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Effect of Chelating Agent Concentration on the Pseudocapacitive Performance of V2O5 Flakes Prepared by the Hydrothermal Process for Supercapacitor Applications
Vanadium pentoxide (V?O?) flakes were synthesized via a hydrothermal method by varying the amount of lemon juice (5mL for sample-1 and 10mL for sample-2) as a natural chelating agent. Structural and morphological analyses were performed using X-ray diffraction (XRD) and scanning electron microscopy (SEM), confirming crystalline V?O? with flake-like morphologies influenced by chelating agent concentration. Electrochemical performance was evaluated using cyclic voltammetry (CV), galvanostatic chargedischarge (GCD), and electrochemical impedance spectroscopy (EIS) in a 3M KOH electrolyte. Sample-2 exhibited a Significantly higher Specific capacitance of 1536 F?g?1 (CV at 1mVs?1) and 212.37 F?g?1 (GCD at 1 A?g?1) compared to sample-1, demonstrating that increasing lemon juice concentration enhances the capacitive behavior of V?O? flakes by improving ion diffusion and electroactive surface area. The Author(s) under exclusive licence to Sociedade Brasileira de Fica 2025. -
Kinetic characterisation of proteases from Punica granatum, Musa acuminata, Carica papaya, and Ananas comosus as sustainable enzyme sources
Proteases are vital industrial enzymes, contributing approximately 60% of the global enzyme market, by facilitating protein hydrolysis. Fruit peels, a major agricultural waste, offer a sustainable alternative for commercial enzyme production. This study investigates the proteases extracted from the peels of Punica granatum, Musa acuminata, Carica papaya, and Ananas comosus, with a primary focus on determining their optimal pH, temperature, and substrate specificity. Additionally, K? and V??? kinetics were assessed to characterize their catalytic efficiency. Optimal proteolytic activity was observed at pH 8 and 30C for P. granatum, pH 7 and 30C for M. acuminata, pH 8 and 30C for C. papaya, and pH 7 and 50C for A. comosus. substrate specificity of protease was assessed using casein, fish meal, soybean meal, black soldier fly larvae, bovine serum albumin, and egg albumin, revealing broad applicability, especially in P. granatum peels. The stability of P. granatum proteases across substrates suggests multiple isoforms or a flexible active site. Kinetic analysis using Lineweaver-Burk plots revealed Vmax and KM values of 8.45 mol/min/mL and 3.81 M (P. granatum), 4.56 mol/min/mL and 10.08 M (M. acuminata), 2.98 mol/min/mL and 2.84 M (C. papaya), and 2.97 mol/min/mL and 11.38 M (A. comosus) respectively. Among the tested fruit peels, P. granatum exhibited the highest reaction rate, while C. papaya demonstrated the highest substrate affinity, making them as promising candidates for feed supplementation and industrial enzyme applications. The broad substrate specificity and high catalytic efficiency of P. granatum further reinforce its potential for use in feed formulations, enhancing protein hydrolysis and improving nutrient availability. These findings highlight the significant potential of fruit peel-derived proteases in promoting sustainable enzyme production and advancing bioeconomic applications. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026. -
Valorization of waste chilli stalks (Capsicum annuum) as a sustainable substrate for cellulose extraction: insights into its thermomechanical, film forming and biodegradation properties
Rising global population accelerates food waste generation, thereby creating a crisis in food waste management. A solution involves deriving value-added products like cellulose biopolymer from food waste. Chilli stalk wastes are one such food waste which are generated in large quantities and are unsuitable for field use or incineration due to health and environmental challenges. A greener alternative is extracting cellulose biopolymer from chilli stalk waste. The extraction of cellulose biopolymer from chilli stalk results in a renewable, biodegradable and economically efficient biomaterial with a broad range of applications. The extraction process involving alkali treatment (NaOH) and bleaching (alkaline H2O2), resulted in a yield of 29.85% cellulose biopolymer. The extracted cellulose was subjected to quantification and functional property analysis followed by characterization (FTIR, XRD, TGA, DSC and SEM) to analyse functional groups, crystallinity, thermal properties and surface morphology. Functional property analysis resulted in higher values when compared with commercial cellulose. The characterization techniques confirmed the effective removal of impurities such as lignin, hemicellulose and pectin by the chemical treatments. Cellulose sheets, fabricated using solvent casting, exhibited exceptional biodegradability (85.36%) within 20days, surpassing conventional food packaging materials, commercial food packaging paper (15.95 0.12% [%w/w]) and plastic sheets (7.89 0.33% [%w/w]) over the same time period. The novelty of this research lies in the innovative valorization of chilli stalk waste, which often remains unused in large quantities globally. This study introduces a cost-effective method to convert it into a value-added, highly biodegradable biopolymer. The resulting cellulose sheets provide an eco-friendly substitute for traditional food packaging materials. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Eco-conscious photocatalytic degradation of organic textile dyes using green synthesized silver nanoparticles: a safe and green approach toward sustainability
Green synthesized nanoparticles from Strobilanthes barbatus leaf extracts are environmentally safe and feasible for enduring wastewater treatment, especially for organic textile dye degradation. The synthesized Strobilanthes barbatusmediated silver/silver-oxide nanoparticles (SB-Ag/AgO NPs) showed maximum absorbance at 428nm. The SB-Ag/AgO NPs were generally spherical with an average diameter of 37.59nm (FESEM and TEM analysis). The importance of functional groups in the production of SB-Ag/AgO NPs was recorded by FTIR investigations. In the degradation and rate of degradation for textile dyes, after 320min, SB-Ag/AgO NPs displayed 96.60% (5.31 10?1 L mg?1min?1) and 87.50% (1.179 10?1 L mg?1min?1) degradation of Reactive Blue 220 (RB-220) and Reactive Blue 222A (RB-222A), respectively. When compared to dye effluents, SB-Ag/AgO NPs-treated dye solutions revealed a considerable decrease in inhibitory efficiency during phytotoxicity evaluation on test organisms, Vigna radiata and Artemia salina. The biosynthesized SB-Ag/AgO NPs could serve as a feasible photocatalyst for the treatment of organic textile dyes in organic substancepolluted water ecosystems. SB-Ag/AgO NPs can serve as efficient, cost-effective and environmentally friendly sources for dye degradation. The current research offers a safe and environmentally friendly strategy for sustaining the environment. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Valorization of bovine tannery fleshing waste as a fish meal replacer: a conceivable green approach
The study intended to utilize bovine tannery fleshing (BTF) a significant contributor of solid wastes in leather industries, in its unhydrolyzed form (raw fleshing flour [RFF]) as well as in fermented form (fermented fleshing flour [FFF]) as fish meal (FM) replacer in formulated aqua feeds. In line with this, experimental diets were formulated, characterized, and evaluated for their virtue. Improvement in the physical quality of diets was achieved with FFF incorporation, enabling better pelletability, palatability, and feed texture. As the formulated diets were of sinking type, feeding trials on column as well as bottom feeders were concertedly attempted, as a value-added application of proteinaceous feed ingredient (BTF) in aquaculture sector. FFF inclusion diets proved superior to RFF inclusion diets. Maximum protein and lipid retentions of 89% and 92% were evidenced. Fish feeding experiments disclosed the productive impact of substituting FM with FFF by 50 and 75% on the performance (fish growth) of Cirrhinus mrigala (19.03 cm final length, 112.89 g Kg-1 final body weight, and 99% survival rate) and Labeo rohita (22.19 cm final length, 214.99 g Kg-1 final body weight, and 97% survival rate) respectively, with enhanced muscle biochemical compositions. FFF inclusion diets best suited column feeders than bottom feeders, with acceptable feed conversion ratio (< 2) and about 65% and 69% of protein in Rohu and Mrigal, respectively after 90 days of feeding. Absence of feed related mortality and multimycotoxins in FFF inclusion diets authenticated its invulnerable nature, signifying the need of bacterial fermentation processes to pull out the maximum worth of the solid waste. Thus, bovine tannery fleshing (BTF) would probably be used as a relatively inexpensive, effectual, safe, and an absolute source of protein for marine animals, reinforcing aquaculture business to strengthen up its profitability and eventually; this is an assuring conscientious solid waste management strategy that could be scaled-up to develop high-quality aquaculture feeds. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. -
Floral waste as a potential feedstock for polyhydroxyalkanoate production using halotolerant Bacillus cereus TS1: optimization and characterization studies
The versatile properties and high degree of biodegradability of polyhydroxyalkanoates (PHA) have made them the ideal candidate for biomedical and other applications. Although extensive research on PHA-producing bacterial isolates from terrestrial environments is documented in the available literature, the potential of marine bacterial isolates in PHA production remains less explored and offers a great scope for future research. This research work primarily focuses on isolation and characterization of PHA-producing bacterial isolates from samples collected from coastal areas of Kerala, India. Furthermore, the possibility of PHA production from the most potential isolate Bacillus cereus TS1 using jasmine waste hydrolysate-based media was explored in this study. The utilization of floral waste hydrolysate (FWH) for PHA fermentation is not widely discussed in the available literature and is the major novelty factor of this research work. Under optimized conditions of glucose (1.2% w/v), yeast extract (0.15% w/v), NaCl (5.02% w/v), and incubation period (60h), a maximum PHA yield of 1.13g/L was achieved. The characterization of PHA polymer was done using Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), X-ray diffraction (XRD) and thermogravimetric analysis (TGA). Thus, this research work integrates floral waste valorisation with microbial biopolymer production and highlights an innovative approach for sustainable development. The scale of this method on an industrial scale in future may prove helpful in the cost-effective production of PHA using cheap raw materials. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. -
Novel biocompatible zinc oxide nanoparticle synthesis using Quassia indica leaf extract and evaluation of its photocatalytic, antimicrobial, and cytotoxic potentials
Prognostic research points to the necessity and relevance of revamping polluted environments. The toxic effect of textile dyes released into waterbodies can be reduced by the degradation process and alternate methods in nanotechnology are used to lessen the gravity of the situation. Compared with chemical and physical NP synthesis, plant extract-based nanoparticle synthesis is an environmentally friendly alternative method, and the use of waste leaves in this process is an added advantage. Quassia indica zinc oxide nanoparticles (QI-ZnO NPs) were synthesised in the current work employing a simple and cost-effective process using Q. indica leaf extract. The surface plasmon peak was visible in the UV-Vis absorption spectrum of the decreased reaction mixture at 346 nm. The average crystallite size of the QI-ZnO NPs was found to be 16.66 nm. The QI-ZnO NPs were found to have a stable zeta potential of ?28.4 mV. The surface morphology of the optimised QI-ZnO NPs was observed to be hexagonal using field emission scanning electron microscopy and high-resolution transmission electron microscopy. Under UV light irradiation, the photocatalytic degradation of industrial textile dyes Reactive Blue-220, Reactive Yellow-145, Reactive Red-120, and Reactive Blue-222 showed degradation efficiency of 8090%. Antibacterial and antifungal activity was assessed using well diffusion on gram-positive and gram-negative microorganisms. When administered to the A549 and MDA-MB-231 cancer cell lines, QI-ZnO NPs displayed significant anticancer activities. Limited studies in the area of plant extract-based nanoparticle synthesis mark the novelty of this attempt and this trailblazing and pioneering approach using non-toxic QI-ZnO NPs synthesised through green synthesis is futuristic and sustainable helping in effective wastewater treatment. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. -
Bioconversion of chicken feather waste into feather hydrolysate by multifaceted keratinolytic Bacillus tropicus LS27 and new insights into its antioxidant and plant growth-promoting properties
Abstract: Keratin, the main structural constituent of feathers, contains a lot of valuable amino acids which are potential bioactive compounds as well. Since conventional methods are not efficient enough to achieve complete removal of chicken feather waste, biological mode of feather degradation is one of the most appropriate ways to utilize feathers, thereby reducing wastes as well as generating value-added products from feathers. This study was focussed on valorizing chicken feather into feather hydrolysate (FH) containing bioactive compounds for plant growth promotion. Keratinolytic bacteria capable of degrading chicken feathers were isolated from the poultry waste dumping site of Russell Market, Shivajinagar, Bangalore, Karnataka, India. The isolated bacteria was identified as Bacillus tropicus LS 27. A minimal media with chicken feather as the sole source of carbon and nitrogen was prepared and inoculated with Bacillus tropicus LS 27 [5% (v/v)]. Degradation of keratin protein by bacteria caused the solubilization of amino acids which was confirmed by high-performance liquid chromatography (HPLC) analysis where an appreciable amount of amino acids like cysteine, valine, isoleucine, proline, lysine, methionine, and phenylalanine was detected. The Fourier transform infrared spectroscopy (FTIR) analysis of hydrolysed chicken feathers showed C=0 stretching, S-H bond stretching, and formation of carboxylic acid groups indicating effective degradation of chicken feathers. Scanning electron microscope (SEM) images revealed the degradation pattern of feathers showing complete degradation of barbs and barbules with a portion of rachis remaining. Feather hydrolysate was further explored for its antioxidant activity using DPPH scavenging assay, and the value was found to be 1.5 mg/mL. The bacterial cells when screened for heavy metal tolerance showed significant metal tolerance to lead (Pb) and chromium (Cr). Since Bacillus tropicus LS27 showed indole-3-acetic acid (IAA), siderophore, and ammonia production, the prepared feather hydrolysate along with the bacterial cells were used as soil amendment for plant growth studies over Spinacia oleracea L. The study revealed that plants supplemented with 20% (v/v) FH showed elevated plant growth, therefore proving to be optimum for the support of plant growth. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. -
Fatigue surface analysis of AL A356 alloy reinforced hematite metal matrix composites
This study intends to investigate how copper chill affects the fatigue behaviour of composites made of aluminium alloy A356 and hematite. It was cast by altering the weight fraction particles of hematite (0 to 12%wt in increments of 3%wt) by sand casting method with and without copper chills at its end to get isotropic and homogenous significant characteristics under liquid metallurgical way. The test specimens were prepared in accordance with ASTM specifications. Ducom-type fatigue testing equipment (rotating bending-low cycle fatigue) is used in experiments to examine fatigue behaviour. The micrographic images were taken with a scanning electron microscope (SEM) and interpreted uniform reinforcement of hematite particles, and X-ray diffraction (XRD) patterns were used to reveal microscopic details. The existence of the hematite particles and their phases was revealed by the X-ray diffraction analysis. The results show that the composites cast with copper chills have significantly greater fatigue strength than the casting obtained without copper chills. It was also observed that at 9%wt, copper chilled composite shows improve in fatigue strength about 10.2% as compared without chilled composites. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. -
A sustainable approach for fish waste valorization through polyhydroxyalkanoate production by Bacillus megaterium NCDC0679 and its optimization studies
Polyhydroxyalkanoates (PHAs) are considered as the only class of truly biodegradable and biocompatible polymers. Although extensive research has been carried out in producing them from a wide variety of organisms, their commercialization still faces hurdles majorly associated with the cost of production media. This research work exploits the use of discarded fish scale waste as a major media component for biopolymer production. The major novelty of the research work is the utilization of a Bacillus megaterium NCDC0679 for PHA production using fish scale waste that is not reported previously. Furthermore, a sequential and systematic statistical optimization strategy employing response surface methodology was used to trace out the level of the most significant variables and their interaction effects on PHA production add to the significant novelty of this work. The significance of the model developed was determined from the p values of ANOVA. Under optimized levels of glucose (50g/L), NaCl (0.125g/L), and fish scale hydrolysate concentration (62.5% v/v), maximum PHA yield of 6.33g/L was achieved in the shake flask culture system. This was found to be 5.50-fold higher than the unoptimized medium. The ANOVA results established the significance of the model (p < 0.05). The extracted polymer was characterized through Fourier-transform infrared (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Thus, the present investigation suggests an innovative method for valorization of fish scale waste for commercial production of PHA. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. -
Distillery effluent valorization through cost effective production of polyhydroxyalkanoate: optimization and characterization
The devastating effect of fossil plastics in the biosphere has tuned the concern for bioplastic production in the last few decades. Polyhydroxyalkanoate, a biopolyester, has a wide range of applications as they impose positive societal impact by being biodegradable and void of any ill-effects when used in vivo. Despite their eco-friendly nature, the outreach of PHA is bounded in industrial scale as the overall expense is highly comparable to conventional plastics. Therefore, in an attempt to attain a feasible production, the present study aims at utilizing raw distillery effluent for PHA production using Bacillus subtilis NCDC 0671. Different dilutions of spent wash (5%, 10%, 15%, and 20%) were assessed for PHA production in the modified medium among which 10% showed maximum PHA accumulation. Furthermore, statistical optimization by response surface methodology enhanced PHA synthesis to 6.3g/L which is 3.3-fold increases. FTIR and NMR characterization of the biopolymer from the optimized medium was similar to the previous literature which provides a promising approach for cost effective production. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. -
A comprehensive molecular docking-based study to identify potential drug-candidates against the novel and emerging severe fever with thrombocytopenia syndrome virus (SFTSV) by targeting the nucleoprotein
Severe fever with thrombocytopenia syndrome (SFTS) is a newly emerging haemorrhagic fever that is caused by an RNA virus called Severe fever with Thrombocytopenia Syndrome virus (SFTSV). The disease has spread globally with a case fatality rate of 30%. The nucleoprotein (N) of the virus has a pivotal role in replication and transcription of RNA inside the host. Considering that no specific treatment regime is suggested for the disease, N protein may be regarded as the potential candidate drug target. In the present study, in silico molecular docking was performed with 130 compounds (60 natural compounds and 70 repurposed synthetic drugs) against the N protein. Based on the binding affinity (kcal mol?1), we selected Cryptoleurine (?10.323kcalmol?1) and Ivermectin (?10.327kcalmol?1) as the top-ranked ligands from the natural compounds and repurposed synthetic drugs groups respectively, and pharmacophore analysis of these compounds along with other high performing ligands revealed that two aromatic and one acceptor groups could strongly interact with the target protein. Finally, molecular dynamic simulations of Cryptoleurine and Ivermectin showed stable interactions with the N protein of SFTSV. To conclude, Cryptoleurine and Ivermectin can be considered as a potential therapeutic agent against the infectious SFTS virus. The Author(s) under exclusive licence to Archana Sharma Foundation of Calcutta 2024. -
Improved piezoelectric energy harvester design using aluminum nitride for improved voltage and power output
This research focuses on improving the performance of piezoelectric energy harvesters (PEHs), which convert ambient kinetic energy into electricity. One of the primary challenges with piezoelectric harvesters is their high resonant frequencies, which often do not align with the lower natural frequencies of ambient vibrations, limiting their efficiency. The goal of this research is to propose a new technique to optimize the design of PEHs, enhancing voltage output and power conversion efficiency. The proposed method combines an Arithmetic Optimization Algorithm to optimize the harvesters dimensions with a Dual Temporal Gated Multi-Graph Convolution Network (DTGMGCN) to forecast resonant frequency and harvested voltage. The principal objective is to reduce resonant frequency errors and enhance energy conversion efficiency. The results, implemented on a MATLAB platform, demonstrate that the proposed method outperforms the existing techniques, such as robust chaotic Harris Hawk optimization, K-Nearest Neighbor Algorithm, and Heaviside Penalization of Discrete Material Optimization. The existing techniques show errors of 0.04%, 0.06%, and 0.08%, while the proposed method achieves an error of only 0.02%. Additionally, in terms of efficiency, the proposed method reaches 98%, significantly higher than the 65%, 78%, and 85% achieved by the existing techniques. These findings indicate the efficiency of the proposed approach in improving the design and performance of piezoelectric energy harvesters, offering a promising solution for more efficient energy harvesting systems. King Abdulaziz City for Science and Technology 2025. -
Modelling bivariate vector autoregressive model using copula approach
In this study, we propose a novel approach to model the relationship between bivariate time series by introducing a bivariate vector autoregressive model with Ali-Mikhail-Haq(AMH) copula, incorporating non-normal errors. The utilization of the Ali-Mikhail-Haq copula will allow for flexible modeling of the dependence structure between the two time series. This copula framework enables us to model the joint distribution of the errors with greater accuracy. Our approach provides a way to capture the relationships between the two time series, making it more suitable for complex data structures where traditional methods based on normal error assumptions may fall short. The Inference Functions for Margins (IFM) technique is employed to estimate both the model parameters and the dependency structure in our proposed model. To evaluate the accuracy of the proposed model, we conduct an extensive simulation study. The results demonstrate that the suggested model performs robustly across different scenarios, effectively capturing the dependence structure and delivering precise parameter estimates. The AMH copula efficiently models moderate levels of both negative and positive dependence. To enhance forecasting performance, we introduce a hybrid extension in which an artificial neural network(ANN) is applied to the residuals of the copula-based AMHVAR model. This hybrid approach captures remaining nonlinear patterns not explained by the linear VAR dynamics and the copula-based dependence structure, leading to improved predictive accuracy. Finally, we apply the proposed models to real-world data, further validating its practical applicability. 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 2026. -
Remote sensing data analyzed by machine learning to predict structural changes
Natural disasters can cause extensive structural damage, necessitating rapid and reliable post-event assessment to support emergency response and recovery planning. Although several methods exist for pixel-level damage classification using post-disaster imagery, translating these outputs into meaningful, building-wise assessments remains challenging. Building-level damage prediction provides more interpretable insights, enabling a clearer estimation of the severity of impact on individual structures and a comprehensive understanding of the overall destruction. This information is crucial for quantifying damage magnitude and prioritizing relief operations. This paper proposes Damage Estimation U-Net (DE-U-Net), a deep learning framework designed to estimate structural damage across four classes: No Damage, Minor Damage, Major Damage, and Destroyed. The model is trained on the xBD dataset to learn representative damage patterns. DE-U-Net is developed by integrating a modified Siamese U-Net with a Damage Ratio Analyzer (DRA) algorithm for building-level damage conversion. The DRA algorithm comprises three components: (1) Connected Component Analysis (CCA) to transform pixel-level predictions into building-level predictions (2) size filtering to remove noise and eliminate small artifacts, and (3) a damage estimation module to compute the number of pixels corresponding to each damage class per building. Model performance is evaluated using standard metrics, including accuracy, precision, recall, and F1-score. 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 2026. -
Decoding customer sentiments in quick commerce: comparative insights from BlinkIt, Zepto, and JioMart utilizing machine and deep learning models
The rapid expansion of quick commerce platforms like BlinkIt, Zepto, and JioMart has introduced unique challenges in understanding customer sentiments due to their operational focus on ultra-fast deliveries and hyper-local logistics. This study conducts a comprehensive analysis of sentiment classification methodologies, exploring both traditional ML techniques and advanced DL models to classify customer reviews into positive, negative, and neutral categories. Traditional models, while offering simplicity and interpretability, achieved moderate accuracy (83% with SVM) but struggled to capture the complexities of neutral sentiments. In contrast, DL models, particularly LSTM, achieved superior performance with an accuracy of 88.96% and a macro F1-score of 0.64, leveraging pre-trained embeddings like GloVe to enhance semantic understanding and contextual representation. Further experiments with optimizers, including Adam, RMSprop, SGD, and Nadam, revealed their limited impact on resolving class imbalance and improving neutral sentiment classification. To address these challenges, we integrated hybrid architectures combining GloVe and BERT embeddings, achieving a significant accuracy of 90.69% and demonstrating improved generalization across sentiment classes. However, the classification of neutral sentiments remained a persistent challenge, underscoring the need for advanced techniques like data augmentation and ensemble strategies. This research highlights the importance of adopting hybrid and deep learning-based approaches for sentiment analysis in quick commerce platforms. The findings provide actionable insights for enhancing customer satisfaction and service quality, while also paving the way for future research in domain-specific sentiment classification and scalable solutions for underrepresented sentiment categories. 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 2026. -
Digitization assisted circular economy: a business strategy to attain sustainability in global supply chains
Contemporary businesses that aim for sustainable global supply chains (GSCs) through circular economy (CE) models has been a crucial topic of research and practice for addressing the climate change risks and resource scarcity. This study identifies and prioritizes the critical success factors (CSFs) for digitalization assisted CE for sustainability in GSCs using a modified multi criteria decision making technique, Grey Decision-Making Trial and Evaluation Laboratory (DEMATEL). Analysing the cause-and-effect relationships among 14 identified CSFs for digitization assisted CE in GSCs offers actionable insights for organizations and policymakers seeking to enhance sustainability efforts by navigating the complexities of integrating digitization and CE practices. The findings from the study reveal that process improvement and optimization through digitization and human centric sustainable operations towards CE as the highest ranked CSFs. The results suggest that managers shall invest in digital integration, prioritize transparency, and foster collaboration to create resilient and sustainable supply chain ecosystems and this will serve as the initial step towards the future digital transformations. This study provides a strategic roadmap for managers and policymakers aiming to integrate CE principles through digital transformation. 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 2026. -
A shap-enhanced PCA-DBSCAN framework for interpretable retail customer segmentation and strategic insight
The rapid expansion of online retail underscores the critical need for precise customer segmentation to drive personalized marketing, reduce churn, and boost lifetime value. This study develops an end-to-end, highly interpretable segmentation pipeline encompassing advanced feature engineering, dimensionality reduction, exhaustive hyperparameter tuning, and robust validation to reveal stable, actionable customer groups in a large, real-world UK online-retail dataset (541,909 records). We augment the classic RFM (Recency, Frequency, Monetary) framework with: TPAC TF-IDF embeddings of item descriptions, holiday-purchase flags, and exponential recency decay; CACV net monetary value and cancellation ratios. After outlier filtering on RFM scores, we apply PCA (230 dimensions) and compare ten clustering methods (selected to represent major algorithmic paradigms: centroid-based [K-Means], probabilistic [GMM], hierarchical [BIRCH, Agglomerative], density-based [DBSCAN, OPTICS, HDBSCAN], graph-based [Spectral], message-passing [Affinity Propagation], and mode-seeking [Mean Shift]). We perform a full grid search per algorithm using a 'safe' silhouette scorer (ignoring noise) and also report Davies-Bouldin and Calinski-Harabasz indices. Temporal stability is assessed via adjusted Rand indices across time splits, and cluster interpretability is enhanced through SHAP-based feature importance analyses. By integrating textual, temporal, and cancellation behaviors into segmentation followed by systematic tuning and multi-metric validation our pipeline delivers superior cluster quality and actionable business insights compared to prior work. Segments directly enable strategic interventions: 'High-Decay Loyalists' (precision = 0.92) receive VIP retention offers yielding 2231% ROI lift, while 'At-Risk Cancellers' (recall = 0.89) trigger targeted win-back campaigns. We also demonstrate a reproducible framework for selecting both model and feature set. DBSCAN (? = 0.3, min_samples = 3 on 10 PCA components) achieved the best silhouette score (0.986), markedly exceeding the 0.72 benchmark in the literature. Agglomerative clustering (average linkage, 2 clusters) scored 0.776, while OPTICS and Spectral Clustering also outperformed classical Gaussian- or centroid-based models. A temporal ARI above 0.8 confirms cluster stability. 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 2025. -
Bayesian and non-bayesian inference of the generalized Lomax distribution under a unified hybrid censoring scheme with applications in failure times in biomedical and aerospace materials
The unified hybrid censoring scheme is a combination of different types of censoring schemes used in reliability testing. This paper presents the statistical inference of generalized Lomax distribution under unified hybrid censoring scheme. The point and interval estimates of the parameters ?,?, and ? of the generalized Lomax distribution have been studied for unified hybrid censored data. In point estimation, the maximum likelihood estimation method is used for computing the estimates, and Tierney and Kadane estimation method is used for Bayes estimation. A 100(1-?)% approximate confidence interval and Bayesian credible intervals for the parameters ?,?, and ? have been computed in the interval estimation part. Mean squared errors are computed for all the estimates and comparison of estimates have been done. The results indicate that the Bayesian estimation method yields more accurate and reliable parameter estimates compared to the maximum likelihood approach. Finally, data representing failure times of fatigue fracture of Kevlar 373/epoxy and failure times of aircraft windshields have been used for point and interval estimations of all parameters as application of real-life scenarios. 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 2025. -
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.