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A Family of Mexican Hat Wavelet Stieltjes Transform for Unbounded Non-decreasing Functions
In the present article, we examine the characteristics of the Mexican hat wavelet Stieltjes transform (MHWST) for a specific set of functions belonging to one of the sub-class of bounded variation functions. The subset comprises functions that are unbounded and non-decreasing. Further, a unified approach is applied to establish a uniqueness theorem and subsequently derive a representation theorem for the MHWST. The Author(s), under exclusive licence to The National Academy of Sciences, India 2024. -
A Compartmental Mathematical Model of Novel Coronavirus-19 Transmission Dynamics
The COVID-19 pandemic has spread quickly throughout the world, posing a serious threat to human-to-human transmission. The novel coronavirus pandemic is described quantitatively in this paper using a mathematical model of COVID-19 driven by a system of ordinary differential equations. The suggested model is used to provide predictions regarding the behavior of a COVID-19 outbreak over a shorter time frame. It is demonstrated that the system of model equations has a unique and existing solution. Furthermore, the answer is positive and bounded. Thus, it is argued that the model created and discussed in this work is both mathematically and biologically sound. A threshold parameter that controls the disease transmission is used in a qualitative analysis of the model to confirm the existence and stability of disease-free and endemic equilibrium points. Additionally, the key parameters undergo sensitivity analysis to ascertain their relative significance and potential influence on the COVID-19 virus dynamics. 2024 NSP Natural Sciences Publishing Cor. -
The little I receive is not enough: A qualitative study of food insecurity in the South Bronx
The objective of this study was to explore the lived experiences of food insecurity amongst Bronx residents. Applying a community-based participatory research approach, we conducted a qualitative study, entailing 38 interviews with food pantry recipients, 4 key informant interviews with social service administrators, and two focus groups with 12 food pantry staff and social service providers in New York City (NYC). Applying a precarity framework, we identified three themes: (1) unaffordability of living expenses in NYC; (2) financial hardships during the COVID-19 pandemic; and (3) institutional and technological barriers to food access. We identified the following subthemes under theme one: rising food costs and high cost of living. Under theme two, we identified four subthemes: (a) large household size driving poverty for Bronx families; (b) vulnerabilities to food insecurity among older adults; (c) budgeting for reduced incomes during the COVID-19 pandemic; and (d) managing unstable employment. Under the third theme, we identified three subthemes: (a) lack of access to healthy, culturally appropriate foods; (b) need for wider service availability; (c) and not having smartphones for telehealth. Study findings demonstrate how precarity impacts the lived experiences of food insecurity and financial hardship for residents of the South Bronx during the COVID-19 pandemic. 2024 Association for the Study of Food and Society (ASFS). -
Translation and Validation of the Malayalam Version of the Subjective Happiness Scale
The subjective happiness scale (SHS) is a brief instrument used to measure global subjective happiness that has been translated from its original English to many other languages. To date, there is no reported translation of this scale into Malayalam, a language spoken by over 32 million people especially in the southern state of Kerala, India. In the present study, 656 community-dwelling older adults participating in the Kerala Einstein study (KES) completed the Malayalam version of the SHS. The Malayalam version demonstrated high internal consistency and good convergent validity, as assessed by comparison to measures of depression and anxiety. We also used factor analysis to determine that the Malayalam version of the SHS has a unidimensional structure, akin to the original English as well as other language adaptations. Our study adds to the repertoire of tools to measure happiness in non-English-speaking populations, enabling future research to explore the foundations of well-being across diverse cultures. The Author(s) 2024. -
Does robotic service quality determine robotic restaurant diners engagement behaviors? Role of customer engagement andattachment to the restaurant
Purpose: Robotic restaurants are very novel, and service robots in these restaurants are identified as offering unique advantages in terms of efficiency, tireless service and potentially lower operational costs. However, studying customer engagement with the robots can reveal aspects of robotic service that resonate with diners. Understanding how diners interact with robots can help create a more engaging and enjoyable atmosphere, bringing more business to restaurants. Building on the stimulus-organism-response (SOR) theory and place attachment theory, the purpose of this paper is to study the impact of the robotic service quality (RSQ) on the customer attachment to the robotic restaurant with the mediating role of the different dimensions of the customer engagement, like the Absorptive Attention, Enthusiastic Participation and Social Connection. Subsequently, the impact of the customer attachment to the robotic restaurant on different dimensions of customer engagement behaviors like augmenting, co-developing, influencing and mobilizing behaviors was also studied. Design/methodology/approach: The cross-sectional data from 786 robotic restaurant diners in India who answered the self-administered structured questionnaires is utilized for this descriptive study. The study employed a purposive sampling strategy. The SMART-PLS 4.0 program was used to run structural equation modeling and analyze the data. Findings: The results indicate that customer engagement dimensions like Absorptive Attention, Enthusiastic Participation and Social Connection differentially mediate the relationship between RSQ and customer attachment with the robotic restaurant. Customer attachment to the restaurant and the robotic services subsequently positively impact customer engagement behaviors. Research limitations/implications: The study relied upon cross-sectional data from the Indian population above 18years to test the proposed model. Further studies could test the model across different populations to generalize the study results. Originality/value: This study addresses the need to investigate robotic restaurant diners engagement behaviors. By testing place attachment theory and the SOR framework, this study is the first to show that RSQ will impact the customer attachment with the robotic restaurant and that different dimensions of customer engagement mediate the relationship. It also validates the previous research findings that customer engagement is not a single global construct, and different sub-dimensions are to be explored. This study is also the first to show customer attachment to the robotic restaurant will impact customer engagement behaviors differently. 2024, Emerald Publishing Limited. -
A Comparative Study of Nutrient Composition, Proteolytic Activity, Phytochemical Profiles, Vitamin C Content, and Antioxidant Properties in the Peels of Selected Perennial Fruits
The escalating global demand for fruits has led to a surge in fruit production, resulting in significant fruit waste, particularly peels. The present study aims to investigate the nutrient content, proteolytic activity, phytochemical levels, vitamin C and antioxidant properties of five perennial fruits, namely Carica papaya (papaya), Selenicereus costaricensis (Red dragon fruit), Ananas comosus (Pineapple), Musa acuminata (Cavendish banana), Punica granatum (Pomegranate) peels of varying ripening stages. Accordingly, two ripening stages for pomegranate, papaya and dragon fruit (PoR1 and PoR2; PaR1 and PaR2; DR1 and DR2, respectively) and three stages for banana and pineapple (BR1, BR2 and BR3; PiR1, PiR2 and PiR3, respectively) were identified based on ethylene gas emission. The elemental analysis showed that fruit peels of Pineapple (PiR3), Banana (BR2), Papaya (PaR2), and Dragon fruit (DR2) showed significantly higher content of macro and micro-elements compared to the other ripening stages. Pomegranate peels exhibited the highest proteolytic activity (5.09 0.98unitsg?1), total phenolics (246.09 0.25mgg?1), total flavonoids (158.27 1.72mgg?1), tannins (103.94 0.09mgg?1), DPPH scavenging activity (129.43 1.34%), and antioxidant activity (127.14 1.35mgg?1 by phosphomolybdate assay). A. comosus peels had the greatest vitamin C levels (95.53 3.52mgg?1). Anti-nutrient analysis revealed safe levels of oxalates, phytates, and alkaloids, except for high oxalate levels in pomegranate peels. Notably, all parameters exhibited an increasing trend with ripening stages, with a decline during senescence in Banana (BR3) and Pomegranate peel (PoR2). This knowledge of fruit peel composition can enhance their utilization by humans, pharmaceutical and food industries, while also contributing to more effective waste management. Our study addresses the pressing need for sustainable fruit peel utilization in the context of escalating fruit production and waste. The Author(s), under exclusive licence to National Academy of Agricultural Sciences 2024. -
Investigate the distinctive link between a balanced scorecard and organizational performance in ITand non-IT sectors
Purpose: The purpose of this research is to examine how the implementation of a balanced scorecard (BSC) affects business outcomes in both information technology (IT) and non-IT sectors. Design/methodology/approach: Partial least squares structural equation modeling (PLS-SEM) was used to test the hypothesis. A random sample was used to collect 170 responses from the IT companies and 166 from non-IT companies by using the questionnaire method. The questionnaire was distributed to the top- and middle-level managers in Bangalore city, and we used SmartPLS software to explore the relationship between our research constructs. Findings: The results of this study indicate that a BSC has a significant and positive impact on organizational performance in IT and non-IT sectors. The main distinction in this study is that all BSC perspectives [learning and growth perspective, internal business process (IBP) perspective, customer perspective (CP) and financial perspective (FP)] have a significant, direct and indirect impact on IT companies. On the other hand, solely three BSC perspectives (IBP perspective, CP and FP) have a significant impact on non-IT companies, while learning and growth perspective has an insignificant impact on the FP. Originality/value: This study provides a critical theoretical and practical contribution of a BSC on business performance in IT and non-IT industries. 2024, Emerald Publishing Limited. -
On ?(k)-colouring of Some Wheel Related Graphs
The question on how to colour a graph G when the number of available colours to colour G is less than that of the chromatic number ?(G), such that the resulting colouring gives a minimum number of edges whose end vertices have the same colour, has been a study of great interest. Such an edge whose end vertices receives the same colour is called a bad edge. In this paper, we use the concept of ?(k)-colouring, where 1 ? k ? ?(G) ? 1, which is a near proper colouring that permits a single colour class to have adjacency between the vertices in it and restricts every other colour class to be an independent set, to find the minimum number of bad edges obtained from the same for some wheel related graphs. The minimum number of bad edges obtained from ?(k)-colouring of any graph G is denoted by bk(G). 2024 the Author(s), licensee Combinatorial Press. -
Modelling Climate, COVID-19, and Reliability Data: A New Continuous Lifetime Model under Different Methods of Estimation
In this article, a new continuous probability distribution called Arvind distribution is developed and studied. The proposed distribution has only one parameter but it exhibits a wide variety of shapes for density and hazard rate functions. A number of important distributional properties including mode, quantile function, moments, skewness, kurtosis, mean deviation, probability-weighted moments, stress-strength reliability, order statistics, reliability and hazard rate functions, Bonferroni Lorenz and Zenga curves, conditional moments, mean residual and mean past life functions, and stochastic ordering of the Arvind distribution are derived. For point estimation of the parameter of the proposed distribution, six estimation procedures including maximum likelihood, maximum product spacings, least squares, weighted least squares, Cram-von Mises, and Anderson-Darling estimators are used. The interval estimation of the unknown parameter has also been discussed using observed Fishers information. A vast simulation study has been conducted to examine the behaviour of different estimation procedures. Finally, the applicability of the proposed model is demonstrated by using three real-life datasets. The results of the real data analysis clearly announce that the Arvind distribution can be a better alternative to several existing models for modelling different types of data from various fields. 2024, Society of Statistics, Computer and Applications. All rights reserved. -
Multifunctional SnO?-Chitosan-D-carvone Nanocomposite: A Promising Antimicrobial, Anticancer, and Antioxidant Agent for Biomedical Applications
Nanocomposite made up of inorganic and biocompatible polymer have gained significant attention for biomedical applications due to their enhanced multifunctional properties, offering solutions to serious issues like antimicrobial resistance and cancer treatment. Nanocomposite composed of SnO?, chitosan and D-carvone (SnO2-Cs-Dcar) was prepared to ascertain its efficacy in application for antimicrobial, anticancer activities, and antioxidant effects. The synthesized nanocomposite was characterized by XRD, UV-Vis, FTIR, PL, SEM, TEM, and XPS techniques, confirming successful integration. XRD results confirmed the tetragonal rutile phase of SnO2. The band gap energy was calculated as 4.32eV for SnO2 nanoparticles and 3.11eV for SnO2-Cs-Dcar nanocomposite as observed from UV-Visible spectra. PL emission results showed that SnO2-Cs-Dcar nanocomposite exhibited green emission at 507nm corresponds to number oxygen vacancy site. SEM and TEM results showed that the SnO2-Cs-Dcar nanocomposite entities appear more compact, and the single SnO2 particles are less differentiated, possibly because they have been covered by chitosan and D-carvone. Antimicrobial activity against the pathogens Klebsiella pneumoniae, Candida albicans, Shigella dysenteriae, Bacillus subtilis, and Staphylococcus aureus demonstrated that SnO2-Cs-Dcar exhibited enhanced bacteriostatic effect when compared to bare SnO2. MTT assay on MOLT-4 cancer cells revealed that SnO2-Cs-Dcar nanocomposite exhibited enhanced anticancer activity upon compared to SnO? nanoparticles. The IC50 values were calculated as 13.6 for SnO2 and 12.1 for SnO2-Cs-Dcar nanocomposite. SnO?-Cs-Dcar nanocomposites exhibits high antioxidant activity evidenced by improved free radical scavenging action in comparison with a bare SnO?. Experimental result indicates that the SnO?-Cs-Dcar nanocomposites can be used as biocidal agent for antimicrobial and anticancer therapies. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Effects of Yoga and Combined Yoga with Neuro-Linguistic Programming on Psychological Management in Mothers of Adolescents: A Randomized Controlled Trial
Adolescent parenting presents significant challenges for mothers, often leading to elevated levels of stress and anxiety that can adversely affect their well-being and parenting effectiveness. This study aims to evaluate the efficacy of yoga alone and in combination with Neuro-Linguistic Programming (NLP) in managing stress and anxiety among mothers of adolescent children. In this randomized controlled trial, 90 participants aged 35-55 years (mean age 44.564.58 years), each with at least one child aged 13-19 years, were randomly assigned to one of three groups: control, yoga, or yoga with NLP. Interventions were conducted over 12 weeks, with outcome measures assessed pre- and post-intervention by trained research assistants blinded to group allocation. The Depression, Anxiety, and Stress Scale (DASS-21), and Pittsburgh Sleep Quality Index (PSQI), were utilized to evaluate outcomes. Both intervention groups demonstrated significant reductions in depression, anxiety, and stress levels compared to the control group. The yoga with NLP group exhibited superior improvements across all primary outcomes, with statistically significant differences noted in depression (mean difference =7.1, p<0.001), anxiety (mean difference =5.1, p<0.001) and stress levels (mean difference =5.5, p<0.001). Additionally, sleep quality improved significantly in both intervention groups, with the yoga with NLP group showing greater benefits. This study provides evidence that yoga, particularly in combination with NLP, is an effective non-pharmacological approach for reducing stress and anxiety and improving sleep quality among mothers of adolescents. These findings support the integration of mind-body practices into mental health care, highlighting the potential synergistic benefits of combining physical and cognitive interventions. Future research should explore long-term effects and the mechanisms underlying these improvements. 2024 Montenegrin Sports Academy. All rights reserved. -
Carboplatin-loaded zeolitic imidazolate framework-8: Induction of antiproliferative activity and apoptosis in breast cancer cell
The challenge with breast cancer is its ongoing high prevalence and difficulties in early detection and access to effective care. A solution lies in creating tailored metalorganic frameworks to encapsulate anticancer drugs, enabling precise and targeted treatment with less adverse effects and improved effectiveness. Zeolitic imidazolate framework-8 (ZIF-8) and carboplatin (CP)-loaded ZIF-8 were synthesized and characterized using various analytical techniques. High Resolution-transmission electron microscopy of ZIF-8 and CP@ZIF-8 indicates that the particles had a spherical shape and were nanosized. The drug release rate of CP is 98% under an acidic medium (pH 5.5) because of the dissolution of ZIF-8 into its coordinating ions, whereas 35% in a physiological medium (pH 7.4) with the addition of CP, the high porosity, and pore diameter of ZIF-8 decrease from 1243 to 1041m2/g. Breast cancer MCF-7 cells were shown greater IC50 in CP@ZIF-8 (15.013.03g/mL) than free CP (34.984.25g/mL) in an in vitro cytotoxicity assessment. The cytotoxicity of the CP@ZIF-8 against MCF-7 cells was studied using the methylthiazolyldiphenyl-tetrazolium bromide method. The morphological changes were examined using fluorescent staining (acridine orangeethidium bromide and Hoechst 33258) methods. The comet assay assessed the DNA fragmentation (single-cell gel electrophoresis). The results from the study revealed that CP@ZIF-8 can be used in the treatment of breast cancer. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
A Worldwide Test of the Predictive Validity of Ideal Partner Preference Matching
Ideal partner preferences (i.e., ratings of the desirability of attributes like attractiveness or intelligence) are the source of numerous foundational findings in the interdisciplinary literature on human mating. Recently, research on the predictive validity of ideal partner preference matching (i.e., Do people positively evaluate partners who match vs. mismatch their ideals?) has become mired in several problems. First, articles exhibit discrepant analytic and reporting practices. Second, different findings emerge across laboratories worldwide, perhaps because they sample different relationship contexts and/or populations. This registered reportpartnered with the Psychological Science Acceleratoruses a highly powered design (N = 10,358) across 43 countries and 22 languages to estimate preference-matching effect sizes. The most rigorous tests revealed significant preference-matching effects in the whole sample and for partnered and single participants separately. The corrected pattern metric that collapses across 35 traits revealed a zero-order effect of ? =.19 and an effect of ? =.11 when included alongside a normative preference-matching metric. Specific traits in the level metric (interaction) tests revealed very small (average ? =.04) effects. Effect sizes were similar for partnered participants who reported ideals before entering a relationship, and there was no consistent evidence that individual differences moderated any effects. Comparisons between stated and revealed preferences shed light on gender differences and similarities: For attractiveness, mens and (especially) womens stated preferences underestimated revealed preferences (i.e., they thought attractiveness was less important than it actually was). For earning potential, mens stated preferences underestimatedand womens stated preferences overestimatedrevealed preferences. Implications for the literature on human mating are discussed. 2024 American Psychological Association -
Is corporate reputation associated with voluntary cybersecurity risk reporting?
Purpose: This study investigated the effect of voluntary cybersecurity risk reporting (VCRR) on corporate reputation. By examining the association between VCRR and corporate reputation, this study aims to provide exploratory evidence of how cybersecurity risk is sensitive to a companys image and reputation. Design/methodology/approach: An automated content analysis of VCRR by 95 Bombay Stock Exchange-listed companies was undertaken using Python code. Signaling and legitimacy theories were adopted to interpret the findings, establishing whether VCRR was related to corporate reputation. Findings: The results confirm that VCRR improves the corporate reputation in the financial market. The results also confirm the signalling and legitimacy theory that a company can manage reputational risks through higher voluntary risk disclosure. Practical implications: The corporations managers can gain insights from the studys findings and proactively address cybersecurity risks through strategic disclosure and management practices. In addition, organizations can recognize that investors value transparency and establish a positive reputation for those who communicate openly. Social implications: A significant association between VCRR and corporate reputation implies that such disclosures enhance trust and transparency in the business sector and induce security and accountability among investors engaging with the company. Originality/value: To the best of the authors knowledge, this study is the first that empirically investigates this issue and adds to the international literature a new explanatory variable, corporate reputation, to explain VCRR practices. 2024, Emerald Publishing Limited. -
Navigating the need for accessible labelling through the narratives of consumers with visual impairment in India
This study aims to understand the strategies consumers with visual impairment (CWV) use in acquiring product information and explores preferences for accessible labelling and its benefits. This study employed the qualitative approach of thematic analysis. A snowball sampling technique was used to recruit participants. Data were collected from CWV through semi-structured interviews. The sample size of this study was 12. The data were analysed using NVivo software. The study revealed three strategies used by CWV to obtain product information, namely reliance on caregivers, staff, and technology. However, all the strategies employed have multiple drawbacks. The study reported a high preference for accessible labelling in braille and quick response (QR) codes. Implementing a combination of braille labels and QR codes on product packages was the most beneficial strategy for CWV. The Implementation of accessible labels ensures inclusion in the marketplace. The Author(s) 2024. -
The Problem of Perception in Sandor Mais Embers: An Advaitic Study
This article attempts to study the problem of perception in Sandor Mais celebrated novel Embers from the standpoint of the pramana (a method of knowledge) of Advaita Vedanta. An epistemic problem, the problem of perception, concerns the overwhelming questions of life, culminating in an enigmatic amalgamation of dilemmas and paradoxes. Genuine dilemmas and paradoxes problematize human relationships, which is evident in the complex narrative of Embers. Our contention in this article is to show how, even though enacted within the periphery of the purely fictional, Embers bears testimony to the complexities of life that are quickened by the limits of human perception, which keeps one from seeing how things really are by creating a shadow or reflected consciousness. Set against the backdrop of the Austro-Hungarian Empire, the novel opens up a dialogic space at the intersection of a triangular relationship enacted on the threshold of perception and its multidimensional problems. 2024 Management Centre for Human Values. -
Brain Tumor Classification Using an Ensemble of Deep Learning Techniques
The article reflects on the classification of brain tumors where several deep learning (DL) approaches are used. Both primary and secondary brain tumors reduce the patient's quality of life, and therefore, any sign of the tumor should be treated immediately for adequate response and survival rates. DL, especially in the diagnosis of brain tumors using MRI and CT scans, has applied its abilities to identify excellent patterns. The proposed ensemble framework begins with the image preprocessing of the brain MRI to enhance the quality of images. These images are then utilized to train seven DL models and all of these models recognize the features related to the tumor. There are four models which are General, Glioma, Meningioma, and Pituitary tumors or No Tumor model, which helps in reaching a joint profitable prediction and concentrating solely on the strength of the estimation and outcome. This is a significant improvement over all the individual models, attaining a 99. 43% accuracy. The data used in this research was gotten from Kaggle website and comprised of 7023 images belonging to four classes. Future work will focus on increasing the dataset size, investigating additional DL architectures, and enhancing real-Time detection to improve the accuracy of diagnostic scans and their overall relevance to clinical practice. 2013 IEEE. -
MADeGen: Multi-Agent based Deep Reinforcement Learning for Sequential Keyphrase Generation
Keyphrase generation is an essential tool in the field of natural language processing for information retrieval, document summarization, and text recommendation applications, extracting succinct and representative phrases from the text document. Traditional keyphrase extraction methods applied the supervised or unsupervised learning fail to capture the sequential keyphrase generation in a dynamic environment. The keyphrase generation approaches lack focus on explicitly discriminating the present and absent keyphrases, leading to the inadequate generation of semantically rich absent keyphrases. Hence, this work utilizes the potential benefits of reinforcement learning with the design of a distinguished reward function for present and absent keyphrases for sequential decision-making in the keyphrase generation. Thus, this work presents a novel keyphrase generation system, MADeGen, utilizing Multi- Agent Deep Reinforcement Learning (MADRL). In particular, a multi-agent reinforcement system collaboratively enables the generation of representative and coherent keyphrases by the evaluation metric-aware cooperative reward function analysis and adaptively training the agents. The proposed MADeGen incorporates two major phases, such as multi-agent modelling and actor critic-based policy optimization towards accurate keyphrase generation. In the first phase, the proposed approach designs two learning agents, including the extraction agent and generation agent, with the incorporation of a pre-trained language model. In the multi-agent system, the generation agent is the finetuned version of the extraction agent with the integration of the Wikipedia source. Secondly, the evaluation-aware adaptive reward function is designed to evaluate each agent's generated keyphrases with reference to ground-truth keyphrases. In subsequence, the cooperative reward analysis triggers the actor critic-based policy optimization for the generation agent in the multi-agent system to precisely generate the semantically relevant keyphrases with the assistance of an external web source. Experimental results on several benchmark datasets, such as Inspec, PubMed, and wiki20, illustrate the effectiveness of the proposed MADeGen compared to the existing keyphrase extraction models, yielding state-of-the-art performance in keyphrase extraction tasks. The proposed MADeGen proves its higher performance in the present as well as absent keyphrase extraction as 0.367 and 0.438 F1-score, respectively, while testing on the Inspec dataset. (2024), (Intelligent Network and Systems Society). All Rights Reserved. -
The impact of the COVID-19 pandemic on e-learning adoption in an emerging market: a longitudinal study using the UTAUT model
Purpose: The COVID-19 pandemic provided unprecedented impetus to the evolution of the e-learning learning ecosystem by compelling students to adopt e-learning systems. This paper aims to use the UTAUT model to provide insight into the differences in factors influencing the adoption of e-learning systems before and after the pandemic. Design/methodology/approach: This longitudinal study uses two surveys conducted among graduate students in the city of Bengaluru in India. One prior to the start of the COVID-19 pandemic and a second in its aftermath. PLS-SEM is used to analyze both data sets to draw insights into the constructs that influence Behavioral intention to adopt e-learning systems. The moderating effect of gender is also analyzed. Findings: Pre COVID-19, Facilitating Conditions, Performance Expectancy and Effort Expectancy (quadratic behavior) were dominant factors influencing the adoption of e-learning technologies. Post pandemic, Performance Expectancy and Social Influence are drivers of e-learning adoption. Effort Expectancy and Facilitating Conditions grouped as Ease of Use is a significant driver of e-learning adoption post pandemic. Gender is found to not have a moderating influence. Originality/value: The unique longitudinal study of the differences in factors influencing students intention to adopt e-learning pre- and post-COVID-19 can prove useful to policy makers in the higher education sector. Academics can use the post-pandemic e-learning models findings in multiple contexts such as generational cohorts, educational contexts and social contexts. 2024, Emerald Publishing Limited. -
Esther reimagined: feminist essence in Sara Josephs narrative
Gynocentric approaches to biblical women uncover narratives of liberation and empowerment. These perspectives highlight the gaps and omissions in the representation of women within the overarching metanarrative of the Bible. Sara Josephs novel, Esther, serves as a feminist reimagining of the biblical story of Esther, offering a pluralistic lens through which to examine the experiences and lives of women against the backdrop of patriarchy. This paper utilises the feminist hermeneutic method to critically engage with the narrative, drawing on the feminist frameworks established by scholars such as Elizabeth Fiorenza and Esther Fuchs. It argues that biblical women can be reinterpreted as positive role models, saviours, heroines, and vital contributors to an extraordinary narrative of survival and redemption. 2024 Informa UK Limited, trading as Taylor & Francis Group.