Search results

This paper aims to present a direct analysis to demonstrate why markedly different tensile and compressive behaviors of concretes could not be simulated with the Drucker–Prager yield criterion.

This study proposed an extended form of the latter for establishing a new elastoplasticity model with evolving yield strengths.

Explicit closed-form solutions to non-symmetric tensile and compressive responses of uniaxial specimens at finite strain are for the first time obtained from hardening to softening.

With such exact solutions, the yield strengths in tension and compression can be explicitly prescribed by uniaxial tensile and compressive stress-strain functions. Then, the latter two are further provided in explicit forms toward accurately simulating tensile and compressive behaviors. Numerical examples are supplied for meso-scale heterogeneous concrete (MSHC) and high-performance concrete (HPC), etc. Model predictions are in good agreement with test data.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

The purpose of this paper is to undertake an unsteady flow problem of an anomalous Maxwell fluid. The flow takes place between two side walls over a plate perpendicular to them and is driven by a sudden pressure force with constant gradient.

A finite element method is invoked and is blended with a finite difference method for left Caputo fractional time derivatives in order to study the anomalous dynamics of the fluid.

A numerical scheme for the constitutive equations of the prescribed flow in order to approximate the velocity field is designed. The graphical results to draw different physical conclusions on the flow problem are also presented.

A rigorous mathematical exposition of the numerical scheme is provided and the results are valid for large values of the parameters.

The purpose of the study is to investigate strategies for enhancing pollution oversight by local governments while reducing government-enterprise collusion (GEC) levels. Additionally, the factors influencing pollution control efforts at incineration plants are explored. Potential approaches to improving them and for effectively reducing waste incineration pollution are suggested.

The authors examined the most effective methods for mitigating incineration-related pollution and preventing collusion and developed a differential game model involving interactions between local governments and incineration plants. The findings of this work have significant policy implications for central governments worldwide seeking to regulate waste incineration practices.

The results indicate that, first, elevating environmental assessment standards can incentivize local governments to improve their oversight efforts. Second, collusion between incineration plants and local governments can be deterred by transferring benefits from the plants to the local government, while increased supervision by the central government and the enforcement of penalties for collusion can also mitigate collusion. Third, both central and local governments can bolster their supervisory and penalty mechanisms for instances of excessive pollution, encouraging incineration plants to invest more in pollution control. Finally, when the central government finds it challenging to detect excessive incineration-related pollution, enhancing rewards and penalties at the local government level can be a viable alternative.

This study stands out by considering the dynamic nature of pollutants. A differential game model is constructed which captures the evolving dynamics between local governments and incineration plants, offering insights regarding the prevention of collusion from a dynamic perspective. The findings may provide a valuable reference for governments as they develop and enforce regulations while motivating incineration plants to actively engage in reducing waste-incineration pollution.

The rapid change of technology has significantly affected the financial markets in Thailand. In order to enhance the market efficiency and liquidity, the Stock Exchange of Thailand (SET) has granted Thai stock brokers permission to develop and offer their customers algorithm and automatic stock trading. However, algorithm trading on SET was not widely adopted. This chapter intends to design and empirically estimate a model in explaining Thai investors’ acceptance of algorithm trading. The theoretical framework is based on the theory of reasoned action and technology acceptance model (TAM). A sample of 400 investors who have used online stock trading and 300 investors who have used algorithm stock trading were observed and analyzed using structural equations model (SEM) and generalized linear regression model (GLM) with a Logit specification. The results confirm that attitudes, subjective norm, perceived risks, and trust toward algorithm stock trading are factors determining investors’ behavior and acceptance of using algorithm stock trading. Investor’s perception and trust on algorithm stock trading as a trading strategy is a major factor in determining their perceived behavior and control, which affect their decision on whether to invest using algorithm trading. Accordingly, it can be concluded that Thai investors is willing to accept algorithm trading as a new financial technology, but still has concern about the reliability and profitable of this new stock trading strategy. Therefore, algorithm trading can be promoted by building investors’ trust on algorithm trading as a reliable and profitable trading strategy.

Online food delivery applications (OFDAs) provide an expedient platform, and consumers’ access to food has been drastically altered, especially during and after the COVID-19 pandemic. This study aimed to completely explore the attributes that influence consumers' purchase intention and how an app's aesthetics can evoke feelings that predict continuous usage intentions for OFDAs. The food industry, especially restaurants, heavily relies on mobile technology to facilitate critical online food delivery during the pandemic crisis.

The data for this study are gathered from 477 food consumers located in the federal capital territory (FCT) of Islamabad, Pakistan, through convenient sampling by developing a self-administrated online survey. SmartPLS is used for structural equation modeling to test the proposed research model and perform bootstrapping and algorithmic analysis.

Our findings revealed that perceived value positively predicted consumers’ purchase intentions. Moreover, perceived value mediates the association of information quality, familiarity, time-saving, usability and reputation with purchase intentions and fear of COVID-19 moderates the relationship between perceived value and purchase intention.

This research work has significant implications for researchers, web developers, app designers, delivery services, restaurants and other enterprises as it demonstrates the importance of aesthetically pleasing OFDAs in eliciting positive emotions and bolstering consumers’ intentions to continue using the app for efficient food delivery services.

This study expanded the application of the technology acceptance model (TAM) and attention, interest, desire and action (AIDA) by examining consumers’ purchase intentions in the context of OFDAs. Further, the successful utilization of TAM enhanced the understanding of consumer perceptions and behavioral intentions about the usage of OFDAs.

The purpose of this study is to determine the funding ratio of BRICS nations in various research areas. The leading funding institutions that support research in the developing world have also been researched.

This study involves the funding acknowledgment analysis of the data retrieved from the “Clarivate Analytics' InCites database” under “22 specific research areas” to determine whether the publication was funded.

This study shows that China achieves the highest funding ratio of 88.6%, followed by Brazil (73.74%), Russia (72.93%) and South Africa (70.94%). However, India has the lowest funding ratio of 58.2%. For the subject areas, the highest funding ratio is by microbiology in Russia (86.6%), India (84.3%) and China (96.9%) and space science in Brazil (93.7%) and South Africa (94.82%). However, economics and business achieves the lowest funding ratio in Brazil (38.6%), India (20.1%) and South Africa (30.24%). Moreover, the regional funding agencies are the leading research sponsors in the BRICS nations.

This study implies increasing the funding ratio across various research areas, including arts, humanities and social sciences. The nations, particularly India, also need to gear up sponsoring the research to improve the funding ratio for scientific development, bringing overall good.

This study efforts to show the status of countries and research subjects in terms of funding ratio and reveals the prominent funders working toward scientific growth.

This paper aims to examine the relationship between six factors of consumers’ perceived risk and consumers’ online purchase intentions. In particular, this study will examine the relationship between financial risk, product risk, security risk, time risk, social risk and psychological risk and online purchase intention.

Survey method was used for the purpose of data collection, and quantitative analysis was used to test the hypotheses. A total of 350 respondents participated on an online survey, and data were quantitatively analyzed via IBM SPSS Statistics 24.

The findings from this study suggest consumers’ perceived risks when they intend to purchase online. Five factors of perceived risk have a significant negative influence on consumer online purchase intention, while social risk was found to be insignificant. Among these factors, security risk is the main contributor for consumers to deter from purchasing online.

This study provides useful information to online retailers in electronic commerce (e-commerce) activities. Previous studies show that many online retailers are still facing some risks in online business, and this will affect the transaction and performance of the retailers. It is hoped that the findings can help online retailers to formulate strategies to reduce risks in the online shopping environment, especially security risks for better e-commerce.

The development of online shopping has led to some challenges to consumers, which comprise security of payment, data protection, the validity and enforceability of e-contract, insufficient information disclosure, product quality and enforcement of rights. This issue emerged because many online retailers do not understand the main factors that will contribute to consumers’ perceived risk. Consumers’ perceived risks will influence consumer attitudes toward online shopping and purchase behaviors. Studies on consumers’ perceived risks toward online purchase intentions are still inconclusive. Thus, this paper fills the gap in the research area.

The purpose of this paper is to examine the relationship between the stress experienced by parents during the pandemic and their cyberchondria. The research was carried out in a descriptive and cross-sectional manner.

The sample of the research: living in Turkey and has created 432 parents with at least one child between the ages of 6 and 15. Participant information form, parental stress scale and cyberchondria scale were used in the study. Data were collected through online surveys between July 1, 2020, and August 31, 2020.

In the study, when the scores obtained from the Parental Stress Scale and the Cyberchondria Scale were compared with the demographic characteristics, a significant difference was found between gender, age, marital status, education level, economic status, number of children and presence of chronic diseases (p < 0.05). It was determined that there is a significant difference between the responses of the parents regarding the pandemic process and the Parental Stress Scale and the Cyberchondria Scale (p < 0.05). A positive significant correlation was found between the Parental Stress Scale and the total and subdimensions of the Cyberchondria Scale (p < 0.05).

The research was carried out with only parents with children between the ages of 6 and 15, but it reveals the stress and cyberchondria of the parents during the pandemic.

The results obtained reflect the factors affecting the stress and cyberchondria levels experienced by parents during the pandemic process. Also, as the stress of the parent's increases, it has seen that the level of cyberchondria increases in parallel.