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Emergence of women chefs and their status in the hotel industry: A study with special reference to Bengaluru /
International Journal of Advance Research In Computer Science And Management Studies, Vol.6, Issue 2, pp.50-57, ISSN No:2321-7782. -
Emerging challenges for the agro-industrial food waste utilization: A review on food waste biorefinery
Modernization and industrialization has undoubtedly revolutionized the food and agro-industrial sector leading to the drastic increase in their productivity and marketing thereby accelerating the amount of agro-industrial food waste generated. In the past few decades the potential of these agro-industrial food waste to serve as bio refineries for the extraction of commercially viable products like organic acids, biochemical and biofuels was largely discussed and explored over the conventional method of disposing in landfills. The sustainable development of such strategies largely depends on understanding the techno economic challenges and planning for future strategies to overcome these hurdles. This review work presents a comprehensive outlook on the complex nature of agro-industrial food waste and pretreatment methods for their valorization into commercially viable products along with the challenges in the commercialization of food waste bio refineries that need critical attention to popularize the concept of circular bio economy. 2022 -
Emerging Issues and Trends in Indian Business and Management: Volume 2: Business and Society: Issues and Cases in the Indian Context
There are many theories on why managers do not (as a behavior) or should not (as a value) supplement profit orientation with people-centrism and planet sensitivity. In practice, managers do not supplement profit orientation with considerations for people and the planet unless they have the tools and know how to make that possible. This book seeks to address that by focusing on the normative dimension of organizational development. There are two competing norms for developing an organization: first, as a profit-oriented business enterprise; and second, as a people-centric, planet-sensitive, profit-oriented business or social enterprise. The performance of a business is a concern for all stakeholders. With the growing realization of the importance of indirect stakeholders like the society and the planet, it is increasingly important to raise awareness about the social and environmental responsibilities of businesses and organizations. This book is a must-read for academics, researchers, practitioners and policymakers who are concerned about the triple bottom-line (Planet-People-Profit) performance of businesses, which is critical for their long-term sustainability. It covers topics pertaining to the relationship between business and society, including social entrepreneurship and corporate social responsibility, among others, and draws from real-life case studies on social initiatives. 2024 by World Scientific Publishing Co. Pte. Ltd. -
Emerging Nanomaterials as Versatile Nanozymes: A New Dimension in Biomedical Research
The enzyme-mimicking nature of versatile nanomaterials proposes a new class of materials categorized as nano-enzymes, ornanozymes. They are artificial enzymes fabricated by functionalizing nanomaterials to generate active sites that can mimic enzyme-like functions. Materials extend from metals and oxides to inorganic nanoparticles possessing intrinsic enzyme-like properties. High cost, low stability, difficulty in separation, reusability, and storage issues of natural enzymes can be well addressed by nanozymes. Since 2007, more than 100 nanozymes have been reported that mimic enzymes like peroxidase, oxidase, catalase, protease, nuclease, hydrolase, superoxide dismutase, etc. In addition, several nanozymes can also exhibit multi-enzyme properties. Vast applications have been reported by exploiting the chemical, optical, and physiochemical properties offered by nanozymes. This review focuses on the reported nanozymes fabricated from a variety of materials along with their enzyme-mimicking activity involving tuning of materials such as metal nanoparticles (NPs), metal-oxide NPs, metalorganic framework (MOF), covalent organic framework (COF), and carbon-based NPs. Furthermore, diverse applications of nanozymes in biomedical research are discussed in detail. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Emerging Nanomaterials for Catalysis and Sensor Applications
This book reviews emerging nanomaterials in catalysis and sensors. The catalysis section covers the role of nano-photocatalysts in organic synthesis and health care application, oxidation and sulphoxidation reactions, liquid phase oxidation, hydrogen evolution and environmental remediation. It highlights the correlation of surface properties and catalytic activity of the mesoporous materials. The sensor section discusses the fabrication and development of various electrochemical, chemical, and biosensors. Features: Combines catalysis and sensor applications of nanomaterials, including detailed synthesis techniques of these materials. Explores methods of designing, engineering, and fabricating nanomaterials. Covers material efficiency, their detection limit for sensing different analytes and other properties of the materials. Discusses sustainability of nano materials in the industrial sector. Includes case studies to address the challenges faced by research and development sectors. This book is aimed at researchers and graduate students in Chemical Engineering, Nanochemistry, Water Treatment Engineering and Labs, Industries, Research Labs in Catalysis and Sensors, Environmental Engineering, and Process Engineering. 2023 selection and editorial matter, Anitha Varghese and Gurumurthy Hegde; individual chapters, the contributors. -
Emerging Nanoparticle-Based Diagnostics and Therapeutics for Cancer: Innovations and Challenges
Malignant growth is expected to surpass other significant causes of death as one of the top reasons for dismalness and mortality worldwide. According to a World Health Organization (WHO) study, this illness causes approximately between 9 and 10 million instances of deaths annually. Chemotherapy, radiation, and surgery are the three main methods of treating cancer. These methods seek to completely eradicate all cancer cells while having the fewest possible unintended impacts on healthy cell types. Owing to the lack of target selectivity, the majority of medications have substantial side effects. On the other hand, nanomaterials have transformed the identification, diagnosis, and management of cancer. Nanostructures with biomimetic properties have been grown as of late, fully intent on observing and treating the sickness. These nanostructures are expected to be consumed by growth in areas with profound disease. Furthermore, because of their extraordinary physicochemical properties, which incorporate nanoscale aspects, a more prominent surface region, explicit geometrical features, and the ability to embody different substances within or on their outside surfaces, nanostructures are remarkable nano-vehicles for conveying restorative specialists to their designated regions. This review discusses recent developments in nanostructured materials such as graphene, dendrimers, cell-penetrating peptide nanoparticles, nanoliposomes, lipid nanoparticles, magnetic nanoparticles, and nano-omics in the diagnosis and management of cancer. 2025 by the authors. -
Emerging Novel Functional Materials from Biomass for Environmental Remediation
The Earth faces complex environmental challenges caused by both human activities and natural processes, affecting all life forms and ecosystems. Biomass-derived materials, sourced from renewable resources, serve as effective adsorbents, catalysts, and ion exchangers, providing sustainable solutions to environmental issues like water and air pollution, soil contamination, and waste management. Their significance lies not only in their biodegradability and sustainability but also in standardized testing and scalability considerations. The field of functional materials from biomass has the potential to transform environmental remediation, leading to a cleaner and more sustainable world. Here, we aimed to portrait the key approaches and recent developments in emerging functional materials from biomass tailored for environmental remediation, delving into their fundamental theories and concepts, various applications, and potential to reshape the remediation landscape. It evaluates the sustainability and biodegradability aspects of these materials, addresses challenges, and peers into the dynamic and rapidly evolving future of this field. Collaborative efforts between researchers, industry, and policymakers are pivotal to establishing guidelines and regulations ensuring the safe and responsible use of these materials. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Emerging technology adoption and applications for modern society towards providing smart banking solutions
The rapid advancement of emerging technologies has brought significant transformations to various sectors, including banking and finance. This chapter explores the adoption and application of emerging technologies in modern society, particularly focusing on their role in providing smart banking solutions. Technologies such as artificial intelligence (AI), blockchain, internet of things (IoT), and biometrics are revolutionizing traditional banking practices, enabling enhanced security, efficiency, and personalized services for customers. Through a comprehensive analysis of current trends and case studies, this chapter highlights the impact of these technologies on improving customer experiences, streamlining operations, mitigating fraud risks, and fostering financial inclusion. Additionally, it discusses the challenges and opportunities associated with the integration of these technologies into banking systems, including regulatory concerns, data privacy issues, and the need for skill development among banking professionals. 2024, IGI Global. All rights reserved. -
Emerging ternary nanocomposite of rGO draped palladium oxide/polypyrrole for high performance supercapacitors
In this work, novel electrodeposited palladium oxide-polypyrrole (PdP) and its ternary composite with reduced graphene oxide (PdPGO) draped over the surface of PdP were synthesised to achieve the excellent electrochemical properties and high stability. An exhaustive study has been carried out to correlate the crystalline structure, chemical bonding, morphological behaviour, redox reactions at the electroactive species, and its promising influences on the electrochemical performance. The electrodeposited PdPGO composite on stainless steel bestows superior electrochemical properties and a specific capacitance of 595 F g?1 at 1 A g?1 in 1 M H2SO4. The incorporation of rGO with the PdP matrix prevents the aggregation of rGO layers and is responsible for the enhanced electrostatic interactions at the electrode-electrolyte interface in PdPGO. Outstanding supercapacitance retention of 88% even after 5000 cycles at 5 A g?1 was accomplished for the ternary composite of Pd. These profound electrochemical characteristics are due to the synergistic effect of the individual components involved, manifest a great potential for Pd based composites toward novel electrode materials for supercapacitors of high efficiency. This method facilitates blueprints for synthesizing a series of advanced electrode materials for enhancing high storage capability. The high electrochemical performance of the PdPGO reveals how synergy plays a very important role to work on the blueprint to create active electrode materials for energy storage solutions. 2020 Elsevier B.V. -
Emerging world of the metaverse: An Indian perspective
[No abstract available] -
Emission line star catalogues post- Gaia DR3: A validation of Gaia DR3 data using the LAMOST OBA emission catalogue
Aims.Gaia Data Release 3 (DR3) and further releases have the potential to identify and categorise new emission-line stars in the Galaxy. We perform a comprehensive validation of astrophysical parameters from Gaia DR3 with the spectroscopically estimated emission-line star parameters from the LAMOST OBA emission catalogue. Method. We compare different astrophysical parameters provided by Gaia DR3 with those estimated using LAMOST spectra. By using a larger sample of emission-line stars, we performed a global polynomial and piece-wise linear fit to update the empirical relation to convert the Gaia DR3 pseudo-equivalent width to the observed equivalent width, after removing the weak emitters from the analysis. Results. We find that the emission-line source classifications given by DR3 is in reasonable agreement with the classification from the LAMOST OBA emission catalogue. The astrophysical parameters estimated by the esphs module from Gaia DR3 provides a better estimate when compared to gspphot and gspspec. A second degree polynomial relation is provided along with piece-wise linear fit parameters for the equivalent width conversion. We notice that the LAMOST stars with weak H? emission are not identified to be in emission from BP/RP spectra. This suggests that emission-line sources identified by Gaia DR3 are incomplete. In addition, Gaia DR3 provides valuable information about the binary and variable nature of a sample of emission-line stars. 2022 EDP Sciences. All rights reserved. -
Emoji Sentiment Analysis of User Reviews on Online Applications Using Supervised Machine Learning
Analyzing the sentiment behind emojis can provide valuable insights into the emotional context and user sentiment associated with textual content. To conduct a comparative analysis of diverse supervised machine learning models that can achieve the highest level of accuracy in Emoji Sentiment Analysis is the purpose of this research. Five machine learning models used in this research are K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), Logistic Regression, Naive Bayes, and Random Forest. The experimental process resulted in ANN and KNN models giving an accuracy of 92%. The ANN model shows its proficiency in effectively managing large datasets. ANN also supports fault tolerance. The KNN model refrains from conducting calculations during the training phase and only constructs a model when a query is executed on the dataset. This characteristic makes KNN particularly well-suited for data mining. Both ANN and K-NN excelled in the experimental study due to these distinctive attributes. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
EMONET: A Cross Database Progressive Deep Network for Facial Expression Recognition
Recognizing facial features to detect emotions has always been an interesting topic for research in the field of Computer vision and cognitive emotional analysis. In this research a model to detect and classify emotions is explored, using Deep Convolutional Neural Networks (DCNN). This model intends to classify the primary emotions (Anger, Disgust, Fear, Happy, Sad, Surprise and Neutral) using progressive learning model for a Facial Expression Recognition (FER) System. The proposed model (EmoNet) is developed based on a linear growing-shrinking filter method that shows prominent extraction of robust features for learning and interprets emotional classification for an improved accuracy. EmoNet incorporates Progressive- Resizing (PR) of images to accommodate improved learning traits from emotional datasets by adding more image data for training and Validation which helped in improving the model's accuracy by 5%. Cross validations were carried out on the model, this enabled the model to be ready for testing on new data. EmoNet results signifies improved performance with respect to accuracy, precision and recall due to the incorporation of progressive learning Framework, Tuning Hyper parameters of the network, Image Augmentation and moderating generalization and Bias on the images. These parameters are compared with the existing models of Emotional analysis with the various datasets that are prominently available for research. The Methods, Image Data and the Fine-tuned model combinedly contributed in achieving 83.6%, 78.4%, 98.1% and 99.5% on FER2013, IMFDB, CK+ and JAFFE respectively. EmoNet has worked on four different datasets and achieved an overall accuracy of 90%. 2020. All Rights Reserved. -
EMOTICONS AND THE NON-VERBAL COMMUNICATION: WITH REFERENCE TO FACEBOOK
In the recent years, the use of emoticons in text-based and computer-mediated communications has gained a lot of popularity. Though emoticons (a combination of punctuation marks and letters) first began as a representation of facial expression, they have over the years been transformed to now include graphical representations of a variety of items (both static and animated). The usage of emoticons and their interpretation differ from one person to another, depending on factors such as gender, age and culture. Facebook is a platform where people across the globe communicate, share opinions and connect with each other. The researcher, thus, seeks to understand whether emoticons have the ability to infuse the text-based computer-mediated- communications on Facebook with the richness and authenticity of face-to-face interactions, and to arrive at an understanding of how these different groups use and interpret emoticons. A sample size of 139 was selected using the snowball sampling technique. The methods of primary data collection included surveys in the form of questionnaires that were distributed online. A quantitative analysis of the collected data was conducted using SPSS. The study revealed that age, gender and location do have a bearing on the patterns of usage and interpretation of emoticons. It also showed that emoticons cannot provide the text-based computer-mediated- communications on Facebook with the richness and authenticity of face-to-face interactions. -
Emotion Detection Using Machine Learning Technique
Face Emotion Recognition (FER) is an emerging and crucial topic today; since much research has been done in this field, there are still many things to explore. In daily life, where people dont have time to fill out feedback, emotion detection plays an important role, which helps to know customer feedback by analyzing expressions and gestures. Analyzing current studies in emotion recognition demonstrates notable advancements made possible by deep learning. A thorough overview of facial emotion recognition (FER) is provided in this publication. The literature cited in this study is taken from various credible research published in the last 10years. This study has built a model for emotion recognition using photos or a camera. The paper is based on the concepts of Machine Learning (ML), Deep Learning (DL), and Neural Networks (NN). A range of publicly available datasets have been used to evaluate evaluation metrics. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Emotion Regulation and Psychological Well-being as Contributors Towards Mindfulness Among Under-Graduate Students
Emotion regulation is generally described as the ability of an individual not only to manage emotions effectively but also to respond effectively to the emotional experience. It has also been viewed as a crucial aspect for psychological well-being. It is a psychological state which means more than just being free from stress and not having any other psychological disorder reported by the individual. At the same time, students with higher emotion regulation and psychological well-being are expected to be more attentive and able to observe, describe and participate in the present moment, effectively, with non-judgmental awareness, which is in turn defined as mindfulness. Hence, it has been expected that participants with higher emotion regulation and psychological well-being would also report higher levels of mindfulness. Therefore, the present empirical investigation has been conducted with an objective of assessing the level of emotion regulation, psychological well-being and mindfulness among under-graduate students. Additionally, it was also expected that all the said variables would be positively correlated and emotion regulation and psychological well-being would predict mindfulness positively for under-graduate students. For this purpose, ex post facto research design was adopted, and standardized tools pertaining to emotion regulation, psychological well-being and mindfulness were administered on a sample of 104 under-graduate students. The results of correlation statistics revealed that emotional regulation (r=0.27; p<0.01) and psychological well-being (r=0.21; p<0.01) are the positive and significant correlates of mindfulness. Additionally, statistical outcomes of stepwise multiple regression analysis confirm that emotion regulation and psychological well-being are the significant predictors of mindfulness and contribute collectively towards a 11% variance towards the same. 2020, Springer Nature Switzerland AG. -
Emotional Abuse and the Pandemic in India: Implications for Policy, Research, and Practice
During the COVID-19 outbreak, cases of violence and abuse have increased significantly around the world, necessitating a reevaluation of our relation-ships. Both violence and abuse seek to control and instill fear in the individ-ual, gradually disrupting their overall well-being. Emotional abuse does not receive the same level of attention and social response as other forms of abuse due to its subtle nature. Its effects are as harmful as physical and sexual abuse, with serious consequences for the mental health of individual and their families. The COVID-19 pandemic has brought to light the importance of mental health. With the imposition of lockdown in India, the number of helplines for domestic violence and abuse has skyrocketed. Abuse experien-ces can be seen to be bidirectional; women are not alone in such instances. Many cases, however, go unreported and never reach formal institutions. The National Family Health Survey (2019-2021) reveals the current state of Indian health and nutrition, but emotional abuse (also referred to inter-changeably in this article as emotional violence) only includes responses from women and is no longer included under spousal violence in the most recent edition. This article also includes recommendations and attempts to highlight existing shortcomings in addressing the issue of emotional violence. The articles cited in this article were obtained from electronic databases. Other secondary data sources mentioned include newspaper articles, magazines, census reports, and periodicals. 2024 Springer Publishing Company. -
Emotional Inhibition and Personality as Predictors of Anxiety and Depression in Young Adults
Purpose: Anxiety and depression have been major contributors to the global burden of disease, and the impact has been exacerbated following the COVID-19 pandemic. Therefore, the aim of this study was to understand the association between emotional suppression and the introverted-extraverted dimension of personality in young people and anxiety and depression. Method: Participants were 152 Indian females between the age group of 18-25 years who provided basic demographic details and completed three questionnaires via a google form. Findings: Results described a significant negative correlation of anxiety r (152) = .500, p <0.01and depression r(152)=.471, p <0.01 with emotional inhibition. There was also a significant positive correlation of anxiety r (152) = .288,p < 0.01 and depression r(152)= .288, p <0.01 with personality. While Emotional inhibition emerged as a significant negative predictor of anxiety (R2= .250) as well as of depression (R2=.222), personality (R2=.243) emerged as a significant predictor of depression. Conclusion/Value: Contrary to popular belief, the results of this study suggest that anxiety and depression are inversely related to emotional inhibition. It restores the complexity of emotions and the need to investigate their role in various pathologies. These findings provide an initial basis for further investigation into the role of emotional expression and suppression in the Indian population. 2024 RJ4All. -
Emotional Intelligence and Cross-Cultural Adaptation of Indian Students in the Context of Interstate Education
India is known for its cultural diversity based on several factors, such as language, religion, race, and customs. In India, people used to move from one place to another for various purposes, and this was particularly the case with students in pursuit of education. In such situations, cross-cultural adaptation is one of the factors that facilitate their adjustment to new cultures and surroundings. Cross-cultural adaptation is needed when a person has to live in a different cultural setting than their own native place. Being sensitive to others emotions is essential when one lives in a new place. Emotional intelligence helps in that way and influences cross-cultural adaptation. Therefore, the present study was intended to explore the influence of emotional intelligence on cross-cultural adaptation. As many as 332 students, aged 17 to 29, who moved to another state for education, participated in the study. Emotional Intelligence Scale and Cross-Cultural Adjustment Scale were used for data collection. The components of emotional intelligence, such as self-emotional appraisal (SEA) and others emotional appraisal (OEA), were found to significantly influence expatriate adjustment. Furthermore, SEA and OEA have also influenced cultural novelty and the use of emotions (UOE). Students from rural areas were found to have more cross-cultural adaptation in the presence of their friends company compared to urban dwellers. In summary, the current study emphasizes the importance of higher emotional intelligence for better cross-cultural adaptation. 2025 Common Ground Research Networks. All rights reserved. -
Emotional Intelligence and General Well-Being Among Middle Aged People
International Journal of Research in Social Sciences, Vol-2 (4), pp. 454-471. ISSN-2249-2496