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Role of Blockchain in the Healthcare Sector: Challenges, Opportunities and Its Uses in Covid-19 Pandemic
As the world grapples with the Covid-19 pandemic and major populations are getting vaccinated, increasing realisation processes healthcare industry needs to be augmented. It includes managing supply chains, healthcare records, and patient care. With a scarcity of time and resources, adaptation of blockchain technology will help mitigate the pressures on existing infrastructure. A blockchain distributed ledger helps to exchange health information securely without complex intermediation of trust with secure access. The organisations and persons in the blockchain network can verify and authorise the data, thus protecting patient identity, privacy, medical information system, and reducing transaction costs. The paper examines managing and protecting electronic medical records and personal health records data using blockchain. It also analyses issues in healthcare, blockchain implementation, and its uses in the Covid-19 pandemic. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Gamification for industry 5.0 at the core of society 5.0
Gamification has become a popular approach to engage employees, customers, and other stakeholders in various industries. With the advent of Industry 5.0 and Society 5.0, the use of gamification is expected to increase, as companies and organizations look for innovative ways to enhance productivity, creativity, and collaboration. Industry 5.0 is the next phase of industrial development, characterized by the integration of advanced technologies, such as AI, IoT, and robotics, with human skills and creativity. Society 5.0, on the other hand, refers to a human-centered society that leverages technology to create solutions for social problems. This chapter explores the potential of gamification in the context of Industry 5.0 and Society 5.0. It discusses the various applications of gamification, including training, education, marketing, and sustainability. It also examines the benefits of gamification, such as increased engagement, motivation, and collaboration. 2023 by IGI Global. All rights reserved. -
Role of emerging technologies in smart marketing and smart business for modern society
In the digital age, the fusion of emerging technologies with marketing and business strategies has become imperative for staying competitive and meeting evolving consumer demands. This chapter explores the pivotal role of emerging technologies in facilitating smart marketing and business practices in modern society. Through a comprehensive review of literature and case studies, this chapter examines the impact of technologies such as artificial intelligence (AI), machine learning (ML), big data analytics, internet of things (IoT), augmented reality (AR), and blockchain on reshaping marketing and business landscapes. The integration of AI and ML algorithms enables predictive analytics, personalized marketing, and enhanced customer experience through precise targeting and recommendation systems. Big data analytics empowers businesses to derive actionable insights from vast datasets, enabling data-driven decision-making and dynamic market segmentation. 2024, IGI Global. All rights reserved. -
COVID-19 and the world with co-morbidities of heart disease, hypertension and diabetes
Newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) pandemic has now spread across the globe in past few months while affecting 26 million people and leading to more than 0.85 million deaths as on 2nd September, 2020. Severity of SARS-CoV-2 infection increases in COVID-19 patients due to pre-existing health co-morbidities. This mini-review has focused on the three significant co-morbidities viz., heart disease, hypertension, and diabetes, which are posing high health concerns and increased mortality during this ongoing pandemic. The observed co-morbidities have been found to be associated with the increasing risk factors for SARS-CoV-2 infection and COVID-19 critical illness as well as to be associated positively with the worsening of the health condition of COVID-19 suffering individuals resulting in the high risk for mortality. SARS-CoV-2 enters host cell via angiotensin-converting enzyme 2 receptors. Regulation of crucial cardiovascular functions and metabolisms like blood pressure and sugar levels are being carried out by ACE2. This might be one of the reasons that contribute to the higher mortality in COVID-19 patients having co-morbidities. Clinical investigations have identified higher levels of creatinine, cardiac troponin I, alanine aminotransferase, NT-proBNP, creatine kinase, D-dimer, aspartate aminotransferase and lactate dehydrogenase in patients who have succumbed to death from COVID-19 as compared to recovered individuals. More investigations are required to identify the modes behind increased mortality in COVID-19 patients having co-morbidities of heart disease, hypertension, and diabetes. This will enable us to design and develop suitable therapeutic strategies for reducing the mortality. More attention and critical care need to be paid to such high risk patients suffering from co-morbidities during COVID-19 pandemic. 2020 Journal of Pure and Applied Microbiology. All rights reserved. -
Developing a Framework and Wireframe for AI-Driven Personalization and Recommendation Systems in Library Management: A Design Thinking Approach
This research develops a framework and wireframes for an AI-driven personalization and recommendation system designed to enhance Library Management Systems (LMS). AI adapts library services dynamically to individual user characteristics and behaviors, such as reading preferences and interaction patterns, using predictive algorithms and behavioral analysis to deliver tailored recommendations. The study is primarily grounded in a User-Centered Design Thinking approach to ensure the system is intuitive, responsive, and meets diverse user needs. The proposed framework emphasizes seamless data integration and adaptive interface design. Prototypes created using Figma reflect intuitive, inclusive, and accessible features aligned with user needs. The prototype was evaluated in a controlled environment with high-frequency LMS users using the System Usability Scale (SUS) to assess usability and user satisfaction, achieving a score indicating excellent usability. Although the AI processing engine remains conceptual, this research provides a structured foundation for the future implementation of AI-driven recommendation systems in LMS, supporting enhanced user engagement and improved Selective Dissemination of Information through personalized and inclusive library experiences. 2026 P. Arumugam, Jayachristrayar S, Rega R and Jesus Rayar. -
Cyberdeviance among students a multidimensional scaling approach
Cyberdeviance off late has been gaining a lot of attention because of the increased use. Educational institutions have also made the internet available to its student to improve their exposure to various educational information. Hence, it becomes essential to identify a model that helps understand college factors to cyberdivert. The study focused on assessing whether college students are involved in cyberdeviation and the demographic effect on internet behaviour and cyberdeviance. The multidimensional approach was used to understand cyberdeviance. Data were collected from 264 students using convenience sampling in Bengaluru city, India. The study found that the respondents prefer to use the internet mainly for games and prefer least for theft, harassment, adult content, and hacking. They misused the internet due to the fear of unemployment and were involved in internet fraud to deploy knowledge. Copyright 2025 Inderscience Enterprises Ltd. -
Towards an Epistemology of Reading: Defining the Process of Reading in Modern Terms
The chaotic space caused by information explosion in present times has made the process and purpose of reading to be always questioned. Technological advancement has made reading appear as a mere mockery at the very outset. But the world still prioritizes knowledge that is acquired through observation, valuation and interpretation. At the time of Big Data, there still persists a sense of agency to define a given information as episteme. The present essay emphasizes on looking at reading as a modern phenomenon by presupposing the epistemological presence at the centre of any rational pursuit. Based on the Kantian precepts on enlightenment, the paper attempts to understand this presence of knowledge by delving into the major disciplines of modern philosophy that help in observing, valuing and interpreting the act of reading in present times. More than laying terms for defining the text within the modern space, the study essentializes reading in a virtually driven algorithmic world. AesthetixMS 2021 -
Enhancing Diagnostic Accuracy in Familial Alzheimers Disease Through Gene Expression Profiling and Optimized Machine Learning Algorithms
The abstract should summarize the contents of the paper in short terms, i.e. 150250 words Early and accurate diagnosis of the Familial Alzheimers Disease (FAD) is critical for effective treatment of this genetically inherited form of Alzheimers disease. A prediction of FAD from gene expression data is investigated and the performance of various machine learning models on the discovered patterns is evaluated. We compare the output of Linear, Ridge Regression and a LightGBM model with hyper-tuned parameters on data from the Gene Expression Omnibus. The LightGBM model is then hyperparameter tuned to better capture the non-linear complexity of the data. To find the predictive performance, a model is evaluated using MSE, R squared and accuracy. The results show that both the LightGBM model and the traditional models have lower MSE, higher R squared and better accuracy. By examining FAD data on high-dimensional gene expression data these results show that when dealing with high-dimensional gene expression data, sophisticated machine learning models perform better than other approaches, such as LightGBM show higher diagnostic accuracy in FAD. It is shown in this research the power of machine learning is immense and is a powerful tool for the predictive modeling of Alzheimers Disease, as well as possible early detection and personalized treatment. Future work might also aim to further improve model performance with other more complex genetic datasets. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Effects of dark matter in star formation
The standard model for the formation of structure assumes that there existed small fluctuations in the early universe that grew due to gravitational instability. The origins of these fluctuations are as yet unclear. In this work we propose the role of dark matter in providing the seed for star formation in the early universe. Very recent observations also support the role of dark matter in the formation of these first stars. With this we set observable constraints on luminosities, temperatures, and lifetimes of these early stars with an admixture of dark matter. 2019, Springer Nature B.V. -
Alternate models to dark energy
One of the unresolved questions currently in cosmology is that of the non-linear accelerated expansion of the universe. This has been attributed to the so called Dark Energy (DE). The accelerated expansion of the universe is deduced from measurements of Type Ia supernovae. Here we propose alternate models to account for the Type Ia supernovae measurements without invoking dark energy. 2017 COSPAR -
Dark matter, dark energy, and alternate models: A review
The nature of dark matter (DM) and dark energy (DE) which is supposed to constitute about 95% of the energy density of the universe is still a mystery. There is no shortage of ideas regarding the nature of both. While some candidates for DM are clearly ruled out, there is still a plethora of viable particles that fit the bill. In the context of DE, while current observations favour a cosmological constant picture, there are other competing models that are equally likely. This paper reviews the different possible candidates for DM including exotic candidates and their possible detection. This review also covers the different models for DE and the possibility of unified models for DM and DE. Keeping in mind the negative results in some of the ongoing DM detection experiments, here we also review the possible alternatives to both DM and DE (such as MOND and modifications of general relativity) and possible means of observationally distinguishing between the alternatives. 2017 COSPAR -
Gammaless gamma-ray bursts?
One of the possible resolutions of the compactness problem in gamma-ray bursts (GRBs) is by invoking the Lorentz factors associated with the relativistic bulk motion. This model applies to GRBs where sufficient energy is converted to accelerate the ejected matter to relativistic speeds. In some situations, this may not be a possible mechanism, and as a result, the gamma rays are trapped in the region. In this work, we look at such possible scenarios and where the neutrino pair production process can dominate. As a result, the neutrinos can escape freely. This could give rise to a scenario where the release of neutrinos precedes the gamma-ray emission that is much attenuated. This model can thus possibly explain why fewer GRBs are observed than what is expected. 2023, Indian Association for the Cultivation of Science. -
Synthetic biology for sustainable food ingredients production: recent trends
Problems with food security result from increased population, global warming, and decrease in cultivable land. With the advancements in synthetic biology, microbial synthesis of food is considered to be an efficient alternate approach that could permit quick food biosynthesis in an eco-friendly method. Furthermore, synthetic biology can be assumed to the synthesis of healthy or specially designed food components like proteins, lipids, amino acids and vitamins and widen the consumption of feedstocks, thus offering possible resolutions to high-quality food synthesis. This review describes the impact of synthetic biology for the microbial synthesis of various food ingredients production. 2022, Jiangnan University. -
Integrated biorefinery development for pomegranate peel: Prospects for the production of fuel, chemicals and bioactive molecules
Current experimental evidence has revealed that pomegranate peel is a significant source of essential bio compounds, and many of them can be transformed into valorized products. Pomegranate peel can also be used as feedstock to produce fuels and biochemicals. We herein review this pomegranate peel conversion technology and the prospective valorized product that can be synthesized from this frequently disposed fruit waste. The review also discusses its usage as a carbon substrate to synthesize bioactive compounds like phenolics, flavonoids and its use in enzyme biosynthesis. Based on reported experimental evidence, it is apparent that pomegranate peel has a large number of applications, and therefore, the development of an integrated biorefinery concept to use pomegranate peel will aid in effectively utilizing its significant advantages. The biorefinery method displays a promising approach for efficiently using pomegranate peel; nevertheless, further studies should be needed in this area. 2022 Elsevier Ltd -
Filamentous fungi for pharmaceutical compounds degradation in the environment: A sustainable approach
Pharmaceutical compounds play an important role in enhancing the quality of human life. They substantially increase the life expectancy of humans and the well-being of livestock. The expansion in the global human population has increased the usage of pharmaceuticals in an enormous way. This has led to the emergence of pharmaceutical compounds as environmental pollutants because these components are continuously released to various water sources and terrestrial ecosystems. The pharmaceutical components are released during their synthesis, as waste from human and veterinary healthcare sectors, and dumping of drugs that are not used. Pharmaceutical components are known to persist in their potential even at lower concentrations and can create serious issues for ecosystems, especially aquatic systems. Various efforts are being made to remove or reduce the toxicity of pharmaceutical components in aquatic systems. Bioremediation using fungi is one of the most secure and sustainable ways of decontaminating polluted environments. With their strong morphology and diverse metabolic abilities, Fungi employ different methods including fungal enzymes to clear pollutants. Studies have proven that fungi and fungal enzymes can transform these pharmaceutical compounds into less toxic components. This review highlights the role of fungi in the bioremediation of pharmaceutical compounds. 2023 The Author(s) -
Microbial Synthesis of Alkaloids and Applications in Healthcare
Plant alkaloids are a large group of natural compounds with wide-ranging bioactive characteristics, but the number of alkaloids obtained from the plant is low. Mass extraction of these bioactive alkaloids is affected by the trouble in large-scale propagation of these plants and absence of efficient strategies for extraction. However, production by chemical reactions is a substitute method; it is less effective due to its highly complex structure. The extensive study of alkaloid biosynthesis in plants and the advancement of genetic and metabolic engineering techniques enabled the opportunity to synthesise alkaloids through microbial hosts via metabolic engineering and bioprocess optimisations. In this chapter, we discuss the various gene-manipulation strategies to produce alkaloids in various microbial hosts and their application in the healthcare industry. 2023 selection and editorial matter, Ranjna Sirohi, Amit Kumar Rai, Luciana Porto de Souza Vandenberghe, and Binod Parameswaran; individual chapters, the contributors -
Microbial Enzymes for Synthesis of Chiral Drug Intermediates
Microbes or microbial enzymes can catalyze the synthesis of bioorganic compounds, and this process is defined as biocatalysis. Biocatalysis has become an essential technique in organic biotransformation, typically applied in chemical industries. Biocatalysts generally show high activity and excellent enantio, stereo, regio, and chemo-selectivity. They offer practical and cost-effective ways to synthesize semi-synthetic analogues and novel drug molecules. Many bacteria and fungi-derived enzymes could catalyze highly specific hydroxylations of various substrates that are highly complex to synthesize by chemical methods. This chapter details and discusses different biocatalytic microbial platforms that permit to produce the chiral drug intermediates. 2023 selection and editorial matter, Ranjna Sirohi, Amit Kumar Rai, Luciana Porto de Souza Vandenberghe, and Binod Parameswaran; individual chapters, the contributors -
Optimal Shortest Path Routing over Wireless Sensor Networks Using Constrained Genetic Firefly Optimization Algorithm
In Wireless Sensor Networks (WSNs), a large number of sensor nodes are placed over a specific area in any real-life application. The sensor node is small, with limited battery life, memory, and computing capacity. Due to the limited power of the battery, WSNs must expand the system life by minimizing the energy usage. In the existing system, the methods have limitations related to optimal shortest routing path, node energy consumption, network reconfiguration, and so on. In order to overcome these issues, aConstrained Genetic FireFly Optimization Algorithm (CGFFOA) is proposed. The CGFFOA algorithm is designed to select the best shortest path routing through the selection of Cluster Head (CH) nodes based on the better energy utilization, delay, and high throughput sensor nodes. It is used to optimize the routing path based on the energy, hop count, inter and intra cluster delay, and lifetime. The simulation findings therefore conclude that, with regard to reduced energy consumption, higher throughput, and lower end-to-end delay, the proposed CGFFOA algorithm is preferable to existing methods such as Particle Swarm Optimization (PSO) and Dynamic Source Routing (DSR). 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
SWITCHING INTENTION AND SWITCHING BEHAVIOR OF ADULTS IN THE NON-LIFE INSURANCE SECTOR: MEDIATING ROLE OF BRAND LOVE
In this digital era, customers in the insurance sector always look for better insurance products and services at an affordable price. When customers are unsure about service, they switch over to a better service provider. This behavior is more relevant to non-life insurance. However, the switching behavior of customers is hampered by certain switchover barriers such as brand consciousness, brand pride, brand loyalty, etc. This study focuses on exploring switching intentions and switching behaviors of adults in India keeping brand love as a mediator. A structured questionnaire was employed to collect the primary data from adults having non-life insurance products to analyze switching intentions and switching behaviors. The collected data were analyzed employing SPSS software and Hayes Process Model and appropriate statistical tools. The study results show that the switching intentions of adults vary based on their age, annual income, and education. Mean scores reveal that the lesser the age, the higher the intention to switch over. Further, based on annual income, adults who earn up to Rs 2 lakhs annually have more switching-over intentions (Mean score: 3.9719) followed by adults who earn Rs more than 2 lakhs to 5 lakhs annually (Mean score: 3.7590). Mean scores of education levels regarding switching intentions are higher among more educated adults and less among those who are qualified up to the school level. Arun Kumar N., Girish S., Suresha B., Mahesh E., 2023.