

Generalized structural models of general object system (including general thing system and general dynamic system, general cognitive system and general value system) are given in this paper. It shows a unique perspective of broad‐spectrum analysis, its close relationship with general system theory and the viewpoints of many questions in general system.

The details of the structural models in this paper have to be worked out.

The methodological principle for us to analyze, study, optimize, and control the general system is provided.

Generalized structural models of this paper originate from pansystem methodology and discrete mathematics. This paper has the value of methodology for those who are studying general systems.

This chapter examines which coping mechanisms citizens used during the pandemic and how these mechanisms related to overall well-being. Using the Transaction Theory of Stress and Coping to frame the analysis, the chapter investigates predictive factors for various coping strategies and identifies which groups were more likely to use adaptive as opposed to maladaptive strategies. I examine how coping strategies used in April 2020 predict change in well-being, measured by life satisfaction, in November 2020. Americans reported greater use of maladaptive coping and less use of the adaptive coping strategies compared to their Finnish counterparts. Americans reported more frequent use of religious coping strategies. Interestingly, worrying about COVID-19 did not increase the use of maladaptive coping for Finns or Americans. Regarding the effect of the coping strategies on life satisfaction, the analyses revealed that those who reported using maladaptive strategies in April 2020 showed a significant decrease in life satisfaction in November 2020. However, this finding was only significant for Finnish residents. Unexpectedly, Finnish and US residents who reported using Active/Expressive and Planning coping reported a decrease in life satisfaction from April to November 2020. Finally, Finnish and US residents who were married, had higher self-esteem, or had higher social capital were more likely to report an increase in life satisfaction from April 2020 to November 2020. These findings raise questions for future research. The context of the pandemic may have created a unique situation that rendered coping mechanisms to behave in unusual ways.

Tourism, as a system, develops strategies for risk prevention and mitigation. The shock generated by the COVID-19 pandemic is different when compared with previous events because it is more intense and prone to structural changes. Tourists' perceptions condition their behaviour and decisions, with adverse results on travel and tourism consumption; and hygiene and health risks generate a cause-effect relationship on destination specificities.

From globalisation to risk perception and crisis management, in a framework where technology, communication and digital content represent undeniable importance, we are facing circumstances especially conducive to the redesign of the collective future, where the sustainability of tourism is a collective goal, arising from the right balance between the competitiveness of destinations and climate action.

Given the prospects for the next decade, health and hygiene are structural factors to be considered in decision-making processes. Thus, so the proposed approach contributes to the awareness, by the various stakeholders, of its importance and the need to implement methods and processes compatible with more inclusive and responsible tourism.

The purpose of this study is to investigate the impact of terrorist attacks on the volatility and returns of the stock market in Tunisia.

The employed sample comprises 1250 trading day from the Tunisian stock index (Tunindex) and stock closing prices of 64 firms listed on the Tunisian stock market (TSM) from January 2011 to October 2015. The research opts for the general autoregressive conditional heteroscedasticity (GARCH) and exponential generalized conditional heteroscedasticity (EGARCH) models framework in addition to the event study method to further assess the effect of terrorism on the Tunisian equity market.

The baseline results document a substantive impact of terrorism on the returns and volatility of the TSM index. In more details, the findings of the event study method show negative significant effects on mean abnormal returns with different magnitudes over the events dates. The outcomes propose that terrorism profoundly altered the behavior of the stock market and must receive sufficient attention in order to protect the financial market in Tunisia.

Very few evidence is found on the financial effects of terrorism over transition to democracy cases. This paper determines the salient reaction of the stock market to terrorism during democratic transition. The findings of this study shall have relevant implications for stock market participants and policymakers.

One challenge for tourism recommendation systems (TRSs) is the long-tail phenomenon of ratings or popularity among tourist products. This paper aims to improve the diversity and efficiency of TRSs utilizing the power-law distribution of long-tail data.

Using Sina Weibo check-in data for example, this paper demonstrates that the long-tail phenomenon exists in user travel behaviors and fits the long-tail travel data with power-law distribution. To solve data sparsity in the long-tail part and increase recommendation diversity of TRSs, the paper proposes a collaborative filtering (CF) recommendation algorithm combining with power-law distribution. Furthermore, by combining power-law distribution with locality sensitive hashing (LSH), the paper optimizes user similarity calculation to improve the calculation efficiency of TRSs.

The comparison experiments show that the proposed algorithm greatly improves the recommendation diversity and calculation efficiency while maintaining high precision and recall of recommendation, providing basis for further dynamic recommendation.

TRSs provide a better solution to the problem of information overload in the tourism field. However, based on the historical travel data over the whole population, most current TRSs tend to recommend hot and similar spots to users, lacking in diversity and failing to provide personalized recommendations. Meanwhile, the large high-dimensional sparse data in online social networks (OSNs) brings huge computational cost when calculating user similarity with traditional CF algorithms. In this paper, by integrating the power-law distribution of travel data and tourism recommendation technology, the authors’ work solves the problem existing in traditional TRSs that recommendation results are overly narrow and lack in serendipity, and provides users with a wider range of choices and hence improves user experience in TRSs. Meanwhile, utilizing locality sensitive hash functions, the authors’ work hashes users from high-dimensional vectors to one-dimensional integers and maps similar users into the same buckets, which realizes fast nearest neighbors search in high-dimensional space and solves the extreme sparsity problem of high dimensional travel data. Furthermore, applying the hashing results to user similarity calculation, the paper greatly reduces computational complexity and improves calculation efficiency of TRSs, which reduces the system load and enables TRSs to provide effective and timely recommendations for users.