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Driven by the explosive growth of artificial intelligence, WealthTech has played a pivotal role in reshaping the wealth management industry in recent years. Within this context, this study aims to explain the antecedents of users’ continuance intention to use the WealthTech platform by integrating the technology continuance theory (TCT), task-technology fit (TTF) and digital nudging.

To empirically test the research model, an online survey was conducted among 337 investors who had previously used WealthTech platform. The authors used partial least squares structural equation modeling (PLS-SEM) to assess the research model and test the hypotheses.

PLS-SEM results show that the proposed model has moderate explanatory power in explaining WealthTech continuance intention. The results also found that attitude, digital nudging and satisfaction are important drivers in promoting WealthTech continuance intention. According to importance performance map analysis, digital nudging, expectation confirmation and satisfaction are critical factors in explaining continuance intention, which require managerial action.

To the best of the authors’ knowledge, this is one of the earliest studies that analyze the determinants of WealthTech continuance intention by integrating TCT with TTF and digital nudging. The study’s findings highlight the importance of fit factors and digital nudging in promoting successful WealthTech services.

Artificial intelligence (AI)-based systems can save the lives of many people by assessing the safety of flight paths. Unfortunately, the world witnessed a horrible event in January 2020 with the case of flight 752 of Ukrainian International Airlines from Tehran to Kiev and it has prompted us to ask how AI can prevent such events by warning to flight path planners. This paper aims to propose a framework for assessing the safety of flight paths from a shooting of an airplane by air defense systems installed on the path. Unlike the existing studies, this study takes a new look at pre-flight risk assessment by using textual information in social and news networks. To this end, the authors use existing information retrieval techniques to identify high flight risk areas by examining the news articles, comments, posts, tweets, etc., in social media and then estimate the probability of targeting a passenger aircraft by the air defense systems probably installed on high-risk areas with the help of a statistical model. This estimation can then be used by fight planners to avoid such events.

To design a framework for estimating the probability of a fatal shooting of an airplane by air defense systems installed on its flight path, the authors have used the idea of information retrieval in conjunction with statistical methods. The authors have extracted some significant variables in the shooting of flights and proposed an AI-based framework to estimate the probability of a fatal shooting of an airplane during its flight and sketched a case study for using machine learning approaches to assist with flight path planning. As a case study, the authors covered flight 752 to explain the usefulness of the proposed framework in this context.

Unlike the existing methods, this study investigates flight path safety assessment from the social media and crowdsourcing perspective. In this study, the authors proposed an AI-based framework to avoid aviation hazards by estimating the probability of a shooting of an airplane by air defense systems installed on its flight path. Moreover, this study was designed to show how estimating the safety of flight paths by using AI-based methods can help flight planners to avoid such events and gain further insights into the use of AI-based systems in pre-flight risk assessment.

The idea behind the proposed method is original and as the authors’ best knowledge, there is no similar framework using social media for flight path safety assessment.

12. The provisions of these Regulations with respect to prohibiting any preservative or colouring matter or thickening substance in articles of food and requiring the labelling of certain articles of food and of articles sold as preservatives shall not apply in the case of any article which is intended to be exported or re‐exported or in the case of butter intended for use as ships' stores.

Since the rise of rationalism (Bond, 1935) the imagination has often been considered too subjective, and at times regarded with scholarly skepticism (Burke, 2008). Yet, imagination seems to provide basic psychological functions for the human intellect and our understanding particularly of large problems (Hillman, 1975), (Winnicott, 1971). More than the mere ‘fancy’ criticized by Dr Johnson (Havens, 1943), the imagination serves both speculative and interpretive functions, displaying distinct use of cerebral imagery to solve complex environmental and interpersonal challenges. Yorke (2013) argues that humans experience the world dialectically, interpreting everything as cause and effect. Imagination plays a vital role in these universal narratives, shaping our cultural heritage, expression and experience (Zittoun & Gläveanu, 2018). Our oldest tales feature monsters, creatures who are often more interesting and memorable than the heroes who fight them. Halberstam (1995) theorises that monsters are meaning machines. Monsters serve an admonitionary role, and their transgressive nature defines them while displaying a distinct visuality. Like imagination, monsters enable us to analyse and approach difficult topics in innovative ways.

H. P. Lovecraft is one of the most influential horror writers of the twentieth century (King, 1985). Imagination, the visual and the monstrous find a unique balance in his works. Using Lovecraft's copious correspondence, his drawings and his 1927 short story The Call of Cthulhu as a lens, the relationships between imagination, the visual and the monstrous are examined. These postulate an underlying mutual interdependence between the normative and the monstrous and suggest Lovecraft's imaginative use of the visual and monstrous to transgress the bounds of conventional epistemologies and experiences, thereby displacing the anthropocentric focus of conventional narratives.

This paper aims to present the continuous Nigerian Government’s failure to protect the lives and property of its citizens against the incessant itinerant herders’ violence, despite its numerous programs in attempts to end the carnage. It sought also to examine the relationship between this government’s failure to meet its responsibility and the ineluctable self-defense mechanisms adopted by the people of Plateau State, Nigeria.

The research was both quantitative and qualitative. The study was conducted in four of the 17 Local Government Areas of the state: Bassa, Jos-south, Riyom and Barkin Ladi. A sample size of 400 was determined using Yamane Taro’s sampling size formula. Four hundred respondents were interviewed using a Google questionnaire (found at this link: https://forms.gle/tu96ZDwP85e8JsGu8). In this study, a total of seven key informant interviews and nine focus group discussions were conducted.

The finding revealed that most indigenous ethnic groups were dissatisfied with the government’s handling of the nomadic herders’ aggression. Therefore, 99.1% of Berom, 99.0% of Irigwe and 92.9% of other ethnicities argued that the government’s failure to protect them is a tacit permission for self-defense. On the contrary, 60.0% of the Fulani were satisfied with the government’s strategies in ending the aggression and 95.0% of them argued that the government’s failure to protect its citizens is not an implied permission for self-defense. It was also found that a relationship exists between the government’s lack of capacity to end the nomadic herders’ aggression and implied consent for self-defense in Plateau State, Nigeria.

This is a research paper that uses primary data. The findings are germane to ending the challenge of recurrent aggression of nomadic herders on other Nigerians. The study concludes that the government must live up to its responsibility of the protection of its citizens’ lives and property, failure to do so is an implicit permission to the citizens to defend themselves. It also recommended that the government should return displaced people to their communities.

This study aims to improve the detection and quantification of cardiac issues, which are a leading cause of mortality globally. By leveraging past data and using knowledge mining strategies, this study seeks to develop a technique that could assess and predict the onset of cardiac sickness in real time. The use of a triple algorithm, combining particle swarm optimization (PSO), artificial bee colony (ABC) and support vector machine (SVM), is proposed to enhance the accuracy of predictions. The purpose is to contribute to the existing body of knowledge on cardiac disease prognosis and improve overall performance in health care.

This research uses a knowledge-mining strategy to enhance the detection and quantification of cardiac issues. Decision trees are used to form predictions of cardiovascular disorders, and these predictions are evaluated using training data and test results. The study has also introduced a novel triple algorithm that combines three different combination processes: PSO, ABC and SVM to process and merge the data. A neural network is then used to classify the data based on these three approaches. Real data on various aspects of cardiac disease are incorporated into the simulation.

The results of this study suggest that the proposed triple algorithm, using the combination of PSO, ABC and SVM, significantly improves the accuracy of predictions for cardiac disease. By processing and merging data using the triple algorithm, the neural network was able to effectively classify the data. The incorporation of real data on various aspects of cardiac disease in the simulation further enhanced the findings. This research contributes to the existing knowledge on cardiac disease prognosis and highlights the potential of leveraging past data for strategic forecasting in the health-care sector.

The originality of this research lies in the development of the triple algorithm, which combines multiple data mining strategies to improve prognosis accuracy for cardiac diseases. This approach differs from existing methods by using a combination of PSO, ABC, SVM, information gain, genetic algorithms and bacterial foraging optimization with the Gray Wolf Optimizer. The proposed technique offers a novel and valuable contribution to the field, enhancing the competitive position and overall performance of businesses in the health-care sector.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.