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A novel survey for young substellar objects with the W-band filter IV: detection and characterization of low-mass brown dwarfs in Serpens Core
We present spectroscopic confirmation of nine M5 or later Serpens Core candidate members, identified using a combination of CFHT WIRCam photometry and IRTF SpeX spectroscopy. Through spectral fitting, we find that the latest of these nine candidate members is best fit by an L0 spectral standard (in the range of M8L2), implying a mass of ?0.010.035M?. If confirmed as a cluster member, this would be one of the lowest mass Serpens Core objects ever discovered. We present analysis of the physical properties of the sample, as well as the likely membership of the candidate Serpens Core members. 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Stratified Bioconvective Jet Flow of Williamson Nanofluid in Porous Medium in the Presence of Arrhenius Activation Energy
Due to the higher coefficients of heat and mass transfer, the jet flow has become an effective source for the transfer of heat and mass in various industries. Due to these high coefficients, the heat and mass transfer rates will be high in the appliances equipped with the jet flow. Further, the existence of the magnetic field helps in controlling the velocity and the presence of the gyrotactic microorganisms ensure proper mixing of nanoparticles. A dilute nanoparticle suspension is assumed so that it will not affect the movement of motile cells that leads to bioconvection. Hence, this paper aims to analyze the characteristics of heat transfer as well as mass transfer of the jet flow of Williamson nanofluid past a porous stretching sheet in the existence of microorganisms. The mathematical model obtained as a result of these assumptions is transformed into nonlinear ordinary differential equations for which acceptable solutions are obtained using the numerical method. The results thus obtained are presented graphically and based on the outcomes, it is perceived that the magnetic field has control over the velocity profile thus influencing the thermal profile. The increase in the Williamson parameter also reduces the velocity of the fluid flow. Further, an increase was noticed in the thermal and concentration profiles of the nanofluid for higher values of thermophoresis parameter and the increase in the porosity reduced the speed of the flow of nanofluid. 2023 World Scientific Publishing Company. -
Protection of Artificial Intelligence Autonomously Generated Works under the Copyright Act, 1957-An Analytical Study
Artificial Intelligence (AI) is not new anymore; it has become a new normal. In the present 3A era (Advanced, automated and autonomous), the Next Rembrandt paintings, Shimons lyrics and songs and Bot Dylans Irish folk songs are the works generated by the AI without any considerable human contribution. In the US, the Copyright Act, 1976 does not protect the works generated independently by the AI without human intervention and thus dropping such works in the public domain immediately after their creation. However, in the UK, the Copyright, Patents and the Designs Act, 1988 under Section 9 (3) attributes copyright to the person by whom the arrangements necessary for the creation of the work are undertaken in case of AI generated works. India has taken a giant leap by considering AI as the joint author along with the human responsible for the creation of work. However, there is not much comprehensive literature available that focuses on the impact of AI being considered as a joint author. This paper aims to create a concrete foundation by emphasising such impact under the Copyright Act, 1957. Furthermore, the paper considers the stance of the US, UK and Australia in protecting AI generated works to suggest measures to the current copyright regime in India. 2023, National Institute of Science Communication and Policy Research. All rights reserved. -
IEEHR: Improved Energy Efficient Honeycomb Based Routing in MANET for Improving Network Performance and Longevity
In present scenario, efficient energy conservation has been the greatest focus in Mobile Adhoc Networks (MANETs). Typically, the energy consumption rate of dense networks is to be reduced by proper topological management. Honeycomb based model is an efficient parallel computing technique, which can manage the topological structures in a promising manner. Moreover, discovering optimal routes in MANET is the most significant task, to be considered with energy efficiency. With that motive, this paper presents a model called Improved Energy Efficient Honeycomb based Routing (IEEHR) in MANET. The model combines the Honeycomb based area coverage with Location-Aided Routing (LAR), thereby reducing the broadcasting range during the process of path finding. In addition to optimal routing, energy has to be effectively utilized in MANET, since the mobile nodes have energy constraints. When the energy is effectively consumed in a network, the network performance and the network longevity will be increased in respective manner. Here, more amount of energy is preserved during the sleeping state of the mobile nodes, which are further consumed during the process of optimal routing. The designed model has been implemented and analyzed with NS-2 Network Simulator based on the performance factors such as Energy Efficiency, Transmission Delay, Packet Delivery Ratio and Network Lifetime. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Computer Vision Based Automatic Margin Computation Model for Digital Document Images
Margin, in typography, is described as the space between the text content and the document edges and is often essential information for the consumer of the document, digital or physical. In the present age of digital disruption, it is customary to store and retrieve documents digitally and retrieve information automatically from the documents when necessary. Margin is one such non-textual information that becomes important for some business processes, and the demand for computing margins algorithmically mounts to facilitate RPA. We propose a computer vision-based text localization model, utilizing classical DIP techniques such as smoothing, thresholding, and morphological transformation to programmatically compute the top, left, right, and bottom margins within a digital document image. The proposed model has been experimented with different noise filters and structural elements of various shapes and size to finalize the bilateral filter and lines and structural elements for the removal of noises most commonly occurring due to scans. The proposed model is targeted towards text document images and not the natural scene images. Hence, the existing benchmark models developed for text localization in natural scene images have not performed with the expected accuracy. The model is validated with 485 document images of a real-time business process of a reputed TI company. The results show that 91.34 % of the document images have conferred more than 90 % IoU value which is well beyond the accuracy range determined by the company for that specific process. 2023, Crown. -
Artemisia stelleriana-mediated ZnO nanoparticles for textile dye treatment: a green and sustainable approach
Textile effluents being one of the major reasons for water pollution raises major concern for water bodies and the habitation surrounding them. The lack of biologically safer treatment solutions creates a major concern for the disposal of these effluents. The present study focuses on the degradation of textile dyes using leaf extract of Artemisia stelleriana-assisted nanoparticles of zinc oxide (ZnO-NPs). ZnO NPs synthesized were confirmed using spectroscopic, X-ray diffraction and microscopic analysis. The current research utilizes widely used major textile dyes, Reactive Yellow-145 (RY-145), Reactive Red-120 (RR-120), Reactive Blue-220 (RB-220) and Reactive Blue-222A (RB-222A), which are released accidentally or due to the non-availability of cost-effi-cient, dependable and environment-friendly degradation methods, making this work a much-needed one for preventing the discharge before treatment. The biosynthesized ZnO-NPs were top-notch catalysts for the reduction of these dyes, which is witnessed by a gradual decrease in absorbance maximum values. After 320 min, ZnO-NPs under UV light exposure showed 99, 95, 94 and 45% degradations of RY-145, RR-120, RB-220 and RB-222A dyes, respectively. The phytotoxicity study conducted at two trophic levels revealed that the A. stelleriana-mediated ZnO-NPs have great potential for the degradation of textile dyes, allowing them to be scaled up to large-scale treatments. 2023 The Authors. -
Intentions to adopt the blockchain: investigation of the retail supply chain
Purpose: Blockchain can track the material from the manufacturer to the end customers. Therefore, it can ensure the product's authenticity, transparency and trust in the retail supply chain (SC). There is a need to trace and track the retail products before it reaches the customers to check the quality of the products so that expired products can be recycled and reused, which in turn will help gain customers' trust. This research aims to investigate retail employees' behavioural intention to adopt blockchain in the retail SC. Design/methodology/approach: To examine the behavioural intention of employees in the retail SC, the research uses three theories the technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour. The technology acceptance model measures the employee's acceptance of blockchain in the retail SC. The unified theory of acceptance is used in this research to measure how blockchain adoption will improve the performance of the employees. The theory of planned behaviour is used in this research to measure whether the employees intend to adopt blockchain. A survey was carried out in the retail stores of India. Exploratory factor analysis and structural equation modelling were used for data analysis. Findings: This study found that the employees of the retail stores have a positive intention and attitude to adopt blockchain technology. Further, it was found that perceived behavioural control and effort expectancy was not promoting blockchain adoption in the retail sector. Practical implications: This study will help the retail stores' employees understand the blockchain in their operations and will motivate the top management of the retail companies to adopt this technology. The study is limited to the retail SC in India only. Originality/value: This study uses three theories technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour, which were not used in earlier studies of blockchain adoption in the retail SC. 2023, Emerald Publishing Limited. -
Influence of composite mixtures between nematic liquid crystal and porous carbon nanoparticles towards photoluminescence and UV absorbance
The optical parameters of the liquid crystalline materials can be tuned by the dispersion of nanoparticles. Concentration of dopant in the host LC material affects its optical properties significantly, which makes the dispersed system suitable for LC-based devices. In the present investigation, we have studied the effect of different concentrations of nanoparticles on the optical properties of LC, as a guesthost system, where PCNP is guest material and NLC is host material. Porous carbon nanoparticles (PCNPs) were dispersed into the nematic liquid crystal (NLC) in three different concentrations. Optical parameters were measured for pure NLC and NLC-PCNP composites. Photoluminescence (PL) study was performed and it was found that the PL intensity increased for the PCNP dispersed system. High photoluminescence has much importance in the luminescent displays. Full width half maxima (FWHM) were also determined by the Gaussian fitting of PL intensity data. UV absorbance was also measured which gets increased for the PCNP dispersed NLC system when compared to pure NLC. Optical bandgap was found to be reduced after the dispersion of PCNP into NLC. Several other parameters such as absorption coefficient and optical density were also determined. The proposed work may be significant for the liquid crystal displays (LCDs) and other devices which require less bandgap materials. This work may also put some light on the effect of dopants on the LC material in the research based on guesthost system. Increasing the photoluminescence and creating less bandgap materials using carbon nanoparticles is a real challenge, and porous nanoparticles used here overcome this challenge. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature. -
Enhanced Security for Large-Scale 6G Cloud Computing: A Novel Approach to Identity based Encryption Key Generation
Cloud computing and 6G networks are in high demand at present due to their appealing features as well as the security of data stored in the cloud. There are various challenging methods that are computationally complicated that can be used in cloud security. Identity-based encryption (IBE) is the most widely used techniques for protecting data transmitted over the cloud. To prevent a malicious attack, it is an access policy that restricts access to legible data to only authorized users. The four stages of IBE are setup, key extraction or generation, decryption and encryption. Key generation is a necessary and time-consuming phase in the creation of a security key. The creation of uncrackable and non-derivable secure keys is a difficult computational and decisional task. In order to prevent user identities from being leaked, even if an opponent or attacker manages to encrypted material or to decode the key this study presents an advanced identity-based encryption technique with an equality test. The results of the experiments demonstrate that the proposed algorithm encrypts and decrypts data faster than the efficient selective-ID secure IBE strategy, a competitive approach. The proposed method's ability to conceal the identity of the user by utilizing the Lagrange coefficient, which is constituted of a polynomial interpolation function, is one of its most significant aspects. 2023 The Authors. Published by AnaPub Publications. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/) -
GCMS analysis, anthelmintic, antibacterial and antifungal properties of unripe fruit peel extract of Musa paradisiaca L.
Endoparasites, namely, Ascaris sp., Taenia sp., Haemonchus contortus, Ancylostoma duodenale etc. are of serious concern since they can lead to financial loss if farm animals are attacked by these parasites. Finding out cost-effective natural remedies for these infections is an area of research in the field of veterinary sciences. The current study was undertaken with a view to explore the anthelmintic property of banana peel along with its other bioactive properties. The fruit is available abundantly throughout the year and the peel is often discarded as waste. This study has shown that the extracts of the Nendran variety of Musa paradisiaca L. fruit peel have potent anthelmintic, antibacterial and antifungal activities. Preliminary cytotoxicity studies have also given positive results. GCMS analysis has revealed the major phytochemicals responsible for the bioactive properties of the peel. Since the United Nations has urged countries to align research and development with a thrust on sustainable development, these kinds of natural alternatives are best suited in place of synthetic drugs. 2023 World Research Association. All rights reserved. -
Organisational justice, job performance and work engagement: The mediating role of perceived supervisory support
The study establishes a relationship between organisational justice, work engagement, job performance, perceived supervisory support and their sub-dimensions. The major research objectives of the study were to check if perceived supervisory support does mediate between organisational justice, work engagement and job performance of faculty in higher educational institutions. A research model was framed and tested to determine the direct and indirect effect of justice of faculty members on work engagement and job performance in the presence of supervisory support in higher education sector. The present study is based on 912 faculty members of higher educational institutions. Five valid, reliable and standard questionnaires were adopted to collect primary data from the higher educational institutions' faculty members in south India. From the study, it is proved that perceived supervisory support partially mediates organisational justice, work engagement and job performance. 2023 British Educational Research Association. -
Machine Learning and Artificial Intelligence Techniques for Detecting Driver Drowsiness
The number of automobiles on the road grows in lockstep with the advancement of vehicle manufacturing. Road accidents appear to be on the rise, owing to this growing proliferation of vehicles. Accidents frequently occur in our daily lives, and are the top ten causes of mortality from injuries globally. It is now an important component of the worldwide public health burden. Every year, an estimated 1.2 million people are killed in car accidents. Driver drowsiness and weariness are major contributors to traffic accidents this study relies on computer software and photographs, as well as a Convolutional Neural Network (CNN), to assess whether a motorist is tired. The Driver Drowsiness System is built on the Multi-Layer Feed-Forward Network concept CNN was created using around 7,000 photos of eyes in both sleepiness and non-drowsiness phases with various face layouts. These photos were divided into two datasets: training (80% of the images) and testing (20% of the images). For training purposes, the pictures in the training dataset are fed into the network. To decrease information loss as much as feasible, backpropagation techniques and optimizers are applied. We developed an algorithm to calculate ROI as well as track and evaluate motor and visual impacts. 2022 Boppuru Rudra Prathap et al., published by Sciendo. -
UVIT Observations of the Small Magellanic Cloud: Point-source Catalog
Three fields in the outskirts of the Small Magellanic Cloud were observed by the UltraViolet Imaging Telescope (UVIT) on board AstroSat, between 2017 December 31 and 2018 January 1. The observations were carried out on a total of seven filters, three in the far-ultraviolet (FUV; 1300-1800 band and four in the near-ultraviolet (NUV; 2000-3000 band. We carried out photometry of these observations that have a spatial resolution better than 1.?5. We present here the first results of this work, which is a matched catalog of 11,241 sources detected in three FUV and four NUV wavelengths. We make the catalog available online, which would be of use to the astronomical community to address a wide variety of astrophysical problems. We provide an expression to estimate the total count rate in the full point-spread function of UVIT that also incorporates the effect of saturation. 2023. The Author(s). Published by the American Astronomical Society. -
Cost effective porous areca nut carbon nanospheres for adsorptive removal of dyes and their binary mixtures
Novel porous nanospheres from areca nuts (ACNPs) were synthesized via one-step pyrolysis without the use of any chemical treatment and the materials were used as adsorbents for the removal of cationic methylene blue (MB) and anionic methyl orange (MO) as well as their binary mixtures. Around, 67 tonnes of areca nut biowaste is generated every year which are then burnt due to their slow rate of decomposition resulting in higher carbon footprints. Biosorbents are generally a preferable alternative for dye adsorption but involve chemical modification for surface enhancement and complex sample treatment. In this work, ACNPs, were investigated for their efficiency in the raw form and were characterized by SEM, EDS, FTIR, XRD, and BET techniques before and after subjecting to the dye adsorption studies. The BET analysis of the adsorbents showed a high specific surface area of 693.8 m2/g when prepared at 1000 C, while the N2 adsorption-desorption plot showed type-IV isotherm, suggesting the microporous nature of the carbon matrix. Batch equilibrium studies showed the removal efficiency of >95% for both the dyes and their binary mixtures under the optimum conditions of 0.15 g/L dosage, 10 ?M concentration and contact time of 70 min. Due to the synergistic effects of the binary dyes, higher removal efficiency of MB compared to MO was observed in the binary mixture. Adsorption results were tested using Langmuir, Freundlich, Temkin, Redlich-Peterson, and Elovich isotherms to assess the best fit of the models. The qm value of MB was found to be 97.37 mg/g, while that of MO was 71.22 mg/g which is higher compared to individual dye components having lower values of 86.12 mg/g and 50.35 mg/g, respectively. Extended Langmuir and Jain and Snoeyink isotherms were used for binary data interpretation. The kinetic results showed good agreement with the Pseudo-second order equation, indicating internal diffusion. The possible mechanism involved electrostatic and ?-? interactions between the dye molecules and ACNPs. This approach is comprehensible and cost effective and can be utilized for dye removal in textile industries. 2023 Elsevier Inc. -
Water is life and death: Symbolic representation in all customs and rituals in India
For the Koch, Koch Rajbongshi, and Rajbanshi people of India, water is central to their culture. They share river music and ancestry. They lost their language in 1931 and split into three or more clans due to flood relocation. They also introduced food, the river, the sun, the moon, the bamboo tree, and cactus plant worship to the highlands. The parent group was identified as tribal in the 1931 census. Still, the Indian government could not grant Koch, Koch Rajbongshi, and Rajbanshi scheduled tribe status for Assam and conserve their culture, traditions, and language. Indian scientists are trying to solve Assam's centuries-old flood issues, which are worsening. The new Indian water framework must treat water access and value of water resources as essentially good and human rights issues. India must review its Assam flood failures and compensate locals. Assam needs political, social, economic, and administrative procedures to develop and manage water resources and offer services at different societal levels. 2023 Policy Studies Organization. -
Investigating sustainable development for the COVID-19 vaccine supply chain: a structural equation modelling approach
Purpose: Immunization is one of the most cost-effective ways to save lives while promoting good health and happiness. The coronavirus disease 2019 (COVID-19) pandemic has served as a stark reminder of vaccines' ability to prevent transmission, save lives, and have a healthier, safer and more prosperous future. This research investigates the sustainable development (SD) of the COVID-19 vaccine supply chain (VSC). Design/methodology/approach: This study investigates the relationship between internal process, organizational growth, and its three pillars of SD environmental sustainability, economic sustainability and social sustainability. Survey-based research is carried out in the hospitals providing COVID-19 vaccines. Nine hypotheses are proposed for the study, and all the hypotheses got accepted. The survey was sent to 428 respondents and received 291 responses from health professionals with a response rate of 68%. For the study, the healthcare professionals working in both private and public hospitals across India were selected. Findings: The structural equation modelling (SEM) approach is used to test the hypothesis. All nine hypotheses are supported. This study examines a link between internal processes and organizational learning and the three sustainability pillars (environmental sustainability, economic sustainability and social sustainability). Practical implications: This study will help the management and the policymakers to think and adopt SD in the COVID-19 VSC. This paper also implies that robust immunization systems will be required in the future to ensure that people worldwide are protected from COVID-19 and other diseases. Originality/value: This paper shows the relationship between organizational learning and internal process with environmental sustainability, economic sustainability and social sustainability for the COVID-19. Studies on VSC of COVID-19 are not evident in any previous literature. 2022, Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka, Surya Kant Pal and Ramji Nagariya. -
CoFe2O4/g-C3N4 intercalated Ti3C2 MXene for efficient electrocatalytic hydrogen evolution reaction
Seeking high-efficiency and stable electrocatalysts remains key to boosting electrocatalytic water splitting. Herein, a well-designed nontoxic MXene based composite, Ti3C2-CoFe2O4/g-C3N4 is prepared via ultrasonication for enhancing the hydrogen evolution reaction (HER). Intercalation of CoFe2O4 and g-C3N4 within the multi-layered Ti3C2 MXene results in improved properties such as high surface area, large pore volume, and a low restacking tendency that leads to enhanced electrochemical active sites, high charge carrier separation, and stability. The prepared composite is characterized via various physicochemical techniques. The amalgamated composite shows a lower overpotential of 223 mV in an alkaline medium at a current density of 10 mA cm?2. The Tafel slope and charge transfer resistance (Rct) value for the HER are 48.5 mV dec?1 and 3.94 ?, respectively. The heterojunction formation improves the efficacy of the MXene composite and provides a new perception that can be beneficial for water splitting applications. 2023 The Royal Society of Chemistry. -
HHO-Based Vector Quantization Technique for Biomedical Image Compression in Cloud Computing
In the present digital era, the exploitation of medical technologies and massive generation of medical data using different imaging modalities, adequate storage, management, and transmission of biomedical images necessitate image compression techniques. Vector quantization (VQ) is an effective image compression approach, and the widely employed VQ technique is Linde-Buzo-Gray (LBG), which generates local optimum codebooks for image compression. The codebook construction is treated as an optimization issue solved with utilization of metaheuristic optimization techniques. In this view, this paper designs an effective biomedical image compression technique in the cloud computing (CC) environment using Harris Hawks Optimization (HHO)-based LBG techniques. The HHO-LBG algorithm achieves a smooth transition among exploration as well as exploitation. To investigate the better performance of the HHO-LBG technique, an extensive set of simulations was carried out on benchmark biomedical images. The proposed HHO-LBG technique has accomplished promising results in terms of compression performance and reconstructed image quality. 2023 World Scientific Publishing Company. -
FO-DPSO Algorithm for Segmentation and Detection of Diabetic Mellitus for Ulcers
In recent days, the major concern for diabetic patients is foot ulcers. According to the survey, among 15 people among 100 are suffering from this foot ulcer. The wound or ulcer found which is found in diabetic patients consumes more time to heal, also required more conscious treatment. Foot ulcers may lead to deleterious danger condition and also may be the cause for loss of limb. By understanding this grim condition, this paper proposes Fractional-Order Darwinian Particle Swarm Optimization (FO-DPSO) technique for analyzing foot ulcer 2D color images. This paper deals with standard image processing, i.e. efficient segmentation using FO-DPSO algorithm and extracting textural features using Gray Level Co-occurrence Matrix (GLCM) technique. The whole effort projected results as accuracy of 91.2%, sensitivity of 100% and specificity as 96.7% for Nae Bayes classifier and accuracy of 91.2%, sensitivity of 100% and sensitivity of 79.6% for Hoeffding tree classifier. 2023 World Scientific Publishing Company. -
Multi-atlas Graph Convolutional Networks and Convolutional Recurrent Neural Networks-Based Ensemble Learning for Classification of Autism Spectrum Disorders
Autism spectrum disorder (ASD) has an influence on social conversation and interaction, as well as encouraging people to engage in repetitive behaviors. The complication begins in childhood and persists through adolescence and maturity. Autism spectrum disorder has become the most common kind of childhood development worldwide. ASD hinders the capacity to interact, socialize, and build connections with individuals of all ages, and thus its early intervention is critical. This paper discusses some of the most recent approaches to diagnostics using convolutional networks and multi-atlas graphs for autism spectrum disorders. Also, several pre-processing approaches are elaborated. Graph convolutional neural networks (GCNs) to diagnose autism spectrum disorder (ASD) because of their remarkable effectiveness in illness prediction using multi-site data. Convolutional neural network (CNN) and recurrent neural networks (RNN) infrastructure studies functional connection patterns between various brain regions to find particular patterns to diagnose ASD. In our research, we implemented the GCN + CRNN ensemble method and achieved 89.01% accuracy based on resting-state data from the fMRI (ABIDE-II), a novel framework for detecting early signs of autism spectrum disorders is presented and discussed. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.