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This study aims to evaluate the dyeing of the p-aramid fibre with cationic dyes and investigate the effect of dyeing in the protection of the fibre from ultraviolet (UV) light.

P-aramid fabric has been dyed with cationic dyes using benzyl alcohol as swelling agent to promote the penetration of dye molecules into the fibre. The fabrics were evaluated against colour strength (K/S) value and colour fastness properties after dyed with cationic dyes using full factorial design. This design was used to study the effect of factors that affect the response variables as well as to study the interactions among the factors on response variable. The bursting strength, scanning electron microscopy analysis and X-ray diffraction analysis of undyed and dyed p-aramid fabric were performed before and after exposure to UV light to investigate the changes in mechanical behaviour.

The results show that the p-aramid fabric dyed with cationic dyes has good K/S values and good fastness properties. The exposure of undyed p-aramid fabric to UV light causes serious loss in strength over short duration i.e. 40 h. Dyeing of p-aramid fabric enhances the resistance to UV light which reduces the loss in strength.

Most of the work is patented and no one has done the process optimization for the industry, so this study offers promising outcomes concerning the dyeing of p-aramid fabric with enhanced shade depth and good colour fastness characteristics.

The reliability and corrosivity of two VOC ‐ free, no‐clean fluxes (C and D) were assessed using traditional test method such as copper mirror and copper corrosion tests. Modified surface insulation resistance (SIR) tests using coupons fluxed with various methods were performed in 50°C/90%RH environmental conditions. Printed circuit boards and assemblies were fluxed and exposed to a 50°C/90%RH chamber to assess long‐term reliability. To evaluate the corrosion rates of copper and solder sheets in as‐ received liquid fluxes, electrochemical polarisation measurements were employed. These showed that the corrosion rate of copper in flux D is 100 times higher than that in flux C. These quantitative data agreed with the qualitative copper mirror test results, i,e, flux C passed and flux D failed the test. However, both flux residues were found to corrode copper traces underneath the solder mask and copper pads on the PCB after three weeks in a 50°C/90% RH environment chamber. Large amounts of blue/green corrosion products were observed on the bare copper SIR coupons within seven days when using either flux; and SIR values were below the required 10₈ ohms. Based on the test results, neither flux was qualified for no‐clean processes because of the issues with corrosion. The corrosiveness of the VOC‐ free, no‐ clean flux residue is believed to be due to the activator packages used.

The transformative impact of artificial intelligence (AI) and technological advancements has captured the attention of various stakeholders, from researchers to policymakers and the general public. Despite the promise of AI's benefits, concerns persist regarding its ethical, privacy, security, and societal implications. Public trust in AI remains low, with fears surrounding its future use and governance growing among scholars and the public. These anxieties are fueled by media narratives raising scenarios such as the “AI revolution” or “AI apocalypse.” Moreover, the prospect of technology-driven unemployment adds to this climate of anxiety. Meanwhile, AI's increasing geopolitical influence has shifted its focus from innovation to dominance, with national governments viewing it as a tool for competitive repositioning. However, AI also poses threats to democracy, as it facilitates the spread of misinformation and undermines electoral integrity. In this chapter, we explore further the challenges AI presents to modern society and democracy, focusing on political practices and electoral risks. Our analysis focuses on the political and social dimensions of AI, arguing that its impacts are shaped by specific political decisions rather than abstract technological dynamics. We emphasize the need to acknowledge and address the political implications of AI to foster a more informed discourse surrounding its deployment and regulation.

Purpose – The goal of this chapter is to demonstrate the importance of incorporating gene by environment (G×E) interactions into behavioral science theory and research.

Design/methodology/approach – We critique behavioral genetics, discuss the emergence of epigenetics, review findings on G×E effects, and present the differential susceptibility model of gene–environment interplay.

Findings – The studies reviewed demonstrate that genetic variation often interacts with environmental context to influence the probability of various behaviors. Importantly, in many, and perhaps most, of the studies reviewed, the genetic variable, unlike the environmental variable, has little if any main effect on the outcome of interest. Rather, the influence of the genetic variable is limited to its moderation of the effect of the environmental construct.

Research limitations/implications – Molecular G×E research does not undermine the importance of environmental factors; rather it shows how social scientific explanations of human behavior might be made more precise by incorporating genetic information. This suggests expanded research opportunities for those interested in social causation.

Social implications – This model of molecular G×E research presented suggests that a substantial proportion of the population is genetically predisposed to be more susceptible than others to environmental influence. We argue that this model of G×E is particularly relevant to sociologists and psychologists and has the potential to enhance the development of theory in both areas.

Originality/value – This chapter will be of particular interest to sociologists and psychologists who have found the behavioral genetic paradigm off-putting because of its emphasis on genetic main effects and genetic determinism. The current chapter offers an alternative model that may better capture the available data and better integrate social processes with genetic and biological processes.

This paper aims to demystify the creative experiences of an extraordinary group of pastry chefs – The Malaysian World Pastry Team, champions of the 2019 World Pastry Cup. The authors adopted an expressionist theoretical lens informed by two aesthetic philosophers – John Dewey and Wassily Kandinsky.

A two-year portraiture was conducted – a qualitative methodology that draws features from phenomenology and narrative inquiry, rendering artistically and empirically written “portraits” that reflect themes and patterns of participants’ experiences. In-depth interviews, observations and material artifacts were collected amid a journey alongside nine extraordinary Malaysian pastry chefs.

Presented in story structures, the authors offer three “portraits” of culinary creativity, each representing a core essence of the creative phenomenon: creative harmony in the form of sensorial and symbolic poetry; imaginative episodes as a hypnotic state of inspiration and incubation; and the creative duality of scientific rationalism and artistic fashion. The authors delineated the intricacies of each theme by presenting them as individual narratives.

The portraits indicated that culinary creativity reflects an organic and emancipating aesthetic experience that is unbounded by formative structures or sequential processes. This provides a novel theoretical view that moves beyond conventional studies’ capitalistic frameworks, and toward the intimate viewpoints of the chef-creators. Specific contributions are discussed.

Through a unique qualitative approach and an aesthetic theoretical framework, this study provided a novel perspective on the culinary creative process. The aesthetic view captures culinary creativity through the eyes of the creator, a viewpoint less considered, yet imperative to the culinary profession.

Various time integration methods and time finite element methods have been developed to obtain the responses of structural dynamic problems, but the accuracy and computational efficiency of them are sometimes not satisfactory. The purpose of this paper is to present a more accurate and efficient formulation on the basis of the weak form quadrature element method to solve linear structural dynamic problems.

A variational principle for linear structural dynamics, which is inspired by Noble's work, is proposed to develop the weak form temporal quadrature element formulation. With Lobatto quadrature rule and the differential quadrature analog, a system of linear equations is obtained to solve the responses at sampling time points simultaneously. Computation for multi-elements can be carried out by a time-marching technique, using the end point results of the last element as the initial conditions for the next.

The weak form temporal quadrature element formulation is conditionally stable. The relation between the normalized length of element and the suggested number of integration points in one element is given by a simple formula. Results show that the present formulation is much more accurate than other time integration methods and its dissipative property is also illustrated.

The weak form temporal quadrature element formulation provides a choice with high accuracy and efficiency for solution of linear structural dynamic problems.

Boreout is a psychological state of intense boredom and apathy. Characterized by the absence of mental stimuli (i.e. menial tasks) required to keep employees conscious about their environment, and this incessant decline in mental stimuli may turn employees into “professional zombies.” The diversity in work needs and preferences across generations has become a key organizational factor, generational differences have been studied in Western countries, not much information is available about generational cohorts and satisfaction (i.e. career, life and job satisfaction) in developing countries. The purpose of this paper is to provide more insights on these phenomena.

Drawing upon conservation of resources theory, this paper examines the potential effects of boreout on important job outcomes (i.e. career, life and job satisfaction) conditioned by generation (Gen-Xers and Gen-Yers) in the service industry. Data analyses with Artificial Intelligence technique (i.e. artificial neural network) and structural equation modeling were conducted with data collated from Nigerian service employees.

Results revealed that boreout has a negative impact on career, life and job satisfaction. The hypothesized relationships were significantly moderated by generation cohorts as Gen-Xers and Gen-Yers were found to be distinct cohorts.

This paper advocates that non-western organizations should avoid utmost service standardization and rigid stylization of work processes and procedures.

This study examines the relationships among workplace incivility, job satisfaction and turnover intention for tourist hotel chefs. Furthermore, emotional intelligence is taken as the moderating variable on the relationships between workplace incivility and job satisfaction and workplace incivility and turnover intention.

Tourist hotel chefs were invited to participate in this study using purposive sampling, and a structured questionnaire was administered to carry out the investigation on tourist hotel chefs.

The results show that workplace incivility has negative effects on job satisfaction and casts positive effects on turnover intention through job satisfaction. Emotional intelligence has a significant moderating effect on the relationship between workplace incivility and job satisfaction.

This study firstly demonstrated the relationships among workplace incivility, job satisfaction and turnover intention for tourist hotel chefs. Furthermore, the moderating effect of emotional intelligence on the relationship between workplace incivility and job satisfaction was also validated.

With the continuous increase of users, resources and tags, social tagging systems gradually present the characteristics of “big data” such as large number, fast growth, complexity and unreliable quality, which greatly increases the complexity of recommendation. The contradiction between the efficiency and effectiveness of recommendation service in social tagging is increasingly becoming prominent. The purpose of this study is to incorporate topic optimization into collaborative filtering to enhance both the effectiveness and the efficiency of personalized recommendations for social tagging.

Combining the idea of optimization before service, this paper presents an approach that incorporates topic optimization into collaborative recommendations for social tagging. In the proposed approach, the recommendation process is divided into two phases of offline topic optimization and online recommendation service to achieve high-quality and efficient personalized recommendation services. In the offline phase, the tags' topic model is constructed and then used to optimize the latent preference of users and the latent affiliation of resources on topics.

Experimental evaluation shows that the proposed approach improves both precision and recall of recommendations, as well as enhances the efficiency of online recommendations compared with the three baseline approaches. The proposed topic optimization–incorporated collaborative recommendation approach can achieve the improvement of both effectiveness and efficiency for the recommendation in social tagging.

With the support of the proposed approach, personalized recommendation in social tagging with high quality and efficiency can be achieved.

The purpose of this paper is to perform the computational fluid dynamics (CFD) simulation with experimental validation to investigate the particle segregation effect in abrupt and smooth shapes circulating fluidized bed (CFB) risers.

The experimental investigations were carried out in lab-scale CFB systems and the CFD simulations were performed by using commercial software BARRACUDA. Special attention was paid to investigate the gas-particle flow behavior at the top of the riser with three different superficial velocities, namely, 4, 6 and 7.7 m/s. Here, a CFD-based noble simulation approach called multi-phase particle in cell (MP-PIC) was used to investigate the effect of traditional drag models (Wen-Yu, Ergun, Wen-Yu-Ergun and Richardson-Davidson-Harrison) on particle flow characteristics in CFB riser.

Findings from the experimentations revealed that the increase in gas velocity leads to decrease the mixing index inside the riser. Moreover, the solid holdup found more in abrupt riser than smooth riser at the constant gas velocity. Despite the more experimental investigations, the findings with CFD simulations revealed that the MP-PIC approach, which was combined with different drag models could be more effective for the practical (industrial) design of CFB riser. Well agreement was found between the simulation and experimental outputs. The simulation work was compared with experimental data, which shows the good agreement (<4%).

The experimental and simulation study performed in this research study constitutes an easy-to-use with different drag coefficient. The proposed MP-PIC model is more effective for large particles fluidized bed, which can be helpful for further research on industrial gas-particle fluidized bed reactors. This study is expected to give throughout the analysis of CFB hydrodynamics with further exploration of overall fluidization.