Browse Items (11810 total)
Sort by:
-
Identifying Wage Inequality in Indian Urban Informal Labour Market: A Gender Perspective
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. -
Enhancing Patient Safety and Efficiency in Intravenous Therapy: A Comprehensive Analysis of Smart Infusion Monitoring Systems
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. -
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. -
Bioinformatics applications for evaluating health and pharmacological properties of tea: Use of computer-assisted drug discovery tools
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. -
Marine microbial biopolymers and their applications
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. -
Climate Change Adaptation Strategies for Achieving Net-Zero Economy
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. -
2D Photonic Crystal Nano Biosensor with IoT Intelligence
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. -
Fluorescent carbon nanoparticle hybrids: synthesis, properties and applications
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. -
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. -
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. -
A Brief Review onDifferent Machine Learning-Based Intrusion Detection Systems
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. -
Economic aspects of marine biopolymers
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. -
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. -
Impact of Multi-domain Features for EEG Based Epileptic Seizures Classification
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. -
IoT-Enabled Analysis of COVID Data: Unveiling Insights from Temperature, Pulse Rate, and Oxygen Measurements
The COVID-19 pandemic has forced unparalleled transformation on healthcare systems around the world, demanding new and improved approaches for effective monitoring and diagnosis. In this context, we present a study titled IoT-Enabled Analysis of COVID Data: Unveiling Insights from Temperature, Pulse Rate, and Oxygen Measurements. The global impact of COVID-19, with millions of confirmed cases and fatalities, underscores the urgency of finding efficient monitoring solutions. To address this crisis, IoT-Enabled Health Monitoring Systems have emerged as a promising tool for remote patient monitoring and infection risk reduction. These systems leverage sensors to collect real-time data on the temperature, pulse rate, and oxygen saturation levels of the subject. The integration of a mobile application enables immediate access to this critical health information. In this study, we explore the use of IoT systems, which have demonstrated accuracy comparable to other devices on the market. By leveraging these technologies, we aim to provide healthcare professionals with valuable insights into patients health status, aiding in early detection, monitoring, and timely intervention. Our research contributes to the efforts to battle the COVID-19 pandemic by highlighting the potential of IoT-enabled monitoring systems in enhancing healthcare delivery, reducing infection risks, and ultimately saving lives. 2024 Scrivener Publishing LLC. -
Fluorescent carbon nanoparticles for catalytic and photocatalytic applications
In the present times, catalysis is ubiquitous in chemical processes. Catalysts range from macromolecules consisting of enzymes to nanoparticles, including metals/metal oxides and composite materials. Due to their harmlessness, biocompatibility, high stability, versatility, and ease of functionalization, carbon nanomaterials (CNMs) which are fluorescent in nature, are used extensively for catalytic applications. Several studies regarding the catalytic applications of CNMs have been reported. These applications range from homogeneous to heterogeneous catalysis, where CNMs are used as supports for metal/metal oxide nanoparticles. Extensive studies on nanocomposites, doping strategies, and their utility in catalysis have been carried out. Carbon-based electrocatalysts find applications in both storage and conservation of energy. The exceptional properties of these materials make them an apt choice for various environment-friendly organic transformations. Photocatalysis is another area in which CNMs have excelled. Photoluminescence, photostability, and electron transfer properties of CNMs make them potent candidates for several photoinduced reactions. Various CNMs, namely graphene, carbon dots, nanotubes, graphitic carbon nitride, fullerenes, and graphdiyne, find applications in medicine, catalysis, sensing, bioimaging, supercapacitors, and many more. This chapter focuses on the catalytic and photocatalytic applications of CNMs. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Nature of music engagement and its relation to resilient coping, optimism and fear of COVID-19
The COVID-19 pandemic has resulted in unprecedented lockdowns, a work from home culture, social distancing and other measures which badly affected the world populace.Individuals over the globe reported experiencing several psychosocial and psychosomatic problems.Nevertheless, this pandemic allowed us to be with ourselves, to understand the importance of healthy lifestyles and to devote time to our passions and hobbies when we were socially isolated.Against this background, the present study was undertaken to explore the nature of peoples everyday musical engagement and to examine how the experience and functions of music were related to resilient coping, life orientation and fear from COVID-19.In an online survey, a total of 197 participants responded to a questionnaire designed to assess the nature of musical engagement (level of musical training, functional niche of music, listening habits and involvement in musical activities), functions of music (FMS), resilient coping (BRCS), life orientation (LOT-R), and fear of COVID-19 (FCV-19S).Results indicate that for most of the respondents, music listening was a preferred activity during the pandemic which resulted in positive effects on their mood, heart rate and respiratory rates.More than 80 per cent of respondents reported music as a source of pleasure and enjoyment and claimed that it helped to calm them, release their stress, and help them relax.Significant positive correlations were found between the functions of music (memory-based and mood-based), optimism and resilient coping and mood-based functions of music and optimism were found to predict resilient coping among individuals.These results suggest that meaningful and active music engagement may lead to optimism which may result in effective resilient coping during the crisis.Moreover, reflecting upon our everyday musical engagements can promote music as a coping skill. 2025 selection and editorial matter, Asma Parveen and Rajesh Verma; individual chapters, the contributors. -
The Shame of Ageing During Fourth Industrial Revolution: A Thematic Analysis of Indian Adults
The Fourth Industrial Revolution (4IR), a term popularised by Klaus Schwab in 2016, connected the physical-biological and the digital world. This is an era of artificial intelligence and computational technologies suited to satiate the needs of the human race. The emphasis is also on a digital identity we have developed alongside our physical and psychological entities. Millennials and Gen Z have a cognizant grip on their digital identity and are known to use the fruits of 4IR in their everyday livelihood. However, with the advent of Industry 4.0, the generation of Baby Boomers and Gen X have had to undergo much re-learning and accommodate the newer ways of integrating digitalization in their lives. The process has brought about occupational threats and shaming related to failure to upgradation and flexibility. This article explores the influences of these social experiences on the identity and self-concept of the quinquagenarians and the sexagenarians. The article follows a qualitative method where using a thematic approach, the emerging themes from the in-depth interviews will be analyzed in detail to form a theoretical framework for shaming among the Indian Baby Boomers and Gen X. The variables in focus are adjustment, coping styles, resilience, the purpose of life, and Self-Image. The study explores the themes of Indian adults, which emerge from interviewing 46 participants, who have been associated with full-time employment and are between 77 and 59 years of age, representing the Baby Boomers, and those between 43 and 58 years of age, representing Gen X. The analysis adopts a psychoanalytic approach, where the data is interpreted using an Eriksonian lens. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Surface functionalized fluorescent carbon nanoparticles and their applications
Fluorescent carbon nanoparticles or carbon dots (CDs) are zero-dimensional nanomaterials embodying physicochemical characteristics appropriate for novel and improved applications in various disciplines. Tunable photoluminescence, photostability, small size, low cost, biocompatibility, etc., are some of the promising features of CDs. The CDs are usually composed of a graphitic core surrounded by shell layers containing various functional groups. Surface functionalization of CDs is known to customize, and regulate the properties of CDs, thereby proliferating their applications. A variety of physical and chemical methods have been used for the preparation of CDs with tailored surfaces. The choice of the synthetic strategy generally depends on the type of surface modification required and the fluorescence behavior expected. This chapter summarizes and discusses the existing strategies for preparing surface functionalized CDs and the resultant fluorescence phenomena. The surface functionalization of CDs can decisively influence their suitability in several applications. In some applications, surface functionalization improves the existing utility, while novel utilities are emerging in others. The influence of surface functionalities of CDs on biomedical and catalytic applications has been discussed in detail in this chapter. CDs have emerged as a promising material for enhancing the performance, sustainability, and safety of various energy storage devices like batteries, supercapacitors etc. Continued research and development in this area could lead to the realization of more efficient and environmentally friendly energy storage solutions. The chapter concludes by discussing the challenges in synthesizing surface functionalized CDs and their acceptability in biomedical and industrial applications. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Comprehensive Data Analysis of Anticorrosion, Antifouling Agents, and the Efficiency of Corrosion Inhibitors in CO2 Pipelines
This study explores the various methods that are being proposed for their anticorrosion and antifouling capabilities and also reviews the unique properties that make them suitable for such applications. Special attention has also been given to the problem of corrosion in CO2 pipelines, considering the corrosion inhibitors currently being used and performing statistical analysis about if and how various factors such as temperature, flow velocity, pH, and CO2 pressure affect the rate of corrosion of the CO2 pipelines. Tests including ANOVA, correlation, and graph analyses were conducted to explore their relationships, and suitable conclusions were drawn for the data collected. 2024 Scrivener Publishing LLC.