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Businesses embark on cause-related marketing (CRM) initiatives as a marketing strategy to fortify consumers' behavioural intentions. Prior research indicates that human values could be tapped to understand the consumers' responses to perceived organizational motives behind undertaking social cause initiatives. This research employs Schwartz's theory of human values to examine consumers' patronage intentions towards CRM-linked fashion products. Moreover, fashion leaders play a crucial role in the diffusion of the latest fashion and fashion trends. This research investigates by integrating human values and fashion leadership, offering insights into CRM-linked fashion consumption motives.

The overarching goal was to investigate the complex interplay between human values and female fashion leadership to predict CRM patronage intention (CPI). Hence, a large-scale research study on 2,050 samples was undertaken by adopting threefold partial least squares–multigroup analysis–artificial neural network (PLS-MGA-ANN) to establish and empirically test a comprehensive model.

This study is unique as it establishes and validates the relative or normalized importance placed on human values by fashion leaders, thereby predicting CPIs. The results revealed that women with high-fashion leadership and specific value types (benevolence, universalism, self-direction) are more likely to patronize CRM-linked fashion retailers. In addition, the findings validated that women with low-fashion leadership and specific value types (tradition, security, conformity) are more likely to patronize CRM-linked fashion stores.

The findings provide a valuable rationale to non-profit marketers, fashion marketing experts and practitioners to design customer value-based profiling and manage crucial CRM decisions.

Recent studies have observed rise in consumer’s ethical concerns about the online retailers while making a purchase decision. The impetus for businesses to use corporate social responsibility (CSR) is evident, but the effects of CSR motives on corresponding processes underlying cause-related marketing (CRM) patronage intention have not been thoroughly examined. This study, anchored on attribution theory, established a research model that better explains the influence of CSR motives on patronage intentions toward CRM-oriented online retailers. Additionally, this study aims to examine the moderating role of spirituality (SPT) on CSR motives and CRM patronage intention (CPI).

Primary data has been collected from 722 respondents and analyzed by using deep neural-network architecture by using the innovative PLS-SEM-ANN method to predict/rank the factors impacting CPI.

The results revealed the normalized importance of the predictors of CPI and found that value-driven motive was the strongest predictor, followed by strategic motive, SPT, age and stakeholder-driven motive. In contrast, egoistic motive, education and income were found insignificant.

The pandemic has transformed the way consumers shop and fortified the online economy, thereby resulting in a paradigm shift toward usage of e-commerce platforms. The results offer valuable insights to online retailers and practitioners for predicting patronage intentions by CSR motives and, thus, effectively engage CRM consumers by designing promotions in a way that would deeply resonate with them. This study assessed and predicted the factors influencing the CPI s, thereby guiding the online retailers to design CSR strategies and manage crucial CRM decisions.

The Government of India’s National Policy of Education 2020 stipulates that in the following five years all stand-alone teacher education colleges will be required to convert to multidisciplinary higher education institutions. This calls for a complete overhaul of the country’s vast, diverse, and age-old system of teacher preparation. Evidence-based policy implementation is thus the need of the hour. This chapter attempts to aid the process by presenting insights from a comparative education research on pre-service teacher education (PSTE) of secondary school teachers at stand-alone teacher education institutions (TEIs) in the Indian city of Mumbai and university-based teacher education in the Chinese city of Hong Kong. Documentary sources, field visits, and 57 interviews form the basis of the findings. The dimensions for comparison include academic freedom and autonomy; pathways to PSTE; linkages of teacher education providers; and role and working conditions of teacher educators. The chapter deduces the core differences in teacher education at stand-alone TEIs vis-à-vis that at a university and draws out implications of shutting down the former. It concludes by laying down a road map for the effective universitization of teacher education in India that will result in genuinely improving teacher quality.

Medical tourism demands tremendous responsiveness and accountability. The triple bottom line in medical tourism indicates that these organizations must emphasize on economic profits, environmental protection, and conservation of social resources. Developing a resilient medical tourism ecosystem is another critical necessity after the COVID-19 pandemic. The present study attempts to study the various aspects of medical tourism while synthesizing the relevant theories. This synthesis was used to propose a framework for developing a resilient medical tourism system. The outcomes of the chapter also propose the long, medium, and short-term goals. These goals focus on relevant stakeholders for developing highly integrated and resilient medical-tourism destinations.

Since the spread of mass education around the world in the mid- to late-twentieth century, teacher quality has been heralded as the key factor to improve education quality nationwide. National education systems worldwide are also engaged in ongoing and often high stakes cross-national comparisons. As a result, policy-makers and educators in most national education systems are looking at and implementing new ways to improve education overall by raising teacher quality levels, and India is no exception. In India, teacher quality is publicly blamed for both perceived low education quality and demonstrated low average student performance, especially following Indian students’ performance on the 2009 Programme for International Student Assessment. Indian education policy-makers are, therefore, looking at teacher quality as a key factor to improve student performance. Little is known about the impact or implementation of Indian policy frameworks on teacher quality and associated student outcomes in India. This introductory chapter identifies and analyzes various measures of teacher quality and how teacher quality varies in India both in response to and in spite of national policies related to teacher quality. It begins by providing evidence regarding the global importance of teacher quality on student outcomes and then addresses the ambiguity of the term “teacher quality.” This chapter then briefly discussed national education policy in India and the role teacher quality has played in these national policies, especially in the early twenty-first century, including NCF 2005, NCFTE 2009, Draft NPE 2016, Draft NPE 2019, and NPE 2020.

The purpose of this paper is to study elastic properties of III-V nitride nanotubes (NNTs) using second generation (REBO) potential.

In the present research paper elastic properties of BN, AlN and GaN nanotubes have been investigated, using the second generation REBO potential by Brenner and co-workers, which is a bond order potential earlier used for carbon nanostructures successfully. In the present calculation, the same form of potential is used with adjusted parameters for h-BN, h-AlN and h-GaN. In all these cases the authors have considered graphite like network and strongly polar nature of these atoms so electrostatic forces are expected to play an important role in determining elastic properties of these nanotubes. The authors generate the coordinates of nanotubes of different chirality’s and size. Each and every structure thus generated is allowed to relax till the authors obtain minima of energy. The authors then apply the requisite compressions, elongations and twists to the structures and compute the elastic moduli. Young’s Modulus, Shear Modulus and Poisson’s ratio for single-walled armchair and zigzag tubes of different chirality’s and size have been calculated. The computational results show the variation of Young’s Modulus, Poisson’s ratio and Shear Modulus for these NNTs with nanotube diameter. The results have been compared with available data, experimental as well as theoretical.

The authors have calculated bond length, cohesive energy/bond, Strain energy, Young’s Modulus, Shear Modulus and Poisson’s ratio.

To the best of the knowledge this work is the first attempt to study elastic properties of III-V NNTs using second generation REBO potential

The purpose of this study was to determine the rate of concordance and discordance between clinical diagnosis and post‐mortem findings in patients admitted to the hospitals of the Saskatoon Health Region.

A retrospective record review of the medical and autopsy charts was carried out for all the deceased adult in‐patients admitted during calendar years 2002, 2003 and 2004. A total of 3416 in‐patient deaths were registered during the study period. Autopsies were performed on 206 of the deceased resulting in an autopsy rate of 6 percent. In accordance with selection criteria, 158 cases were included for this study. The mean age of subjects was 66.6±15.3 years with a range of 16‐94 years. The study group consisted of 92 males (58.2 percent) and 66 females (41.8 percent) with an average length of stay at the hospital of 12.9±10.9 days.

The concordance rate between clinical and autopsy diagnosis was found to be 75.3 percent. The discordance rate was 20.9 percent and in 3.8 percent of the study population a conclusive clinical or autopsy diagnosis was not finalized.

These results suggest that despite of the technical advances in medical and diagnostic modalities, diagnostic discrepancies in the present day health care system remain prevalent.

The authors encourage residents and physicians to continue using autopsy as an important tool to extend understanding of disease processes.

Phishing is one of the major threats affecting businesses worldwide in current times. Organizations and customers face the hazards arising out of phishing attacks because of anonymous access to vulnerable details. Such attacks often result in substantial financial losses. Thus, there is a need for effective intrusion detection techniques to identify and possibly nullify the effects of phishing. Classifying phishing and non-phishing web content is a critical task in information security protocols, and full-proof mechanisms have yet to be implemented in practice. The purpose of the current study is to present an ensemble machine learning model for classifying phishing websites.

A publicly available data set comprising 10,068 instances of phishing and legitimate websites was used to build the classifier model. Feature extraction was performed by deploying a group of methods, and relevant features extracted were used for building the model. A twofold ensemble learner was developed by integrating results from random forest (RF) classifier, fed into a feedforward neural network (NN). Performance of the ensemble classifier was validated using k-fold cross-validation. The twofold ensemble learner was implemented as a user-friendly, interactive decision support system for classifying websites as phishing or legitimate ones.

Experimental simulations were performed to access and compare the performance of the ensemble classifiers. The statistical tests estimated that RF_NN model gave superior performance with an accuracy of 93.41 per cent and minimal mean squared error of 0.000026.

The research data set used in this study is publically available and easy to analyze. Comparative analysis with other real-time data sets of recent origin must be performed to ensure generalization of the model against various security breaches. Different variants of phishing threats must be detected rather than focusing particularly toward phishing website detection.

The twofold ensemble model is not applied for classification of phishing websites in any previous studies as per the knowledge of authors.

The complications caused by metallic orthopaedic bone screws like stress-shielding effect, screw loosening, screw migration, higher density difference, painful reoperation and revision surgery for screw extraction can be overcome with the bioabsorbable bone screws. This study aims to use additive manufacturing (AM) technology to fabricate orthopaedic biodegradable cortical screws to reduce the bone-screw-related-complications.

The fused filament fabrication technology (FFFT)-based AM technique is used to fabricate orthopaedic cortical screws. The influence of various process parameters like infill pattern, infill percentage, layer height, wall thickness and different biological solutions were observed on the compressive strength and degradation behaviour of cortical screws.

The porous lattice structures in cortical screws using the rapid prototyping technique were found to be better as porous screws can enhance bone growth and accelerate the osseointegration process with sufficient mechanical strength. The compressive strength and degradation rate of the screw is highly dependent on process parameters used during the fabrication of the screw. The compressive strength of screw is inversely proportional to the degradation rate of the cortical screw.

The present study is focused on cortical screws. Further different orthopaedic screws can be modified with the use of different rapid prototyping techniques.

The use of rapid prototyping techniques for patient-specific bone screw designs is scantly reported. This study uses FFFT-based AM technique to fabricate various infill patterns and porosity of cortical screws to enhance the design of orthopaedic cortical screws.

The coronavirus disease 2019 (COVID-19) pandemic has been reported to have a major impact on the mental health of an individual. Healing the mental stress, anxiety, depression and insomnia of an individual's immediate surroundings play a major role. Therefore, this study reviews how the built environment impacts the healing of an individual's state of mind.

Various works of literature on healing environments were analysed to create frameworks that can facilitate psychological healing through architectural elements. Articles were selected from various journals like SAGE, PubMed, Journal of Applied and Computational Mechanics (JACM), Routledge Taylor and Francis, Journal of Contemporary Urban Affairs (JCUA), ScienceDirect, and Emerald databases, news articles, official web pages, and magazines that have been referred.

Indicators (spatial, sensory comfort, safety, security, privacy and social comfort) are linked to sub-indicators (access, distractions and views) and design characteristics (indoor climate, interior view, outside view, privacy, communication, noise, daylighting, temperature) which help in better connection of the built environment with individual's mental health. From the above indicators, sub-indicators and design characteristics, the authors have come to a conclusion that a view to the outside with better social interaction has an in-depth effect on an individual's mental health.

This study predominantly talks about healing in hospitals but quarantining of COVID-19 patients happens in residences too. So, it is important to find the healing characteristics in residences and in which typology the recovery process is high.

This paper has been written completely by the author and the co-authors and has not been copied from any other sources.