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Application of Corn Oil Derived Carbon Nano-onions Using Flame Pyrolysis as Durable Catalyst Support for Polymer Electrolyte Membrane Fuel Cells
The reliance of carbon black as catalyst support for Pt in PEM fuel cell has posed a major challenge in its durability as carbon blacks are highly prone to corrosion. As an alternative, CNTs, CNFs, and graphene are explored as catalyst support, however at the expense of tedious synthesis procedure and production cost. So to combat this issue, a facile flame pyrolysis route was adopted to produce carbon nano-onions using eco-friendly corn oil. Further modification in the carbon nano-onions exhibited better corrosion resistance in comparison to carbon black (Vulcan XC-72R). Also, a systematic approach was adopted towards developing a durable electrocatalyst which was designed to withstand harsh fuel cell operating conditions. The electrocatalyst was successfully analyzed using stringent standard testing protocols (< 40% ECSA loss). Among all the electrocatalyst studied, Pt/fOC exhibited only 37.1% loss in electrochemical active surface area (ECSA) after 5000 cycles, thus indicating its excellent durability. A full cell was also constructed with Pt/fOC as cathode electrocatalyst which showed a maximum power density of 365 mW cm?2, comparable to commercial Pt/C (367 mW cm?2). To the best of our knowledge, this is the first study on the application of corn oil derived carbon nano-onions as catalyst support for PEM fuel cells. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Self-assembled free nanocarrier prodrugs based on camptothecin and dihydroartemisinin exhibit accumulation and improved anticancer efficacy
Small molecule targeted inhibitor therapies often have several drawbacks, including limited oral bioavailability, quick metabolism, toxic effects that limit dosage, and poor water solubility. This study aims to develop a nanodrug self-delivery system that does not require a carrier by utilizing the self-assembly of camptothecin (CPT) and dihydroartemisinin (DHA). CPT/DHA nanoparticles (NPs) with varying diameters can be synthesized without requiring further carrier materials or chemical modifications by changing the CPT-to-DHA ratio (10:1, 5:1, 2:1, 1:1). Even more crucially, CPT/DHA NPs generate an AIE impact when they self-assemble. CPT/DHA NPs are used for cell tracking and bioimaging fluorescent probes. We chose CPT/DHA NPs (2:1) with a size of approximately 140nm for the anticancer examinations. The A549 cells were used to assess the cytotoxicity, morphological changes by biochemical staining methods and apoptosis by flow cytometric techniques of CPT/DHA NPs. Finally, in vitro anticancer research proved that CPT/DHA NPs are biocompatible and have strong synergistic anticancer properties. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Advanced Machine Learning Techniques for Detecting Irregularities in Skin Lesion Borders: Enhancing Early Skin Cancer Detection
Dermatograms are pivotal in the early detection of skin cancer, a disease with significant mortality rates. This paper introduces a novel feature extraction method that captures irregularities in the boundaries of abnormal skin regions. Each raw dermatogram is converted into a binary mask image using an effective segmentation algorithm. The boundary of the lesion region is extracted from the mask. The boundary, together with the centroid of the lesion mask, is used to define a set of directional vectors. An Arc is defined using these directional vectors, and a new Arc feature is calculated based on the number of times the lesion boundary crosses the arc. The proposed Arc feature is evaluated using three standard skin lesion datasets: ISBI 2016, HAM10000, and PH2. Additionally, color features and Local Binary Pattern (LBP) features are implemented for comparison. Classical machine learning algorithms are employed to evaluate these features. Results indicate that for the ISBI 2016 and HAM10000 datasets, the Arc feature set demonstrates superior classification accuracy. In contrast, the PH2 dataset benefits more from the LBP feature. Comparative analysis with recent studies highlights the dependency of accuracy on datasets and classifiers, underscoring the necessity for models incorporating feature fusion and ensemble classifiers. The proposed method outperforms traditional color and texture features and shows competitive results against deep learning models, particularly in scenarios with limited computational resources. These findings suggest that the Arc feature is a promising approach for improving skin cancer detection, although further investigation is needed to fine-Tune performance, optimize classifier selection, and explore feature fusion strategies. 2024 World Scientific Publishing Company. -
Advanced electrochemical performance of N-Ti3C2/MnO2 MXene as a promising electrode for energy storage
In this study, we demonstrate a simple and efficient two-step synthetic strategy to design a high-performance N-Ti3C2/MnO2 composite for energy storage application. Nitrogen doping alters the electronic structure of electrode materials and enhances pseudocapacitance. N-Ti3C2 serves as a supporting substrate for MnO2, boosting the active surface area by preventing Ti3C2 layer stacking. Benefitting from the collaborative contribution and synergistic interaction within this multicomponent system, N-Ti3C2/MnO2 results in exceptional specific capacitance of 2107.1 Fg?1 at 1 Ag?1. It also exhibits a low internal resistance and maintains a capacitive retention of 94% over 3000 cycles. The asymmetric capacitor also delivers an energy density of 117.1 Whkg?1 at a power density of 1290.1 Wkg?1. This work presents a straightforward method for modifying Ti3C2 through nitrogen doping and the insertion of MnO2 as an interlayer spacer to enhance electrochemical performance. Qatar University and Springer Nature Switzerland AG 2024. -
Automated epileptic seizure classification using adaptive fast Fourier transform with non-uniform sampling and improved deep belief network
In automated brain-computer interaction (BCI), EEG signals are essential. This research uses AI to detect epileptic seizures, employing data from the BONN dataset (UCI), CHB-MIT dataset (physionet server), and Bangalore EEG Epilepsy Dataset (BEED). The goal is to develop an automated system for accurate seizure detection using adaptive fast Fourier transform with non-uniform sampling (AIFFT-NS) and an improved deep belief network (IDBN) model to enhance classification accuracy. The AIFFT-NS model serves as a channel for transforming spectro-temporal data. Using various EEG datasets, a number of extensive experiments are carried out, resulting in the validation of the efficacy of the proposed approach. High accuracy metrics, with 96.16% for the BEED dataset, 99.41% for the BONN dataset, and 96.31% for the CHB-MIT dataset, represent the evidentiary outcomes. This study emphasises the critical function of AI-facilitated spectro-temporal EEG analysis within the domain of medical diagnostics, going beyond the realm of automated seizure onset classification. Copyright 2024 Inderscience Enterprises Ltd. -
Impact of human resource practice on work engagement and turnover intention in information technology companies
Orientation: The information technology (IT) sector, a global economic driver, faces high employee turnover because of low work engagement. This study examines the relationship between human resource management (HRM) practices and their impact on work engagement and turnover intention (TI) in IT companies. Research purpose: The primary purpose of this research article is to investigate how HRM practices influence employee work engagement and TI in the IT sector. Motivation for the study: This study is motivated by the need to address this critical issue by exploring the role of HRM practices in shaping employee engagement and TI. Research approach/design and method: The research data came from 10 IT organisations in Pune IT parks. Non-probability convenience sampling was used to collect data. Data were analysed using Structural Equation Modelling (SEM), Statistical Package for Social Science (SPSS) and Moment Structure Analysis to evaluate the hypotheses. Main findings: The study found that HRM practices such as effective communication (EC), training satisfaction (TS), performance appraisal satisfaction (PAS), pay satisfaction (PS) and opportunities for development (OFD) positively influence work engagement among IT employees. Addressing these HRM practices can enhance employee retention and engagement in the IT sector. Practical/managerial implications: Implementing these strategies can lead to a more committed and productive workforce, improving overall organisational performance and retention. Contribution/value-add: This research offers actionable recommendations for IT companies to improve employee retention and engagement, filling a gap in existing literature by focussing exclusively on the unique challenges and dynamics of the IT industry. 2024. The Authors. -
Structural and Optical Properties of Alumino Lead Borate Glasses Containing Copper Oxide
The alumino lead borate glasses with small amounts of copper oxide were synthesized by melting and quenching according to the relation 50B2O3-30PbO-(20x)Al2O3-xCuO with x = 0, 0.10, 0.25, 0.50, 0.75 and 1.00 mol%. The powder XRDs had no sharp peaks which show that the samples are amorphous. Density of the glasses increased as the content of the CuO increased. FTIR spectroscopic studies reveal the presence of BO3, BO4, PbO4, AlO4, pentaborate [B5O8], diborate [B4O72] and dipentaborate B512 structural units. The UV-visible absorption studies showed that the refractive index, indirect energy gap, oxide ion polarizability and optical basicity had composition dependence which were related to the glass structure. As the CuO concentration increased, the refractive index decreased, indirect energy gap increased, oxide ion polarizability decreased and optical basicity decreased. Optical band gap increased with increasing CuO content as the band gap for bridging oxygens is higher than that for non-bridging oxygens. 2024 Indian Ceramic Society. -
Young adult consumers perception of value proposition towards organic foods: a tweet based analysis using NVivo
Given the increasing focus on sustainable food production, the present study investigates consumer perceptions of organic food and its value proposition. Twenty thousand tweets between May 7, 2020, and May 7, 2021, from Indian consumers concerning organic food were analyzed using the text analytics program (Nvivo) to find an ongoing conversational theme. The study demonstrates that value propositions highlighting personal health attributes (such as being nutritious, dairy-free, and gluten-free) and consumption benefits (like taste and deliciousness) significantly convince people to eat more organic food. Despite the documented environmental benefits associated with organic food consumption, our analysis of customer interactions revealed a limited focus on sustainability or ecological considerations. The study highlights the significance of creating covered messaging tactics targeting various clientele groups. Moreover, it underscores the consequence of employing complex value propositions that emphasize various advantages that promote sustainable consumption practices among clients. Future studies could look into more inclusive platforms and demographic representations to understand peoples perceptions of organic food. Moreover, the implications extend to managerial strategies that support businesses in aligning product offerings with consumer preferences to create a more sustainable food environment. The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024. -
Normalized group activations based feature extraction technique using heterogeneous data for Alzheimers disease classification
Several deep learning networks are developed to identify the complex atrophic patterns of Alzheimers disease (AD). Among various activation functions used in deep neural networks, the rectifier linear unit is the most used one. Even though these functions are analyzed individually, group activations and their interpretations are still not explored for neuroimaging analysis. In this study, a unique feature extraction technique based on normalized group activations that can be applied to both structural MRI and resting-state-fMRI (rs-fMRI) is proposed. This method is split into two phases: multi-trait condensed feature extraction networks and regional association networks. The initial phase involves extracting features from various brain regions using different multi-layered convolutional networks. Then, multiple regional association networks with normalized group activations for all the regional pairs are trained and the output of these networks is given as input to a classifier. To provide an unbiased estimate, an automated diagnosis system equipped with the proposed feature extraction is designed and analyzed on multi-cohort Alzheimers Disease Neuroimaging Initiative (ADNI) data to predict multi-stages of AD. This system is also trained/tested on heterogeneous features such as non-transformed features, curvelets, wavelets, shearlets, textures, and scattering operators. Baseline scans of 185 rs-fMRIs and 1442 MRIs from ADNI-1, ADNI-2, and ADNI-GO datasets are used for validation. For MCI (mild cognitive impairment) classifications, there is an increase of 14% in performance. The outcome demonstrates the good discriminatory behaviour of the proposed features and its efficiency on rs-fMRI time-series and MRI data to classify multiple stages of AD. 2024 Vaithianathan et al. -
Photoisomerization Dynamics of 2-[(E)-(4-fluorophenyl)diazenyl]-1 H -imidazole: A Theoretical and Experimental Insight
This study investigates the photoresponsive behavior of substituted azobenzenes with a specific focus on their nonlinear optical response. This study suggests that azoimidazole substitution is a better alternative to azobenzene derivatives for nonlinear optical responses. The synthesis, characterization, photophysical property and isomerization pathway of 2-[(E)-(4-fluorophenyl)diazenyl]-1H-imidazole (E-2g) are presented as an optical limiter through a comprehensive blend of experimental and theoretical approaches. Notably, E-2g exhibited a lower energy barrier than reported azobenzenes. The trans-to-cis photostationary state was reached in 75 min, while the cis-to-trans state was achieved in 60 min at 354 nm. The study further explores the photoisomerization pathway of E-2g, highlighting its nonlinear absorption, which has a nonlinear absorption coefficient (?eff) of 8.8 10-11 m/W at 20 ?J, as determined by Z-scan measurements. The results suggest that E-2g exhibits significant nonlinear absorption characteristics, which helps in applications requiring protection from intense light sources. 2024 World Scientific Publishing Company. -
GLOBAL POVERTY AND HUMAN SECURITY: A VASUDHAIVA KU?U?BAKA? PERSPECTIVE
Poverty has been a persistent issue throughout human history, affecting societies worldwide. In the major industrialized nations, social welfare policies served as the primary approach to poverty alleviation until the late 20th century. In 1994, the United Nations Development Programme (UNDP) introduced a human-centred sustainable development model, emphasizing human security as a means to eradicate poverty and other forms of insecurity. Despite these efforts, data from the World Bank and other international organizations indicate that a significant portion of the global population remains impoverished, highlighting the ongoing need for development and inclusivity. The ancient Indian concept of vasudhaiva ku?u?baka?, which promotes open-mindedness, interconnectedness, brotherhood, and fairness, offers a universal vision rooted in a family model. Interpreted in a contemporary context, vasudhaiva ku?u?baka? presents a global perspective that resonates with the principles of human security. Integrating this concept with the human security framework holds the potential to address global poverty and promote the universality of human rights. This article seeks to reconstruct the human security paradigm through the perspective of vasudhaiva ku?u?baka? in order to eradicate poverty and promote global well-being. 2024 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
A novel approach for integrating cryptography and blockchain into IoT system
The quick advancement of Internet of Things (IoT) emphasizes the significance of cryptography and blockchain ensuring the security of sensitive data and connected devices. Blockchain technology and encryption play key roles in ensuring the security of the expansive IoT network. Blockchain offers decentralized trust, immutability, and transparency to IoT networks and transactions, while encryption serves to protect IoT data from unauthorized access. It is a novel approach for integrating cryptography and blockchain into IoT System, cryptography and blockchain stand out as robust technologies that enhance the security of IoT systems. The implementation of an integrated architecture, along with a strategic integration approach, further strengthens the security measures. This methodology proves valuable for managing and validating digital transactions on decentralized, immutable networks. This work also explores the potential significance of integrating cryptography and blockchain into IoT System, this functions and applications in enhancing IoT security. This methodology introduces encryption techniques tailored for resource-constrained IoT devices, which are essential for ensuring end-to-end security. 2024, Taru Publications. All rights reserved. -
Energy-efficient and secure routing strategy for opportunistic data transmission in WSNs
Driven by the critical importance of routing in Wireless Sensor Networks (WSNs) and the security vulnerabilities present in existing protocols, this research aims to address the key challenges in securing WSNs. Many current routing protocols focus on computational efficiency but fall short of providing strong security measures, leaving them vulnerable to malicious attacks. Reactive protocols, often preferred for their reduced bandwidth usage, heighten security concerns due to their limited resources for maintaining network routes, while proactive alternatives require more resources. Additionally, the ad hoc nature and energy limitations of WSNs make traditional security models, designed for wired and wireless networks, impractical. To overcome these limitations, this paper introduces the Secured Energy-Efficient Opportunistic Routing Scheme for sustainable WSNs. The proposed protocol is designed to enhance security by continuously updating neighbor information and verifying the validity of routing parameters, while also being power-aware, a critical factor given the energy constraints of WSNs. The protocol has been evaluated through simulation experiments, measuring key performance indicators such as throughput, average end-to-end delay (E2 delay), energy consumption, and network lifetime. The results demonstrate that the proposed protocol effectively strengthens WSN security while addressing the unique operational constraints of these networks. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Development vs. Rights A Case for Sustainable Development of Onge Tribes of Little Andaman
Human rights and environmental protections are often violated as a consequence of development activities. In addition to harming the environment, this increases the marginalisation of those who are already marginalised. The development paradigm that is based on the interests of the majority not only tends to retard the indigenous people but also renders them incapable of competing with the majority. For the indigenous people, development has always been a problem rather than a solution. Development initiatives under the umbrella of globalisation with a label of monotony, ignore the aspects of the diverse livelihoods of many indigenous peoples. The Niti Aayog proposed in its vision document, the Sustainable Development of Little Andaman, in 2021, that the island should be developed into a megacity by utilising its natural features and strategic location. The long-term objective is to develop the island into a major financial tourism hub that can rival Hong Kong and Singapore. This plan will, on the one hand, advance commerce, employment, and economic growth; on the other hand, environmental conservation issues will also arise. Concerns over this vision document have indeed been voiced by several academics, environmentalists, and conservationists due to issues with Onge indigenous rights, ecological fragility, and earthquake and tsunami susceptibility. In this context, the research article aims to study and analyse the proposed megacity project and its impact on the rights of Onge tribes and the environment. Sahana Florence and Achyutananda Mishra, 2024. -
A hybrid deep learning and quantum computing approach for optimized encryption algorithms in secure communications
As online dangers get worse, there is a greater need for strong encryption methods to protect private conversations. Utilizing the strengths of both deep learning and quantum computing, this study suggests a new mixed method for improving the security of communication systems by making encryption algorithms work better. When it comes to keeping up with new online threats, traditional security methods often fall behind. Deep learning techniques could be a good way to improve encryption algorithms because they let the system learn and change to new attack methods. In the meantime, quantum computing offers unmatched computing power that can completely change how cryptography works by using quantum events like superposition and entanglement. Our suggested method combines the flexibility of deep learning with the computing power of quantum computing to get around the problems with current encryption methods. This will make safe communication systems more resistant to attacks from smart people. Through tests and models, we show that our mixed approach works better and more effectively than current encryption methods. This shows that it has the ability to solve the growing safety problems in a world that is becoming more and more linked. 2024, Taru Publications. All rights reserved. -
Development and Analysis of Current Collectors for Proton Exchange Membrane Fuel Cells
Hydrogen fuel cells are gaining popularity in power-consuming devices due to their zero-emission characteristics. However, ohmic resistance, which arises from the resistance to electron flow through the electrodes and external circuit, can cause reduced efficiency and voltage drops in a fuel cell. This research aims to develop current collector plates for proton exchange membrane fuel cells with optimal design, high electrical conductivity, and thermal conductivity to mitigate ohmic resistance. Six different designs and five different materials-copper, brass, aluminum, stainless steel 316, and stainless steel 304 were considered for this purpose. The study involved experimental electrical conductivity and fuel cell performance tests to identify the best material and design for the current collector. Results indicated that brass and copper exhibited the least resistivity and favorable material characteristics. Consequently, all six current collector plate designs were developed using brass and copper with various machining and finishing processes. Performance testing on a fuel cell test station revealed that brass current collector plate design 5, featuring open ratios, demonstrated superior performance. Ultimately, the optimum design and material selection of the current collector plates have led to the development of fuel cells with reduced ohmic resistance and improved overall performance. 2024, Politechnika Lubelska. All rights reserved. -
Development of Biocompatible Barium peroxide/Pluronic F127/L-ornithine Composite for Enriched Antimicrobial, Antioxidant and Anticancer Potential: An in vitro Study
Osteosarcoma (MG-63) is a type of bone cancer affects mostly adolescents and young adults. Disease-causing microorganisms like Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Candida albicans pose serious illness in humans. There is a need to develop multifunctional composite to combat cancer and other most common disease caused by disease causing microorganisms. In this context, BaO2 and pluronic F127, L-Ornithine coated BaO2 (BaO2-PF127-LO) composite have been prepared and characterized by XRD, FTIR, UV-Vis, SEM, HRTEM, EDAX, and XPS analytical techniques. BaO2 and BaO2-PF127-LO were orthorhombic crystalline structure and the crystallite size was found as 32nm for BaO2 and 26nm for modified BaO2 PL studies revealed the green emission observed at 506nm for BaO2-PF127-LO composite which is absent in the case of bare BaO2. Antimicrobial activity of BaO2 and BaO2-PF127-LO was investigated. MTT assay was performed to determine the anticancer potential while the DPPH free radical scavenging assay was carried out to determine the antioxidant potential. The experiment study revealed that the BaO2-PF127-LO exhibited enhanced antimicrobial, antioxidant, and anticancer activity and low toxicity when compared to pristine BaO2. The experimental results revealed that the BaO2-PF127-LO composite holds promising potential for biomedical applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
DISTANCE SPECTRUM OF TWO FAMILIES OF GRAPHS
Let H1 and H2 be two copies of the complete graph Kn, n ? 3 with vertex sets V(H1) = {v1,v2...,vn} and V(H2) = {u1,u2,...,un}. Graph ?(n,p), 1 ? p ? n-1, is obtained from the union of graphs H1 and H2 by adding edges {uivi)|i ? {1, 2...,p}}. Graph ?(n) is obtained from the union of graphs H1 and H2 by joining each vertex vi of H1 to every vertex in {u1, u2, ..., un} \ {ui}, i = 1, 2, ..., n. The adjacency spectrum of ?(n, p) and ?(n) were determined in [9]. An open problem posed in [7] was to find families of graphs of diameter greater than two, for which the adjacency and distance spectrum are both integral. To answer the open problem, the distance spectrum of the above family of graphs is calculated, and new distance equienergetic graphs are constructed in this paper. 2024 Jangjeon Research Institute for Mathematical Sciences and Physics. All rights reserved. -
Machine Learning Based Optimal Feature Selection for Pediatric Ultrasound Kidney Images Using Binary Coati Optimization
Chronic kidney disease (CKD) one of the most dangerous illnesses. Early detection is vital for improving survival rates and underscoring the need for an intelligent classifier to differentiate between normal and abnormal kidney ultrasound images. Features extracted from an image have a significant impact on classification accuracy. In this study, we present a Binary Coati optimization algorithm (BCOA) for feature selection in CKD, which focuses on reducing the high dimensionality features extracted from ultrasound images, including GLCM, GLRLM, GLSZM, GLDM, NGTDM, and first order, by employing BCOA-S shaped and BCOA-V shaped transfer functions that convert BCOA from a continuous search space to a binary form, which helps in the selection of optimal features to improve the classification performance while reducing the feature dimensionality. The reduced feature was evaluated using six machine-learning classifiers: Random Forest, Support Vector Machine, Decision tree, K-nearest Neighbor, XG-boost, and Nae Bayes. The efficiency of the proposed framework was assessed based on accuracy, precision, recall, specificity, f1 score and AUC curve. BCOA-V outperformed in terms of accuracy, precision, recall, specificity, F1 score and AUC curve by 99%,100%,97%,100%, 98%, and 98%, respectively. This makes it a superior choice for CKD diagnosis and is a valuable tool for feature selection in medical diagnosis. (2024), (Intelligent Network and Systems Society). All rights reserved. -
We are Treated as Outsiders in Our Own City: Lived Experiences of Intersectional Stigma Against Sex Workers in Kolkata, India
Introduction: Sex workers in India experience intersectional stigma related to their gender identity, sexuality, and profession. The objective of the present study is to analyze the lived experiences of intersectional stigma against sex workers in Kolkata. Methods: We interviewed 30 cisgender female sex workers in March 2023 in Kolkata, India. Interviews were digitally audio recorded, translated from Bengali into English, and transcribed and coded using thematic analysis. Results: We identified five main themes regarding intersectional stigma: (1) internalized stigma regarding the shame associated with being a female sex worker, (2) perceived stigma of sex work as a dirty profession, associated with lower caste status, (3) enacted stigma against sex workers who are mothers, (4) enacted stigma against the children of sex workers, and (5) reduction of stigma through unionization/labor organizing. Conclusions: Intersectional stigma against sex workersis impacted by negative attitudes regarding gender, caste status, single motherhood, and occupation. We identified internalized stigma as a source of shame for sex workers. Sex workers also were perceived to beengaged in afilthy profession, associated with lower caste status. Those sex workers who were mothers experienced discrimination, as did their children. Respondents reported how collectivization has helped to address these experiences of stigma anddiscrimination. Policy Implications: Addressing the intersectional stigma against sex workers in Kolkata necessitates a shift in social attitudes.Findings underscore the urgent need for stigma reduction interventions and socialpolicies, including (1) labor protections for sex workers, (2) individual/community-level interventions for sex workers, and (3) media campaigns to address stigma reduction. By understanding the lived experiences of sex workers, we may develop better interventions to reduce stigma in the lives of sex workers in Kolkata and throughout India. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.