Search results

COVID-19, an infectious disease first identified in China, has resulted in an ongoing pandemic all over the world. Most of the countries have been experiencing a difficult period during the fighting of this pandemic. The purpose of this study is to explore the effect of privacy concerns and cultural differences on public opinion related to the pandemic. The authors conducted a comparative analysis of public opinion in the US and in China as a case study, in order to determine the results.

National policies on important issues faced during the COVID-19 pandemic in the US and in China were examined through a comparative analysis. The authors used text clustering and visualization to mine public opinion on two popular social media platforms, Twitter and Weibo. From the perspectives of concern for privacy and of national culture, this study combines qualitative and quantitative analysis to discover the acceptance level of national policies by the public in the two countries.

The anti-pandemic policies and measures of the US and China reflect the different characteristics of their respective political systems and national cultures. When considering the culture of the US, it is hard to establish and enforce a rigorous regulation on either mask wearing in public or home quarantine on the national level. The opinions of US people are diverse, regarding national COVID-19 policies, but they are rather unified on privacy issues. On the other hand, Chinese people show a high acceptance of national policies based on their mask-wearing customs and their culture of collectivism.

Prior studies have paid insufficient attention to the ways in which user privacy and cultural difference affect public opinion on national policies between the US and China. This case study that compares public opinion on current and topical issues which are closely bound up with public life shows originality, as it innovatively provides a cross-cultural perspective on the research of public opinion dissemination during emergencies by considering the ongoing COVID-19 pandemic.

COVID-19, a causative agent of the potentially fatal disease, has raised great global public health concern. Information spreading on the COVID-19 outbreak can strongly influence people behaviour in social media. This paper aims to question of information spreading on COVID-19 outbreak are addressed with a massive data analysis on Twitter from a multidimensional perspective.

The evolutionary trend of user interaction and the network structure is analysed by social network analysis. A differential assessment on the topics evolving is provided by the method of text clustering. Visualization is further used to show different characteristics of user interaction networks and public opinion in different periods.

Information spreading in social media emerges from different characteristics during various periods. User interaction demonstrates multidimensional cross relations. The results interpret how people express their thoughts and detect topics people are most discussing in social media.

This study is mainly limited by the size of the data sets and the unicity of the social media. It is challenging to expand the data sets and choose multiple social media to cross-validate the findings of this study.

This paper aims to find the evolutionary trend of information spreading on the COVID-19 outbreak in social media, including user interaction and topical issues. The findings are of great importance to help government and related regulatory units to manage the dissemination of information on emergencies, in terms of early detection and prevention.

A set of routers that are connected over communication channels can from network-on-chip (NoC). High performance, scalability, modularity and the ability to parallel the structure of the communications are some of its advantages. Because of the growing number of cores of NoC, their arrangement has got more valuable. The mapping action is done based on assigning different functional units to different nodes on the NoC, and the way it is done contains a significant effect on implementation and network power utilization. The NoC mapping issue is one of the NP-hard problems. Therefore, for achieving optimal or near-optimal answers, meta-heuristic algorithms are the perfect choices. The purpose of this paper is to design a novel procedure for mapping process cores for reducing communication delays and cost parameters. A multi-objective particle swarm optimization algorithm standing on crowding distance (MOPSO-CD) has been used for this purpose.

In the proposed approach, in which the two-dimensional mesh topology has been used as base construction, the mapping operation is divided into two stages as follows: allocating the tasks to suitable cores of intellectual property; and plotting the map of these cores in a specific tile on the platform of NoC.

The proposed method has dramatically improved the related problems and limitations of meta-heuristic algorithms. This algorithm performs better than the particle swarm optimization (PSO) and genetic algorithm in convergence to the Pareto, producing a proficiently divided collection of solving ways and the computational time. The results of the simulation also show that the delay parameter of the proposed method is 1.1 per cent better than the genetic algorithm and 0.5 per cent better than the PSO algorithm. Also, in the communication cost parameter, the proposed method has 2.7 per cent better action than a genetic algorithm and 0.16 per cent better action than the PSO algorithm.

As yet, the MOPSO-CD algorithm has not been used for solving the task mapping issue in the NoC.

Extreme high temperatures are a significant feature of global climate change and have become more frequent and intense in recent years. These pose a significant threat to both human health and economic activity, and thus are receiving increasing research attention. Understanding the hazards posed by extreme high temperatures are important for selecting intervention measures targeted at reducing socioeconomic and environmental damage.

In this study, detrended fluctuation analysis is used to identify extreme high-temperature events, based on homogenized daily minimum and maximum temperatures from nine meteorological stations in a major grassland region, Hulunbuir, China, over the past 56 years.

Compared with the commonly used functions, Weibull distribution has been selected to simulate extreme high-temperature scenarios. It has been found that there was an increasing trend of extreme high temperature, and in addition, the probability of its indices increased significantly, with regional differences. The extreme high temperatures in four return periods exhibited an extreme low hazard in the central region of Hulunbuir, and increased from the center to the periphery. With the increased length of the return period, the area of high hazard and extreme high hazard increased. Topography and anomalous atmospheric circulation patterns may be the main factors influencing the occurrence of extreme high temperatures.

These results may contribute to a better insight in the hazard of extreme high temperatures, and facilitate the development of appropriate adaptation and mitigation strategies to cope with the adverse effects.

The paper aims to investigate the possible changes in mean temperature in the Mongolian Plateau associated with the 1.5 and 2°C global warming targets and how snow changes in the Mongolian Plateau when the mean global warming is well below 2°C or limited to 1.5°C.

In total, 30 model simulations of consecutive temperature and precipitation days from Coupled Model Inter-comparison Project Phase 5 (CMIP5) are assessed in comparison with the 111 meteorological monitoring stations from 1961–2005. Multi-model ensemble and model relative error were used to evaluate the performance of CMIP5 models. Slope and the Mann–Kendall test were used to analyze the magnitude of the trends and evaluate the significance of trends of snow depth (SD) from 1981 to 2014 in the Mongolian Plateau.

Some models perform well, even better than the majority (80%) of the models over the Mongolian Plateau, particularly HadGEM2-CC, CMCC-CM, BNU-ESM and GFDL-ESM2M, which simulate best in consecutive dry days (CDD), consecutive wet days (CWD), cold spell duration indicator (CSDI) and warm spell duration indicator (WSDI), respectively. Emphasis zones of WSDI on SD were deeply analysed in the 1.5 and 2 °C global warming period above pre-industrial conditions, because it alone has a significant negative relation with SD among the four indices. It is warmer than before in the Mongolian Plateau, particularly in the southern part of the Mongolian Plateau, indicating less SD.

Providing climate extremes and SD data sets with different spatial-temporal scales over the Mongolian Plateau. Zoning SD potential risk areas and proposing adaptations to promote regional sustainable development.

This paper aims to determine a suitable anti-wear and friction-reducing compounding additive for lithium greases (LG) by investigating the effects of three single additives potassium borate (PB), zinc dialkyl dithiophosphate and molybdenum dialkyl dithiophosphate (MoDDP) and two compound additives on the friction, wear and extreme pressure properties of LG.

The effects of the above five additives on the friction, wear and extreme pressure properties of LG were investigated using an SRV-5 friction tester. An X-ray photoelectron spectrometer was used to analyze the various elements presented on the wear surface as well as the types of compounds.

The compound additive suitable for grease consists of PB and MoDDP, which have excellent friction reduction, anti-wear and extreme pressure properties. And a boundary protection film consisting of oxide and MoS₂ is formed on the friction surface, thus improving the friction reduction and anti-wear performance of the grease.

This study can improve the anti-wear and friction-reduction performance of greases, which is of great importance in the field of industrial lubrication. The results of this paper are expected to be useful to researchers and academics of grease.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0350/

The purpose of this paper is to present a laboratory accelerated periodic immersion wet/dry cyclic corrosion test, reflecting the alternate wet/dry process during the atmospheric exposure of metallic materials, which can be applied to evaluate the atmospheric corrosion resistance (ACR) of weathering steels in a very short period.

This test method uses 0.01 M sodium bisulfite aqueous solution with pH 4.4 as the immersion medium, simulating the notable characteristics of sulfur dioxide pollutant in industrially polluted atmospheres. During the test process, the tested specimens are immersed into the solution for 12 minutes, immediately followed by the subsequent drying process for 48 minutes, and such alternate process consists of a cyclic period, i.e. 1 hour. As a result of this procedure, a relative corrosion rate is defined to determine the ACR. To determine a preferred test period, different test periods including 72 and 200 hours were compared.

Compared with several other commonly used test methods, it was confirmed that the relative ACR of various steels can be determined after testing for only 72 hours. The constituent of the corrosion products, i.e. the rust layer, was consistent with that formed after long-term exposure in a typical outdoor atmospheric environment.

The test method enables comparative testing for ranking the ACR of weathering steel during the development of new weathering steels.

We take a state-stewardship view on corporate governance and executive compensation in economies with strong political involvement, where state-appointed managers act as responsible “stewards” rather than “agents” of the state.

We test this view on China and find that Chinese managers are remunerated not for maximizing equity value but for increasing the value of state-owned assets.

Managerial compensation depends on political connections and prestige, and on the firms’ contribution to political goals. These effects were attenuated since the market-oriented governance reform.

Economic reform without reforming the human resources policies at the executive level enables the autocratic state to exert political power on corporate decision making, so as to ensure that firms’ business activities fulfill the state’s political objectives.

As a powerful social elite, the state-steward managers in China have the same interests as the state (the government), namely extracting rents that should adhere to the nation (which stands for the society at large or the collective private citizens).

As China has been a communist country with a single ruling party for decades, the ideas of socialism still have a strong impact on how companies are run. The legitimacy of the elite’s privileged rights over private sectors is central to our question.

Chinese executive compensation stimulates not only the maximization of shareholder value but also the preservation of the state’s interests.

With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the social climate of China.

This study examines 97 severe corruption cases of high-ranking officials in China, which occurred between 2012 and 2015. As this insinuates that both institutional and social corruption are major problems in China, the analysis delves into multiple facts of corruption, including different types, four primary underlying causes, and suggestions regarding the implementation of three significant governmental shifts that focus on investigation, prevention tactics and legal regulations.

China’s corruption is not only individual-based but also it has developed into institutional corruption and social corruption. Besides human nature and instinct, the causes of corruption can be organised into four categories, namely, social customs, social transitions, institutional designs and institutional operations. For the removed high-ranking officials, the formation of interest chains was an important underlying cause behind their corruption.

This study makes a significant contribution to the literature because this study provides a well-rounded approach to a complex issue by highlighting the significance of democracy and the rule of law as ways to regulate human behaviour to combat future corruption.