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This study explores features that impact consumers' purchase intention through artificial intelligence (AI), because it is believed that through artificial intelligence, consumers' intention to purchase grows significantly, especially in the retail sector, whereby retailers provide lucrative offers to motivate consumers. The study develops a theoretical framework based on media-richness theory to investigate the role of perceived anthropomorphism toward an intention to purchase products using AI.

The study is based on cross-sectional data through an online survey. The data have been analyzed using PLS-SEM and SPSS PROCESS macro.

The results show that consumers tend to demand anthropomorphized products to gain a better shopping experience and, therefore, demand features that attract and motivate them to purchase through artificial intelligence via mediating variables, such as perceived animacy and perceived intelligence. Moreover, trust in artificial intelligence moderates the relationship between perceived anthropomorphism and perceived animacy.

The study investigates and concludes with managerial and academic insights into consumer purchase intention through artificial intelligence in the retail and marketing sector.

This research paper aims to investigate reinforced concrete (RC) walls' behaviour under fire and identify the thermal and mechanical factors that affect their performance.

A three-dimensional (3D) finite element (FE) model is developed to predict the response of RC walls under fire and is validated through experimental tests on RC wall specimens subjected to fire conditions. The numerical model incorporates temperature-dependent properties of the constituent materials. Moreover, the validated model was used in a parametric study to inspect the effect of the fire scenario, reinforcement concrete cover, reinforcement ratio and configuration, and wall thickness on the thermal and structural behaviour of the walls subjected to fire.

The developed 3D FE model successfully predicted the response of experimentally tested RC walls under fire conditions. Results showed that the fire resistance of the walls was highly compromised under hydrocarbon fire. In addition, the minimum wall thickness specified by EC2 may not be sufficient to achieve the desired fire resistance under considered fire scenarios.

There is limited research on the performance of RC walls exposed to fire scenarios. The study contributed to the current state-of-the-art research on the behaviour of RC walls of different concrete types exposed to fire loading, and it also identified the factors affecting the fire resistance of RC walls. This guides the consideration and optimisation of design parameters to improve RC walls performance in the event of a fire.

Immigration-themed children’s literature can be an important resource in the classroom, especially because some U.S. immigrant groups, including French-Canadians, have received limited curricular representation. Using the qualitative method of critical content analysis, this study aims to examine depictions of French-Canadian immigrants to the United States in contemporary children’s books.

Postcolonialism is employed as an analytical lens with special attention given to the ways immigrant characters are constructed as different from the dominant group (i.e., othering), how dominant group values are imposed on immigrant characters, and how immigrant characters resist othering and domination. Three books comprise the sample: “Charlotte Bakeman Has Her Say” by Mary Finger and illustrated by Kimberly Batti, “Other Bells for Us to Ring” by Robert Cormier, and “Red River Girl” by Norma Sommerdorf.

The findings reveal multiple instances in which French-Canadian immigrants are constructed as Other and few instances in which these characters resist this positioning, and these books reflect the real ways French-Canadians were perceived as subalterns during the mass migration from Québec to the United States between the late 19th and early 20th centuries.

This study is significant because it examines portrayals of a substantial immigrant group that has been overlooked in the immigration history curriculum. This sample of children’s books may be used to teach children the complexities of immigration history and provide a more nuanced understanding of immigration during the 19th and 20th centuries.

This study examines the effect of temperature-dependent material models for normal-strength (NSC) and high-strength concrete (HSC) on the thermal analysis of reinforced concrete (RC) walls.

The study performs an one-at-a-time (OAT) sensitivity analysis to assess the impact of variables defining the constitutive and parametric fire models on the wall's thermal response. Moreover, it extends the sensitivity analysis to a variance-based analysis to assess the effect of constitutive model type, fire model type and constitutive model uncertainty on the RC wall's thermal response variance. The study determines the wall’s thermal behaviour reliability considering the different constitutive models and their uncertainty.

It is found that the impact of the variability in concrete’s conductivity is determined by its temperature-dependent model, which differs for NSC and HSC. Therefore, more testing and improving material modelling are needed. Furthermore, the heating rate of the fire scenario is the dominant factor in deciding fire-resistance performance because it is a causal factor for spalling in HSC walls. And finally the reliability of wall's performance decreased sharply for HSC walls due to the expected spalling of the concrete and loss of cross-section integrity.

Limited studies in the current open literature quantified the impact of constitutive models on the behaviour of RC walls. No studies have examined the effect of material models' uncertainty on wall’s response reliability under fire. Furthermore, the study's results contribute to the ongoing attempts to shape performance-based structural fire engineering.

This paper aims to identify the variables responsible for classifying the investors into risk takers (RT) and risk avoiders (RA) across their economic perspectives.

The research offers a novel and unobtrusive measure of classifying investors into RT and RA based on a set of financial risk tolerance (FRT) questions. The authors have investigated the causes of discrimination across economic perspectives over a sample of 552 investors exposed to market risk.

The authors identify that out of the total of 11 risk assessment variables, only three are responsible for classifying investors into RA and RT. The variables are risk return trade-off, comfort level dealing with risk, and understanding short-term volatility. Financial literacy is considered as an emerging cause of discrimination. Further, the authors highlight the most striking finding to be the discriminating factors across wealth and source of income of the investors.

Existing research on FRT can be loosely segregated into three groups: the relationship between an individual's financial and non-FRT, estimation of FRT score (FRTS), and perceived self-assessed FRTS. The current research roughly falls into the third category of study where the authors have not only studied the self-assessed risk tolerance but also evaluated the predictors. Most of the studies have focussed on estimating self-assessed FRT with the help of one direct question to the respondent. However, the uniqueness of this study is that the researchers have used an instrument comprising a series of direct and indirect questions that can easily estimate the self-assessed risk perception and also discriminate the role of the economic factors that have any impact on self-assessed FRTS.