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Generalized Ricci soliton and paracontact geometry
In the present paper, we study generalized Ricci soliton in the framework of paracontact metric manifolds. First, we prove that if the metric of a paracontact metric manifold M with Q?= ?Q is a generalized Ricci soliton (g,X) and if X? 0 is pointwise collinear to ?, then M is K-paracontact and ?-Einstein. Next, we consider closed generalized Ricci soliton on K-paracontact manifold and prove that it is Einstein provided ?(?+ 2 n?) ? 1. Next, we study K-paracontact metric as gradient generalized almost Ricci soliton and in this case we prove that (i) the scalar curvature r is constant and is equal to - 2 n(2 n+ 1) ; (ii) the squared norm of Ricci operator is constant and is equal to 4 n2(2 n+ 1) , provided ??? - 1. 2021, Instituto de Matemica e Estattica da Universidade de S Paulo. -
Impact of use of technology on student learning outcomes: Evidence from a large-scale experiment in India
One of the Sustainable Development Goals (SDG-4) adopted by the United Nations focuses on ensuring inclusive and equitable quality education for all. Most research on impact of technology on learning outcomes depends on designs that require low student-to-computer ratio and extensive retraining of teachers. These requirements make the designs difficult to implement on a large scale and hence are limited in terms of inclusivity and ability to provide equitable opportunity for all. Our paper is the first to evaluate an intervention design that is aimed at dealing with these concerns. We conduct a large-scale randomised field experiment in 1823 rural government schools in India that uses technology-aided teaching to replace one-third of traditional classroom teaching. Even with high student-to-computer ratios and minimal teacher training, we observe a positive impact on student learning outcomes. The study thus presents a low cost, resource-light design, which can be implemented in a developing country on a large scale to address the problem of poor learning outcomes, thereby making the intervention inclusive and equitable in line with the spirit of SDG-4. 2019 Elsevier Ltd -
Machine Learning based Food Sales Prediction using Random Forest Regression
Sales forecasting is crucial in the food industry, which experiences high levels of food sales and demand. The industry has concentrated on a well-known and established statistical model. Due to modern technologies, it has gained tremendous appeal in improving market operations and productivity. The main objective is to find the most accurate algorithms to predict food sales and which algorithm is most suitable for sales forecasting. This research work has mentioned and discussed about several research articles that revolve around the techniques usedfor sales prediction as well as finding out the advantages and disadvantages of the said techniques. Various techniques were discussed as to predicting the sales but mainly Incline Increasing Regression and Accidental Forestry Lapse is used for attention. The manufacturing has concentrated on a well-known and established statistical model. Although algorithms like Modest Direct Regression, Incline Increasing Lapse, Provision Course Lapse, Accidental Forest Lapse, Gradient Boosting Regression, and Random Forest Regression are well familiar for outdoing others, it has remained decisively established that Random Forest Regression is the most appropriate technique when associated to the others. After doing the whole examination, the Random Forest Regression technique fared well when compared to other algorithms. The feature importance is generated for the selected dataset using Python and Random Forest Regression and the nose position chart is also explainedin detail. The proposed model is compared three major parameters that are accuracy score, mean absolute error and max error. The proposed random forest regression accuracy score is improved nearly 1.83% and absolute error rate is reduced 4.66%. 2022 IEEE. -
Structural engineering on indole derivative for rechargeable organic lithium-ion battery
In the present work, the indole derivative, namely, 3,3?,3?-methane-triyl-tris-1H-indol(tris-Ind), is synthesized and characterized as an organic electrode material in rechargeable lithium-ion batteries (RLIB). The structural characterization of the synthesized molecule is carried out using physicochemical techniques. The ball milling method is used for the lithiation process to form electroactive lithiated tris-Ind (Li-tris-Ind). The electrochemical activity of Li-tris-Ind is measured in aqueous and non-aqueous electrolytic media, and the results are compared. The aqueous cell system delivers an average cell potential of 0.76V with a discharge capacity of 189 mAhg?1, whereas the non-aqueous cell system delivers an average potential of 1V with 506 mAhg?1. The potentiostatic electrochemical impedance spectroscopic studies reveal the kinetics of finite diffusion. The organic electrode shows good cyclic stability and reproducibility in both systems, making it a significant practical material for RLIB applications. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Lithiated indole derivative in reduced graphene oxide framework as efficient electrode for lithium-ion battery
The traditional wet-chemical approach was used to synthesise N,N?-bis-Ind[?1H-indol-3-ylmethylidene]benzene-1,2-diamine (N,N?-bis-IBD), which was then lithiated using ball milling. The physical and spectrochemical characteristics of the as-prepared materials in lithiated and unlithiated forms were found to be considerably different. The activity of the lithiated N,N?-bis-IBD electrode material towards battery application was investigated using cyclic voltammetry (CV) and galvanostatic charge potential limit (GCPL) studies. The electrochemical studies on this electrode material revealed the active strong redox characteristics and anodic behaviour in aqueous electrolyte. At 100 cycles in aqueous medium, the lithiated moiety exhibited an impressive battery performance with a discharge capacity of 277 mAhg?1. Interestingly, addition of 20 wt % reduced graphene oxide (rGO) to lithiated N,N?-bis-IBD sample greatly improved the battery performance showing a high discharge capacity of 766 mAhg?1 after 100 cycles. The improved electrochemical performance implicates rGO-mixed lithiated indole-based composite as an effective anode material for lithium-ion battery (LIBs) application. 2023 Elsevier B.V. -
Solute-solvent interaction and DFT studies on bromonaphthofuran 1,3,4-oxadiazole fluorophores for optoelectronic applications
In the present work, computational and experimental studies were carried out to explore the photophysical properties of bromonaphthofuran substituted 1,3,4-oxadiazole derivatives for optoelectronic applications. Density functional theory (DFT) was used to demonstrate the electronic and optical properties of the synthesised molecules. The theoretical ground state dipole moments of the fluorophores in gas and solvent environments were also computed using Gaussian 09W software. Further, the HOMO-LUMO energies of the fluorophores determined using DFT agree well with the experimental values. Molecular electrostatic potential 3D plots were used to identify the sites which are electrophilic and nucleophilic in nature. Dipole moment of both the fluorophores in ground and excited states were determined experimentally. The excited state dipole moments being higher than that of the ground state shows the redistribution of electron densities in the excited state than in the ground state in both the fluorophores. The solute-solvent interactions, both specific and non-specific, were assessed using Catalan parameters. Further, the nature of chemical reactivity was determined based on global descriptors. The photophysical properties of the fluorophores studied suggest their potential use as promising candidates for organic light emitting diode (OLED), solar cell and chemosensor applications. 2022 Elsevier Inc. -
Exploring ocean pH dynamics via a mathematical modeling with the Caputo fractional derivative
Global warming is a complex problem with far-reaching global implications. One of its notable repercussions is the escalation of CO2 levels in the atmosphere, resulting in the phenomenon known as Ocean Acidification (OA). In this research, we have established a correlation between four key factors: marine species, human population, CO2 levels, and ocean pH. By formulating a Caputo fractional differential equation, we investigated the dynamics of these variables to evaluate the significance of this climatic phenomenon. The model analysis reveals that the rise in anthropogenic CO2 emissions causes a reduction in the oceans pH level and increases OA.This process, in turn, decreases the oceans ability to absorb CO2, making it less effective in mitigating climate change. In this study, it was demonstrated that elevated levels of CO2 result in a reduction in pH levels, which in turn causes a decrease in the population of marine species that play a critical role in numerous economic sectors such as tourism, aquaculture, and fisheries. Moreover, we conducted a comprehensive analysis of the influence exerted by the intrinsic growth rate of the human population. We examined various theoretical aspects, including the assessment of existence and uniqueness. Numerical simulations are carried out to illustrate the effect of key parameters on the dynamics of the system using the generalized AdamsBashforthMoulton method. The Author(s) 2024. -
A chaos control strategy for the fractional 3D LotkaVolterra like attractor
In this paper, we have considered a three-dimensional LotkaVolterra attractor in the frame of the Caputo fractional derivative to examine its dynamics. The theoretical concepts like existence and uniqueness and boundedness of the solution are analyzed. To regulate the chaos in this fractional-order system, we have developed a sliding mode controller and conditions for global stability of the controlled system with and without uncertainties and outside disruptions are derived. The ability of the designed controller is examined in terms of both commensurate and non-commensurate fractional order derivatives for all the aspects. The Lyapunov exponent is the novelty of this paper which is used to illustrate the behavior of the chaos and demonstrate the dissipativeness of the considered chaotic system. We have examined the effect of fractional order derivatives in this system. With the help of numerical simulations, the theoretical claims regarding the impact of the controller on the system are established. 2023 International Association for Mathematics and Computers in Simulation (IMACS) -
Design of a fractional-order atmospheric model via a class of ACT-like chaotic system and its sliding mode chaos control
Investigation of the dynamical behavior related to environmental phenomena has received much attention across a variety of scientific domains. One such phenomenon is global warming. The main causes of global warming, which has detrimental effects on our ecosystem, are mainly excess greenhouse gases and temperature. Looking at the significance of this climatic event, in this study, we have connected the ACT-like model to three climatic components, namely, permafrost thaw, temperature, and greenhouse gases in the form of a Caputo fractional differential equation, and analyzed their dynamics. The theoretical aspects, such as the existence and uniqueness of the obtained solution, are examined. We have derived two different sliding mode controllers to control chaos in this fractional-order system. The influences of these controllers are analyzed in the presence of uncertainties and external disturbances. In this process, we have obtained a new controlled system of equations without and with uncertainties and external disturbances. Global stability of these new systems is also established. All the aspects are examined for commensurate and non-commensurate fractional-order derivatives. To establish that the system is chaotic, we have taken the assistance of the Lyapunov exponent and the bifurcation diagram with respect to the fractional derivative. To perform numerical simulation, we have identified certain values of the parameters where the system exhibits chaotic behavior. Then, the theoretical claims about the influence of the controller on the system are established with the help of numerical simulations. 2023 Author(s). -
Uplifting and Uncanny Conversations Around Death and Dying: Qualitative Study Among Indian Adolescents and Emerging Adults
This study explores perspectives of adolescents and emerging adults on having conversations around death and dying, if there is a value in discussing death early in life, and to explore the views on likelihood of introducing death education in Indian curriculum. Using constructivist grounded theory of qualitative research, the study inquired the perspectives of adolescents and emerging adults employing semi-structured interviews. All participants showed interest in discussing the topic; they actively participated in sharing their views, something that they heard, and inquiring about cultural practices. In analyzing the interview data, mainly three themes emerged: 1. Understanding death in relation to shadow and spirit stories; 2. Existential view on death and managing grief and anxiety; 3. Social and cultural narratives into death education. This study sets out to address a gap in research among adolescents and emerging adult attitudes and opinions toward death. However, there is a need to understand barriers in normalizing conversations around death and dying in wider communities in India and further research is essential. The Author(s) 2024. -
Insights on research techniques towards cost estimation in software design
Software cost estimation is of the most challenging task in project management in order to ensuring smoother development operation and target achievement. There has been evolution of various standards tools and techniques for cost estimation practiced in the industry at present times. However, it was never investigated about the overall picturization of effectiveness of such techniques till date. This paper initiates its contribution by presenting taxonomies of conventional cost-estimation techniques and then investigates the research trends towards frequently addressed problems in it. The paper also reviews the existing techniques in well-structured manner in order to highlight the problems addressed, techniques used, advantages associated and limitation explored from literatures. Finally, we also brief the explored open research issues as an added contribution to this manuscript. 2017 Institute of Advanced Engineering and Science. All rights reserved. -
Intelligence-Software Cost Estimation Model for Optimizing Project Management
With the evolution of pervasive and ubiquitous application, the rise of web-based application as well as its components is quite rising as such applications are used both for development and analysis of the web component by developers. The estimation of software cost is controlled by multiple factors right from human-driven to process driven. Most importantly, some of the factors are never even can be guessed. At present, there are no records of literature to offer a robust cost estimation model to address this problem. Therefore, the proposed system introduces an intellectual model of software cost model that is mainly targets to perform optimization of entire cost estimation modeling by incorporating predictive approach. Powered by deep learning approach, the outcome of the proposed model is found to be cost effective in comparison to existing cost estimation modeling. 2019, Springer Nature Switzerland AG. -
Pain track analysis during gestation using machine learning techniques
During the gestation period women experience Braxton Hicks which is called the false labor, contractions during the second trimester. These contractions are not in regular intervals and also they are often unnoticed. The real labour or the true labour contractions develop late in the third trimester of the gestation usually beyond 36th week (excluding pre-term birth). Some women often fail to identify these pains in the third trimester of the gestation where an efficient facial recognition algorithm along with the support vector machine (SVM) helps them to identify these pains and take optimum care of themselves. The authors in this paper convey a mechanism to identify the pains effectively by creating a database of images pertaining to the pregnant women, her emotional states throughout the pregnancy. Using MATLAB the algorithm of decision tree is implemented and the values obtained from them help us analyze the pain type efficiently. 2021 Institute of Advanced Engineering and Science. All rights reserved. -
In Vitro Production of Saponins
Plants have been utilized as food, feed, and fodder since the dawn of civilization. Plants are also thought to be a rich source of bioactive compounds with a variety of pharmacological actions. Saponins are one such group of molecules which are present in various plant species. As triterpenoid glycosides, they have a 30C oxidosqualene precursor aglycone moiety (sapogenin), which is then linked with glycosyl residues to form saponin. These saponins have a unique platform in the field of pharmaceutical and nutraceutical industries. Saponins are used for the treatment of various diseases which include cancer, diabetic, cardiac, hepatic, and nervous disorders. The production of saponins through conventional approaches is time-consuming and hard to extract pure compounds, and thus to achieve this, in vitro methods have been developed and enhanced the production and extraction of the metabolites. The present chapter focuses on the in vitro production of saponins through various tissue culture techniques such as shoot, callus, cell suspension, adventitious root, hairy root culture, and applications of bioreactors at commercial level. The chapter also focuses on biosynthetic pathway, extraction methods, and biological activities of saponins. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
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). -
Trespassers detection system for agriculture fields using artificial intelligence & methods thereof /
Patent Number: 202041047576, Applicant: Dr. Sunanda Dixit.
System alarms on detection of Trespassers in agriculture fields .The system will receive data of trespassers with the help of camera, weight sensors & RFID Tags of employees of filed, the data upon processing will alert the alarm on detection of trespassers if any. -
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 -
Algorithms for better decision-making: a qualitative study exploring the landscape of robo-advisors in India
Purpose: This paper explores the current state of Robo-advisory services in India. This paper further highlights the problems experienced by the service providers in disseminating the innovative business model among the Indians. Design/methodology/approach: The study adopts a qualitative approach to investigate the industry experts by conducting semi-structured interviews. The data collected were transcripted and further analyzed using the content analysis technique. Finally, the authors utilized categorization and coding techniques to frame broad study themes. Findings: The study findings reveal that the three pillars of Robo-advisory are ease and convenience, the time factor and transparency in operations. Robo-advisory services are still at a nascent stage in India. Furthermore, keeping the sentiments of Indians in mind, FinTech companies could combine automated Robo-advisory with a human touch of a wealth manager for optimal advisory services. Research limitations/implications: Since the present study is qualitative, the authors cannot generalize the study results. Future research can focus on empirically proving the constructs of the study using quantitative methods. Practical implications: Robo-advisors have a well-established market in developed nations but are still nascent in developing countries like India. The current focus of service providers and regulatory authorities must be to increase awareness among investors by educating the investors and building trust. Originality/value: The present study is the first to qualitatively synthesize the challenges faced by the FinTech service providers in the Indian market. 2023, Emerald Publishing Limited. -
A Scoping Review on the Factors Affecting the Adoption of Robo-advisors for Financial Decision-Making
Robo-advisors have recently gained popularity as an algorithm-based method of simplifying financial management. The present study explores the factors that lead many potential consumers to use Robo-advisors in financial decisions. Adopting a scoping review approach formulated by Arksey and O'Malley, the study examines the factors affecting the acceptance and usage of financial Robo-advisors in different parts of the world. The results suggest that performance expectancy, effort expectancy, trust in technology, financial knowledge, investing experience, cost-effectiveness, facilitating conditions, and intrinsic motivation are positively related to adopting Robo-advisors. On the contrary, anxiety, risk perception, investor age, data security, and behavioral biases negatively influence the investor attitude toward Robo-advisors. This creates a barrier to the diffusion of financial Robo-advisors among the investors. The study concludes by providing recommendations to service providers, policymakers, and marketers for the speedy distribution and acceptance of algorithms for the public's financial decision-making. The study identifies gaps in the existing literature and suggests areas for future research for aspiring academics. 2024 University of Pardubice. All rights reserved. -
An empirical analysis of the antecedents and barriers to adopting robo-advisors for investment management among Indian investors
This study aims to provide a research framework to understand the antecedents and barriers to adopting Robo-advisors for investment decision-making in India. The study employed a research model based on the extended UTAUT 2, along with three additional constructs, i.e. personal innovativeness (PI), perceived risk (PR), and technological anxiety (TA). Data collected were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) with the help of SmartPLS 4.0 software. This research will help banks, wealth management service providers, FinTech companies, and Robo-advisor developers improve their platforms, offers, products, and marketing tactics for these automated advisory services. 2024 Informa UK Limited, trading as Taylor & Francis Group.