Browse Items (16488 total)
Sort by:
-
Raman spectroscopy: an introduction, instrumentation, and its applications in polymer composites and nanocomposites
Raman spectroscopy, a nondestructive technique based on molecular vibrations, offers insights into molecular structures and interactions through the inelastic scattering of monochromatic light. This method facilitates the identification of chemicals by using unique molecular fingerprints. The ability of this technique to analyze samples in situ, in any form, is very advantageous. Over the years, improvements have been made in the sensitivity and resolution of Raman spectroscopy in instrumentation and data analysis, which has broadened its range of applications in chemistry, biology, and materials research. Raman spectroscopy has become a vital tool for applied research and basic sciences. In the area of composites and nanocomposites, it offers tremendous possibilities, such as material identification, phase separation, and defect analysis, reinforcement agent characterization, stress and strain analysis, crystallinity and orientation, and micromechanical deformation. 2026 Elsevier Ltd. All rights reserved. -
Blockchain Technology: Proof of Work vs Proof of Stake Consensus Mechanism
The purpose of blockchain technology is to record transactions after they have been confirmed. Blockchain?s ability to guarantee decentralized, transparent transactions with solid security has increased the appeal of new virtual currencies. The consensus mechanism, one of the key components of a blockchain network?s operation, plays a crucial role in a decentralized system. The debate surrounding an adequate consensus method has attracted significant attention, particularly in comparing Proof of Work (PoW) and Proof of Stake (PoS). This chapter comprehensively examines the Proof of Work (PoW) and Proof of Stake (PoS) algorithms and compares other consensus algorithms utilized in contemporary blockchain systems. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Business Resilience
Business resilience has emerged as one of the key elements for ensuring the survival and success of the organization in the 21st century which has been marked by socio-economic crisis, notable disruptions, and tumultuous market shifts. The term Business resilience is defined as the capacity of an organization to navigate through adversity, adapt to changing conditions, and emerge stronger from setbacks. Financial, operational, organizational, digital, and supply chain resilience are among the measures that resilient organizations invest on. Companies that are financially strong put careful money management first and protect shareholders wealth. Organizational resilience promotes flexibility and ongoing learning, whereas operational resilience guarantees the continuation of vital business operations. While supply chain resilience concentrates on minimizing disruptions, digital resilience entails strong cybersecurity measures. Effective leadership is essential for managing uncertainty, and a flexible strategy for enhancing resilience guarantees continuous adjustment. In the end, corporate resilience is about overcoming hardship and integrating resilience as a strategic requirement for sustained success in a changing business climate. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Movie-Induced Tour Guiding: Concepts and Future Implications in South Asian Perspective
Movies have an extensive impact on tourism and its promotion. Movie-induced tourism has been a worldwide phenomenon for the last couple of decades, but this phenomenon is confined to the marketing and promotion of tourism destinations. Here, a new approach has been introduced for co-creating a quality destination experience through traditional tour guiding. Considering the increasing emphasis on tourists experience, satisfaction, and destination imagery over the decades, this concept of movie-induced tour guiding will produce a synergistic value in the overall process of the outdoor leisure tour packages. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Digital Content Marketing
Digital Content Marketing (DCM) is the strategic creation and distribution of relevant brand-related content on digital platforms, aiming to foster favorable brand engagement, trust, and relationships with current or potential customers. Despite its widespread use in practice, academic research on DCM is limited, creating a significant knowledge gap. This study addresses this gap by conducting an exploratory research synthesis of DCM literature from 2008 to 2024. The primary objective is to provide a comprehensive overview of pertinent studies and create a conceptual integration that elucidates DCM?s impact on marketing practices. Utilizing a targeted search on the Web of Science Database, 15 published papers were identified and analyzed based on specified search criteria. The findings contribute to a more holistic understanding of DCM?s role as a prevalent trend in contemporary marketing practices. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Sustainability Reporting
Today, with the increased awareness among the various stakeholders, the success and growth of companies are not gauged by their financial performance but by the impact of their business operation on the environment and society. Companies are under immense pressure from different stakeholders to undertake sustainability practices and publish sustainability reports. Due to this, sustainability reporting has transformed from a voluntary exercise to a strategic imperative for companies. This chapter aims to explain the concept of sustainability reporting (SR), various drivers, and its benefits for the various stakeholders. It also provides a brief overview of the evolution of the notion of SR and the discourse of voluntary versus mandatory approach to SR. Further, this chapter discusses prominent global SR guidelines, frameworks, and challenges in the adoption of sustainability reporting practices. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Ethical Sourcing
In an era where sustainable development is a celebrated concept, the notion of ethical sourcing has been explored comprehensively as companies are making a conscious and sustainable effort to gauge their supply chains and examine the sources of procurement of their material and services. This chapter delves deeper into the importance of ethical sourcing, focusing on its benefits and fundamental needs. It also talks about why ethical sourcing is an essential concept in corporate realms, drawing a distinction between sustainable and ethical sourcing. Today, ethical sourcing can be an important tool in the hands of corporations to draw a competitive edge and there would be serious repercussions of indulging in unethical practices. Further, it discusses key principles that act as a beacon of light for sourcing the material ethically, the three levels of ethical sourcing, and how technology can be leveraged to ensure the same. It is crucial to have partnerships and collaborations for sustainable procurement along with robust mechanisms to measure the impact of ethical sourcing. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Emergency response to natural disaster victim identification: Blockchain to the rescue
Rapid, coordinated action by various stakeholders is required to respond effectively to a natural disaster. Suffice it; such efficiency has been missing in many previous rescue attempts. Is blockchain capable of making this happen? The Disaster Victim Identification (DVI) process is a sophisticated operation in which post-mortem (PM) identifying data, including fingerprints, DNA, and dental records, are acquired and matched with antemortem (AM) data from the missing people list. Although there are solutions to human identification, they must provide the tools required to achieve human identification promptly. Blockchain technology is one of the technologies that has gained much attention recently and is undergoing heavy media operations. It creates trustworthy, secure, and comprehensive ecosystems by disseminating siloed AM and PM data across systems, preventing breaches, redundancies, inconsistencies, and errors. Using real-world scenarios, the authors present several good use cases in this chapter to gain a holistic understanding of the challenges and how blockchain technology addresses such challenges and facilitates multi-jurisdictional data information sharing in conjunction with the upcoming distribution of patients electronic medical and dental records. 2025 Elsevier Inc. All rights reserved. -
Optimization procedure for multilayer heat transfer in nanoliquid with Joule heating using response surface methodology
In this chapter, magnetohydrodynamic flow (MHD) and heat transfer in a multilayer vertical channel are studied with one phase containing pure water and the other phase containing oil-based Cu nanofluid. The effects of viscous dissipation and Joule heating are included in the energy equation. The modeled equations are coupled and nonlinear; they are solved using the regular perturbation method (RPM) and the differential transform method (DTM). The analysis examines the impact of the Hartmann number, thermal Grashof number, nanoparticle volume fraction (NVF), and Brinkman number on the Nusselt number, velocity, and temperature distributions. Furthermore, an optimization of the Nusselt number is performed for three different levels of the Hartmann number (5?M?6), the Brinkman number (0.1?Br?0.3), and the NVF (1%???3%) using the Response Surface Methodology (RSM). The Hartmann number and NVF were found to suppress flow, while the thermal Grashof number and the Brinkman number increase the flow field. Sensitivity computations reveal that the Nusselt number on the left wall is more sensitive to the Hartmann number and the NVF, while the Nusselt number of the right wall is more sensitive to the Brinkman number and NVF. 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Simulation and multiscale modeling of carbon nanomaterials
Carbon nanomaterials have become more and more significant for simulation and multiscale modeling due to their distinctive features and prospective uses in a variety of disciplines. We give a thorough computational analysis of the electrical, mechanical, and thermal characteristics of carbon nanotubes, graphene, and fullerenes in this chapter. Our simulations combine classical and quantum mechanical techniques, such as density functional theory and molecular dynamics. We are able to bridge the gap between atomistic simulations and macroscopic behavior thanks to our multiscale modeling technique, which offers important insights into the behavior of carbon nanomaterials at various length and time scales. For the creation and advancement of novel nanomaterials for diverse applications, our findings offer a basic knowledge of the characteristics of carbon nanomaterials. 2025 Elsevier Inc. All rights reserved. -
Synthesis of carbon nanomaterials from vegetables
This chapter looks into new horizons of sustainable nanotechnology developed through innovative carbocentrism that focuses on the development of carbon based nanomaterials from different categories of vegetables. This chapter is centered on the green synthesis of vegetable-derived sweet potato, garlic, lemon, and radish into carbon dots (CDs), graphene sheets, and carbon quantum dots through hydrothermal and aqueous extraction methods. To surpass traditional methods of nanomaterial synthesis, researchers are developing vegetable-derived nanomaterials that possess unique properties such as fluorescence and ranging surface functionalities. Such practices are recommended for reducing environmentally hazardous substances while upholding important eco-friendly principles and sustainable accountable nanotechnology. These methodologies address the misuse of dangerous substances and provides effective eco friendly approaches which emphasizenew direction towards sustainable nanotechnology. The versatility of these vegetable-derived carbon nanomaterials is evident in their applications, spanning from biomedical fields, such as drug delivery and bioimaging to environmental monitoring, particularly in the selective detection of metal ions. The advancements of medical technology are much needed in society today that is being more particular about green approaches and innovations. This willthe help low toxic and biocompatible nanomaterials live up to their full potential for eco-friendly biomedical technologies. This chapter serves as a comprehensive exploration of the synthesis, applications, and broader implications of carbon nanomaterials from vegetables, providing valuable insights into the evolving landscape of green nanotechnology. 2025 Elsevier Inc. All rights reserved. -
Characterization and properties of plant extract-derived nanostructured carbon materials
The remarkable features of carbon nanomaterials, which include graphene, fullerenes, carbon nanotubes (CNTs), and carbon nanofibers, have elevated them to the forefront of material science study. These nanoparticles are very desirable for a variety of applications, such as electronics, energy storage, composites, and biomedical devices, due to their exceptional mechanical, electrical, thermal, and chemical properties. This chapter offers a thorough rundown of the essential characteristics and cutting-edge methods for characterizing carbon nanomaterials. We examine the inherent qualities of several carbon nanostructures, emphasizing their surface chemistry, electrical and thermal conductivity, and mechanical strength. Every one of these characteristics is essential for figuring out whether carbon nanoparticles are appropriate for a given application. The chapter also covers cutting-edge characterization methods that are crucial for assessing the caliber and characteristics of carbon nanomaterials. AFM, X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), scanning electron microscopy (SEM), and other spectroscopic techniques are covered in detail. These methods offer vital information on the shape, composition, purity, density of defects, and electrical characteristics of carbon nanomaterials. 2025 Elsevier Inc. All rights reserved. -
Synthesis methods of nanostructured carbon materials
One of the most crucial factors in the synthesis of carbon nanomaterials is the choice of synthesis method. Since the synthesis process is heavily reliant on the particle size and molecular structure, it has a significant impact on the final properties of the nanoparticles. The top-down and bottom-up approaches are the two primary approaches. In contrast to the top-down method, which breaks down larger carbon sources like graphite or bulk carbon materials into nanoscale structures, the bottom-up method uses a variety of chemical reactions, including dehydration, carbonization, polymerization, and other irreversible chemical reactions, to create nanoparticles. In this chapter, the various top-down and bottom-up synthesis routes are covered, along with their effects on the physico-chemical characteristics of carbon nanomaterials. 2025 Elsevier Inc. All rights reserved. -
Advanced Machine Learning Model for Optimizing Pricing Strategies for Logistic Firms
Cost optimization in logistics is a very crucial aspect for businesses to remain profitable and competitive by identifying and eliminating unnecessary costs. Most of the researchers concentrated primarily on demand modeling, vehicle routing challenges, and warehouse cost optimization, hence the existing models underperform. This study introduces a novel prediction model that optimizes costs by considering critical factors such as labor charges, material costs, transportation expenses, task types, and branch location. The current model is worked on a primary dataset of 2468 rows and 28 columns which was obtained from an established relocation company in India with all the confidentiality followed. To improve model performance, the required features were adjusted by rigorous feature engineering and data pretreatment techniques such as box-cox scaling, Winsorization, robust scaling, and one-hot encoding. Three ensemble learning techniques were tested: AdaBoost, XGBoost, and gradient boosting. The gradient boosting model correctly captured the complicated nonlinear connections between cost components and income, enabling for cost optimization decisions across a wide range of operational conditions. The proposed model has shown excellent results with the values achieving an MSE of 15% which demonstrates the effectiveness in cost optimization. However, the presence of residuals and potential outliers suggests that more model refinement and process improvements are required. The studys findings offer a data-driven framework for logistics and relocation companies to reduce costs, boost profitability, and gain a competitive advantage in the marketplace. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Using Document Similarity Algorithms for Suicidal Detection in Social Media: A Case Study of User Tweets
Suicidal detection and treatment from the clinical and public health perspective are reactive. For an action whose consequences are irreversible, a reactive approach to the problem cannot be the answer. A proactive approach is needed to solve and detect suicidal intent. Social media has become the television and diary of millennials and Gen z alike; hence, it is imperative to create techniques and approaches to study their actions in this particular space. This research involved creating document similarity algorithms from Corpora mined from the Twitter Developer API. Making the data unique to this platform, a methodology design involving validating data at various spectrum and selecting an appropriate threshold to classify the similarity levels were created as well as a lexicon unique to the Twitter Dataset. With an accuracy score of 84%, the Jaccard document similarity algorithm was able to spot suicidal intent from users tweets, and with an accuracy of 93%, it was also able to spot non-suicidal intent. The Jaccard model seemed to be the most durable and computationally efficient for the problem and was chosen as the algorithm for detecting suicidal tendencies in users tweets. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Tackling Malnutrition Among Children in India: The Role of National Health Policies
Child malnutrition in India is a significant public health concern. While there has been progress in reducing stunting, wasting, and underweight rates among children, the prevalence of malnutrition remains high, especially with a recent increase in childhood anaemia. It is essential to implement effective national health policies and programmes to address this issue. Initiatives such as the Integrated Child Development Services (ICDS), the Mid-Day Meal Scheme (MDMS), and the National Health Policy 2017 play a pivotal role in enhancing nutritional and health outcomes for children. However, challenges such as inadequate infrastructure, socio-economic disparities, and a lack of parental education and awareness hinder the effectiveness of these programmes. Misconceptions about nutrition and child-feeding practices among mothers are also significant contributors to malnutrition. This chapter aims to explore the potential of national health policies in combating child malnutrition in India and addressing the role they play in improving childrens nutritional status. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
The paradox of sex: A thematic analysis of identity among indian cis-gendered female asexuals
Asexuality is the absence of sexual attraction to others or a low desire for sexual activity. In the collectivistic culture of India, the lack of sexual relations after marriage is judged from a lens of "normalcy." Asexuality is often an invisible spectrum among the queer population and usually does not get the desired attention. Individuals who identify as asexuals may not always be opposed to romantic relationships. However, the heteronomative pressures of adhering to approved social roles for romantic partners may affect them. The study aims to understand the different sources of coercion and constraints in romantic relationships experienced by individuals who identify as asexuals through in-depth interviews. The interviews tap into the mental health of asexual women in a heteronormative society. The variables in focus are coping styles, beliefs, self-image, social attitude, and relationship dynamics. The study follows a thematic approach where the emerging themes from the in-depth interviews will be analyzed in detail to form a theoretical framework to explain the heteronormative pressures on asexual women. The findings will be examined from a feminist perspective, considering the equality of all genders and sexual expressions. The findings are also analyzed using Kristeva's concept of abjection, to explore asexuality as an "abject" in a collectivistic society. Asexuality is thus seen as deviant and worthy of separation from "normal sexual expression" in a society that has conflicting opinions about sex and sexuality. Springer Nature Singapore Pte Ltd. 2025. All rights reserved. -
Effectiveness of relationship education programs for premarital romantic and sexual relationships for adolescents and young adults: A systematic review
Relationship Education Programs (REPs) have gained significant attention in recent years in Western cultures as a preventative approach to promoting healthy romantic and sexual relationships. These programs aim to provide individuals with the knowledge and skills necessary to build and maintain positive romantic and sexual relationships, and to reduce negative societal outcomes such as teenage pregnancy and single-parent households. This systematic review will provide a comprehensive analysis of the current literature on relationship education programs for pre-marital romantic and sexual relationships in terms of their effectiveness, various formats in which they are delivered, and outcome variables being studied. The findings show that the outcomes could be divided into seven categories: self improvement, knowledge acquisition, attitudinal changes, behavioral changes, psychological impacts, skill development, and changes in relational dynamics. It has been demonstrated that REPs are effective in knowledge and skill transfer for romantic relationships. Effectiveness testing was done using quasi-experimental designs, experimental studies with a control group, or randomized control trials. Most of the REP research was conducted in the USA; very few studies were obtained from other parts of the world. The effectiveness of REP, program characteristics, testing, gender differences etc. are also discussed. Springer Nature Singapore Pte Ltd. 2025. All rights reserved. -
Blockchain and IoT Integration for Financial Sector Revolution
The Industrial Internet of Things (IoT) is transforming the globe. Industrial Internet of Things (IIoT) speaks about the use of Internet of Things (IoT) concepts and technology in industrial environments. The financial industry has long traded in the things that areintangible, from once-tangible but now-less-tangible items like stock certificates and even money itself. The Internet of Things (IoT) and blockchain technologythat offer and storedata aboutthings mighthave direct influence on how financial services institutions operate their businesses. The Financial Industry is adopting IoT for fast and effective transactions. The invention of disruptive technology like blockchain, which is a decentralized, unchangeable ledger makes tracking assets and record transactions easier. Decentralized Finance (DeFi) is based on the peer-to-peer idea that eliminates intermediaries from the system. It is possible to establish smart contracts, which will do away with the need for any middlemen. Due to the IoTs broad application and dispersed nature, security and privacy are the primary concerns in the financial sector. Blockchain is essential for IoT applications where data security and privacy are top priorities. Blockchain can secure data and keep the transactions private. IoT enhances business opportunities and offers firms a competitive edge in both established and developing industries. It has an impact on every aspect of technology, including the methods used to gather data and the locations, timings, and purposes for doing so. Since this data must be safeguarded, we need a standard blockchain-oriented architecture for IoT applications. The data generated by the financial industry is crucial because it establishes future market trends and preserves data on consumer and investor investments. Financial data is vulnerable to assaults and needs to be protected. This paper explores the need for regulations and policy in this area and attempts to understand how blockchain technology can be used to overcome barriers to IoT adoption in the financial sector. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Role of the Functionalized Carbon Nanotubes in Nanodiagnostic Devices and Nanobiomedicines
Carbon nanotubes (CNTs) have gained immense attention and have emerged as an instrumental tool in various applications including electrochemical sensing, biomedical applications, water purification, and biofuel cells. Their heightened utilization is attributed to their unique properties, such as high specific surface area, enzyme loading capacity, biocompatibility, mass transfer resistance, ease in crossing biological barriers, and ease of functionalization and immobilization. Possessing all these characteristics improves their applicability in biomedical applications including diagnosis, imaging, nanobiomedicine, and drug delivery. The functionalization of CNTs is highly crucial as it improves their biocompatibility and overcomes their limitation of insolubility in water and organic solvents. Functionalization also transforms them into more complex and effective drug delivery and biosensing tools with enormous and specific biomedical properties. This chapter provides a comprehensive discussion of the various structural and chemical properties, types, and synthesis strategies of CNTs. It also gives an insight into the kinds of functionalization for ameliorating their properties and comprehensively discusses their applications in nanodiagnostic devices and nanobiomedicine, ensuring the audience feels informed and knowledgeable. Springer Nature Singapore Pte Ltd. 2025.