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This work intends to evaluate experimentally the ratcheting behaviour of AM MS300. Furthermore, cyclic plasticity modelling (modified Abdel-Karim and Ohno model) is examined as a means of predicting ratcheting.

Uniaxial stress-controlled cyclic loading histories were utilised to evaluate ratcheting for Maraging Steel 300 (MS300) fabricated via laser powder bed fusion (LPBF) additive manufacturing (AM). Heat-treated and as-built AM and conventionally manufactured (CM) MS300 coupons were tested at room temperature, under constant and incrementally variable stress amplitude and mean stress. Two sets of AM test coupons were used, printed at horizontal and vertical built orientation. The AM material ratcheting was predicted via constitutive modelling and numerical simulation. The Abdel-Karim and Ohno cyclic plasticity model was modified by introducing a memory surface, to improve ratcheting prediction.

The hysteresis stress–strain response and low cycle fatigue (LCF) life were obtained from the different loading histories. Both the AM and CM MS300 exhibited an accumulation of axial strain (ratcheting) for all tests, attributed to the application of non-zero mean stress. The AM MS300 has demonstrated a higher ratcheting accumulation rate than the CM material. The achieved agreement between the numerical results of the new model and the experimental data offers an indication on the suitability and the robustness of this model.

The ratcheting behaviour of the AM MS300 material has been characterised for the first time in the published literature, for a variety of loading histories selected. A modified Abdel-Karim and Ohno plasticity model has been developed to account for the ratcheting performance of this material.

The main purpose of this study is to make a comparative evaluation of the impacts of previous outbreaks and coronavirus disease 2019 (COVID-19) on the tourism industry. COVID-19 appears to have disrupted all memorizations about epidemics ever seen. Nobody has anticipated that the outbreak in late December will spread rapidly across the world, be fatal and turn the world economy upside down. Severe acute respiratory syndrome, Ebola, Middle East respiratory syndrome and others caused limited losses in a limited geography, thus similar behaviors were expected at first in COVID-19. But it was not so. Today, people continue to lose their lives and experience economic difficulties. One of the most important distressed industries is undoubtedly tourism.

This study is a literature review. In this review, a comparative evaluation between the impact of previous outbreaks and COVID-19 on the tourism industry has been made based on statistics and previous research studies.

The information and figures obtained show that COVID-19 and previous outbreaks have such significant differences that cannot be compared. COVID-19 has been one of the worst to live in terms of spreading speed, the geography where it spreads, loss of lives and negative effects in the whole area.

It is noteworthy that COVID-19 is very severe in terms of death cases and also its impacts on the economy compared to other pandemics. It remains to be argued that COVID-19 can also be a reference in terms of possible new outbreaks in the future, and is an effective actor in determining future strategies.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.

A total of 1,432 crashes and 19,714 baselines were collected for the Strategic Highway Research Program 2 naturalistic driving research. The authors used a case-control approach to estimate the prevalence and the population attributable risk percentage. The mixed logistic regression model is used to evaluate the correlation between different driver demographic characteristics (age, driving experience or their combination) and the crash risk regarding cell phone engagements, as well as the correlation among the likelihood of the cell phone engagement during the driving, multiple driver demographic characteristics (gender, age and driving experience) and environment conditions.

Senior drivers face an extremely high crash risk when distracted by cell phone during driving, but they are not involved in crashes at a large scale. On the contrary, cell phone usages account for a far larger percentage of total crashes for young drivers. Similarly, experienced drivers and experienced-middle-aged drivers seem less likely to be impacted by the cell phone while driving, and cell phone engagements are attributed to a lower percentage of total crashes for them. Furthermore, experienced, senior or male drivers are less likely to engage in cell phone-related secondary tasks while driving.

The results provide support to guide countermeasures and vehicle design.

This paper is a survey of recent academic developments in the literature on green bonds, which have become an important financial instrument in socially responsible investment. This study provides a review of papers that study the market pricing of green bonds, the economic and environmental effects of green bond financing, as well as legal and institutional issues in the green bond market. The literature on market pricing focuses mainly on the existence of greenium, which represents the extent to which green bonds carry a price premium over otherwise identical non-green counterparts. The literature on the economic and environmental effects mainly concerns stock market reaction to green bond issuance and associated economic value implications to other stakeholders, as well as investment in green projects. This paper discusses current issues in the green-bond market and avenues for future research.