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Narratives of Substance Users in Rehabilitation Centers: Exploring Usage, Identity, and Recovery
Addiction and Substance use are complicated issues that have a significant impact on a persons identity and social interactions. To gain a thorough understanding of identity construction and the recovery process, this study aimed to investigate the narratives of substance users in the rehabilitation center. Using a qualitative approach, semi-structured interviews were conducted with 11 participants selected through purposive sampling at a rehabilitation center in Delhi. The data was analyzed using Catherine Riessmans Narrative Analysis. Seven core narratives emerged: Substance as the Main Character, Substance as Air, Nostalgia over Lost Life, Confronting the Reality, Oscillating Recovery, Coexistence of Hope and Despair, and Push and Pull of Support. These narratives illustrate the multifaceted nature of addiction, where substances are not merely consumed but become central to identity, daily existence, and interpersonal relationships. The findings provide insights into the complexities of substance use and recovery by highlighting the constant oscillation between hope and despair in the recovery journey, as well as the ambivalent nature of family and society. The study concludes that substance use cannot be understood solely as a disorder. It often becomes intertwined with an individuals life and narrative. A holistic and humanized approach is necessary to address the personal, familial, and societal factors that influence addiction and recovery. The Author(s), under exclusive licence to Springer Nature India Private Limited 2025. -
Narratives of the self: Comments and confessions on Facebook
Narratives are structured around events, which are used to tell a story. The self is perpetually being constructed through narratives of experience. This chapter focuses on the phenomenon of Facebook confession pages and how they contribute to the construction of digital identity. Drawing on insights from my project on the role of Facebook College Confession pages, the chapter examines how these platforms have transformed the way users express and shape their identities. The anonymity provided by these pages allows users to post confessions without revealing their identities, encouraging a form of virtual self-exploration. These confessions, often written by nameless authors, generate a complex and ongoing narrative of identity, shaped by the interaction of multiple voices and viewpoints. The chapter also explores the motivations behind sharing personal confessions, even when the responses may be negative, and how this contributes to the perpetual construction of the digital self. By examining the intersection of public and private spheres in these online spaces, this chapter highlights how the breaking of the public-private divide enables users to create and negotiate their identities in a digital, networked world. The narrative constructed is endless, and the post is not an end in itself. It paves the way for the generation of an endless narrative by multiple authors with multiple viewpoints. This chapter explores the reasons behind sharing such posts on Facebook, even if the comments are negative in tone. It will refer to Anthony Giddens' concept of time-space "distanciation" (Keefer et al., 2019) to show how multiple tellers through their narratives help to build the complex networked identity of a user. The study will also analyse the role played by the breaking of the public-private divide in creating such spaces for the construction of a private self through public voices. 2024 Rimi Nandy. -
Narratives on using critical approaches in teacher education
Using the approach of autoethnographic narrative, three teacher educators from a cosmopolitan city in South India discuss how they use critical approaches in preparing preservice teachers and educational psychologists in the courses that they teach at a private university. The students are sensitized about the marginalized and the privileged sections in a multicultural and multilingual nation as India and to become culturally responsive in their classrooms or with their clientele in terms of their dispositions, knowledge, and skills. The chapter also describes the integration of critical approaches in the doctoral program aimed at addressing educational disparities and promoting social justice in education. 2024, IGI Global. All rights reserved. -
Narrativising chaos via narrative agency: COVID-19 comics as narrative meta-control
The initial COVID-19 pandemic phase was a period of chaos, instability, and disorder. In this context, this paper explores the narrative potentialities of COVID-19 comics as a means of narrative meta-control over the chaotic nature of the lived pandemic experiences. Meta-control, the act of regaining a sense of agency over a contingent circumstance that is otherwise uncontrollable, offers narrative agency as a means of navigating meaning-making and the reality of chaos. In this paper, This Quarantine Life: A COVID-19 Era Comics Anthology (2020), a global anthology brought forth by the New York Arts Students League, is analysed as a chaos narrative. Interrogating normative understandings of chaos narratives, the paper reframes these comics as spaces of and for narrative resistance, where aesthetic form functions as narrative repair by interrogating its acts of meta-control. Interweaving both conceptual reframing and multimodal discourse analysis, this paper shows how comic artists use narrative strategies of braiding, arthrology, and spatio-topia to work with chaos. In working with chaos, such strategies affirm comics as a narrative agent that helps capture and work through the reality of chaos. This study furthers contemporary concerns with graphic medicine about the practicalities of narrative agency in comics in a post-COVID-19 reality. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Narrativity and the Problematics of Authenticity in Hungry Ghosts by Kevin Jared Hosein
Postcolonial historical fictions, set in turbulent times, grapple with the question of authenticity in their fictional representations of events and individuals of the past. Trinidadian novelist Kevin Jared Hoseins Hungry Ghosts (2023), set in the estate barracks and surrounding milieu of 1940s Trinidad, is no exception. The paper argues for a nuanced understanding of the term authenticity in our reading of historical fictions, and explores Hoseins use of the formal, imaginative and affective dimensions of narration in negotiating representational adequacy and strengthening the significant thematic concerns in the text. Through textual analysis, the paper explores how Hosein situates his text firmly within the spatio-temporal reality of the period and captures the struggles of becoming confronting a population whose lives are coloured by historical trauma and continuing spatial hierarchy. 2024 The Editorial Board, Current Writing. -
Narrowband and Wideband Directional Beamformer with Reduced Side Lobe Level
In this paper, the synthesis of narrow and wideband beamformers with reduced side lobe level and wide beam steering capability is presented. A closed form expression with slope equalization technique is derived for array factor of the beamformer to meet the desired beam-pattern specifications of Half Power Beam-Width (HPBW)and Side Lobe Level (SLL). The proposed beamformer design is adaptable to any bandwidth and null placement in the desired direction. The slope equalization method improves the SLL of the beamformer. Compared to Kaiser, Chebyshev, DPSS and Taylor beamformers, the proposed narrowband and wideband beamformers exhibit lower and tapered side lobes, hence improved First Null to Last Null (FNLN)ratio. The proposed wideband beamformer exhibits superior performance in the wideband frequency range of 1-3GHz. 2019 IEEE. -
Natech guide words: A new approach to assess and manage natech risk to ensure business continuity
The risk posed by natural hazards to the technological systems is known as Natech risk. It is different from the more widely known and studied risk posed by such sites to the environment and society. Though currently, available risk assessment techniques recognize Natech, the specific qualitative technique for Natech risk assessment and reduction has not yet been developed. After analyzing past data of Natech accidents, relevant guide words have been suggested in this study. These guide words will help anticipate Natech risk and visualize the Natech scenario. Once the Natech risk is identified, corresponding risk reduction measures can be taken to avoid possible Natech accidents and consequences. 2021 Elsevier Ltd -
National cinema in India: exploring myths and realities
[No abstract available] -
National Development through women empowerment
International Journal of Physical and Social Sciences Vol.3, Issue 3, pp.77-89 -
National Education Policy 2020: Equity and inclusion in India's education system
The term "equity" in education refers to justice and fairness in the allocation of educational resources and opportunities. In order to achieve educational equity, it is necessary to remove the structural obstacles that prevent students from realizing their full potential. Obstacles like socioeconomic inequalities, prejudice, and unequal resource distribution often act as barriers to quality education. In this background, the present chapter will critically analyze a few significant opportunities offered by the New Education Policy 2020, such as three language formulas, privatization, NEP financing, special education zones policy implications, and challenges in implementation. Even though the opportunities and milestones offered by NEP 2020 are irrefutable, apprehensions pertaining to its scope and usefulness also exist, questioning the sanguinity of the policy. 2024, IGI Global. All rights reserved. -
Natural biotic polymer bombyx mori silk fibroin for gold nanoparticles: Fabrication, characterisations and application as colorimetric ammonia detection
Gold nanoparticles (AuNPs) were fabricated using a cost-effective and environmentally benign method, using silk fibroin (SF) as a stabilizing and reducing agent. As a natural, renewable protein polymer, silk fibroin can reduce and stabilize material as well as provide shape-tailoring agent. This resulted bio-polymer with gold nanoparticles was biodegradable, biocompatible, and very stable. Au ions are proficiently reduced to neutral Au atoms by silk fibroin, which governs the size, shape, and distribution of the nanoparticles and, consequently, their optical characteristics. The fabricated nanoparticles are very well characterized using a set of advanced analytical techniques that include UV-Vis Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Transmission Electron Microscopy (TEM), and Fluorescence Spectroscopy (FL). The sensing performance of ammonia in aqueous ammonia using the SF-AuNPs is presented herein based on an optical sensing approach utilizing surface plasmon resonance (SPR). It is obvious from the results that the materials synthesized have exhibited some unique plasmonic properties due to the interaction between silk fibroin and gold surfaces, hence enhanced sensitivity in colorimetric detection. The AuNPs acted as an ammonia optical sensor with a detected limit of about 1 parts per billion (ppb), very outstanding performance. Ammonia and AuNPs interact to cause a change in their surface plasmon resonance simple rapid and low-cost to realize, eco-friendly, and can find applications towards environmental monitoring and biomedical research fields for ammonia detection. 2026 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Natural convection of a binary liquid in cylindrical porous annuli/rectangular porous enclosures with cross-diffusion effects under local thermal non-equilibrium state
The present article reports an analytical study of the double diffusive natural convection (DDNC) in cylindrical porous annuli (CPA) and rectangular porous enclosures (RPE), which are handled in a unified way using the curvature parameter, saturated by a binary liquid under the assumption of local thermal non-equilibrium (LTNE) state. The buoyancy forces (thermal and solutal) driving the flow are assumed to be induced by the maintenance of constant and uniform heat and mass fluxes applied along the vertical (radial) walls and insulation of both horizontal walls of the annuli/rectangular enclosures. The Darcy-Boussinesq equations with LTNE assumption between the fluid and solid phases are employed to model the problem of DDNC in a binary liquid-saturated porous medium with cross-diffusion effects. The analytical results are obtained by employing the Oseen-linearization transformation technique in the study. The influence of various dimensionless parameters on heat and mass transports of the system are depicted using the Nusselt and Sherwood numbers and isotherms plots, and the obtained results are analysed with the physical explanation. Special attention is given to understand the effect of LTNE parameter and cross-diffusion parameters on heat and mass transports of the system. Different aspect ratio values are chosen to obtain the results of three types of CPA/RPE (shallow, square and tall). Among these CPA/RPE, maximum and minimum heat and mass transports are achieved in the cases of shallow and tall CPA/RPE, respectively. The results of the pure thermal convection problem is obtained at the zero value of buoyancy ratio and solute Rayleigh number. The increasing value of N magnifies the heat and mass transports in the system due to the augmented buoyancy effect resulted from the thermal and solutal gradients. The increase of solid inner cylinder radius, by fixing its volume, makes the annulus slender which yields to decrease the heat and mass transports in the system. The effects of LTNE parameter and cross-diffusion parameters on heat and mass transports of the system are clearly brought out. The results of LTE model are obtained at the infinite value of ratio of porosity modified thermal conductivities, ?, as a particular case of the present model. From the study, we conclude that the shallow porous annulus and tall rectangular enclosure are best suited in the design of heat removal and heat storage systems, respectively. 2021 -
Natural convection of water-copper nanoliquids confined in low-porosity cylindrical annuli
Natural convection in cylindrical porous annuli saturated by a nanoliquid whose inner and outer vertical radial walls are respectively subjected to uniform heat and mass influxes and out fluxes is studied analytically using the modified Buongiorno-Darcy model (MBDM) and the Oseen-linearization technique. Nanoliquid-saturated porous medium made up of water as base liquid, copper nanoparticles of five different shapes, viz., spheres, bricks, cylinders, platelets and blades, and glass balls porous material is considered as working medium for investigation. The thermophysical properties of nanoliquid -saturated porous medium is modeled using phenomenological laws and mixture theory. The effect of various parameters and individual effects of five different shapes of copper nanoparticles on velocity, temperature and heat transport are found. From the study, it is clear that the addition of a dilute concentration of nanoparticles increases the effective thermal conductivity of the system and thereby increases the velocity and the heat transport, and decreases the temperature. In other words, the heat transport is more in the case of heat and mass driven convection compared to purely heat-driven convection. Among the five different shapes of nanoparticles, blade-shaped nanoparticles facilitate the transport of maximum temperature compared to all other shapes. Maximum heat transport is achieved in a shallow cylindrical annulus compared to square and tall circular annuli. The increase of the inner solid cylinder's radius is to decrease heat transport. The results of the KVL single-phase model are obtained from the present study by setting to zero the value of the nanoparticles concentration Rayleigh number. Also, neglecting the curvature effect in the present problem, we obtain the results of the rectangular enclosure problem. 2020 The Physical Society of the Republic of China (Taiwan) -
Natural Disaster Prediction by Using Image Based Deep Learning and Machine Learning
In recent years, diseases and disaster have become more unpredictable. The advent of technology has not only making our lives easier but also technology-dependent. Nevertheless, the natural disasters cause great adversity by disrupting considerable human lives. Also, the disasters obstruct and affect many industries and services either directly or indirectly. Hence, it is necessary to study and observe data patterns and warning signs that lead to a natural disaster, its potential risk and its ability to resolve management strategies, which can be implemented immediately to minimize the socio-economic loss. This article reviews the state-of-the-art research works and findings through a technological perspective on data analysis, natural disaster prediction, and the utilization of technology for deploying management strategy. Also, this paper focuses on investigating the today's Industry 4.0 that utilizes cognitive computing. The primary aim of this article is to review the research ideas that leverage big data and data mining to observe and track patterns, which can impelment predictive analysis to anticipate the forthcoming disasters. Furthermore, this research work analyzed the posed predictive models by specifically using ANN (Artificial Neural Networks), sentiment model, and smart disaster prediction application (SDPA) to predict the flash flood. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Natural Language Processing (NLP) in chatbot design: NLP's impact on chatbot architecture
The creation and development of chatbots, which are the prevalent manifestations of artificial intelligence (AI) and machine learning (ML) technologies in today's digital world, are built on Natural Language Processing (NLP), which serves as a cornerstone in the process. This chapter investigates the significant part that natural language processing (NLP) plays in determining the development and effectiveness of chatbots, beginning with their beginnings as personal virtual assistants and continuing through their seamless incorporation into messaging platforms and smart home gadgets. The study delves into the technological complexities and emphasizes the problems and improvements in natural language processing (NLP) algorithms and understanding (NLU) systems. These systems are essential in enabling chatbots to grasp context, decode user intent, and provide replies that are contextually appropriate in real time. In spite of the substantial progress that has been made, chatbots continue to struggle with constraints. 2024, IGI Global. All rights reserved. -
Natural Language Processing and Information Retrieval: Principles and Applications
This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining. Features: Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation. Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data. Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining. Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing. Covers latest datasets for natural language processing and information retrieval for social media like Twitter. The text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. 2024 selection and editorial matter, Muskan Garg, Sandeep Kumar and Abdul Khader Jilani Saudagar chapters. -
Natural Language Processing in Medical Applications
Medical applications of machine learning are very new, and there are still several obstacles that limit their widespread use. There is still a need to address issues like high dimensionality data and a lack of a standard data schema. An intriguing way to explore the possibilities of machine learning in healthcare is to apply it to the difficult problem of cardiovascular disease diagnosis. At the present day, cardiovascular disorders account for the majority of deaths worldwide. It is often too late to adopt appropriate treatment for many of them because they progress for a long time without showing any symptoms. Because of this, its crucial to get checked up on routinely so that any developing diseases can be caught early. If the sickness is caught early enough, effective therapy can be put into place to stop the progression of the illness. This is done with the intention of analysing data from many sources and making use of NLP to overcome data heterogeneity. This paper evaluates the usefulness of several machine learning methods (such as the Naive Bayes (NB), Transductive Neuro-Fuzzy Inference, and Terminated Ramp-Support Vector Machine (TR-SVM)) for healthcare applications and suggests using Natural Language Processing (NLP) to address issues of data heterogeneity and the transformation of plain text. The implementation, testing, comparison of performance and analysis of the parameters of the algorithms used for diagnosis have simplified the process of selecting an algorithm better suited to a certain instance. TWNFI is particularly effective on larger datasets, while Terminated Ramp-Support Vector Machine is well suited to lesser datasets with a lower number of magnitudes due to performance difficulties. 2024 Scrivener Publishing LLC. -
Natural Language Processing on Diverse Data Layers through Microservice Architecture
With the rapid growth in Natural Language Processing (NLP), all types of industries find a need for analyzing a massive amount of data. Sentiment analysis is becoming a more exciting area for the businessmen and researchers in Text mining NLP. This process includes the calculation of various sentiments with the help of text mining. Supplementary to this, the world is connected through Information Technology and, businesses are moving toward the next step of the development to make their system more intelligent. Microservices have fulfilled the need for development platforms which help the developers to use various development tools (Languages and applications) efficiently. With the consideration of data analysis for business growth, data security becomes a major concern in front of developers. This paper gives a solution to keep the data secured by providing required access to data scientists without disturbing the base system software. This paper has discussed data storage and exchange policies of microservices through common JavaScript Object Notation (JSON) response which performs the sentiment analysis of customer's data fetched from various microservices through secured APIs. 2020 IEEE. -
Natural polymer-based hydrogels as prospective tissue equivalent materials for radiation therapy and dosimetry
Natural polymer-based hydrogels have been extensively employed in tissue engineering and biomedical applications, owing to their biodegradability and biocompatibility. In the present work, we have investigated the efficacy of hydrogels such as agarose, hyaluronan, gelatin, carrageenan, chitosan, sodium alginate and collagen as tissue equivalent materials with respect to photon and charged particle (electron, proton and alpha particle) interactions, for use in radiation therapy and dosimetry. Tissue equivalence has been investigated by computing photon mass energy absorption coefficient (?en/?), kinetic energy released per unit mass (KERMA), equivalent atomic number (Zeq) and energy absorption build-up factors (EABF) relative to human tissues (soft tissue, cortical bone, skeletal muscle, breast tissue, lung tissue, adipose tissue, skin tissue, brain) in the energy range of 0.01515MeV. Ratio of effective atomic numbers (Zeff) have been examined for tissue-equivalence in the energy range of 10keV1GeV for charged particle interactions. Analysis using standard theoretical formulations revealed that all the selected natural polymers can serve as good tissue equivalent materials with respect to all human tissues except cortical bone. Notably, sodium alginate, collagen and hyaluronan are found to have radiation interaction characteristics close to that of human tissues. These results would be useful in deciding on the suitability of a natural polymer hydrogel as tissue substitute in the desired energy range. 2021, Australasian College of Physical Scientists and Engineers in Medicine.