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Mother Daughter Relationship: Daughters' Experience
This study explores daughters' experience of their relationship with their mothers, and how this relationship has been perceived and interpreted by them during different periods in their lives, starting from childhood till the time of their motherhood. Further it recognizes the changes in the mother daughter relationship and factors contributing to these changes over a period of time. The study also explores stressful times in the mother daughter relationship, and the impact that the mother has on the daughter. 11 married women with at least one child were interviewed using life history method and data was analyzed using Thematic Analysis. Findings indicated changes in daughters' communication with her mother over the life cycle and change in roles for the daughter as evident through role reversal and mutual mothering. Factors contributing to growth and change in the relationship were identified as the daughter experiencing wife and mother roles herself. Daughters' pregnancy, and birth of grand children have been identified as factors which evoked a lot of support from mothers. Further, adolescence was reported as a stressful period in the mother daughter relationship. In addition, the mother's values, and behaviour was found to have a direct or indirect impact on the role attitudes and behaviours of some daughters in the study. The power of the mother's influence lied in her implicit and explicit messages given to the daughter more than her actual role choice. Some mothers and daughters had gender based expectations for each other. -
Mother Phubbing and Psychological Well-being: Exploring Mediating Role of Loneliness
Mothers phubbing has been connected to a rise in loneliness and a fall in well-being in the role of parenthood. Study examined loneliness as a mediator between mother phubbing and psychological well-being. In total 186 mothers (30-45 years) were surveyed. Results highlighted that Mother phubbing negatively correlated with psychological well-being (r = -0.29) and loneliness (r = -0.39). Loneliness is negatively correlated with psychological well-being (r = -0.40). Loneliness mediated the relationship (b = -0.13, p<.001). 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Mother Phubbing and Psychological Well-being: Exploring Mediating Role of Loneliness
Mothers phubbing has been connected to a rise in loneliness and a fall in well-being in the role of parenthood. Study examined loneliness as a mediator between mother phubbing and psychological well-being. In total 186 mothers (30-45 years) were surveyed. Results highlighted that Mother phubbing negatively correlated with psychological well-being (r = -0.29) and loneliness (r = -0.39). Loneliness is negatively correlated with psychological well-being (r = -0.40). Loneliness mediated the relationship (b = -0.13, p<.001). 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Mother Teresa
Indian Posts and Telegraphs Department issued a postage stamp on Saint Teresa of Calcutta, an Albanian-Indian Roman Catholic nun and missionary on 27 August, 1980 to commemorate her noble work and band of devoted associations. The stamp carries the portrait of Mother Teresa along with the facsimile of the reverse of the Nobel Peace Prize medallion. -
Motivation continuum and its effect on electric vehicle acceptance in India
Purpose: The motivation to choose an electric vehicle (EV) is guided by principles of personal values, perceived rewards and preferences. While the benefits of sustainable transportation are known, the acceptance of EVs and the motivation to purchase them is not satisfactory in India. An assessment of the motivation continuum, a range of intrinsic to extrinsic personal and societal drives that encourage specific choices, explains the lack of EV adoption in the country. This study aims to examine the effect of motivation types on EV adoption intentions and also explores the moderating role of gender in this context. Design/methodology/approach: By incorporating constructs from the self-determination theory, the study expands on the technological acceptance model. It uses the structural equation modelling method to test the hypotheses and presents an analysis of responses from 351 participants. Findings: The findings suggest that there are significant relationships between external, identified, integrated motivation and EV buying intentions. The influence of gender on EV adoption is also explored. Originality/value: This study provides an in-depth analysis of varied motivational types on EV buying intentions and the moderating effects of gender on these relationships. 2025, Emerald Publishing Limited. -
MOTIVATION IN RELATION TO WORK ENGAGEMENT OF SALES PERSONNEL IN TELECOM INDUSTRY
The study is in motivation in relation to work engagement of sales personnel in telecom industry. Motivation is the Internal and external factors that stimulate desire and energy in people to be continually interested in and committed to a job, role, or subject, and to exert persistent effort in attaining a goal. Workengagement is defined as a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption. Vigor is characterized by high levels of energy and mental resilience while working, the willingness to invest effort in one??s work, and persistence even in the face of difficulties; dedication by being strongly involved in one's work, and experiencing a sense of significance, enthusiasm, inspiration, pride, and challenge; and absorption by being fully concentrated and happily engrossed in one??s work, whereby time passes quickly and one has difficulties with detaching oneself from work. When you don't have the motivation to do your work, you will either eventually get fired or you will not likely get promoted and will stay where you are for a long time. If you are the supervisor or the owner, a lack of motivation throughout your company can create a rather unproductive workplace. This will lead to loss of sales, profits, and market share. In this case, it's important to do what it takes to create an environment where people naturally want to do their work. The importance of employee motivation shouldn't be taken lightly here. The company's survival depends on it. Modern organizations need energetic and dedicated employees: people who are engaged with their work. These organizations expect proactively, initiative and responsibility for personal development from their employees. Overall, engaged employees are fully involved in, and enthusiastic about their work. The hypotheses of the study were (a) The interaction effect between MPS and CPS does not significantly influence the personnel outcomes of sales professionals in telecom industry. (b) The interaction effect between work engagement and CPS does not significantly moderate the personnel outcomes of sales professionals in telecom industry.(c) There is no significant difference in demographics in work engagement across demographics. The review of related literature in the area of motivation and work engagement provided the researcher valuable inputs, perspective, insights and direction in understanding these factors and designing this study. The researcher has attempted to seriously and systematically undertake the present investigation. There are two research models; these two models were tested using the statistical technique hierarchical regression model. These two models were framed based on the job diagnostic model of Hackman and Oldham (1974) and Job resource model of Bakker and Demerouti (2010). The research methodology adopted for the study was surveying of 359 sales employees in different telecom industries using structured questionnaires. The independent variable of this study were Motivation(core job dimensions, critical psychological states, personnel outcomes).The dependent variable is work engagement(vigor, dedication, absorption) and the demographic variables are, age, work experience, marital status, and gender. The major findings of the study were: 1.There is a positive significant correlation between critical psychological states and motivation potential score. Critical psychological states promote high performance motivation and satisfaction at work. 2.The interaction effect between MPS and CPS significantly moderate the personnel outcomes of sales professionals in telecom industry. 3.The interaction effect between work engagement and Critical Psychological State significantly moderate the personnel outcomes of sales professionals in telecom industry. 4.Work engagement significantly influences the outcomes. 5.Age and marital status has a significant influence on work engagement. The concept of motivation and work engagement is gaining importance across every organization. This study aims at helping Telecom organizations to build more effective policies with respect to motivation and work engagement .By offering effective policies and encouraging employees to make use of available policies and programmes the organization will in turn be increasing the employee??s level of satisfaction and also commitment towards the organization. This will help the organization retain its best people or talent. -
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Motivational Behaviour of Tourism Employees in Relation to Organisational Culture and Career Orientations
The productivity and effectiveness of any organisation depends mainly on the performance level of the employees in the organisation. Human behaviour scientists over the years have conducted various studies and have concluded that, the performance of employees in any organisation depends largely on their motivational behaviour. Reviews of related literature confirm the role of various factors in the motivational behaviour of employees including organisational culture and career orientation of employees. The title of the present study is Motivational Behaviour of Tourism Employees in Relation to Organisational Culture and Career Orientations. The major objectives included ascertaining the relationship between motivational behaviour and organisational culture and career orientations of tourism employees and finding out whether differences in demographic variables would account for significant differences in motivational behaviour. The population of the study consisted of 323 employees of public sector, private sector and multinational companies working in travel agencies, tour operations, airlines and hotels and resorts in Bangalore. The sampling technique employed was judgment sampling. For the present study three tools namely: Motivational Analysis of Organisations- Behaviour (MAO-B) by Pareek (2003), Organisational Culture Survey by Pareek (2003) and Career orientations Inventory by Schein (1990) were used to collect data. The findings of the study show that while two aspects of organisational culture namely internal and future oriented influence the motivational behaviour of employees working in the private sector, no aspect of organisational culture has any influence on the motivational behaviour of employees working in the public sector. Further, only ambiguity tolerant aspect of organisational culture influence the motivational behaviour of employees working in multinational companies. -
Motivational factors leading to the limited presence of women chefs in the hotel industry of Bengaluru /
International Journal of Innovative Studies In Sociology And Humanities, Vol.3, Issue 8, pp.108-121, ISSN No: 2456-4931. -
Movie Success Prediction from Movie Trailer Engagement and Sentiment Analysis
The diverse movie industry faces many challenges in the promotion of the product across different demographics. Movie trailer engagements provide valuable information about how the audience perceives the movie. This information can be used to predict the success of the upcoming movie before it gets released. The previous research works were mainly concentrating on Hindi language movies to predict success. The current research paper includes the success prediction of movies other than Hindi. This paper aims to analyze various Machine Learning models performance and select the best performing model to predict movie success. The developed model can efficiently classify successful and unsuccessful movies. For the current research, the data is collected from various sources through web scrapping and API calls in Sacnilk, The Movie Database (TMDB), YouTube, and Twitter. Different machine learning classification models such as Random Forest, Logistic Regression, KNN, and Gaussian Nae Bayes are tested to develop the best-performing prediction model. This research can help moviemakers to understand the popularity of the movie among the viewers and decide on an efficient promotional strategy to make the movie more successful. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Movie-Induced Tour Guiding: Concepts and Future Implications in South Asian Perspective
Movies have an extensive impact on tourism and its promotion. Movie-induced tourism has been a worldwide phenomenon for the last couple of decades, but this phenomenon is confined to the marketing and promotion of tourism destinations. Here, a new approach has been introduced for co-creating a quality destination experience through traditional tour guiding. Considering the increasing emphasis on tourists experience, satisfaction, and destination imagery over the decades, this concept of movie-induced tour guiding will produce a synergistic value in the overall process of the outdoor leisure tour packages. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Moving Towards Responsible Consumption: The Road Ahead for Sustainable Marketing
The fundamental tenet of consumerism revolves around the belief that the burgeoning consumption of goods is favourable for the economy. Since the dawn of the Industrial Revolution, humanity has witnessed an exponential upsurge in consumerism. It has been related both to the increase in the population size as well as an increase in our demands due to constant changes in lifestyle. Multiple sources have corroborated the fact that if this consumption behaviour continues unabated, we will soon face an acute shortage of resources of all kinds. Both consumer behaviour patterns such as addictive consumption and conspicuous consumption can be attributed to this. Amongst the solutions available, 'Demarketing' is one. It is a type of marketing when a brand wants to discourage you from buying its product. The paper is descriptive in nature and is based on secondary data which has been collected from journals, blogs, websites, magazines, books, etc. The paper intends to explore the theme of demarketing vis-vis the materialistic purchase behaviour of a modern-day consumer and green demarketing strategies that companies are adopting by way of sustainable marketing. The Electrochemical Society -
MR Brain Tumor Classification and Segmentation Via Wavelets
Timely, accurate detection of magnetic resonance (MR) images of brain is most important in the medical analysis. Many methods have already explained about the tumor classification in the literature. This paper explains the method of classifying MR brain images into normal or abnormal (affected by tumor), abnormality segments present in the image. This paper proposes DWT-discrete wavelet transform in first step to extract the image features from the given input image. To reduce the dimensions of the feature image principle component Analysis (PCA) is employed. Reduced extracted feature image is given to kernel support vector machine (KSVM) for processing. The data set has 90 brain MR images (both normal and abnormal) with seven common diseases. These images are used in KSVM process. Gaussian Radial Basis (GRB) kernel is used for the classification method proposed and yields maximum accuracy of 98% compared to linear kernel (LIN). From the analysis, compared with the existing methods GRB kernel method was effective. If this classification finds abnormal MR image with tumor then the corresponding part is separated and segmented by thresholding technique. 2018 IEEE. -
MRSP-Multi Routing Systems and Parameter Explanations to Build the Path in Underwater Sensor Network
The underwater network is currently widely used to locate moving objects beneath the sea, monitor marine security, and detect changes in the sea water. A large number of sensors, as well as a precise methodology, are necessary to detect changes in sea depth. The protocol should be revised in response to environmental and chronological changes. The sensor should have been designed with multiple knowledge to route packets in order to optimise transmissions. Because the node will choose the best route based on the circumstances, especially in an underwater network, the paper MRSP - multi routing systems and parameter validations to create the path in an underwater sensor network is discussed in the multi routing knowledge sensor operations, energy saving systems, redundancy reduction, and so on. All of these measures, combined with secure transmission with trusted neighbour selection, result in safer transmissions and more accurate path selection. 2022 IEEE. -
Mucormycosis (black fungus) ensuing COVID-19 and comorbidity meets - Magnifying global pandemic grieve and catastrophe begins
Post COVID-19, mucormycosis occurred after the SARS-CoV-2 has rampaged the human population and is a scorching problem among the pandemic globally, particularly among Asian countries. Invasive mucormycosis has been extensively reported from mild to severe COVID-19 survivors. The robust predisposing factor seems to be uncontrolled diabetes mellitus, comorbidity and immunosuppression acquired through steroid therapy. The prime susceptive reason for the increase of mucormycosis cases is elevated iron levels in the serum of the COVID survivors. A panoramic understanding of the infection has been elucidated based on clinical manifestation, genetic and non- genetic mechanisms of steroid drug administration, biochemical pathways and immune modulated receptor associations. This review lime-lights and addresses the What, Why, How and When about the COVID-19 associated mucormycosis (CAM) in a comprehensive manner with a pure intention to bring about awareness to the common public as the cases are inevitably and exponentially increasing in India and global countries as well. The article also unearthed the pathogenesis of mucormycosis and its association with the COVID-19 sequela, the plausible routes of entry, diagnosis and counter remedies to keep the infection at bay. Cohorts of case reports were analysed to spotlight the link between the pandemic COVID-19 and the nightmare-mucormycosis. 2021 Elsevier B.V. -
Mudhr: Malicious URL detection using heuristic rules based approach
Technology advancement helps the people in numerous ways such as it supports business development, banking, education, entertainment etc. Especially time critical and money related activities, people are fully really on internet and web applications. It saves valuable time and money. Despite of the benefits, it also gives wide space for the attackers to focus more victims. Malicious URL based attacks are most common and more dangerous attacks now a day which steals the credentials and sensitive data from the victims and perform malicious activities in the victim's space. Phishing, Spamming, drive by download are the example of such attacks and are preformed through malicious URL. Plenty of approaches are available to detect the malicious URL. That are grouped under three categories such as Blacklist based, Heuristic based and Machine Learning based approaches. Among the three, heuristic approach is better than the blacklist approach in term of better generalizing the malicious URL and gives equally accurate prediction with machine learning approach. This paper presents recent works in the field of malicious URL detection and novel technique to detect malicious URL based on the most important features derived from URL. 2022 Author(s). -
Mudscapes of Meaning: Performative Language of Chikal Kalo
Chikal Kalo is a unique mud festival celebrated in Marcela, Goa, reflecting deep religious, ecological, and cultural significance. This ethnographic study explores the oral tradition and performative practices of Chikal Kalo, which have been transmitted across generations without written documentation. Through participant observation and interviews with local residents, the research examines the festivals origins, symbolic elements, and evolving expressions. It highlights how embodied memory and ritual performance preserve indigenous heritage. The study also underscores the festivals role in reinforcing social cohesion and cultural identity. Chikal Kalo exemplifies a living tradition rooted in ecological consciousness and communal values. The festivals vibrant blend of dance, music, and food attracts travellers while preserving its devotional roots. The findings contribute to broader discussions on intangible cultural heritage and its role in sustainable community development, while safeguarding Konkani culture amid rapid modernization. 2026, IGI Global Scientific Publishing. -
Mul-Sensis: Multilingual Sentiment Analysis Framework for Emotion Detection
Sentiment analysis is a pivotal Natural Language Processing (NLP) task that enables the extraction of actionable insights from textual data, particularly social media. With the rise of public discourse on platforms like Twitter, analyzing sentiment trends has become crucial for decision-making in domains such as policy implementation, feedback evaluation, and public opinion monitoring. Mul-Sensis employs a hybrid approach combining transformer-based models with classical machine learning algorithms to enhance sentiment classification. The system integrates advanced preprocessing techniques to address linguistic complexities like sarcasm, idiomatic expressions, and domain-specific nuances. A robust hybrid annotation approach, incorporating both human expertise and machine-assisted methods, ensures high-quality, bias-free sentiment labeling. This study contributes a scalable, interpretable, and domain-agnostic framework for sentiment analysis, offering valuable insights for policymakers, researchers, and industries relying on textual data analytics. The findings highlight the transformative potential of hybrid and ensemble-based NLP approaches for understanding public sentiment across diverse cultural and linguistic contexts. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Mulberry Leaves (Morus Rubra)-Derived Blue-Emissive Carbon Dots Fed to Silkworms to Produce Augmented Silk Applicable for the Ratiometric Detection of Dopamine
Silk fibers (SF) reeled from silkworms are constituted by natural proteins, and their characteristic structural features render them applicable as materials for textiles and packaging. Modification of SF with functional materials can facilitate their applications in additional areas. In this work, the preparation of functional SF embedded with carbon dots (CD) is reported through the direct feeding of a CD-modified diet to silkworms. Fluorescent and mechanically robust SFare obtained from silkworms (Bombyx mori) that are fed on CDs synthesized from the Morus rubra variant of mulberry leaves (MB-CDs). MB-CDs are introduced to silkworms from the third instar by spraying them on the silkworm feed, the mulberry leaves. MB-CDs are synthesized hydrothermally without adding surface passivating agents and are observed to have a quantum yield of 22%. With sizes of ?4nm, MB-CDs exhibited blue fluorescence, and they can be used as efficient fluorophores to detect Dopamine (DA) up to the limit of 4.39nM. The nanostructures and physical characteristics of SF weren't altered when the SF are infused with MB-CDs. Also, a novel DA sensing application based on fluorescence with the MB-CD incorporated SF is demonstrated. 2023 Wiley-VCH GmbH. -
MuLSA-Multi Linguistic Sentimental Analyzer for Kannada and Malayalam using Deep Learning
Natural language Processing has been always a topic of interest in artificial intelligence. Opinion mining or Sentiment Analysis is an important application of Natural language Processing. Sentiment Analysis of text is to extract the sentiments underlined in the text. In this paper, a multi-linguistic sentimental analyzer (MuLSA), is implemented, a model that would address Malayalam, Kannada and English text. This model explores two languages in three categories of the text, its original script, transliterated script, and the combination of both along with English. Deep Learning, Recurrent Neural Network with LSTM is used as the basis for this model. The model exhibits 82% of prediction accuracy. 2021 IEEE.