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One Pot Hydrothermal Synthesis and Application of Bright-yellow-emissive Carbon Quantum Dots in Hg2+ Detection
Carbon quantum dots (CQD) have drawn great interest worldwide for their extensive application as sensors due to their extraordinary physical and chemical characteristics, good biocompatibility, and high fluorescence in nature. Here, we demonstrate a technique for detecting mercury (Hg2+) ion using a fluorescent CQD probe. Ecology is concerned about the accumulation of heavy metal ions in water samples due to their harmful effects on human health. Sensitive identification and removal of metal ions from water samples are required to reduce heavy metals risk. To find out Mercury in the water sample, carbon quantum dots were used and synthesized by 5-dimethyl amino methyl furfuryl alcohol and o-phenylene diamine through the hydrothermal technique. The synthesized CQD shows yellow emission when exposed to UV irradiation. Mercury ion was used to quench carbon quantum dots, and it was found that the detection limit was 5.2 nM with a linear range of 15100 M. The synthesized carbon quantum dots were demonstrated to efficiently detect Mercury ions in real water samples. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Azopyridine as a Linker Molecule in Polyaniline-Grafted Graphene Oxide Nanocomposite Electrodes for Asymmetric Supercapacitors
Electronically conducting polymers (ECPs)/carbon nanomaterial-based polyaniline electrodes have received great interest in the field of supercapacitors due to their high specific capacitance, good electronic conductivity, good mechanical strength, good chemical and electrochemical stabilities, etc. Among the various available ECPs, they have received much importance due to their excellent electrochemical performances. Herein, we report a facile synthesis of a PANI-grafted graphene oxide (GO)-azopyridine (Azo) (PANI/GO-Azo) nanocomposite and use it as electrodes for fabricating supercapacitors. The azo units present in the nanocomposite act as a spacer between PANI and GO. The interfacial polymerization method is adopted for the synthesis of PANI/GO-Azo nanocomposites. The PANI/GO-Azo nanocomposite electrode exhibits a gravimetric capacitance of 426 F g-1 at a current density of 0.25 A g-1 in 1 M H2SO4 (aqueous) electrolyte. The electrode possesses good cycling stability of more than 5000 cycles with a Coulombic efficiency of 98.5%. An asymmetric supercapacitor fabricated with PANI/GO-Azo as the positive electrode and activated carbon as the negative electrode delivers an energy density of 12.45 W h kg-1 with a power density of 274.9 W kg-1. This study proclaims that the PANI/GO-Azo nanocomposite electrode is highly promising for next-generation supercapacitors. 2023 American Chemical Society -
Tadpole domination number of graphs
The graph obtained by joining cycle Cm to a path Pn with a bridge is called Tadpole graph denoted by Tm,n. A subset D of V (G) is said to be a tadpole dominating set of G if D is a dominating set and the set of vertices of D spans a tadpole graph Tm,n where m ? 3, n ? 1. In this paper, we find the tadpole domination number of cartesian product of certain graphs, namely, paths, cycles and complete graphs. Also the tadpole domination number for the Mycielskian of cycles and paths is obtained. 2023 World Scientific Publishing Company. -
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. -
The effect of climate change on the dynamics of a modified surface energy balance-mass balance model of Cryosphere under the frame of a non-local operator
One of the major causes of the intermittent nature of long-term climate changes is the interaction between the surface energy balance and the mass balance of the Cryosphere. In this paper, the pre-existing surface energy balance-mass balance model of the Cryosphere is modified by incorporating the radiative forcing of CO2 to observe the effect of global warming on the nature of the previous model. The modified model is generalized using Caputo's non-local operator. The stability of the new model is analyzed at all the equilibrium points and also it is shown that there exists a unique and bounded solution for the modified system. Using bifurcation analysis and calculating the values of Lyapunov exponents for different fractional orders of the modified system, it is found that the system exhibits chaos for certain values of the radiating forcing of CO2 To observe and visualize the changes in the nature of the new model, the system is solved using the highly efficient 7th-order RungeKutta method. It is observed that with the inclusion of the radiative forcing of CO2, the nature of the system changes from asymptotically stable to chaotic as we decrease the order of the system. The Poincare map shows that the modified model even has characteristics of a strange attractor which is highly chaotic. The system becomes unstable when the value of the radiative forcing of CO2 is increased. As a result, the predictive power of the surface energy balance-mass balance model of the Cryosphere decreases. In addition to providing insights into the transition from stability to chaos in the Cryosphere model due to CO2 radiative forcing, this research offers a deeper understanding of the intricate interplay between climate dynamics and complex systems behavior. 2023 The Authors -
Protoplanetary disks around young stellar and substellar objects in the ? Orionis cluster
Understanding the evolution and dissipation of protoplanetary disks are crucial in star and planet formation studies. We report the protoplanetary disk population in the nearby young ? Orionis cluster (d? 408 pc; age ? 1.8 Myr) and analyse the disk properties, such as dependence on stellar mass and disk evolution. We utilize the comprehensive census of 170 spectroscopic members of the region refined using astrometry from Gaia DR3 for a wide mass range of ? 190.004 M? . Using the near-infrared (2MASS) and mid-infrared (WISE) photometries, we classify the sources based on the spectral index, into class I, class II, flat spectrum and class III young stellar objects. The frequency of sources hosting a disk with stellar mass <2 M? in this region is 41 7 %, which is consistent with the disk fraction estimated in previous studies. We see that there is no significant dependence of disk fraction on stellar mass among T Tauri stars (<2 M?), but we propose rapid disk depletion around higher mass stars (>2 M?). Furthermore, we found the lowest mass of a disk-bearing object to be ? 20 MJup and the pronounced disk-fraction among the brown dwarf population hints at the formation scenario that brown dwarfs form similar to low-mass stars. 2023, Indian Academy of Sciences. -
Excitation dependent emissive multi stimuli responsive ESIPT organic luminogen for monitoring sea food freshness
Excited state intramolecular proton transfer (ESIPT) organic luminophores with excitation wavelength-dependent color tunability have drawn significant attention due to their exceptional photoluminescent properties in solution and solid state. A novel salicylaldehyde-based Schiff's base molecule, (E)-N'-(3,5-dibromo-2-hydroxybenzylidene)benzohydrazide (BHN) exhibited stimuli (excitation wavelength and pH) induced changes in fluorescence properties which was utilised for applications like trace level water sensing in organic solvents (THF, acetone and DMF), detection and quantification of biogenic amines and anticounterfeiting. In the solution state, BHN rendered a ratiometric detection and quantification of ammonia, diethylamine and trimethylamine, which is further supported by DFT studies. The photoluminescent response of BHN towards various biogenic amines was later utilised to monitor shrimp freshness. The investigation carried out highlights the potential versatility of ESIPT hydrazones, which renders multi stimuli responsive behaviour that can be utilised for water sensing, anticounterfeiting and the detection and quantification of biogenic amines. 2023 Elsevier Ltd -
Power quality disturbance mitigation in grid connected photovoltaic distributed generation with plug-in hybrid electric vehicle
In the last twenty years, electric vehicles have gained significant popularity in domestic transportation. The introduction of fast charging technology forecasts increased the use of plug-in hybrid electric vehicle and electric vehicles (PHEVs). Reduced total harmonic distortion (THD) is essential for a distributed power generation system during the electric vehicle (EV) power penetration. This paper develops a combined controller for synchronizing photovoltaic (PV) to the grid and bidirectional power transfer between EVs and the grid. With grid synchronization of PV power generation, this paper uses two control loops. One controls EV battery charging and the other mitigates power quality disturbances. On the grid connected converter, a multicarrier space vector pulse width modulation approach (12-switch, three-phase inverter) is used to mitigate power quality disturbances. A Simulink model for the PV-EV-grid setup has been developed, for evaluating voltage and current THD percentages under linear and non-linear and PHEV load conditions and finding that the THD values are well within the IEEE 519 standards. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Roxburgh was right: Aponogeton microphyllus and Aponogeton undulatus are distinct species
Aponogeton microphyllus, previously placed under the synonymy of A. undulatus, is recognized here as a distinct species based on morphology, chromosome number, and molecular phylogenetics (nuclear ribosomal internal transcribed (ITS) spacer region). Observations on the type and live specimens revealed morphological differences between the two species. Aponogeton microphyllus flowered regularly and set seeds. Aponogeton undulatus flowered rarely, did not set seeds, but showed formation of young plantlets on the inflorescence axis. Similarly, different chromosome numbers were recorded in Aponogeton microphyllus and the two forms of A. undulatus, viz., AF1 and AF2, whichoccurin distinct populations. Aponogeton microphyllus exhibited polysomaty with root-tip cells showing 2n=40, 42, and 44 chromosomes. The two forms of A. undulatus, AF1 and AF2, showed 2n=84 and 86 chromosomes, respectively. Based on the ITS data, both speciesoccupiedtwo separate clades. Plastid trnK intron region indicated a close relationship between both species. Our study suggests the need for comprehensive phylogenetic analyses of A. undulatus across its distribution range based on more advanced techniques such as high-throughput sequencing data to understand the A. undulatus species complex and to detect natural hybrids of this species. 2023, Indian Academy of Sciences. -
Fuel coke derived nitrogen and phosphorus co-doped porous graphene structures for high-performance supercapacitors: The trail towards a brown-to-green transition
As the looming crisis of global energy market exponentially intensifies, the scientific community prompts the use of supercapacitors as a sustainable energy production/storage model and emission reduction strategy. Therefore, in this work, we present a cutting-edge approach for the high-value utilization of fossil fuel-derived materials in supercapacitor applications, promoting an integrated brown-to-green transition for energy, ecology, and the environment. Herein, nitrogen and phosphorus co-doped porous graphene sheets (a-NPGO) have been prepared from fuel coke, which exhibits outstanding electrochemical performance as a supercapacitor electrode material. The a-NPGO shows a high specific capacitance (322 F/g at 1 A/g) almost 11 times greater than the undoped coke-based graphene derivative. Furthermore, the symmetric supercapacitor assembled with a-NPGO-modified electrodes delivered an exceptional power density of 812 W/kg at energy density of 14 Wh/kg and an excellent capacitance retention of 90 % after 5000 charge-discharge cycles. This impression of coke-derived material in high-performance supercapacitors may broaden the horizon of the current electrochemical energy storage paradigm and afford the eco-conscious implementation of fossil fuel resources. 2023 Elsevier Ltd -
Numerical simulation and mathematical modeling for heat and mass transfer in MHD stagnation point flow of nanofluid consisting of entropy generation
The primary goal of this article is to explore the radiative stagnation point flow of nanofluid with cross-diffusion and entropy generation across a permeable curved surface. Moreover, the activation energy, Joule heating, slip condition, and viscous dissipation effects have been considered in order to achieve realistic results. The governing equations associated with the modeling of this research have been transformed into ordinary differential equations by utilizing appropriate transformation variable. The resulting system of equations was solved numerically by using Bvp4c built-in package in MATLAB. The impact of involved parameters have been graphically examined for the diverse features of velocity, temperature, and concentration profiles. Throughout the analysis, the volume fraction is assumed to be less than 5 % while the Prandtl number is set to be 6. In addition, the entropy generation, friction drag, Nusselt, and Sherwood numbers have been plotted for describing the diverse physical aspects of the underlying phenomena. The major outcomes reveal that the curvature parameter reduces the velocity profile and skin friction coefficient whereas the magnetic parameter, temperature difference parameter, and radiation parameter intensify the entropy generation. 2023, The Author(s). -
FinTech and Financial Capability, What Do We Know and What We Do Not Know: A Scoping Review
Purpose: The scoping review of this study was to investigate the existing literature on FinTech's impact on financial competence and draw conclusions from it. We applied Danielle Levac's recommendations and used the scoping review framework developed by Arksey and O'Malley. Design/Methodology/Approach: The study involved identifying and analyzing 246 papers from major databases, followed by a rigorous screening process to select 54 relevant studies. Data coding, inclusion, and exclusion screening were conducted by us independently. Findings: According to the findings, studies on FinTech and financial capacity started in 2012, and since 2020, the number of studies has sharply increased. The analysis showed that financial inclusion was the primary focus of the major FinTech studies, suggesting possible research gaps in other aspects of financial competence. We suggested recommendations and prospective directions for further research in this developing subject based on these findings. Managerial Implications: This knowledge will help managers find opportunities for collaboration, offer fresh perspectives, and make wise choices, which will improve the sector. Theoretical Implications: Important concepts and relationships were found, new trends were highlighted, and theoretical advancements were suggested as a result of the inquiry. Through the filling of knowledge gaps, the study would guide future theoretical development, facilitate diverse perspectives, and support the construction of robust frameworks in the FinTech and financial capabilities sector. Originality/Value: This study offered a comprehensive review of the body of literature, pointing out areas in need of more research and knowledge gaps. The review's unique perspective for future study and innovation in understanding the relationship between FinTech and financial capacity is derived from its thorough synthesis of many studies. 2023, Associated Management Consultants Pvt. Ltd. All rights reserved. -
Sandwich structured pedot-TiO2/GO/PEDOT-TiO2 electrodes for supercapacitor
In this study, we fabricated a divergent strategy to enhance the electrochemical capacitive properties of electrodes via the cost-effective multistep green and facile electrodeposition and brush coating technique of PEDOT-TiO2/GO/PEDOT-TiO2 composite. The synthesised composite showed both EDLCs and pseudocapacitive behaviour with a good specific capacitance of 501 Fg?1 for sandwiched structure at 1 Ag?1. From the results, synthesized composite has a better ion transportation mechanism which leads to a fast chargedischarge cycle as well as a very high value of power density (500 kW/ kg) suitable for supercapacitor applications. The substance demonstrated excellent electrochemical stability, retaining 94 % of capacitance after 2000 cycles. The obtained nanocomposites were examined by FTIR, XRD, Raman, SEM-EDX and electrochemical analyses such as CV, GCD and EIS analyses. We consider that the highly stable PEDOT-TiO2/GO/PEDOT-TiO2 nanocomposite with super-capacitive behaviours is a very promising material for high-performance electrochemical storage. 2023 The Authors -
Study of nanofluid flow and heat transfer in a stationary cone-disk system
Rheometric, viscosimetric, bio-medical, and several other pharmaceutical machineries utilize the structural advantages provided by the geometry of a stationary conical diffuser. The problem of the Buongiorno nanofluid flow in the conical gap of a stationary cone-disk system for isothermal boundaries is studied. The governing system, comprising the incompressibility condition, NavierStokes equation, energy conservation equation, and conservation of Nanoparticle Volume Fraction (NVF) equation, is analyzed. The Lie-group theory has been used to derive a self-similar model. Solutions of the self-similar equations were computed numerically, and the expressions for the Nusselt number and Sherwood number are obtained. The parametric investigation reveals that the heat and mass transfer rate subside significantly when pre-swirl is introduced to the flow. Furthermore, the nanofluid slip mechanisms enhance the effective temperature of the system. 2023 Elsevier Ltd -
Analysis of nonlinear compartmental model using a reliable method
The goal of this work is to investigate nonlinear models and their complexity using techniques that are universal and have connections to historical and material aspects. Using the premise of a constant population that is uniformly mixed, a nonlinear compartmental model that depicts the movement between voter classes is taken into consideration. In the current work, we investigate the dynamical framework that supports the interactions between the three parties. It is discussed how rate change affects various metrics. The conditions for boundedness, stability, existence, and other dynamics are obtained. We derive the effects of generalizing the model in any order. The current study supports investigations into complex real-world issues and forecasts of necessary plans. 2023 The Author(s) -
Sensitive crop leaf disease prediction based on computer vision techniques with handcrafted features
Agricultural production is considered the primary source of the economy of many countries. Tomato and Potatoes are the most sensitive and consumable vegetables worldwide. However, during the growth of these crops, they suffer from many leaf diseases, which lead to loss of productivity and economy of the farmers. Many farmers detect and find plant diseases that are more time-consuming, expensive, and require expert decisions following the naked eye method. Therefore, early and accurate diagnosis of Tomato and Potato crops leaf diseases plays a vital role in sustainable agriculture. So, this research paper proposes an efficient leaf disease classification model based on computer vision techniques. The proposed Adaptive Deep Neural Network (ADNN) leaf disease classification method is a hybrid model which combines an optimized long short-term memory (OLSTM) and convolution neural network (CNN). The weight values supplied in the LSTM classifier are optimally selected using the Adaptive Raindrop Optimization algorithm. The handcrafted features are extracted from the segmented image and fused with the hybrid deep neural network to improve the classifier performance. The ADNN method consists of five steps: preprocessing, feature extraction, segmentation, handcrafted feature extraction, and classification. At first, the images are given to the preprocessing stage to remove the noise from leaf images. Then, the image-affected portion is segmented using an enhanced radial basis function neural network. After the segmentation process, the segmented image is given as an input to the adaptive deep neural network (ADNN) that classifies various types of diseases in the Potato and Tomato leaves. The efficiency of the ADNN model based on the OLSTM-CNN approach is determined concerning multiple metrics, namely Accuracy, Precision, Recall, F-measure, Specificity, and Sensitivity. The ADNN model achieved the best Accuracy of 98.02% for Tomatoes and 98% for Potatoes. The ADNN is compared with existing state-of-the-art CNN, LSTM, ResNet50, and MobileNet techniques. The performance analysis proved that the ADNN model improved efficiency in terms of all metrics and methods. 2023, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden. -
Classification of HHO-based Machine Learning Techniques for Clone Attack Detection in WSN
Thanks to recent technological advancements, low-cost sensors with dispensation and communication capabilities are now feasible. As an example, a Wireless Sensor Network (WSN) is a network in which the nodes are mobile computers that exchange data with one another over wireless connections rather than relying on a central server. These inexpensive sensor nodes are particularly vulnerable to a clone node or replication assault because of their limited processing power, memory, battery life, and absence of tamper-resistant hardware. Once an attacker compromises a sensor node, they can create many copies of it elsewhere in the network that share the same ID. This would give the attacker complete internal control of the network, allowing them to mimic the genuine nodes' behavior. This is why scientists are so intent on developing better clone assault detection procedures. This research proposes a machine learning based clone node detection (ML-CND) technique to identify clone nodes in wireless networks. The goal is to identify clones effectively enough to prevent cloning attacks from happening in the first place. Use a low-cost identity verification process to identify clones in specific locations as well as around the globe. Using the Optimized Extreme Learning Machine (OELM), with kernels of ELM ideally determined through the Horse Herd Metaheuristic Optimization Algorithm (HHO), this technique safeguards the network from node identity replicas. Using the node identity replicas, the most reliable transmission path may be selected. The procedure is meant to be used to retrieve data from a network node. The simulation result demonstrates the performance analysis of several factors, including sensitivity, specificity, recall, and detection. 2023, Modern Education and Computer Science Press. All rights reserved. -
OpenStackDP: a scalable network security framework for SDN-based OpenStack cloud infrastructure
Network Intrusion Detection Systems (NIDS) and firewalls are the de facto solutions in the modern cloud to detect cyberattacks and minimize potential hazards for tenant networks. Most of the existing firewalls, perimeter security, and middlebox solutions are built on static rules/signatures or simple rule matching, making them inflexible, susceptible to bugs, and difficult to introduce new services. This paper aims to improve network management in OpenStack Clouds by taking advantage of the combination of software-defined networking (SDN), Network Function Virtualization (NFV), and machine learning/artificial intelligence (ML/AI) and for making networks more predictable, reliable, and secure. Artificial intelligence is being used to monitor the behavior of the virtual machines and applications running in the OpenStack SDN cloud so that when any issues or degradations are noticed, the decision can be quickly made on how to handle that issue, being able to analyze data in motion, starting at the edge. The OpenStackDP framework comprises lightweight monitoring, anomaly-detecting intelligent sensors embedded in the data plane, a threat analytics engine based on ML/AI algorithms running inside switch hardware/network co-processor, and defensive actions deployed as virtual network functions (VNFs). This network data plane-based architecture makes high-speed threat detection and rapid response possible and enables a much higher degree of security. We have built the framework with advanced streaming analytics technologies, algorithms, and machine learning to draw knowledge from this data that is in motion before the malicious traffic goes to the tenant compute nodes or long-term data store. Cloud providers and users will benefit from improved Quality-of-Services (QoS) and faster recovery from cyber-attacks and compromised switches. The multi-phase collaborative anomaly detection scheme demonstrates an accuracy of 99.81%, average latencies of 0.27 ms, and response speed within 9 s. The simulations and analysis show that the OpenStackDP network analytics framework substantially secures and outperforms prior SDN-based OpenStack solutions for Cloud architectures. 2023, The Author(s). -
An effective analytical method for fractional Brusselator reactiondiffusion system
In recent years, reactiondiffusion models have attracted researchers for their wide applications. In this article, we consider Brusselator reactiondiffusion system (BRDS), which is known for its cross diffusion and pattern formations in biology and chemistry. We derive an analytical solution of the fractional Brusselator reactiondiffusion system (FBRDS) with the help of the initial condition by a novel method, residual power series method (RPSM). The system solution has been analyzed by graph. 2023 John Wiley & Son Ltd. -
Estimation of stellar parameters and mass accretion rate of classical TTauri stars from LAMOST DR6
Classical T Tauri stars (TTS) are low-mass pre-main sequence stars with an active circumstellar environment. In this work, we present the identification and study of 260 classical TTS using LAMOST Data Release 6, among which 104 stars are newly identified. We distinguish classical TTS from giants and main-sequence dwarfs based on the log g values, and the presence of H ? emission line and infrared excess that arises from the circumstellar accretion disk. We estimated the mass and age of 210 stars using the Gaia colormagnitude diagram. The age is from 0.1 to 20 Myr, where 90% of the stars have age <10 Myr and the mass ranges between 0.11 and 1.9 M? . From the measured H ? equivalent widths, we homogeneously estimated the mass accretion rates for 172 stars, with most values ranging from 10 - 7 to 10 - 10M? yr - 1 . The mass accretion rates are found to follow a power law distribution with the mass of the star, having a relation of the form M?acc?M?1.430.26 , in agreement with previous studies. 2023, Indian Academy of Sciences.