CovalentOrganic Frameworks (COF): An Advanced Generation of Reticular Organic Polymers for Energy and Environmental Applications
adsorption; batteries; covalent organic frameworks (COFs); dye removal; energy storage; environmental applications; heavy metal removal; nanoporous materials; pollutant degradation; redox activity; separation; supercapacitors; TT-conjugated backbones; tunable pores; water treatment
Over the past decade, nanoporous materials have caught strong attention among the scientific community due to their tremendous potential in real-world applications. This chapter introduces one such group of nanoporous materials called Covalent Organic Frameworks or simply COFs. Here, we briefly covered the overview of synthesis of COFs and their post-synthetic modifications employing different linkages boron, imine, triazine linkages, etc. High porosity with adjustable periodic pores, well-defined structures, and tunable skeletons are some of the key properties of COFs. In account of such advantages COFs have been scientifically researched in applications like adsorption, separation, energy storage devices, sensing, and especially in degrading various pollutants like heavy metals As, Cd, Cr, Cu; radionuclides UO 2 2+, TcO 4 ?, Nd 3 +, I 2; organic waste dyes, pharmaceutical waste, organo-phosphorous retardants, etc. This chapter specifically describes the current advancement of COFs in segregating hazardous chemicals by sorption methods. One such example is heavy metal sorption in trace amounts from water which otherwise can pose a great threat to human health if not removed completely. Some of these ions include UO 2 2+. By utilizing weak chemical interactions for dye confinement within COF pores, industrial sewage water can be made dye free. ?-conjugated backbones found in aromatic COFs could function as a signal transducer, or active functional groups evenly spaced could act as a receptor, and the uniform pores can serve as mass transfer inducer/enhancers. As a result, COFs can facilitate facile and smooth ion transport by the virtue of redox activities within COF pores. This makes COF a robust and efficient material for energy applications particularly in designing batteries and supercapacitors. Thus, COFs could act as a potential electrodes both anode and cathode for energy storage devices. The current chapter also highlights the development in the field of environmental applications using COF materials. In a nutshell, this chapter gives the reader an idea about many fold advantages of COFs in the energy and environmental sector to combat rising environmental concerns and energy demands. 2025 WILEY-VCH GmbH, Boschstra 12, 69469 Weinheim, Germany. All rights reserved.
Organic Polymers in Energy-Environmental Applications, pp. 215-242.
Ravi A., Christ University, Department of Chemistry, Laboratory for Nano-Void Chemistry (NAVICHEM), 560029, Bangalore, India; Ajith A.J., Christ University, Department of Chemistry, Laboratory for Nano-Void Chemistry (NAVICHEM), 560029, Bangalore, India; Chaudhari A.K., Christ University, Department of Chemistry, Laboratory for Nano-Void Chemistry (NAVICHEM), 560029, Bangalore, India
The social psychology of COVID-19 stigma
The spread of infectious diseases and the associated stigmatisation of people is an evidenced history. The present chapter is an attempt to explain the stigma of race, class and religion in India with the help of the established intergroup theories of social psychology to highlight the psychosocial consequences resulting out of an outbreak of infectious diseases, i.e., COVID-19. In order to present the implicational value of intergroup theories in explaining the practices of COVID-19-generated stigmatisation of people in India on the basis of their belongingness to particular race, class and religion, a systemic review of the COVID-19-generated stigmatisation of people and groups was carried out. Anecdotal presentations of stigmatised treatments against the several social groups in India are explained from the vantage of intergroup theoretical approaches of social psychology. In our review, intergroup theories of social psychology were found instrumental in explaining COVID-19-generated stigmatised treatments directed against people based on race, class and religion. Intergroup Emotions Theory could explain the stigmatisation of Northeast Indians. Scapegoat theory was found instrumental in explaining the stigmatisation of poor and migrants. Stigmatisation against Muslims could be justifiably explained in the light of social identity theory. At last, the chapter attempts to make certain recommendations aimed to reduce or combat negative psychosocial responses to infectious diseases like COVID-19. 2025 selection and editorial matter, Asma Parveen and Rajesh Verma; individual chapters, the contributors.
Bhanot D.; Verma S.K.; Sharad S.; Bharti B.K.; Singh T.; Mittal S.; Tushir B.
Mental, Emotional and Behavioural Needs of the General Population Following COVID-19 in India: Findings from Qualitative and Quantitative Studies, pp. 114-134.
Bhanot D., Department of Applied Psychology, Ramanujan College, University of Delhi, India; Verma S.K., Vivekananda College, Delhi University, India; Sharad S., Vivekananda College, University of Delhi, India; Bharti B.K., Vivekanand College, University of Delhi, India; Singh T., University of Allahabad, India, Banaras Hindu University, India, National Academy of Psychology (NAOP), International Association of Applied Psychology (IAAP), India; Mittal S., School of Liberal Arts, Bennett University, India; Tushir B., Christ University, Delhi-NCR, India
Robotics: challenges and opportunities in healthcare
health studies; health system; healthcare; IoT; medical; medical device; Robotics
Today, healthcare services and systems are becoming very complex and include a large number of entities characterized by shared, distributed and heterogeneous devices, sensors, and information and communication technologies. Various artificial intelligence techniques have been implemented in various sectors like smart cities, energy, IT sectors, banking, agriculture, retails, and many more, but it has been always challenging to demonstrate this technique effectively in healthcare sector due to its sophisticated procedure and its handling. Data analytics research on healthcare data has grown significantly over the past 10-12 years, and the execution of data analytics algorithms and systems in healthcare has been progressing more quickly. The data analytics service section has gained considerable attention with the development of technology, especially artificial intelligence robots, in the healthcare sector. Robots can help people with cognitive, sensory, and motor disabilities, help the sick or injured, support caregivers, and assist the clinical workforce. The purpose of this study is to provide historical evolution of robotics in healthcare with an overview of the influence of robots in healthcare like clinical support, patient transfer in hospitals, to handle heavy surgical instruments, to transport medical waste, for drug delivery, patient management etc. Furthermore, this chapter also covered the challenges and opportunities in healthcare and also offers a comprehensive aspect at how robots are incorporate in various healthcare applications. 2025 Elsevier Inc. All rights reserved.
Data Science in the Medical Field, pp. 361-367.
Pant R., Department of Mechanical Enginnering, Uttaranchal University, Uttarakhand, Dehradun, India; Joshi K., Department of Computer Science Enginnering, Uttaranchal University, Uttarakhand, Dehradun, India; Mahajan S., Postdoc (Norway), Christ (Deemed to be University), Delhi-NCR, India
Smart therapist: The mental health detector
In this fast-moving world, mental health disorder has turned to be one of the important issues which need utmost care and concern. According to the National Mental Health Survey Report, at least 14% of the India's population needs attention for mental disorders, of which stress, depression, and anxiety are the most common. An automated system that helps in detecting these mental disorders and thereby helps us to lead a better life by moulding our lifestyle is desirable. This chapter proposes an Intelligent Therapist based on machine learning which diagnoses a person's mental state through a set of questionnaires that helps in determining his/her mental state. The chatbot analyses the response and classifies them into different categories as per the severity of the disorder. The model is trained and tested on varying datasets to provide better accuracy in the understanding of human behaviour. This web-based chatbot will be accessible to anyone having access to the internet and will act as a preliminary self-check-up point. 2025 selection and editorial matter, Neha Goel and Ravindra Kumar Yadav; individual chapters, the contributors.
Dutt A.; Nizar Banu P.K.; Bansal A.; Bansal K.
Internet of Things enabled Machine Learning for Biomedical Applications, pp. 167-187.
Dutt A., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Nizar Banu P.K., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Bansal A., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Bansal K., CHRIST (Deemed to be University), Karnataka, Bangalore, India
2D Metal-based Electrocatalysts: Properties and Applications
Metallic nanostructures with thickness ranging from a single atom up to 100 nanometers fall under the category of 2D metals. The modified electronic band structure due to quantum confinement effects leads to intriguing electrical and electronic properties. Moreover, the properties can be further altered by variations in their shape, thickness, and lateral size. The exceptionally high surface area to volume ratio of 2D metals and stretchability are beneficial in electrocatalysis. The exposed atoms on the outer surface of 2D metals with low coordination numbers, possess unique properties, forming numerous active sites on the surface. As a result, 2D metals demonstrate a high ability towards the activation of small molecules, including O2, H2, CO2, HCOOH, CH3OH, C2H5OH, etc. This exceptional oxidation reactivity enables 2D metals to be excellent electrocatalysts for hydrogen/oxygen evolution reaction (HER/OER), oxygen reduction reaction (ORR), and oxidation of small molecules (formic acid, methanol, and ethanol) for fuel-cell applications. As the localized surface plasmon resonance (SPRs) is sensitive to the size/shape of plasmonic 2D metals, the optical absorption enabled by SPRs offers additional advantages for photo-electrocatalytic processes. The stability of highly active catalytic 2D metals presents a challenge due to the propensity of metal surfaces with high reactivity to undergo oxidation. Recent developments in the synthesis, properties, and applications of 2D metal nanostructures for electrocatalytic processes are discussed. The challenges and opportunities in the electrocatalytic application of 2D metal nanostructures have been summarized. 2025 Ram K. Gupta.
Lakshmanan P.; Kumar M K.; Pyarasani R.D.; Amalraj J.
2D Metals Fundamentals, Emerging Applications, and Challenges, pp. 138-155.
Lakshmanan P., Inha University Incheon, South Korea; Kumar M K., CHRIST (Deemed to be University), Karnataka, India; Pyarasani R.D., Universidad catica de Maule Talca, Chile; Amalraj J., Universidad de Talca Talca, Chile
Statistical Data Analysis of Anticorrosion and Antifouling: Unveiling Insights from Performance and Trends
CA (contact angle); CAH (contact angle hysteresis); MIC (microbiologically influenced corrosion); Polymers; SLIPS (slippery lubricant-infused porous surfaces); WCA (water contact angle)
This chapter provides intended insights about the current antifouling and anticorrosion conventional coatings, each with a distinct quality, that fall short of fully satisfying the contemporary requirements of material preservation in a marine environment. To solve these issues and accomplish the required goals, a number of novel terminologies and procedures have been investigated and several recently published research works were referred to and briefly examined in order to provide appropriate conclusions. In order to explore new methodologies that provide total protection for materials from biofouling and corrosion in maritime environments, this study looks into the complex realm of antifouling and anticorrosion methods. 2024 Scrivener Publishing LLC.
Preetham Noel P.; Kumar K.P.; Mani Joseph P.; Pillai V.J.
Novel Anti-Corrosion and Anti-Fouling Coatings and Thin Films, pp. 459-473.
https://doi.org/10.1002/9781394234318.ch16 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207991010&doi=10.1002%2f9781394234318.ch16&partnerID=40&md5=c92d389c3c35d912a0151ffab9edb01b
Preetham Noel P., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Kumar K.P., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Mani Joseph P., Department of Mathematics and Computer Science, Modern College of Business and Science, PC, Muscat, Oman; Pillai V.J., Department of Electronics and Communication Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, India
Identifying Wage Inequality in Indian Urban Informal Labour Market: A Gender Perspective
Gender; informal employees; labour market; Oaxaca-Blinder decomposition; urban
This chapter elucidates the wage differential between male and female informal workers in urban labour market by using employment and unemployment survey 61st (2004-2005) round, 68th (2011-2012), and Periodic Labour Force Survey 2019-2020 data of National Sample Survey Office (NSSO) unit level data. This study found that gender inequality not only increased during getting job but also persists after getting job during wage distribution. Based on the Oaxaca-Blinder (OB) decomposition, it is revealed that gender wage inequality is more in the labour market due to the labour market discrimination, that is, unexplained components. Hence, this study helps researcher, policy makers and government to fix the gender wage discrimination issues exist in the Indian labour market. This will enhance economic growth through the rise of the women labour force participation. 2024 A. Vinodan, S. Mahalakshmi, and S. Rameshkumar.
Informal Economy and Sustainable Development Goals: Ideas, Interventions and Challenges, pp. 335-357.
Pattayat S.S., Department of Economics, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Haluwalia S., Department of Economics, CHRIST (Deemed to be University), Karnataka, Bangalore, India
Enhancing Patient Safety and Efficiency in Intravenous Therapy: A Comprehensive Analysis of Smart Infusion Monitoring Systems
Air embolism; Bioelectronics; Healthcare; IoT; IV fluid; Sensors; Smart hospitals; Smart IV infusion monitoring
Intravenous (IV) fluids, comprising vitamin-rich solutions, are administered to address patient electrolyte imbalances and dehydration through IV infusion therapy. Infusion pumps are integral for precise medication dosage delivery in this common medical procedure, generally posing low risks. These fluids are stored in polypropylene bags connected to patients through tubes. However, when the IV bag empties, the patients blood may flow backward into the IV tube due to higher blood pressure, known as diffusion, potentially leading to complications like air embolism-life-threatening if air enters the bloodstream through the IV line, obstructing blood flow to vital organs. Smart IV Bags emerged as a solution to mitigate such risks, eliminating the need for manual IV bag monitoring while preventing reverse blood flow. This research comprehensively assesses various IoT-enabled IV Bag monitoring systems, comparing their strengths, weaknesses, and unique features. Key evaluation criteria include component efficiency, real-world applicability, accuracy, latency, and technical specifications. The aim is to provide an objective evaluation of each Smart Intravenous Liquid Monitoring System to inform future developments in this field. A systematic approach ensures the selection of systems that best meet specific requirements in diverse healthcare environments. 2024 Scrivener Publishing LLC.
Internet of Things in Bioelectronics: Emerging Technologies and Applications, pp. 171-200.
Sreekumar K., Department of CSE, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Reddy T.P., Department of CSE, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Prathap B.R., Department of CSE, CHRIST (Deemed to be University), Karnataka, Bangalore, India
Biomedical Waste Management: Legal and Regulatory Framework and Remedial Strategies
The present chapter begins with conceptual analysis of legal and regulatory framework from Indian as well as international perspectives. Follow through comparative analysis of Basel Convention on the Control of Trans-Boundary Movement of Hazardous Waste and Their Disposal, 1992; Convention on the Import into Africa and the Control of Trans-Boundary Movement and Management of Hazardous Wastes within Africa, Bamako, 1998; Convention on Persistent Organic Pollutants (POPs), Stockholm 2004; with Biomedical Waste Management Rules 2016 and (Amendment 2018) of India. The chapter also presents the legal and regulatory frameworks from the perspective of the United Kingdom, Indonesia, Kenya, and Sri Lanka as case studies. The chapter focuses on addressing SDG 3 (Good Health and Wellbeing), SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), SDG 10 (Reduced Inequalities), SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 14 (Life Below Water), SDG 15 (Life on Land), SDG 16 (Peace, Justice, and Strong Institutions), and SDG 17 (Partnerships for the Goals). 2025 Moharana Choudhury, Ankur Rajpal, Srijan Goswami, Arghya Chakravorty and Vimala Raghavan.
Hussaini N.; Jain S.A.; Hussaini T.; Alexander D.; John S.; Sarkar B.
Analytical Case Studies on Municipal and Biomedical Waste Management: Perspectives on Sustainable Development Goals, pp. 104-118.
Hussaini N., School of Commerce, Finance and Accounting, Christ University, Bangalore, India; Jain S.A., School of Law, Christ University, India; Hussaini T., Manipal Law School, Manipal Academy of Higher Education, Bengaluru Campus, India; Alexander D., Manipal Law School, Manipal Academy of Higher Education, Bengaluru Campus, India; John S., Manipal Law School, Manipal Academy of Higher Education, Bengaluru Campus, India; Sarkar B., School of Business & Management, Christ University, Bangalore, India
Bioinformatics applications for evaluating health and pharmacological properties of tea: Use of computer-assisted drug discovery tools
CADD; Drug discovery; Phytochemicals; Therapeutics
Bioinformatics has emerged as a crucial tool in tea research, enabling the exploration of the genetic and molecular intricacies underlying tea cultivation, quality, and health benefits. By leveraging bioinformatics, researchers have extensively explored, inferred, and evaluated the pharmacological properties of tea. This groundbreaking approach has unveiled a myriad of possibilities for utilizing the bioactive compounds present in tea. Metabolomics studies have unraveled the intricate metabolic pathways within tea plants, providing insights into the synthesis and accumulation of bioactive compounds. Bioinformatics in tea research opens new avenues for the tea industry, benefiting both producers and consumers worldwide. These advancements not only deepen our understanding of tea biology but also hold immense potential for sustainable tea production, the discovery of novel bioactive compounds, and the optimization of tea flavors and health benefits. This chapter explains the bioinformatic tools used to identify various therapeutic properties of tea biocompounds. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.
Tea in Health and Disease Prevention, pp. 379-390.
Chacko A.M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Bylappa Y., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Nag A., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Marine microbial biopolymers and their applications
antiinflammatory; antimicrobials; Biopolymers; marine microbes
Marine environment has been an important surrounding in recent times for valuable resources such as bioactive polymers. Increasing environmental concerns and realizing the limitation of global petroleum resources, biopolymers has gained utmost importance. Highly abundant renewable biopolymers of different polysaccharides have been produced from microbes, clams, shrimps, etc., exhibiting varying biological activities. Among all these biopolymers, microbial biopolymers are the most promising substitute for the existing synthetic polymers. Microbial polymers are synthesized intracellularly and extracellularly for their cell functions and survival playing specific roles as reserve materials for energy conservation, symbiosis and osmotic adaptation, protective agents that can be extruded and used for various applications. These biopolymers have exceptional moisture and oxygen barrier characteristics in making films for use in food industries and medical aspects. Microbial biopolymers that have been used include the cellulose, levan, pullulans, xanthan, gellan, kefiran, Haloferax exopolysaccharides, Polyhydroxyalkanoates (PHAs), and poly-3-hydroxybutyrates. Marine bacteria such as Bacillus, Halomonas, Alteromonas, Planococcus, Pseudoalteromonas, Vibrio, Zoogloea, and Thermococcus are found to be hyperproducers for biopolymers. Due to their high quality, sustainability, long shelf life, and biodegradability, they have been receiving interest for innumerable biological activities such as antioxidants, antidiabetic, antiinflammatory, and antimicrobial actions. Microbial marine biopolymers with natural biological activity, structural functions can be tailored using genetic engineering to obtain newer biomaterials with novel functionalities. 2025 Elsevier Ltd. All rights reserved.
Marine Biopolymers: Processing, Functionality and Applications, pp. 933-954.
Mayegowda S.B., Department of Psychology, CHRIST-Deemed to be University, Kengeri Campus, Karnataka, Bengaluru, India; Manjula N.G., Department of Microbiology, School of Basic and Applied Sciences (SBAS), Dayananda Sagar University, Karnataka, Bengaluru, India
Climate Change Adaptation Strategies for Achieving Net-Zero Economy
Carbon emissions; Carbon neutrality; CC adaptations; Collective knowledge; Developing economies; Environment management system; Global warming; Net zero; Sustainable development
Today, net zero economy is garnering lot of interest as climate change concerns have become one of the most pressing issues for the organizations. The negative impact of climate change (CC) could be witnessed across all industries. The direct risk (i.e. impairment cost, damages, forced closure from extreme weather events) and indirect risk (i.e. disruption in the business value chain, loss of infrastructure, etc.) emanating from CC has severely impacted the business model of the companies. It is important for companies to address climate challenges in their core business model and take climate action for achieving net zero economy. The aim of this study is to explore the impact of various organizational factors on the climate change adaptation strategies (CCAS) of manufacturing companies in India. The data was collected from 241 respondents and structural equation modelling (SEM) through Smart PLS 3.0 was employed for analysis in the study. Results indicated that corporate knowledge, processes, objectives, financial resources, collective knowledge, and incentives significantly influence the CCAS for the companies. The findings provide valuable input to the managers, practitioners, and other stakeholders interested in promoting climate actions and achieving a net zero economy. This chapter contributes to the extant literature in the field of corporate CC strategies and actions. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Kumar K.; Singh R.; Sharma A.; Lehri B.P.S.
Approaches to Global Sustainability, Markets, and Governance, Vol-2024, pp. 163-183.
Kumar K., School of Management, Bennett University, Greater Noida, India; Singh R., Institute of Business Management, GLA University, Uttar Pradesh, Mathura, India, Department of Management Studies, Kumaun University, Uttarakhand, Nainital, India; Sharma A., Christ University, Bengaluru, India; Lehri B.P.S., University School of Business, Chandigarh University, Mohali, India
2D Photonic Crystal Nano Biosensor with IoT Intelligence
Bio-analyte; Internet of things; Nano biosensor; Photonic crystal; Photonic sensor
Optical biosensors based on photonic crystals (PCs) offer interesting possibilities for the analysis and identification of bioanalytes. PC is a periodically varying artificial dielectric material that determines the propagation of modes present in the structure. Within dielectric media, there are modes that are selected based on structural perturbations. Changes in the refractive index of biological analytes are used to identify biological samples and are therefore used as sensing media in many applications. Because these PC sensors are designed in the nano range, they have excellent selectivity and sensitivity. The PC is ultra-compact and only small amounts of analyte are required for bioanalyte detection. Quantification of bioanalytes and biochemicals is one of the greatest challenges in the medical and diagnostic fields. However, these electronic devices cannot be directly connected to biological analytes, so the most difficult task is to extract the analyte information and convert it into electronic signals. Optical biosensors offer an attractive way to interrogate the content of bioanalytes because they directly convert biological events into electrical signals. It is also called a self-contained integrated physical medium because of its many applications such as food industry, drug delivery, point-of-care diagnostic sensing devices, and environmental monitoring. Based on the analyte placed on the PC sensor, resonant wavelengths are observed and the measurements are stored in a database. Diseases are identified based on the current users cognitive value, and data is transmitted and monitored over the Internet of Things. 2024 Scrivener Publishing LLC.
Balaji V.R.; Jesuwanth Sugesh R.G.; Sreevani N.R.G.; Dhanabalan S.S.; Sridarshini T.; Hegde G.
Internet of Things in Bioelectronics: Emerging Technologies and Applications, pp. 107-124.
Balaji V.R., Centre for Healthcare Advancement, Innovation and Research, Vellore Institute of Technology, Tamil Nadu, Chennai, India; Jesuwanth Sugesh R.G., Department of Electronics and Communication Engineering, CHRIST University, Karnataka, Bangalore, India; Sreevani N.R.G., Department of Computer Science and Engineering, S.A. Engineering College, Tamil Nadu, India; Dhanabalan S.S., Functional Materials and Microsystems Research Group, School of Engineering, RMIT University, Melbourne, VIC, Australia; Sridarshini T., Department of Electronics and Communication Engineering, College of Engineering Guindy Campus, Anna University, Tamil Nadu, Chennai, India; Hegde G., Centre for Nanoscience and Engineering, Indian Institute of Science, Karnataka, Bengaluru, India
Fluorescent carbon nanoparticle hybrids: synthesis, properties and applications
Applications; Fluorescent hybrid carbon nanoparticles; Functional properties; Properties; Synthesis
The development of materials in nanoscale morphologies with novel compositions is one of the major focuses of nanoscience and technology, as these materials are imbibed with unique properties that make them suitable for specific applications in a large variety of fields. Combining two or more chemically distinct constituents into a single nanostructure helps to attain desirable attributes of physical and chemical responses that can be efficiently utilized for specific applications. Hybrid nanomaterials constituted as a combination of multiple components into single nanostructures are known to showcase the properties of the individual components in tandem or synergy. Novel functionalities are also known to arise from integrating Fluorescent carbon nanoparticles (FCNPs) with other counterparts. FCNPs, when combined with other materials to form nanohybrids, provide copious functional attributes due to their inherent properties and the augmentation in properties due to the presence of the other materials. Integrating hybrid counterparts with FCNs improves the functional properties, which can be utilized for various applications such as photocatalysis, bioimaging, bio/chemo sensing, and many more. Herein we present an overview of recent and relevant works related to the synthesis, properties, and applications of fluorescent carbon nanoparticle (FCNP) hybrids. Various synthetic routes of FCNP hybrids via physical and chemical methods are summarized. The properties of the hybrid systems and the influence of hybridization on the properties are discussed. Applications of FCNP hybrids in various fields are also discussed in detail. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.
Varghese N.; John V.L.; Das R.; Sivan M.D.; Remadevi A.B.; Vinod T.P.; Nair Y.
Fluorescent Carbon Nanoparticles: Fundamentals and Applications, pp. 667-722.
Varghese N., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India; John V.L., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Das R., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Sivan M.D., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Remadevi A.B., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Vinod T.P., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Nair Y., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India
Development and validation of middle school under performers checklist in India through virtual platforms post-COVID-19
Education is a holistic development that must be nurtured through hybrid or virtual educational practices. The pandemic brought a sense of psychosocial distress among teenagers that urged the need to understand these psychosocial competencies. Often, our Indian education system is unable to assess the challenging psychosocial competencies of learners in varied learning platforms. Hence, there is a need in todays context to harness adolescents holistic learning to be more flexible, and interactive with innovative instructional methodologies, creative assessment strategies, and virtual resource tools. These psychosocial open learning resources need to be advocated by educators and counsellors for the well-being of teenagers. Thus, this quantitative study aimed to develop a checklist to identify the psychosocial concerns of underperformers in an open learning system. Hence, educators and counsellors must be equipped to recognise their psychosocial concerns to handhold them into becoming autonomous thinkers and contributors in their society. This would further establish the seed of sustainability. Thus, this study aimed to develop and validate a checklist as a psychometric measure to identify middle school underperformers social and personal abilities. The study group comprised 359 school educators and counsellors in Bangalore and Mashed, India (299 educators and 60 counsellors). The checklist was developed using Develop (2016) and Oldenburgs principles of scale development (2021). The Cranach coefficient of the checklist was.924 for 12 items. The statistical results indicated the validation of the checklist as a tool for identifying psychosocial challenges of eighth-grade underperformers as reliable. Exploratory Factor Analysis reduced these items into two distinctive factors. The findings suggest that the checklist can be used as an innovative educational toolkit to identify middle school underperformers personal and social abilities. Further experimentation of this study can be taken up with a larger intergenerational population. 2025 selection and editorial matter, Asma Parveen and Rajesh Verma; individual chapters, the contributors.
Mental, Emotional and Behavioural Needs of the General Population Following COVID-19 in India: Findings from Qualitative and Quantitative Studies, pp. 135-155.
Gomes R.F., CHRIST (Deemed to be University), Bangalore, India, Jyoti Nivas College Autonomous, Bangalore, India; Thomas L., CHRIST (Deemed to be University), Pune, Lavasa, India
Exploring the synergy of IIoT, AI, and data analytics in Industry 6.0
This chapter delves into the transformative intersection of artificial intelligence (AI), Industrial Internet of Things (IIoT), and data analytics within the context of emerging Industry 6.0. As industries continue to emerge towards greater connectivity and automation, the chapter delivers a comprehensive analysis of the convergence of these cutting-edge technologies in reshaping the industrial landscape. It explores the synergistic relationships among IIoT, AI, and data analytics, examining their collaborative potential to enhance efficiency, productivity, and decision-making processes. The chapter begins by offering an in-depth overview of Industry 6.0, highlighting the technological advancements and paradigm shifts that characterize this era. Subsequently, it dissects the role of IIoT as a pivotal enabler, connecting physical devices and systems to facilitate real-time data exchange. The incorporation of artificial intelligence is explored as a premeditated augmentation, empowering machines to learn, adapt, and optimize operations autonomously. Simultaneously, the chapter investigates the significance of advanced data analytics techniques in extracting actionable insights from big data, fueling informed decision-making and predictive maintenance strategies. Furthermore, the chapter delves into practical applications and case studies showcasing successful implementations of this triad in diverse industrial sectors. 2025 selection and editorial matter, C Kishor Kumar Reddy, Srinath Doss, Lavanya Pamulaparty, Kari Lippert and Ruchi Doshi; individual chapters, the contributors.
Vijay Arputharaj J.; William B.N.J.; Haruna A.A.; Prasad D.D.
Industry 6.0: Technology, Practices, Challenges, and Applications, pp. 1-36.
Vijay Arputharaj J., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; William B.N.J., TE Connectivity, Switzerland; Haruna A.A., Department of Computer Science, University of Hafr Al Batin, Saudi Arabia; Prasad D.D., Department of ECE, Vishnu Institute of Technology, Andhra Pradesh, India
A Brief Review onDifferent Machine Learning-Based Intrusion Detection Systems
Decision tree algorithm; Intrusion detection; kNN algorithm; Random Forest algorithm; Support vector Machine algorithm
In the contemporary cybersecurity landscape, the proliferation of complex and sophisticated cyber threats necessitates the development of robust Intrusion Detection Systems (IDS) for safeguarding network infrastructures. These threats make it more challenging to maintain the communitys availability, integrity, and confidentiality. To ensure a secure network, community administrators should implement multiple intrusion detection systems (IDS) to monitor and detect unauthorized and malicious activities. An intrusion detection system examines the networks traffic by analyzing data flowing through computers to identify potential security threats or malicious activities. It alerts administrators when suspicious activities are detected. IDS generally performs two types of malicious activity detection: misuse or signature-based detection, which entails collecting and comparing information to a database of known attack signatures, and anomaly detection, which detects any behavior that differs from the standard activity and assumes it to be malicious. The proposed paper offers an overview of how different Machine Learning Algorithms like Random forest, k - Nearest Neighbor, Decision tree, Support Vector Machine, Naive Bayes, and K- means are used for IDS and how these algorithms perform on different well-known datasets, and Their accuracy and performance are evaluated and compared, providing valuable insights for future work. kNN shows an accuracy of 90.925% for Denial of Service Attacks and 98.244% for User To Root attacks. The SVM algorithm shows an accuracy of 93.051% for Probe attacks and 80.385% accuracy for remote-to-local attacks. According to our implementation, these two algorithms work better than the others. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Samanta S.; Sen A.P.; Mukhopadhyay D.; De S.; Bhattacharyya S.; Platos J.
Lecture Notes on Data Engineering and Communications Technologies, Vol-220, pp. 98-108.
Springer Science and Business Media Deutschland GmbH
Samanta S., Department of Computer Science and Engineering, Cooch Behar Government Engineering College, West Bengal, Cooch Behar, India; Sen A.P., Department of Computer Science and Engineering, Cooch Behar Government Engineering College, West Bengal, Cooch Behar, India; Mukhopadhyay D., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Bangalore, India; De S., Department of Computer Science and Engineering, Cooch Behar Government Engineering College, West Bengal, Cooch Behar, India; Bhattacharyya S., VSB Technical University of Ostrava, Ostrava, Czech Republic, Algebra University, Zagreb, Croatia; Platos J., VSB Technical University of Ostrava, Ostrava, Czech Republic
alternatives; bioeconomics; biological substances; Biomolecules; biotechnology; demand and supply; environment; global market; manufacturer; marine biopolymers; natural resources; pharmaceutical manufacturing
The usage of synthetic polymers such as plastic is a much-debated topic across the globe for a reason; it is not recyclable and harms the environment. However, todays consumers have shifted their preferences to eco-friendly products over harmful products. The biopolymers market globally accounted for about $13.7 billion in 2021, and by 2030, its projected to reach over $35.2 billion, growing at 11.07% [compound annual growth rate (CAGR)]. By 2026, the marine biotechnology sector will be worth $5 billion worldwide. Despite the manufacturing cost of marine biopolymers being higher than that of standard polymers, the market is growing faster because of its benefits across various industries and mainly for stakeholders. The biopolymer industry has evolved due to the depletion of petroleum reservoirs. Key players from countries such as the United States, Brazil, Germany, Netherlands, Italy, United Kingdom, Japan, Germany, and Australia are in the biopolymers market. Different classes of marine biopolymers and their industrial applications prove the precious value of ocean resources to society. 2025 Elsevier Ltd. All rights reserved.
Halaswamy D.; Borehalli Mayegowda S.; Brijesh H.; Bheemappa M.
Marine Biopolymers: Processing, Functionality and Applications, pp. 989-1007.
Halaswamy D., School of Business and Management, CHRIST-Deemed to be University, Kengeri Campus, Karnataka, Bengaluru, India; Borehalli Mayegowda S., Department of Psychology, CHRIST-Deemed to be University, Kengeri Campus, Karnataka, Bengaluru, India; Brijesh H., Department of Biotechnology, School of Applied Sciences, REVA University, Karnataka, Bengaluru, India; Bheemappa M., Department of Biotechnology, School of Applied Sciences, REVA University, Karnataka, Bengaluru, India
Critical Analysis of MoS2-Based Systems for Textile Wastewater Treatment
Indiscriminate discharge of toxic organic contaminant-laden wastewater into water bodies is one of the major issues posing a risk to the environment in general and aquatic living systems in particular. Widely used textile dyes are ubiquitous in the effluents emanating from industries. Photocatalysts, due to their efficiency and eco-friendliness, can be effectively used to remove pollutant dyes from the water bodies. Molybdenum disulfide (MoS2), an emerging co-catalyst, has high photocatalytic activity, strong absorptivity, non-toxicity, and low cost; with a graphene-like structure, it offers functional features similar to graphene: high charge carrier transfer, strong wear resistance, and good mechanical strength. However, in aspects such as cost, abundance, versatile morphologies, and tunable band gap with efficient visible light absorption properties, MoS2 scores over graphene. The present chapter discusses the recent advances in nanostructured MoS2 materials for applications in environmental remediation. Special emphasis has been paid to MoS2 and MoS2-based systems for the photocatalytic degradation of various organic contaminants such as malachite green, methyl orange, rhodamine B, and methylene blue that find extensive use in the textile industry. As a result, MoS2 systems play an essential role in nanocomposites, especially in speeding up photo-induced electron transport and lowering electron recombination rates, making them desirable photocatalysts for the degradation of pollutants. The chapter focuses on addressing SDG 3 (Good Health and Wellbeing), SDG 6 (Clean Water and Sanitation), SDG 7 (Clean and Affordable Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), SDG 14 (Life Below Water), and SDG 15 (Life on Land). 2025 Moharana Choudhury, Ankur Rajpal, Srijan Goswami, Arghya Chakravorty and Vimala Raghavan.
Madhushree R.; Jose A.; Pinheiro D.; Sunaja Devi K.R.
Analytical Case Studies on Municipal and Biomedical Waste Management: Perspectives on Sustainable Development Goals, pp. 55-82.
Madhushree R., Department of Chemistry, Christ (Deemed to be University), Karnataka, Bangalore, 560029, India; Jose A., Molecular Medicine and Pathology, University of Auckland, Auckland, 1023, New Zealand; Pinheiro D., Department of Chemistry, Christ (Deemed to be University), Karnataka, Bangalore, 560029, India; Sunaja Devi K.R., Department of Chemistry, Christ (Deemed to be University), Karnataka, Bangalore, 560029, India
Impact of Multi-domain Features for EEG Based Epileptic Seizures Classification
Adaptive Boosting; Data Standardization; EEG; Epileptic Seizure; Frequency domain; Gaussian Nae Bayes; Machine Learning; Multi-domain Features; Time domain
Accurate detection and classification of epileptic seizures play a pivotal role in clinical diagnosis and treatment. This study introduces an innovative approach that leverages multi-domain features extracted from Electroencephalogram (EEG) data in conjunction with Supervised learning classification techniques. Initially, EEG data undergoes preprocessing through data standardization, followed by the extraction of essential features per instance, encompassing combination of Time domain, Frequency domain, and Time-Frequency domain features. These extracted feature combinations are subsequently fed into the machine learning-based boosting classifier Adaptive Boosting (ADABOOST) for an accurate and precise classification of epileptic signals. Validation of the proposed method is conducted using EEG data from the BEED (Bangalore EEG Epilepsy Dataset) and BONN (University of BONN, Germany) database to detect epileptic seizures. The experimental results show remarkably high levels of classification accuracy for various conditions: 99% accuracy for BEED data, 98% accuracy for BONN data for classifying seizures from healthy states, and 91% accuracy for classifying seizure onset from seizure events. Furthermore, the study applies the Gaussian Nae Bayes (GNB) classifier to differentiate various types of epileptic seizures, employing evaluation metrics such as the confusion matrix, ROC curve, and diverse performance measures. This method demonstrates significant potential in supporting experienced neurophysiologists decision in the clinical classification of epileptic seizure types. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Najmusseher; Banu P.K.N.; Azar A.T.; Kamal N.A.
Lecture Notes on Data Engineering and Communications Technologies, Vol-220, pp. 317-329.
Najmusseher, Department of Computer Science, CHRIST (Deemed to Be University) Central Campus, Karnataka, Bangalore, 560029, India; Banu P.K.N., Department of Computer Science, CHRIST (Deemed to Be University) Central Campus, Karnataka, Bangalore, 560029, India; Azar A.T., College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia, Faculty of Computers and Artificial Intelligence, Benha University, Benha, 13518, Egypt; Kamal N.A., Faculty of Engineering, Cairo University, Giza, Egypt