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Cyclic property of iterative eccentrication of a graph
The eccentric graph of a graph G, denoted by Ge, is a derived graph with the vertex set same as that of G and two vertices in Ge are adjacent if one of them is an eccentric vertex of the other. The process of constructing iterative eccentric graphs, denoted by Gek is called eccentrication. A graph G is said to be ?-cyclic(t,l) if G,Ge,Ge2,...,Gek,Gek+1,...,Gek+l are the only non-isomorphic graphs, and the graph Gek+l+1 is isomorphic to Gek. In this paper, we prove the existence of an ?-cycle for any simple graph. The importance of this result lies in the fact that the enumeration of eccentrication of a graph reduces to a finite problem. Furthermore, the enumeration of a corresponding sequence of graph parameters such as chromatic number, domination number, independence number, minimum and maximum degree, etc., reduces to a finite problem. 2023 World Scientific Publishing Company. -
Soft grafting of DNA over hexagonal copper sulfide for low-power memristor switching
Green electronics, where functional organic/bio-materials that are biocompatible and easily disposable are implemented in electronic devices, have gained profound interest. DNA is the best biomolecule in existence that shows data storage capacity, in virtue of the sequential arrangement of AT and GC base pairs, analogous to the coding of binary numbers in computers. In the present work, a robust, uniform and repeatable room-temperature resistive switching in a Cu/Cu2S/DNA/Au heterojunction is demonstrated. The DNA nanostructures were anchored on the densely packed hexagonal Cu2S structures by simple electrochemical deposition. This heterostructure presents outstanding memristor behavior; the device exhibits resistive switching at a very low threshold voltage of 0.2 V and has a relatively high ON/OFF ratio of more than 102 with a good cycling stability of ?1000 cycles and a negligible amount of variation. The justification for such a switching mechanism is also given on the basis of the energy-band diagram of the Cu2S-DNA interface. Based on the studies herein, the resistive switching is attributed to the reversible doping of DNA by Cu+ ions, leading to intrinsic trap states. Further, the switching is modeled with the help of different transport mechanisms, like Schottky-barrier emission, Poole-Frenkel emission and Fowler-Nordheim tunneling. 2023 The Author(s). -
Lexical Richness of Adolescents Across Multimodalities: Measures, Issues and Future Directions
Lexical Richness (LR) is a scarcely researched subject in India. The objective of this paper is twofold: (i) To statistically inquire whether LR varies across three multimodalities: visual-only, audio-only, and audio-visual; and (ii) To see which of the two measures of LR (MATTR and Guiraud) is independent of text length and is best suited for short oral productions. 270 students across three types of schools were examined, out of whom 100 willingly completed all three oral tasks. The students were asked to retell the stories transacted in each modality in their own words. Randomization of sampling is done to mitigate the confounding modality bias. Additionally, the genre and parts of the storyline in each modality are similar. The students oral speech samples were recorded, transcribed and analyzed on WordCruncher and TextElixir software. The results revealed that there is statistically significant variance among the modalities. Furthermore, the Moving Average Type Token Ratio (MATTR) is seen to be independent of text length compared to Index of Guiraud. This study also throws light on the observations made during the study, pertinent issues in the field of education, and future directions for research on LR. 2023 IUP. All Rights Reserved. -
Phytoextract-mediated synthesis of Cu doped NiO nanoparticle using cullon tomentosum plant extract with efficient antibacterial and anticancer property
In the present study, nickel oxide (NiO) and copper-doped nickel oxide (NiCuO) nanoparticles (NPs) were successfully synthesized using Cullen tomentosum plant extract with the co-precipitation method. This work focuses on the Phyto-mediated synthesis and characterization of NPs for their biological applications. Phytochemicals that exist in the plant extract acts as reducing and capping agent. The successful formation of the NPs was validated by various analysis as XRD, FESEM, EDAX, FT-IR, UVVis, and Photoluminescence. According to XRD studies, the average crystallite size of NiO and NiCuO NPs is 36 nm and 31 nm, respectively. The river stone and nanoflower like morphology for NiO and NiCuO NPs are confirmed by FESEM image. Furthermore, the synthesized NPs were tested against Gram-positive (Bacillus subtilis, Streptococcus pneumoniae) and Gram-negative (Klebsiella pneumoniae, Escherichia coli) bacteria, which showed enhanced antibacterial activity of NiCuO NPs. The cytotoxicity of NPs was investigated against human breast cancer cells (MDA-MB-231) and fibroblast L929 cell lines. Also, the IC50 value for human breast cancer cells is 11.8 ?g/mL. According to these findings, NiCuO NPs are potential nanomaterials with advanced healthcare uses. 2023 -
Analysis and prediction of seed quality using machine learning
The mainstay of the economy has always been agriculture, and the majority of tasks are still carried out without the use of modern technology. Currently, the ability of human intelligence to forecast seed quality is used. Because it lacks a validation method, the existing seed prediction analysis is ineffective. Here, we have tried to create a prediction model that uses machine learning algorithms to forecast seed quality, leading to high crop yield and high-quality harvests. For precise seed categorization, this model was created using convolutional neural networks and trained using the seed dataset. Using data that can be used to forecast the future, this model is used to learn about whether the seeds are of premium quality, standard quality, or regular quality. While testing data are employed in the algorithms predictive analytics, training data and validation data are used for categorization reasons. Thus, by examining the training accuracy of the convolution neural network (CNN) model and the prediction accuracy of the algorithm, the projects primary goal is to develop the best method for the more accurate prediction of seed quality. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Energy Harvesting Using ZnO Nanosheet-Decorated 3D-Printed Fabrics
In this work, we decorated piezoresponsive atomically thin ZnO nanosheets on a polymer surface using additive manufacturing (three-dimensional (3D) printing) technology to demonstrate electrical-mechanical coupling phenomena. The output voltage response of the 3D-printed architecture was regulated by varying the external mechanical pressures. Additionally, we have shown energy generation by placing the 3D-printed fabric on the padded shoulder strap of a bag with a load ranging from ?5 to ?75 N, taking advantage of the excellent mechanical strength and flexibility of the coated 3D-printed architecture. The ZnO coating layer forms a stable interface between ZnO nanosheets and the fabric, as confirmed by combining density functional theory (DFT) and electrical measurements. This effectively improves the output performance of the 3D-printed fabric by enhancing the charge transfer at the interface. Therefore, the present work can be used to build a new infrastructure for next-generation energy harvesters capable of carrying out several structural and functional responsibilities. 2023 American Chemical Society. -
A novel route for isomerization of ?-pinene oxide at room temperature under irradiation of light-emitting diodes
Present investigation demonstrates the potential use of HY-zeolite for photochemical applications in the selective isomerization of ?-pinene oxide to carveol. In this study, ultraviolet lamp and LED (390 nm) light sources were employed under atmospheric conditions. The results revealed that light penetration through protonated zeolite cavity promotes the hydrogen radical formation, facilitating the isomerization reaction in the presence of dimethylacetamide solvent to achieve up to 60% and 40% conversion of ?-pinene oxide to selective carveol (71%) under light irradiation. Here, using in situ spectroscopic studies (EPR and fluorescence), to confirm the hydrogen radical generation after light irradiation on the reaction mixture. Besides, the mechanistic pathway is proposed based on the experimental evidence of the formation of radicals, which is validated by the Density Functional Theory (DFT). By comparing electrical energy consumption for the same reaction using different reaction setups, it is understood that the energy requirement is nearly the same in the case of a reaction performed using a thermal reactor. The power consumption in reactions conducted using thermal, UV lamp and LED-based reactors was 1.6 kW/h, 1.5 kW/h, and 0.00144 kW/h, respectively. It is clear that the energy consumption in thermal and UV lamp-based reactors is higher than that of LED-based reactors, which was 1111 and 1041 times more than LED reactors respectively. Notably, the catalyst was found to be recyclable at least five consecutive runs, and the successful protocol was demonstrated up to 50 g scale. 2023 Elsevier Ltd -
Certain types of metrics on almost coKler manifolds
In this paper, we study an almost coKler manifold admitting certain metrics such as ? -Ricci solitons, satisfying the critical point equation (CPE) or Bach flat. First, we consider a coKler 3-manifold (M,g) admitting a ? -Ricci soliton (g,X) and we show in this case that either M is locally flat or X is an infinitesimal contact transformation. Next, we study non-coKler (?, ?) -almost coKler metrics as CPE metrics and prove that such a g cannot be a solution of CPE with non-trivial function f. Finally, we prove that a (?, ?) -almost coKler manifold (M,g) is coKler if either M admits a divergence free Cotton tensor or the metric g is Bach flat. In contrast to this, we show by a suitable example that there are Bach flat almost coKler manifolds which are non-coKler. 2021, Fondation Carl-Herz and Springer Nature Switzerland AG. -
Towards developing an automated technique for glaucomatous image classification and diagnosis (AT-GICD) using neural networks
Glaucoma is the eye defect that has become the second leading cause of blindness worldwide and also stated as incurable, may cause complete vision loss. The earlier diagnosis of glaucoma in Human Eye is a great confrontation and very important in present scenario, for providing efficient and appropriate treatments to the persons. Though there is much advancement in Ocular Imaging that affords methods for earlier detection, the appropriate results can be obtained by integrating the data from structural and functional evaluations. With that note, this paper involves in developing automated technique for glaucomatous image classification and diagnosis (AT-GICD). The model considers both the textural and energy features for effectively diagnosing the defect. Image Segmentation is processed for obtaining the exact area of optic nerve head; histogram gradient based conversion is employed for enhancing the fundus image features. Further, Wavelet Energy features are extracted and applied to the artificial neural networks (ANN) for classifying the NORMAL and GLAUCOMA images. The Accuracy rate based comparison with other existing models is carried out for evidencing the effectiveness of the proposed model in glaucomatous image classification. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
Development of smart energy monitoring using NB-IOT and cloud
IoT-based applications are growing in popularity nowadays because they offer effective answers to numerous current problems. In this research, With the aim of decreasing human efforts for monitoring the power units and increasing users' knowledge of excessive electricity usage, an IoT-based electric metre surveillance system utilising an Android platform has been developed. With the help of an Arduino Uno and an optical sensor, the electric analyser pulse is captured. To reduce human mistake and the expense of energy usage, a low-cost wireless network of sensors for digital energy metres is implemented alongside a smartphone application that can autonomously read the metre of the unit. In this research, an intelligent power monitoring system with effective communication modules has been developed to make wise use of the electricity. The controller, NB-IoT connection module, and cloud are the three main components of an IOT-based smart energy metre system. The controller is essential for maintaining the functionality of each component. This solution reduces the need for human involvement in electricity maintenance by connecting energy metres to the cloud using an NB-IoT communication module. The IoT-based metre reading system in the proposed work is created to monitor and analyse the metre reading, and the service provider can cut off the source of electricity whenever the customer fails to pay the monthly bill. It also eliminates the need for human intervention, provides accurate metre reading, and guards against billing errors. The proposed SPM improves the overall accuracy ranges of 7.42, 27.83, and 20% better than DR, OREM, and SLN respectively. 2023 -
Rational design of PANI incorporated PEG capped CuO/TiO2 for electrocatalytic hydrogen evolution and supercapattery applications
Synthesis of efficient electrocatalysts for energy applications is a major area scientists are currently focusing on to address the twin challenges of energy shortfall and the production of clean energy. Herein, an efficient electrocatalyst, polyaniline incorporated with polyethylene glycol capped CuO/TiO2 is prepared, which is effective in hydrogen evolution reactions and energy storage applications. The characterizations like XPS, XRD, FT-IR, FE-SEM, HR-TEM, and BET have been carried out to confirm the successful formation of the synthesized PANI/CuO/TiO2 composite. At 10 mA/cm2 current density, the prepared composite exhibits a lesser overpotential of 536 mV and 1587.2 C/g at 1 A/g as the specific capacity. The electrode prepared using the PANI/CuO/TiO2 composite also shows cyclic stability up to 2000 cycles. The synthesized composite is an efficient electrocatalyst for energy related applications. 2023 Hydrogen Energy Publications LLC -
Structural, optical, and electrochromic properties of RT and annealed sputtered tungsten trioxide (WO3) thin films for electrochromic applications by using GLAD technique
Tungsten oxide (WO3) thin films were prepared on the GLAD DC magnetron sputtering (GDMS) and substrate angles were varied from 70 to 80. The WO3 thin films were deposited at room temperature (RT) on corning glass (CG) and fluorine-doped tin oxide (FTO), and substrates and annealed at 400C/2h. The XRD, UvVis spectrometer, and electrochemical analyzer were used to determine the structural, optical, and electrochromic (EC) properties. According to an XRD study, RT-deposited samples were amorphous, but annealed samples displayed crystalline structures. The optical transmittance of RT and annealed samples varied from 59 to 71% and 14 to 28% respectively. The colored/bleached ability of the cyclic voltammograms was RT samples shows greater than in annealed samples. Since the coloration ability and diffusion coefficient of WO3 RT samples show greater than annealed samples. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Students Satisfaction with Remote Learning During the COVID-19 Pandemic: Insights for Policymakers
Purpose: This study aimed to learn more about the factors influencing student happiness and involvement in remote learning in Indian higher education institutions (HEIs). The study aims to assist administrators, strategists, and politicians in efficiently dealing with educations new normal. Methodology: The study used a quantitative research approach to fulfill the research aims. A sample of 546 students from various Indian HEIs was chosen, and data were gathered using standardized questionnaires. Structural equation modeling, confirmatory factor analysis, and importance-performance analysis (IPA) were used to calculate the student satisfaction index and examine the impact of various factors. Findings: The findings of this study revealed that institutional and faculty support emerged as the most influential factor impacting students satisfaction through remote learning. It also highlighted the need for HEIs to redesign the assessment process and evaluation techniques to adapt to the remote learning environment. Practical Implications: The findings of this study indicated the practical consequences for administrators, strategists, and policymakers at Indian HEIs. It was advised that improving institutional and teacher support should be a major concern in order to improve student happiness in remote learning situations. Furthermore, redesigning assessment procedures and evaluation processes may improve learning outcomes and student engagement. Originality: This study contributed to the existing body of knowledge by specifically investigating the factors influencing student satisfaction in remote learning within Indian HEIs. The findings shed light on the unique challenges and opportunities the shift to remote education presented. They offered valuable insights for managing and improving the quality of education during and beyond the pandemic. 2023, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Delayed in sensorimotor reflex ontogeny, slow physical growth, and impairments in behaviour as well as dopaminergic neuronal death in mice offspring following prenatally rotenone administration
The environment is varying day by day with the introduction of chemicals such as pesticides, most of which have not been effectively studied for their influence on a susceptible group of population involving infants and pregnant females. Rotenone is an organic pesticide used to prepare Parkinson's disease models. A lot of literature is available on the toxicity of rotenone on the adult brain, but to the best of our knowledge, effect of rotenone on prenatally exposed mice has never been investigated yet. Therefore, the recent work aims to evaluate the toxic effect of rotenone on mice, exposed prenatally. We exposed female mice to rotenone at the dose of 5mg/Kg b.w. throughout the gestational period with oral gavage. We then investigated the effects of rotenone on neonate's central nervous systems as well as on postnatal day (PD) 35 offspring. In the rotenone group, we observed slow physical growth, delays in physical milestones and sensorimotor reflex in neonates and induction of anxiety and impairment in cognitive performances of offspring at PD-35. Additionally, immunohistochemical analysis revealed a marked reduction in TH-positive neurons in substantia nigra. Histological examination of the cerebellum revealed a decrease in Purkinje neurons in the rotenone exposed group as compared to the control. The data from the study showed that prenatally exposure to rotenone affects growth, physical milestones, neuronal population and behaviour of mice when indirectly exposed to the offspring through their mother. This study could provide a great contribution to researchers to find out the molecular mechanism and participating signalling pathway behind these outcomes. 2023 International Society for Developmental Neuroscience. -
HQA Bot: Hybrid AI Recommender Based Question Answering Chatbot
The COVID pandemic has presented a number of challenges for education, particularly when it comes to reaching and engaging students. As a result, online education has become increasingly important, and artificial intelligence (AI) has played a crucial role in supporting this shift. The proposed tutor assistance question-answering system uses AI to automatically generate responses to student questions. This system includes a feedback mechanism, known as a satisfaction index that measures the efficiency of the generated responses and suggest relevant follow-up questions. The proposed Hybrid Recommender-based Dijkstras algorithm (HRD) improves the system's accuracy. This algorithm uses a combination of techniques to group relevant questions based on context, which improves the accuracy of identifying the next relevant question. In our customized dataset, this approach achieved an accuracy of 96% and an average accuracy of 82% across benchmarked datasets. With this system, we aim to bridge the gap between students and education by providing a more engaging and personalized learning experience. 2023, Ismail Saritas. All rights reserved. -
Role of mixed molecular weight PEO-PVDF polymers in improving the ionic conductivity of blended solid polymer electrolytes
Blended solid polymer electrolytes (BSPE) were prepared by mixing different molecular weight polymers PEO6 (Mw = 1 106 g/mol), PEO5 (Mw = 1 105 g/mol), and PVDF (Mw = 5.25 105 g/mol) complexed with lithium salt. Conductivity and dielectric studies at different temperatures were carried out on these BSPE systems by varying the wt% of PEO5 and PVDF with respect to PEO6, keeping the wt% of lithium salt constant. The electrical characterizations of BSPE systems have been investigated using impedance spectroscopy in the frequency range 0.1106 Hz. The conductivity data shows that inclusion of PEO5 and PVDF into the PEO6 matrix improved the overall lithium-ion dynamics in the polymer matrix. The composition, PEO6 (94 wt%)-PEO5 (3 wt%)/PVDF (3 wt%)-LiClO4, exhibited maximum conductivity of 6.44 10?4 Scm?1 at 303 K. TheDC conductivity variation with temperature of BSPE systems follows Arrhenius relation and variation of AC conductivities with frequency obeys Jonschers power law. The real and imaginary part of dielectric constant and the dielectric relaxation were also investigated. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Non-Noble Bifunctional Amorphous Metal Boride Electrocatalysts for Selective Seawater Electrolysis
The global scarcity of freshwater resources has recently driven the need to explore abundant seawater as an alternative feedstock for hydrogen production by water-splitting. This route comes with new challenges for the electrocatalyst, which has to withstand harsh saline water conditions with selectivity towards oxygen evolution over other competing reactions. Herein, a series of amorphous metal borides based on the iron triad metals (Co, Ni, and Fe), synthesized by a simple one-step chemical reduction method, displayed excellent bifunctional activity for overall seawater splitting. Amongst the chosen catalysts, amorphous cobalt boride (Co?B) showed the best overpotential values of 182 mV for HER and 305 mV for OER, to achieve 10 mA/cm2, in alkaline simulated seawater. This superior activity was owed to the enrichment of the metal site with excess electrons (HER) and the in-situ surface transformation (OER), as confirmed by various means. In alkaline simulated seawater, the overall cell voltage required to achieve 100 mA/cm2 was 1.85 V for the Co?B catalyst when used in a 2-electrode assembly. The Co?B catalyst showed negligible loss in activity even after 1000 cycles and 50 h potentiostatic tests, thus demonstrating its industrial viability. The selectivity of the catalyst was established with Faradaic efficiency of above 99 % for HER and 96 % for OER, with no detection of chloride products in the spent electrolyte. This study using the mono-metallic boride catalysts will turn to be a precursor to exploit other complex metal boride systems as potential candidates for seawater electrolysis for large-scale hydrogen production. 2023 Wiley-VCH GmbH. -
Future perspectives on new innovative technologies comparison against hybrid renewable energy systems
The increase in the dispatchable amount of renewable energy and rural access to the point is proposed. The fuel is used to generate power and electrical energy for the machine. This causes the electricity to manage the single connection point to analyze the hybrid generations. Improving this hybrid generator of renewable power resources can be enabled for the analysis. Photovoltaic power sources have been introduced for converting the power loads and the dumps. The vehicle energy power management technique and the renewable energy system have been used for the analysis. This study shows how vehicle and renewable energy management can help develop geothermal against hydrothermal vents. Hydropower and vehicles can enable bioethanol for vehicle biodiesel. This study allows for the analysis of hydrothermal and biodiesel. In this study, the power of the energy enables the hybrid system, and the combination of the power generator to access the vehicle is proposed. 2023 -
Lie group analysis of flow and heat transfer of a nanofluid in conedisk systems with Hall current and radiative heat flux
A study of the rheological and heat transport characteristics in conedisk systems finds relevance in many applications such as viscometry, conical diffusers, and medical devices. Therefore, a three-dimensional axisymmetric flow with heat transport of a magnetized nanofluid in a conedisk system subjected to Hall current and thermal radiation effects is investigated. The simplified NavierStokes (NS) equations for the conedisk system given by Sdougos et al. [18] Journal of Fluid Mechanics, 138, 379404 are solved by using the asymptotic expansion method for the four different models, such as rotating cone with static disk (Model I), rotating disk with static cone (Model II), co-rotating cone and disk (Model III), and counter-rotating cone and disk (Model IV). The KhanaferVafaiLightstone (KVL) model along with experimental data-based properties of 37 nm Al2O3H2O nanofluid is considered. To obtain the transformations leading to self-similar equations from the NavierStokes (NS) and energy conservation equations, the Lie group technique is used. The self-similar nonlinear problem is solved numerically to examine the effects of physical parameters. There are critical values of the power exponent at which no heat transport from the disk surface occurs. Nanoparticles significantly enhance heat transport when both the cone and disk rotate in the same or opposite directions. The centrifugal force and thermal radiation improve the heat transport in conedisk systems. 2023 John Wiley & Sons Ltd. -
IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model
This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting. 2023 The Authors