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Elucidating the interplay of PPAR gamma inhibition and energy demand in adriamycin-induced cardiomyopathy: In Vitro and In Vivo perspective
Adriamycin is an anticancer anthracycline drug that inhibits the progression of topoisomerase II activity and causes apoptosis. The effective clinical application of the drug is very much limited by its adverse drug reactions on various tissues. Most importantly, Adriamycin causes cardiomyopathy, one of the life-threatening complications of the drug. Altered expression of PPAR? in adipocytes inhibited the glucose and fatty acids uptake by down regulating GLUT4 and CD36 expression and causes cardiotoxicity. Therefore, the influence of Adriamycinin cardiac ailments was investigated in vivo and in vitro. Adriamycin treated rats showed altered ECG profile, arrhythmic heartbeat with the elevated levels of CRP and LDH. Dysregulated lipid profiles with elevated levels of cholesterol and triglycerides were also observed. Possibilities of cardiac problems due to cardiomyopathy were analyzed through histopathology. Adriamycin treated rats showed no signs for atheromatous plaque formation in aorta but disorganized cardiomyocytes with myofibrillar loss and inflammation in heart tissue, indicative of cardiomyopathy. Reduced levels of antioxidant enzymes confirmed the incidence of oxidative stress. Adriamycin treatment significantly reduced glucose and insulin levels, creating energy demand due to decreased glucose and insulin levels with increased fatty acid accumulation, ultimately resulting in oxidative stress mediated cardiomyopathy. Since PPARs play a vital role in regulating oxidative stress, the effect of Adriamycin on PPAR? was analyzed by western blot. Adriamycin downregulated PPAR? in a dose-dependent manner in H9C2 cells in vitro. Overall, our study suggests that Adriamycin alters glucose and lipid metabolism via PPAR? inhibition that leads to oxidative stress and cardiomyopathy that necessitates a different therapeutic approach. 2024 Wiley Periodicals LLC. -
Elusive Healthcare and Ailing Population: An Analysis of Indias Health Policy with Reference to the Health Status of Urban Poor in Bangalore
Health is a state of mental, physical and social well-being. India is in need of a healthcare system that can fulfill the demands of over a billion people who are unable to bear the burden of the cost of healthcare. The major challenges in the countrys healthcare system are the universal access to healthcare, health equity, healthcare human resources and healthcare finance. Increasing population in cities and urban poverty has raised a strong concern in the health condition of the urban poor in particular. The speedy growth of cities in the country in conjunction with the growth of the urban poor has made this position more important at this point of time. The present study basically aimed at finding the major factors influencing urban health and healthcare. This research aims in finding out the reasons for the fragmentation of Bangalores health services with unequal distribution of resources and minimum communication between various services. This study also focuses on areas of health concern like insufficient primary healthcare, lack of referral system, insufficient public participation towards healthcare promotion, co-ordination between various governmental or non-governmental departments etc. It is mainly based on secondary data. Interview guide is used as a tool to collect primary data. Content analysis is used to analyse and describe the present scenario objectively and systematically. Bangalore has a wide infrastructure of healthcare centres but still the poorer sections of the society do not have easy access to them. A significant number of government schemes have been implemented to provide better healthcare services in Bangalore. It can be said that Bangalore has got enough health resources to serve its people. However, the urban poor do not have the necessary means to access a proper healthcare due to various reasons like the shortage of staff, medicines, diagnostic services in public sector and private healthcare expenses which are unaffordable. The government has been failing to achieve its health target in the urban areas and ultimately left the same in the hands of private health sector. The funds allocated on health are not used effectively towards improved health service delivery. Healthcare budgeting, healthcare policies, disease eradication programmes and improvement plans of primary healthcare centres and dispensaries etc. are the main areas in which the government is falling short. There is a need to empower the urban poor to maintain their rights within the context of development. A policy which is more oriented towards the partnership of private and public healthcare sectors is advisable. A universalized system to provide equitable and basic care to every individual is required. Public-Private Partnership in health sector is a key for improving the health of the population. The governments act of financing towards healthcare must in fact be increased to 2-3 per cent of GDP. As such, the present study came out with a lot of suggestions to improve the health status of urban poor. It has also made an attempt to analyse the policy issues associated with healthcare. The researcher believes that this will be definitely an addition to the existing literature on healthcare systems in India. Layout of the dissertation: The dissertation is divided into five chapters. The first chapter is the introductory part of the research. It defines the basic concepts by giving brief summary or by providing information which are necessary to understand this research. This chapter also describes the research problems which motivates the researcher to conduct the study. Second chapter reviews the literature of healthcare problems faced by the common man. It includes reviews of various articles and books contributed towards healthcare and health policies by various health experts and practitioners. The third chapter talks about the methods used to implement the research. It explains the methodological procedures such as tools for data collection, sources of data and research design which are used to carry out the study. Data analysis is the fourth chapter and this part of the research includes the analysis of the various collected data. It includes the process of inspecting and transforming of the collected data with the goal of highlighting useful information, later helping towards suggesting conclusion of the research. The final chapter presents the summary of the research with important findings and suggestions. Key words: healthcare, health policy, health status, ailing people, urban poor, cost of treatment, public health sector, private health sector, health infrastructure. -
Elusive Justice to Dalits in the 'Land of Social Justice'
The recent inhuman incident of mixing human faeces in the overhead tank supplying water to Dalit colony in Vengaivayal village in Pudukkottai district of Tamil Nadu refl ects the perpetuating violence against the Dalits. Locating this brutal violence within the larger framework of violence against Dalits in Tamil Nadu, the lackadaisical attitude of Dravidian parties when dealing with the issues related to Dalits is brought to the fore.. 2023 Economic and Political Weekly. All rights reserved. -
EM AND THE BIG HOOM by Jerry Pinto
[No abstract available] -
Embarrassment in the Context of Negative Emotions and Its Effects on Information Processing
Negative emotions are feelings of sadness arising out of negative evaluation of oneself by self or others. Embarrassment is characterized as a negative emotion which is experienced as a threat to ones social identity. This chapter discusses the differences between embarrassment and related negative emotions, namely shame, guilt and humiliation and its effects on information processing. Around 45 articles have been reviewed in the process, which were selected based on their relation to either negative emotions in general or specifically to one or more of them. The study uses the interactional (bio-psycho-social) approach to determine the antecedents and consequences of experiencing embarrassment and how it affects information processing. It further explores gender differences in the experience of negative emotions. Given that the existing evidence reveals many contradictory findings in the experience of negative emotions, this chapter conceptualizes certain factors that might influence this experience. It also provides some reasons for variations in experience of embarrassment and related negative emotions, on the basis of gender. This chapter concludes by proposing the complexity of embarrassment as an emotion and a conceptual framework of a continuum on which the experiences of embarrassment may lie and the factors determining the placement of these experiences with their cognitive implications. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020, Corrected Publication 2020. -
Embedding behavioral biases into robo-advisory platforms-case of UAE investors
Purpose: This study aims to identify individuals' biases while making investment decisions and explore how these biases can be incorporated into a robo-advisory platform to help mitigate these biases. This paper identifies eight investment-related behavioral biases: mental accounting, gamblers fallacy, hindsight, regret aversion, disposition, trend-chasing, loss aversion and herding. Design/methodology/approach: This study uses primary data from 263 respondents across various age groups, of which approximately 50 were wealth management professionals in the UAE. A random sampling method from probability sampling is employed to gather the primary data. The identified biases serve as dependent variables; the age and income of individuals serve as the independent variables. Findings: Age and income are significantly related to mental accounting, herding, gambler fallacy and loss aversion. Existing studies on behavioral finance demonstrate that individuals who make investment decisions are susceptible to cognitive fallacies, leading to nonrational investment decisions. Practical implications: By studying these biases affecting individuals of varying ages and income levels, wealth management professionals can tailor their financial robo-advisory services to address these biases and help clients build wealth with consistent investment. Originality/value: This study uses survey-based sampling in the context of the UAE; hence, the data and analysis represent originality. 2024, Emerald Publishing Limited. -
Embracing intelligent machines: Aqualitative study to explore thetransformational trends inthe workplace
Purpose: With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines. Design/methodology/approach: We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected. Findings: This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies. Originality/value: This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation. 2024, Sumathi Annamalai and Aditi Vasunandan. -
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.