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The present paper aims at the multi-objective optimization of a reentrant hexagonal cell auxetic structure. In addition, a parametric analysis will be carried out to verify how each of the design factors impact each of the responses.

The multi-objective optimization of five different responses of an auxetic model was considered: mass, critical buckling load under compression effort, natural frequency, Poisson's ratio and failure load. The response surface methodology was applied, and a new meta-heuristic of optimization called the multi-objective Lichtenberg algorithm was applied to find the optimized configuration of the model. It was possible to increase the failure load by 26.75% in compression performance optimization. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. This paper addresses something new in the scientific world to date when evaluating in a multi-objective optimization problem, the compression and modal performance of an auxetic reentrant model.

It was possible to find multi-objective optimized structures. It was possible to increase the critical buckling load by 42.82%, and the failure load in compression performance by 26.75%. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%, and decrease the mass by 15.97%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, increase the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively.

There is no work in the literature to date that performed the optimization of 5 responses simultaneously of a reentrant hexagonal cell auxetic structure. This paper also presents an unprecedented statistical analysis in the literature that verifies how the design factors impact each of the responses.

The authors investigated the effect of basic human values in the prediction of COVID-19 vaccination behavior amongst public security agents in Brazil.

A sample of 15,313 Brazilian public security agents responded to the portrait values questionnaire and a COVID vaccination behavior measure. Multidimensional scaling analysis (MDS) was used to observe the order of the predicted by the theory. For hypotheses, the authors ran a series of Structural equation modeling (SEM) with direct effects between values and vaccination rate.

Results suggest that the values of conservation and self-transcendence positively predicted vaccination. A nonsignificative negative prediction was obtained for openness to change and self-enhancement values on vaccination behavior.

Data were collected using self-report questionnaires.

Institutional management should encourage capacitation campaigns aimed at public security agents, enabling a significant increase in vaccine protection for the public security institutions.

The reinforcement of conservation and self-transcendence values lead to the perception of the vaccine as a measure of caring for people in general and for the members of the ingroup, hence motivating the vaccination behavior.

The findings confirm that values encourage individuals to be vaccinated, due to their intrinsic motivation. This relationship did not appear to be clearly tested by previous empirical studies.

This study aims to apply for the first time in literature a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm and test the sensors' configuration found in a delamination identification case study.

This work aims to study the damage identification in an aircraft wing using the Lichtenberg and multi-objective Lichtenberg algorithms. The former is used to identify damages, while the last is associated with feature selection techniques to perform the first sensor placement optimization (SPO) methodology with variable sensor number. It is applied aiming for the largest amount of information about using the most used modal metrics in the literature and the smallest sensor number at the same time.

The proposed method was not only able to find a sensor configuration for each sensor number and modal metric but also found one that had full accuracy in identifying delamination location and severity considering triaxial modal displacements and minimal sensor number for all wing sections.

This study demonstrates for the first time in the literature how the most used modal metrics vary with the sensor number for an aircraft wing using a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm.

This paper aims at providing a comparative analysis of the existing protocols that address the security issues in the Future Internet (FI) and also to introduce a Collaborative Mutual Identity Establishment (CMIE) scheme which adopts the elliptical curve cryptography (ECC), to address the issues, such as content integrity, mutual authentication, forward secrecy, auditability and resistance to attacks such as denial-of-service (DoS) and replay attack.

This paper provides a comparative analysis of the existing protocols that address the security issues in the FI and also provides a CMIE scheme, by adopting the ECC and digital signature verification mechanism, to address the issues, such as content integrity, mutual authentication, forward secrecy, auditability and resistance to attacks such as DoS and replay attack. The proposed scheme enables the establishment of secured interactions between devices and entities of the FI. Further, the algorithm is evaluated against Automated Validation of Internet Security Protocols and Application (AVISPA) tool to verify the security solutions that the CMIE scheme has claimed to address to have been effectively achieved in reality.

The algorithm is evaluated against AVISPA tool to verify the security solutions that the CMIE scheme has claimed to address and proved to have been effectively achieved in reality. The proposed scheme enables the establishment of secured interactions between devices and entities of the FI.

Considering the Internet of Things (IoT) scenario, another important aspect that is the device-to-location (D2L) aspect has not been considered in this protocol. Major focus of the protocol is centered around the device-to-device (D2D) and device-to-server (D2S) scenarios. Also, IoT basically works upon a confluence of hundreds for protocols that support the achievement of various factors in the IoT, for example Data Distribution Service, Message Queue Telemetry Transport, Extensible Messaging and Presence Protocol, Constrained Application Protocol (CoAP) and so on. Interoperability of the proposed CMIE algorithm with the existing protocols has to be considered to establish a complete model that fits the FI. Further, each request for mutual authentication requires a querying of the database and a computation at each of the participating entities side for verification which could take considerable amount of time. However, for applications that require firm authentication for maintaining and ensuring secure interactions between entities prior to access control and initiation of actual transfer of sensitive information, the negligible difference in computation time can be ignored for the greater benefit that comes with stronger security. Other factors such as quality of service (QoS) (i.e. flexibility of data delivery, resource usage and timing), key management and distribution also need to be considered. However, the user still has the responsibility to choose the required protocol that suits one’s application and serves the purpose.

The originality of the work lies in adopting the ECC and digital signature verification mechanism to develop a new scheme that ensures mutual authentication between participating entities in the FI based upon certain user information such as identities. ECC provides efficiency in terms of key size generated and security against main-in-middle attack. The proposed scheme provides secured interactions between devices/entities in the FI.

The purpose of this paper is to investigate the mechanism of building trust during the transition from online payment to mobile payment, as well as to examine the effect of trust on the satisfaction and continuance intention of mobile payment users. Based on trust transfer theory, this study proposes that trust in online payment (i.e. trust in source) and two source-target relationship factors, namely, perceived similarity and entitativity, affect trust in mobile payment (i.e. trust in target). In turn, the resulting trust influences user satisfaction and continuance intention toward mobile payment in an online-mobile payment context.

The model was empirically tested on data collected from 219 mobile payment users of a famous payment enterprise in China.

The results indicated that the trust transfer process positively influences the continuance intention of mobile payment through satisfaction. Satisfaction is an important factor affecting continuance intention. Moreover, trust in online payment, perceived similarity, and perceived entitativity between online and mobile payments can positively influence trust in mobile payment.

This study investigates the post-adoption usage of mobile payment from the trust transfer perspective. It focuses on the trust-building process and emphasizes the importance of trust on the continuance intention toward mobile payment in an online-mobile payment context.

The financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of artificial intelligence (AI) in the context of FinTech services for enriching customer experiences has become a new norm in this modern era of technological advancement. So, it becomes crucial to understand the customer’s perspective. The current research ranks the factors and sub-factors influencing customers’ perceptions of AI-based FinTech services.

The sample size for this study was decided to be 970 respondents from four Indian cities: Mumbai, Delhi, Kolkata and Chennai. The Fuzzy-AHP technique was used to identify the primary factors and sub-factors influencing customers’ experiences with AI-enabled finance services. The factors considered in the study were service quality, trust commitment, personalization, perceived convenience, relationship commitment, perceived sacrifice, subjective norms, perceived usefulness, attitude and vulnerability. The current research is both empirical and descriptive.

The study’s three top factors are service quality, perceived usefulness and perceived convenience, all of which have a significant impact on customers’ experience with AI-enabled FinTech services discussing sub-criteria three primary criteria for customers’ experience for FinTech services include: “Using FinTech would increase my effectiveness in managing a portfolio (A2)”, “My peer groups and friends have an impact on using FinTech services (SN3)” and “Using FinTech would increase my efficacy in administering portfolio (PU2)”.

The current study is limited to four Indian cities, with 10 factors to understand customers’ preferences in FinTech. Further research can focus on other dimensions like perceived ease of use, familiarity, etc. Future studies can have a broader view of different geographical locations and consider new tech to understand customer perceptions better.

The study’s findings will significantly assist businesses in determining the primary aspects influencing customers’ experiences with AI-enabled financial services. As a result, they will develop strategies and policies to entice clients to use AI-powered FinTech services.

Existing AI research investigated several vital topics in the context of FinTech services. On the other hand, the current study ranked the criteria in understanding customer experiences. The research will substantially assist marketers, business houses, academicians and practitioners in understanding essential facets influencing customer experience and contribute significantly to the literature.

Several industries including banking are booming because of COVID-19. However, it is still unknown whether this growth is momentary or permanent in nature. Hence, this study aims to identify the role of health-related concerns and trust as stimuli on M-payment loyalty.

Data were collected through Google Forms from 431 participants. Subjects were M-payment users. The hypothesized model was tested using structural equational modeling.

Results of the study indicate that perceived severity and trust act as stimuli for M-payment loyalty. Further, trust not only influences loyalty directly but also through intimacy. Additionally, no linear relationship was found between perceived usefulness and M-payment loyalty.

This work is an early attempt to consider health-related concerns and trust as stimuli to predict M-payment loyalty. Further, this study focused on three new constructs, namely perceived severity, perceived susceptibility and intimacy, that are underexplored in digital banking literature.

Hematopoietic stem cell transplant (HSCT) patients can suffer from long-term transplant-related complications that affect their quality of life and daily activities. This study, a narrative review, aims to report the impact of HCT complications, the benefits of rehabilitation intervention, the need for long-term care and highlights the research gap in clinical trials involving rehabilitation.

A comprehensive search strategy was performed on several databases to look for relevant articles published from 1998 to 2018. Articles published in English with the following terms were used: hematopoietic stem cell transplant, chronic graft-versus-host disease, rehabilitation, exercise, physical therapy, occupational therapy. A patient/population, intervention, comparison, and outcomes (PICO) framework was employed to ensure that the search strategies were structured and precise. Study year, design, outcome, intervention, sample demographics, setting and study results were extracted.

Of the 1,411 records identified, 51 studies underwent title/abstract screening for appropriateness, 30 were reviewed in full, and 19 studies were included in the review. The review found that, for the majority of patients who underwent HSCT and developed treatment-related complications, rehabilitation exercises had a positive impact on their overall quality of life. However, exercise prescription in this patient group has not always reflected the scientific approach; there is a lack of high-quality clinical trials in general. The review also highlights the need to educate healthcare policymakers and insurance companies responsible for rationing services to recognise the importance of offering long-term follow-up care for this patient group, including rehabilitation services.

A large number of HSCT patients require long-term follow-up from a multidisciplinary team, including rehabilitation specialists. It is important for healthcare policymakers and insurance companies to recognise this need and take the necessary steps to ensure that HSCT patients receive adequate long-term care. This paper also highlights the urgent need for high-quality rehabilitation trials to demonstrate the feasibility and importance of rehabilitation teams.

Healthcare policymakers and insurance companies need to recognise that transplant patients need ongoing physiotherapy for early identification of any functional impairments and appropriate timely intervention.

This paper aims to assess the direct effects of antecedents of initial trust, the mediating effect of trust and the moderating effect of demographic variables on non-adopters’ behavioral intention to use mobile banking.

The study tested the models of theory of reasoned action and theory of planned behavior to evaluate potential antecedents of trust (diffusion of trust, infrastructure quality, perceived costs, privacy and security) moderators (demographic variables) and mediators (initial trust) that will influence behavioral intention to use mobile banking. The Hayes’ Process Macro developed by Andrew F. Hayes (2013) was used as a statistical analysis in SPSS to estimates the path coefficients using multiple regression. The tool provides insights on the direct and indirect effect of the independent variable on the dependent variable through the existence of moderating variables and mediation variables.

The results show that the non-adopters of mobile banking asserted that the antecedents of initial trust played a significant influence on behavioral intention to use online banking services.

There is a dearth of literature addressing mobile banking in the Philippines. The first initial trust formation in internet banking using computer workstations and laptops in the Philippines was conducted by Chiu et al. (2016). This research fills in the gap by expanding and formulating a deeper understanding of the antecedents of initial trust that influence consumer behavioral intention that might be responsible for the slow diffusion of mobile banking services in the country. The results from this study will help financial institutions create a beneficial connection with consumers while alleviating the fears of non-adopters and enhancing their understanding of the benefits of mobile banking.

The rapid growth of technology, including artificial intelligence (AI), in the banking industry has played a disrupting role in traditional banking channels. This study aims to investigate factors that influence the attitudes and perceptions of digital natives pertaining to mobile banking and comfort interacting with AI-enabled mobile banking activities.

Data were collected from 218 digital natives. This paper uses multivariate regression and two separate multiple regression analyses to examine the differential effects of technology-based (i.e. attitudes toward AI, relative advantage, perceived trust and security in specific mobile banking activities) and non-technology based (i.e. need for service, quality of service) factors on mobile banking usage and AI-enabled mobile banking services.

This study identifies determining factors for mobile banking and AI-enabled mobile banking services. Results indicate a divide in how digital natives perceive relative advantage between our two dependent variables. Consistent with previous studies, the relative advantage construct has the most impact on mobile banking usage. However, relative advantage was not significant for AI-enabled mobile banking, suggesting an extra layer of complexity that goes beyond convenient fast banking.

A limitation of this study is that it does not incorporate age groups outside of digital natives. Further research is needed to test for differential effects between age groups. In addition, the discovery of no significant impact of relative advantage on AI mobile banking warrants more research on the similarities and differences between mobile banking and AI-enabled mobile banking.

To better appeal to digital natives, it is suggested that the banking industry emphasize mobile banking’s anywhere/anytime access to financial accounts, as this is important to college-age customers who may not live near their local banking institution. Moreover, the paper suggests that improvement to mobile banking features for one-on-one interpersonal contact with bank employees is needed.

This study addresses the gap in the understanding of how digital natives perceive mobile banking in comparison to AI-enabled mobile banking services.