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Optical spectroscopy of Gaia detected protostars with DOT: Can we probe protostellar photospheres?
Optical spectroscopy offers the most direct view of the stellar properties and the accretion indicators. Standard accretion tracers, such as H ? , H ? and Ca II triplet lines, and most photospheric features fall in the optical wavelengths. However, these tracers are not readily observable from deeply embedded protostars because of the large line of sight extinction (Av? 50 100 mag) toward them. In some cases, however, it is possible to observe protostars at optical wavelengths if the outflow cavity is aligned along the line-of-sight that allows observations of the photosphere, or the envelope is very tenuous and thin, such that the extinction is low. In such cases, we not only detect these protostars at optical wavelengths, but also follow up spectroscopically. We have used the HOPS catalog (Furlan et al. in 2016) of protostars in Orion to search for optical counterparts for protostars in the Gaia DR3 survey. Out of the 330 protostars in the HOPS sample, an optical counterpart within 2 ? ? is detected for 62 of the protostars. For 17 out of 62 optically detected protostars, we obtained optical spectra (between 5500 and 8900 using nt Object Spectrograph and Camera (ADFOSC) on the 3.6-m Devasthal Optical Telescope (DOT) and Hanle Faint Object Spectrograph Camera (HFOSC) on 2-m Himalayan Chandra Telescope (HCT). We detect strong photospheric features, such as the TiO bands in the spectra (of 4 protostars), hinting that photospheres can form early in the star-formation process. We further determined the spectral types of protostars, which show photospheres similar to a late M-type. Mass accretion rates derived for the protostars are similar to those found for T-Tauri stars, in the range of 10 - 7 10 - 8M? yr - 1 . 2023, Indian Academy of Sciences. -
A critical assessment of technical advances in pharmaceutical removal from wastewater A critical review
Use of pharmaceutical products has seen a tremendous increase in the recent decades. It has been observed that more than thirty million tons of pharmaceuticals are consumed worldwide. The used pharmaceutical products are not completely metabolized in human and animal body. Therefore, they are excreted to the environment and remain there as persistent organic chemicals. These compounds emerge as toxic contaminants in water and affect the human metabolism directly or indirectly. This literature review is an endeavour to understand the origin, applications and current advancement in the removal of pharmaceuticals from the environment. It discusses about the pharmaceuticals used in medical applications such diagnosis and disease treatment. In addition, it discusses about the recent approaches applied in pharmaceutical removal including microbial fuel cells, biofiltration, and bio nanotechnology approaches. Moreover, the challenges associated with pharmaceutical removal are presented considering biological and environmental factors. The review suggest the potential recommendations on pharmaceutical removal. 2023 The Authors -
Experimental and Theoretical Approach of Evaluating Chitosan Ferulic Acid Amide as an Effective Corrosion Inhibitor
Phenolic acid grafted chitosan has widespread drug delivery applications, as bio adsorbent, packing material, etc., due to its excellent antioxidant and antimicrobial properties. However, for the first time, the anticorrosive efficiency of ferulic acid modified chitosan has been investigated. The prepared chitosan derivative is characterized using spectral methods, thermal analytical methods, surface charge, and particle size analysis. The evaluation of corrosion inhibition potential showed a highest value of 95.96% at 303K. Thermodynamic activation and adsorption parameters endorse a mixed adsorption process involving an initial electrostatic interaction followed by chemisorption. Electrochemical studies gave results which agreed well with the gravimetric studies. Surface morphological studies were performed using contact angle measurements, FESEM, EDAX, AFM, optical profilometric and UV spectral techniques. Computational studies involving quantum chemical calculations, Monte Carlo and molecular dynamic simulation studies, and radial distribution function analysis are further done to validate the experimental results. Graphical Abstract: [Figure not available: see fulltext.] 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Revisiting the trade opennessunemployment nexus: anapplication of the novel JKS panel causality test with static anddynamic panel models
Purpose: This paper documents a robust empirical regularity: higher trade openness is associated with a lower unemployment rate. This paper also examines whether or not the effects of trade liberalisation depend on countries' income levels. Further, the dynamic causation between trade openness and unemployment is also examined. Design/methodology/approach: In order to obtain insight into the opennessunemployment nexus, following empirical methods were utilised - static panel models, dynamic panel models and a novel panel Granger causality approach proposed by Juodis etal. (2021). Findings: Results suggest that openness negatively affects unemployment; the extent to which trade liberalisation affects unemployment depends on the income level of each country. The Juodis, Karavias, and Sarafidis (JKS) test confirmed that the past values of trade openness, inflation, foreign direct investment and gross domestic product per capita contain information that helps to predict unemployment in a more robust manner. To simply put, opening upto trade may eventually become a requirement for creating more job opportunities, but this alone may not be enough. The extent to which nations benefit from trade liberalisation is largely dependent on the overall economic conditions and their capability to move up the income scale. Originality/value: A major difference between this study and those performed previously is that this study does not only examine the impact of trade openness on unemployment, but also investigates whether the unemployment effect of liberalisation is affected by countries' income levels an issue that has received little attention in the past. Additionally, the unique panel non-causality approach put forth by Juodis etal. (2021) is used in the first instance to look into the causal link between trade openness and unemployment. This method has advantages in that the method enables capturing Granger-causality in homogeneous or heterogeneous panels amongst multiple variables. 2023, Emerald Publishing Limited. -
The rise of new age social media influencers and their impact on the consumers' reaction and purchase intention
The internet revolution and digitisation have created innovative platforms and spokespersons for brands beyond traditional media. The marketing landscape for brands and customers is evolving towards a more personal and authentic approach; adopting various social media platforms and influencers creates more brand engagement. Influencers are the new third-party endorsers, catering to and recommending products to their loyal community of followers. The influencer and their fans/followers are a brands new storytellers. However, selecting the right influencer for a brands promotional strategy requires careful consideration of several factors. This paper aims to study the impact/effect of these variables, namely, endorsers credibility and corporate credibility, on consumers attitudes towards the brand and its impact on purchase intention, with respect to the millennial era. In the present study, 14 Likert-based questions were designed, asking the respondents to rank their choice of agreement on a scale of 1 to 5. The results were obtained through statistical analysis, including measuring the relationship between variables using confirmatory factor analysis and regression techniques. And the study found that corporate credibility has a significantly higher impact (approximately 90%) than individual endorsements (including those by celebrities) in enhancing customers brand perception. Copyright 2024 Inderscience Enterprises Ltd. -
How does geopolitical risk affect CO2 emissions? The role of natural resource rents
In a panel dataset of 38 developing and industrialized countries from 1970 to 2021, this study investigates how geopolitical risk and resource rents affect CO2 emissions. After implementing diagnostics, the paper observes significant relationships among CO2 emissions, geopolitical risk, natural resource rents, per capita income, and share of renewable energy in the long run. The panel data estimations show that geopolitical risk, natural resource rents, and per capita income increase CO2 emissions. However, the share of renewable energy is negatively associated with it. The mediation effect of geopolitical risk and natural resource rents on CO2 emissions is also positive. Potential policy repercussions are also discussed. 2023 Elsevier Ltd -
Did the Economic Reforms Change the Macroeconomic Drivers of the Indian Economy in the Post-Reform Era? An ARDL Bounds Test Approach
Purpose: The purpose of this study is to investigate the macroeconomic forces that have been driving the Indian economy during both the pre-reform and post-reform eras, that is, from 1950-1951 to 1990-1991 and from 1991-1992 to 2022-2023 respectively. Problem: The Indian economy underwent significant economic and financial sector reforms in 1991-92, with the goal of reviving its stagnant growth. These reforms are intended to spur the economic growth of India. What were the main forces behind the Indian economy before and after the reforms? Is the research question. The goal of the current study is to determine if the economic reforms shifted or maintained the pre-reform eras driving forces for the Indian economy in the post-reform era. Design/Methodology/Approach: The gross domestic product (GDP), the gross domestic savings (GDS), the private consumption expenditure (PFCE), the government final consumption expenditure (GFCE), the inflation rate, the exchange rate, the exports, the imports, the internal and external borrowings of the government, personal remittances, foreign direct investment (FDI), and foreign portfolio investments (FPI) are all taken into consideration in order to fill the research gap that has been identified as a result of the comprehensive review of the literature. Following an analysis of the selected variables' fundamental characteristics, an econometric model is developed using the Autoregressive Distributed Lag (ARDL) Bounds Test Model. Findings: There is no evidence of long-run causation and association between the variables, but the findings of the ARDL Bounds Test showed that in the pre-reform period, PFCE is the major driver of the GDP in the short-run, with strong support from imports. However, since the reform, PFCE, GDS, and Exports are the primary short-and long-term contributors to GDP. Practical Implication: These findings indicate that India's macroeconomic system is shifting. The Indian economy has undergone a dramatic shift, moving away from a reliance on imports and toward one that is consumer-driven and export-driven. As savings and consumer expenditures are the main drivers of the Indian economys growth in the post-reform era, policies should be designed to increase savings and consumption as well as increase exports. 2023, ASERS Publishing House. All rights reserved. -
Effect of age and gender on dietary patterns, mindful eating, body image and confidence
The emergence of Diet Culture came into existence with the era of pop culture, which emphasized the idea of body improvement by embracing the portrayal of unrealistic beauty standards set by the thin-ideal media. This growing and trending culture gained its popularity in India with the COVID pandemic and the imposed lockdown, wherein the prevalence of obesity and binge eating resulted from counter-regulatory eating behaviors and restrictive food intake to a greater extent of skipping meals to achieve the desired body type. The present empirical investigation focuses on understanding the gender and age-based differences (between the ages 18 to 55) among Indian population on dietary patterns, body image, mindful eating and physical appearance confidence using 2 3 factorial design. The tools used were Eating Behavior Pattern Questionnaire (EBPQ) [43], Body Self- image Questionnaire (BSIQ) [40], Mindful Eating Questionnaire (MEQ) [18] and Personal Evaluation Inventory (PEI) [44] were administered on a sample size of 120, selected using convenience sampling technique. The collected data was analyzed using SPSS Version 20.0. Results of the study reveal non-significant age and gender differences for mindful eating and appearance confidence. Significant age- differences were observed for Snacking and convenience F(2,114) = 6.22, p <.05; social dependence F(2,114) = 3.87, p <.05 and height dissatisfaction F(2,114) = 8.79, p <.05. And, significant gender differences were observed for Meal Skipping F(1,114) = 6.46, P <.05; snacking and convenience F(1,114) = 4.19, p <.05; fatness evaluation F(1,114) = 5.94, p <.05 and fitness evaluation F(1,114) = 5.33, p <.05. The only significant interaction effect observed was for social dependence dimension F(2, 114) = 3.96, p <.05. Thus, high exposure to social media and diet-related content contributed significantly to changing dietary patterns, and how they look, feel or perceive their body. 2023, BioMed Central Ltd., part of Springer Nature. -
Extreme photometric and polarimetric variability of blazar S4 0954+65 at its maximum optical and ?-ray brightness levels
In 2022 the BL Lac object S4 0954+65 underwent a major variability phase, reaching its historical maximum brightness in the optical and ?-ray bands. We present optical photometric and polarimetric data acquired by the Whole Earth Blazar Telescope (WEBT) Collaboration from 2022 April 6 to July 6. Many episodes of unprecedented fast variability were detected, implying an upper limit to the size of the emitting region as low as parsec. The WEBT data show rapid variability in both the degree and angle of polarization. We analyse different models to explain the polarization behaviour in the framework of a twisting jet model, which assumes that the long-term trend of the flux is produced by variations in the emitting region viewing angle. All the models can reproduce the average trend of the polarization degree, and can account for its general anticorrelation with the flux, but the dispersion of the data requires the presence of intrinsic mechanisms, such as turbulence, shocks, or magnetic reconnection. The WEBT optical data are compared to ?-ray data from the Fermi satellite. These are analysed with both fixed and adaptive binning procedures. We show that the strong correlation between optical and ?-ray data without measurable delay assumes different slopes in faint and high brightness states, and this is compatible with a scenario where in faint states we mainly see the imprint of the geometrical effects, while in bright states the synchrotron self-Compton process dominates. 2023 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
DMD Based Multi-Object Spectrograph for INdian Spectroscopic and Imaging Space Telescope: INSIST
INdian Spectroscopic and Imaging Space Telescope (INSIST) is the next-generation UV-Optical space mission proposed by the Indian Astronomical community motivated by the great success of India's first multi-wavelength Astronomical satellite (ASTROSAT) where Ultra Violet Imaging Telescope (UVIT) was one of the main payload launched in 2015 by Indian Space Research Organisation. INSIST is primarily designed for photometry observation in three bands (g-[400nm-550nm], u-[300nm-400nm] and UV-[150nm-300nm]) simultaneously over 0.25 sq.degree field of view. INSIST is equipped with a low resolution [R?500] spectrograph for multi-Object slitless spectroscopy over the imaging field of view and also has a medium resolution [R?2000] spectrograph for multi-object slit spectroscopy in UV-band over ?6 sq.arcmin sky. MEMS-based Digital Micromirror Device [DMD] is used to form configurable slits for the selection of objects at the focal plane of the telescope for multi-object slit spectrograph. Multi-Object spectrograph with DMD as a re-configurable slit for INSIST is designed and the performance of the spectrograph is presented. 2023 World Scientific Publishing Company. -
Distributed Feedback Laser (DFB) for Signal Power Amplitude Level Improvement in Long Spectral Band
This study outlines the distributed feedback laser for signal power amplitude level improvement in the long spectral band of 1550 nm wavelength within supporting pumped wavelength of 1480 nm. The bias and modulation peak currents based distributed feedback laser are varied in order to test the signal power level, peak signal amplitude variations after the fiber-optic channel and light detectors. The signal power level, peak signal amplitude is measured against spectral wavelength and time bit period variations. The study emphasis the signal power level, peak signal amplitude are enhanced for the best selection values of both a bias current at 45 mA and modulation peak current at 0.5 mA. 2023 Walter de Gruyter GmbH. All rights reserved. -
Durability and elevated temperature behaviour of geopolymer concrete developed with ground granulated blast furnace slag and sugarcane bagasse ash
In the current experimental study, the durability studies such as rapid chloride permeability, sorptivity and early and long-term effect of sulphate attack were conducted on GGBS-SCBA based geopolymer concrete. Also elevated temperature behaviour of geopolymer concrete specimen subjected to temperatures of 200?, 400?, 600? and 800? were studied to evaluate the strength, mass loss and effect on microstructures due to elevated temperature. The degradation of geopolymer concrete at elevated temperatures was observed by scanning electron microscope, energy dispersive X-ray analysis, X-ray diffraction analysis and Fourier transform infrared spectroscopy analysis. From the test findings it is observed that the geopolymer concrete developed have good durability characteristics. It is also observed that geopolymer concrete retains more than 50% of strength up to a temperature of 600?. From scanning electron microscope analysis of geopolymer concrete developed with GGBS and SCBA, it is found that there are larger crack formations and pores which are visible in the geopolymer concrete matrix when the specimens are exposed to an elevated temperature of 800? which confirms the degradation of CASH gel in the geopolymer concrete mixes developed. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Ensemble Deep Learning Approach for Turbidity Prediction of Dooskal Lake Using Remote Sensing Data
The summer season in India is marked by a severe shortage of water, which poses significant challenges for daily usage and agricultural practices. With unpredictable weather patterns and irregular rainfall, it is crucial to monitor and maintain water bodies such as domestic ponds and lakes in urban areas to ensure they provide clean and safe water for regular use, free from industrial pollutants. In this research paper, we propose an innovative ensemble deep learning approach (e-DLA) that leverages deep learning models to predict the turbidity of Dooskal Lake, located in Telangana, India, using remote sensing data. The proposed approach utilizes various deep learning models, including bagging, boosting, and stacking, to analyze the complex relationships between remote sensing data and turbidity levels in the lake. The study aims to provide accurate and efficient predictions of turbidity levels, which can aid in the management and conservation of water resources in the region. Hyperparameter tuning is employed, and dynamic climatic features are extracted and integrated with the ensemble learning global protective intelligent algorithm to reveal the complex relationship between in situ and measured values of turbidity during the measuring timeline. The proposed approach provides accurate predictions of turbidity levels, enabling the implementation of effective control measures to maintain water quality standards. Experimental results demonstrate that the proposed approach significantly reduces prediction errors compared to existing deep learning models. Overall, this research highlights the potential of machine learning techniques in monitoring and maintaining water resources, particularly in urban areas, to support sustainable water management and usage, and addresses an urgent and pressing issue in India and around the world. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Growth of mobile applications and the rise of privacy issues
Mobile apps are used by more and more internet users for daily chores, but processing personal data with them poses a major security risk. The wide range of data and sensors in mobile devices, the use of different types of identifiers and the increased ability to monitor consumers, the complex mobile application ecosystem and application developer limitations, and the extensive use of third-party technologies and services, are the main risks. Privacy concerns extend beyond mobile users. Corporate executives need fast, global access to their database. White goods/smart building equipment suppliers offer mobile apps for remote use. This research study will integrate these concerns. Due to these factors, smartphone applications have struggled to enforce the General Data Protection Regulations (GDPR) data protection rules. Mobile app designers and service providers may struggle to meet GDPR rules for data disclosure and permission, data protection by design and default, and operational secrecy. Copyright 2024 Inderscience Enterprises Ltd. -
Design and performance analysis of braking system in an electric vehicle using adaptive neural networks
Research article emphasizes on the impact of braking concepts considering regenerative braking system and energy consumption aspects in electric vehicles through a new perspective. The electric vehicle system is modeled and simulated using the MATLAB/Simulink software. A dataset is developed using the virtual simulation environment created by co-simulation using the MATLAB/Simulink and the IPG Carmaker software. This dataset is also used in a neural network model based on adaptive neuro fuzzy logic and the system performance is analyzed. Parameters considered for training the neural network are the brake pedal displacement, braking change rate and the need for brake application. The highlight of this study is the focus on a front wheel driven electric vehicle, which uses a standard drive cycle input to validate the model. The significant parameters evaluated in this study include the braking effects, kinetic energy, regenerative braking torque, battery state of the charge and the motor torque. The torque generation and its intended braking force requirements based on the acceleration, deceleration and braking conditions are the notable observations. The regenerative capability of this proposed system design is also illustrated along with the surface plots based on the training dataset. Investigation and analysis reveal that, the battery state of charge could be revived throughout the drive with a steady and stable increase. Transitions of motor torques between tractive and regenerative phases are also illustrated and explained for clarity and brevity. 2023 Elsevier Ltd -
Biosynthesis of ZnFe2O4@Ag hybrid nanocomposites for degradation of 2,4-Dichlorophenoxyacetic acid herbicide
This work demonstrates recent advancements in the phytosynthetic and environmentally friendly method of preparing ZnFe2O4 and ZnFe2O4@Ag hybrid nanocomposites using Pedalium murex L leaf extract as a stabilizing and reducing agent. The synthesized nanocomposite was characterized with UVvis, FTIR, TGA/DSC, XRD, FE-SEM, and EDX to investigate the electronic as well as morphological properties. Moreover, the photocatalytic behaviour of ZnFe2O4 and ZnFe2O4@Ag hybrid nanocomposites was evaluated with a breakdown of 2,4-dichlorophenoxyacetic acid (2,4-DPA) by exposing to UVVis light. The results obtained suggest that ZnFe2O4@Ag hybrid nanocomposite exhibited photocatalytic activity for the degradation of 2,4-DPA by approximately 94% in 60 min compared to ZnFe2O4. The hybrid nanostructure of ZnFe2O4@Ag significantly promoted charge transfer and prevented electron and hole recombination resulting in the enhancement of photocatalytic activity. Furthermore, ZnFe2O4@Ag nanocomposite showed the fair recyclable capacity for up to five catalytic cycles with an acceptable degradation percentage of 2,4-DPA. The findings of this study identify efficient charge transfer factor as a major contributor to the catalytic activity, with promising possibilities for the design of environmental remediation nanocomposite for harmful contaminants. 2023 The Author(s) -
Analysis of the Thomson and Troian velocity slip for the flow of ternary nanofluid past a stretching sheet
In this article, the flow of ternary nanofluid is analysed past a stretching sheet subjected to Thomson and Troian slip condition along with the temperature jump. The ternary nanofluid is formed by suspending three different types of nanoparticles namely TiO 2, Cu and Ag into water which acts as a base fluid and leads to the motion of nanoparticles. The high thermal conductivity and chemical stability of silver was the main cause for its suspension as the third nanoparticle into the hybrid nanofluid Cu-TiO 2/ H 2O. Thus, forming the ternary nanofluid Ag-Cu-TiO 2/ H 2O. The sheet is assumed to be vertically stretching where the gravitational force will have its impact in the form of free convection. Furthermore, the presence of radiation and heat source/sink is assumed so that the energy equation thus formed will be similar to most of the real life applications. The assumption mentioned here leads to the mathematical model framed using partial differential equations (PDE) which are further transformed to ordinary differential equations (ODE) using suitable similarity transformations. Thus, obtained system of equations is solved by incorporating the RKF-45 numerical technique. The results indicated that the increase in the suspension of silver nanoparticles enhanced the temperature and due to density, the velocity of the flow is reduced. The slip in the velocity decreased the flow speed while the temperature of the nanofluid was observed to be increasing. 2023, The Author(s). -
Memes as multimodal ensemble
Memes have now become a common medium of communication. There are multiple ways memes are considered in academia. Semiotics offers information on how the media and modes that memes consist of can be interpreted and how the characteristics of semiotic resources apply to memes. Drawing from a pool of memes collected during the Kerala assembly election in 2021, this research argues that certain memes need to be categorised as multimodal ensemble. Different modalities play different roles meaning construction, and they also collaborate with each other for a uniform purpose. By comparing existing memes defined in academia and multiple methodologies to analyse memes, the paper puts forth a framework to analyse memes. 2023 De Gruyter Mouton. All rights reserved. -
Machine Learning-Enabled NIR Spectroscopy. Part 3: Hyperparameter by Design (HyD) Based ANN-MLP Optimization, Model Generalizability, and Model Transferability
Data variations, library changes, and poorly tuned hyperparameters can cause failures in data-driven modelling. In such scenarios, model drift, a gradual shift in model performance, can lead to inaccurate predictions. Monitoring and mitigating drift are vital to maintain model effectiveness. USFDA and ICH regulate pharmaceutical variation with scientific risk-based approaches. In this study, the hyperparameter optimization for the Artificial Neural Network Multilayer Perceptron (ANN-MLP) was investigated using open-source data. The design of experiments (DoE) approach in combination with target drift prediction and statistical process control (SPC) was employed to achieve this objective. First, pre-screening and optimization DoEs were conducted on lab-scale data, serving as internal validation data, to identify the design space and control space. The regression performance metrics were carefully monitored to ensure the right set of hyperparameters was selected, optimizing the modelling time and storage requirements. Before extending the analysis to external validation data, a drift analysis on the target variable was performed. This aimed to determine if the external data fell within the studied range or required retraining of the model. Although a drift was observed, the external data remained well within the range of the internal validation data. Subsequently, trend analysis and process monitoring for the mean absolute error of the active content were conducted. The combined use of DoE, drift analysis, and SPC enabled trend analysis, ensuring that both current and external validation data met acceptance criteria. Out-of-specification and process control limits were determined, providing valuable insights into the models performance and overall reliability. This comprehensive approach allowed for robust hyperparameter optimization and effective management of model lifecycle, crucial in achieving accurate and dependable predictions in various real-world applications. Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s). -
Potential of banana based cellulose materials for advanced applications: A review on properties and technical challenges
Biocompatibility, biodegradability, and toxicity issues of synthetic polymers have propelled the search for environmentally friendly and non-toxic alternatives. In this context, biobased materials have gained much popularity due to their non-toxic, biodegradable, and sustainable nature. Bananas are considered as one of such natural material which fulfil the requirements to be tailored as a biocompatible biopolymer. Banana derived wastes can be used for extraction of commercially important biopolymers like starch, cellulose, nanocellulose and their subsequent utilization in wide variety of applications. Banana derived biopolymers and their bio composites and widely used for medical applications such as wound healing, fabrication of bone plates, cellulose based gate dielectrics, and capacitors for insulin pumps, and pacemakers. In addition, banana based nanocellulose can be used in tissue engineering, biosensing, drug delivery, bioimaging, wound healing, enzyme immobilization and preparation of tablets for oral administration. Moreover, banana-based polymers can be employed in applications such as food packaging, biofuel production, and production of multilayered papers. Considering the potential applications of banana-based nanomaterials, this review work is framed to understand the process of extraction of starch, cellulose, nanocellulose and biopolymers from banana derived wastes with specific emphasis on their extraction methods and composite preparation methods. In addition, it discusses in detail the promising and potential applications of the derived materials in health and environmental sectors. The presented review is a comprehensive discussion on banana-based waste conversion strategies to produce value added products useful in medical and environmental applications. 2023 The Author(s)