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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. -
Review on impacts of micro- and nano-plastic on aquatic ecosystems and mitigation strategies
The rapid proliferation of microplastics (MPs) and nanoplastics (NPs) in our environment presents a formidable hazard to both biotic and abiotic components. These pollutants originate from various sources, including commercial production and the breakdown of larger plastic particles. Widespread contamination of the human body, agroecosystems, and animals occurs through ingestion, entry into the food chain, and inhalation. Consequently, the imperative to devise innovative methods for MPs and NPs remediation has become increasingly apparent. This review explores the current landscape of strategies proposed to mitigate the escalating threats associated with plastic waste. Among the array of methods in use, microbial remediation emerges as a promising avenue for the decomposition and reclamation of MPs and NPs. In response to the growing concern, numerous nations have already implemented or are in the process of adopting regulations to curtail MPs and NPs in aquatic habitats. This paper aims to address this gap by delving into the environmental fate, behaviour, transport, ecotoxicity, and management of MPs and NPs particles within the context of nanoscience, microbial ecology, and remediation technologies. Key findings of this review encompass the intricate interdependencies between MPs and NPs and their ecosystems. The ecological impact, from fate to ecotoxicity, is scrutinized in light of the burgeoning environmental imperative. As a result, this review not only provides an encompassing understanding of the ecological ramifications of MPs and NPs but also highlights the pressing need for further research, innovation, and informed interventions. 2023 Elsevier B.V. -
Purple Blue emission in MoO3:Ce3+ nanorods: Investigation on the structural and photoluminescence properties
MoO3:Ce3+ nanophosphors were synthesized with different doping concentrations of cerium by hydrothermal method. Structural, optical, and photoluminescence properties were explored. Raman spectroscopy and X-ray diffraction studies were carried out to examine the crystal structure, vibrational modes and symmetry. XRD and Raman spectroscopy assures the orthorhombic phase of MoO3 for the pure and doped samples. Nanorod like morphology was obtained for pure and doped samples. XPS analysis confirms the presence of Ce3+. While analyzing UVVis absorption spectra, the change in optical bandgap was observed with doping concentration in agreement with size effect. The refractive index of the prepared nanorods was evaluated. For MoO3:Ce3+nanorods excited at 250 nm, purple-blue emission comprising of transitions between 2D ? 2F7/2 along with 2D ? 2F5/2 levels of Ce3+ in MoO3 lattice were obtained. The concentration quenching mechanism was observed in MoO3:Ce3+ nanophosphors. Purple-blue emission from different samples were quantified using CIE chromaticity diagram. This work marks MoO3:Ce3+ nanorods as a suitable candidate for display and fluorescence imaging application. 2023 Elsevier Masson SAS -
Hi line analysis of Herbig Ae/Be stars using X-Shooter spectra
Herbig Ae/Be stars are intermediate-mass pre-main sequence stars undergoing accretion through their circumstellar disk. The optical and infrared (IR) spectra of HAeBe stars show Hi emission lines belonging to Balmer, Paschen and Brackett series. We used the archival X-Shooter spectra available for 109 HAeBe stars from Vioque et al. (2018) and analysed the various Hi lines present in them. We segregated the stars into different classes based on the presence of higher-order lines in different Hi series. We discussed the dependence of the appearance of higher-order lines on the stellar parameters. We found that most massive and younger stars show all the higher-order lines in emission. The stars showing only lower-order lines have Teff< 12 , 000 K and an age range of 510 Myr. We performed a case B line ratio analysis for a sub-sample of stars showing most of the Hi lines in emission. We noted that all but four stars belonging to the sub-sample show lower Hi line ratios than theoretical values, owing to the emitting medium being optically thick. The Hiline flux ratios do not depend on the stars spectral type. Further, from the line ratios of lower-order lines and Paschen higher-order lines, we note that line ratios of most HAeBe stars match with electron density value in the range of 10 9 10 11 cm - 3 . The electron temperature, however, could not be ascertained with confidence using the line ratios studied in this work. 2023, Indian Academy of Sciences. -
The Cartesian product of wheel graph and path graph is antimagic
Suppose each edge of a simple connected undirected graph is given a unique number from the numbers 1, 2, . . ., q, where q is the number of edges of that graph. Then each vertex is labelled with sum of the labels of the edges incident to it. If no two vertices have the same label, then the graph is called an antimagic graph. We prove that the Cartesian product of wheel graph and path graph is antimagic. 2023 Azarbaijan Shahid Madani University. -
Secure medical sensor monitoring framework using novel optimal encryption algorithm driven by Internet of Things
Recently, healthcare monitoring systems have emerged as significant tolls for constant monitoring of patient's physiological characteristics. These systems use implanted sensors. IoT (Internet of Things) have revolutionized healthcare systems where health care equipment's are equipped with many sensors that actively collect data from patients and pass it on to cloud based storages using gateway sensors. Securing data have been significant barriers in many applications as false information get injected, or important information are modified or stolen at different phases of health care systems dependent on IoT. The attacks can also result in fatalities making it imperative to secure IoT based health care systems. A Hybrid technique combining MOAES (Modified Optimal Advanced Encryption Standard) with CM (Chaotic Map) Encryptions called HMOAES-CM technique is proposed. This technique can be helpful in securely accessing the patient data over online mode, and in addition, the data sharing can be performed in an encrypted form for the necessary targets of stakeholders. The proposed authentication approach is aimed at IoT, which is resilient to all kinds of network attacks and its implementation is also simpler. Comparing the suggested work to similar works, the level of evaluation is much improved. 2023 The Authors -
Unlocking the Antimicrobial, Antifungal, and Anticancer Power of Chitosan-Stabilized Silver Nanoparticles
Silver nanoparticles (AgNPs) have become a research focus due to its antimicrobial, anticancer applications and cost-effective properties. In this study the effectiveness of green synthesis of NPs using biological macromolecule chitosan which isacting as a reducingcum stabilizing agent is carried out. An in-depth analysis of the synthesized AgNPs was conducted using a variety of sophisticatedcharacterization techniques such as UV-visible spectroscopy, particle size analysis, zeta potentialmeasurements, transmission electron microscopy (TEM), photoluminescence, and Fourier transform infrared (FTIR) spectroscopy. The antimicrobialactivity of the formulated AgNPs were inspected against two human pathogenic strains. In the antimicrobial activity, the synthesized AgNPs exhibited a reduction in the growth of both themicrobes. The minimum inhibitory concentration (MIC) of 1.22 M was observed for both Candida albicans and Mycobacterium smegmatis. Consequently, AgNPs may be used as an opportunity for modern-day antibiotics to treat infections due to human pathogens. Antiproliferative analysis revealed that AgNPs showed antiproliferative characteristics against MDA-MB-231 cells compared to the control. Such AgNPs have an anticancer effect and are likely to be used as smart drug delivery mediators to treat late-stage cancer. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Goodness of fit test for Rayleigh distribution with censored observations
We develop new goodness of fit tests for Rayleigh distribution based on fixed point characterization. We use U-Statistic theory to derive the test statistics. First we develop a test for complete data and then discuss, how the right censored observations can be incorporated in the testing procedure. The asymptotic properties of the test statistic in both uncensored and censored cases are studied in detail. Extensive Monte Carlo simulation studies are carried out to validate the performance of the proposed tests. We illustrate the procedures using real data sets. We also provide, a goodness of fit test for the standard Rayleigh distribution based on jackknife empirical likelihood. 2023, Korean Statistical Society. -
Phytochemical Analysis and Antibacterial Potential of Stevia rebaudiana (Bertoni, 1899) Leaf Extracts against Aeromonas Species: Influence of Extraction Methods and Solvents in Aquaculture Applications
Recent studies have explored Stevia rebaudiana Bertoni leaf extracts for their antibacterial potential and phytochemical content. However, the impact of extraction methods and solvents on aquaculture bacteria remains understudied. This research aimed to evaluate the antibacterial, radical scavenging, and phytochemical properties of S. rebaudiana extracts against Aeromonas species. Dried S. rebaudiana leaves were extracted using methanol (Mt) and ethanol (Et) through Soxhlet and maceration methods (SMt, SEt, MMt and MEt respectively). Soxhlet extraction yielded higher amounts (36.29% for Mt, 23.87% for Et) compared to maceration. Phytochemical analysis identified phenolics, flavonoids, alkaloids, saponin, tannin, and steroids in all extracts. Notably, MEt had elevated phenolic and flavonoid content, while SEt contained more tannins. MEt exhibited the strongest antioxidant activity (IC50 = 67.95g/mL), aligning with its high phenolic and flavonoid levels. In antibacterial assays against Aeromonas strains, ethanol extract showed the largest zone of inhibition (ZOI) of 16.67mm for A. salmonicida, followed by methanol extract (15mm) at 250 mg/mL, using maceration and Soxhlet methods, respectively. However, none of the extracts displayed activity against A. hydrophila. This suggests that cold maceration is a cost-effective method that preserves heat-sensitive secondary metabolites within a shorter extraction time. In conclusion, this study highlights the significance of extraction techniques and solvents in obtaining potent antibacterial and antioxidant extracts from S. rebaudiana leaves. The findings emphasize the potential of these extracts in aquaculture practices and open avenues for further research in utilizing natural compounds for sustainable aquaculture strategies. The Author(s) 2023. -
Computational Study of MHD Nanofluid Flow with Effects of Variable Viscosity and Non-uniform Heat Generation
The thermodynamic study of an unsteady two-dimensional nanofluid flow through a permeable stretched sheet is looked at. Water is used as the primary fluid, along with four different nanoparticles, including copper (Cu), titanium dioxide (TiO2), copper oxide (CuO), and aluminium oxide (Al2O3). The heat transfer phenomenon is explained by an outside source. Additionally considered are the impacts of heat generation and absorption. A similarity transformation is used to convert the considered set of mathematical equations into a system of ODEs. The BVP4C method is then mathematically applied, coupled with shooting fashion. The results are given for cases involving copper nanoparticles. The effects of various physical parameters on the profiles of the dimensionless flow field, temperature, average entropy generation function, skin friction, and the Nusselt number are examined with illustrations and thorough explanations. As exceptional circumstances of the current inquiry, there is a strong agreement between the current conclusion and the findings of the other researchers. The average entropy generation number, temperature, and velocity profiles are shown to be strongly influenced by regulating factors. The authors conclude that the average entropy production number decreased in the existence of a temperature- and space-dependent heat source/sink, but it increased with increasing the viscosity parameter. 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Endophytic bacteria Klebsiella spp. and Bacillus spp. from Alternanthera philoxeroides in Madiwala Lake exhibit additive plant growth-promoting and biocontrol activities
Background: The worldwide increase in human population and environmental damage has put immense pressure on the overall global crop production making it inadequate to feed the entire population. Therefore, the need for sustainable and environment-friendly practices to enhance agricultural productivity is a pressing priority. Endophytic bacteria with plant growth-promoting ability and biocontrol activity can strongly enhance plant growth under changing environmental biotic and abiotic conditions. Herein, we isolated halotolerant endophytic bacteria from an aquatic plant, Alternanthera philoxeroides, from the polluted waters of Madiwala Lake in Bangalore and studied their plant growth promotion (PGP) and biocontrol ability for use as bioinoculant. Results: The isolated bacterial endophytes were screened for salt tolerance ranging from 5 to 15% NaCl concentration. Klebsiella pneumoniae showed halotolerant up to 10% NaCl and Bacillus amyloliquefaciens and Bacillus subtilis showed up to 15%. All three strains demonstrated good PGP abilities such as aminocyclopropane-1-carboxylic acid (ACC) deaminase activity, phosphate solubilization, ammonia production, and nitrogen fixation. In addition, K. pneumoniae also exhibited high indoleacetic acid (IAA) production (195.66 2.51g/ml) and potassium solubilization (2.13 0.07ppm). B. amyloliquefaciens and B. subtilis showed good extracellular enzyme production against cellulase, lipase, protease, and amylase. Both the isolates showed a broad spectrum of antimicrobial activity against the tested organisms. The optimization of IAA production by K. pneumoniae was done by the response surface methodology (RSM) tool. Characterization of IAA produced by the isolate was done by gas chromatography-mass spectrometry (GCMS) analysis. The enhanced plant growth-promoting ability of K. pneumoniae was also demonstrated using various growth parameters in a pot trial experiment using the seeds of Vigna unguiculata. Conclusion: The isolated bacterial endophytes reported in this study can be utilized as PGP promotion and biocontrol agents in agricultural applications, to enhance crop yield under salinity stress. The isolate K. pneumoniae may be used as a biofertilizer in sustainable agriculture and more work can be done to optimize the best formulations for its application as a microbial inoculant for crops. 2023, The Author(s). -
Copper oxide modified biphasic titania for enhanced hydrogen production through photocatalytic water splitting
Recently, TiO2(B) has been extensively used in catalytic and energy fields owing to its exceptional crystal structure. But being a metastable state, TiO2(B) is transformed easily into other stable crystalline forms like anatase or rutile phase, and the low crystallinity limits the application of the material in catalysis. A combination of TiO2(B) with anatase, which is benefitted by a homojunction, is proven to be blessed with high activity. Herein, hydrogen production via photocatalytic water-splitting is presented using Cu modified biphasic titania nanotubes achieved by a facile hydrothermal procedure. The systems are well characterized using SEM, TEM, XRD analysis, N2 adsorption study, FTIR, DR-UV, Raman, Photoluminescence, and X-ray photoelectron spectral analysis. The homo-junction developed in titania due to anatase TiO2 (B), as well as the heterojunction created by the co-catalyst, tune the photocatalytic activity of TiO2 nanotubes positively, as evident from the enhanced hydrogen production over the system. 2023 -
A Reflection on the Current Status of Animal-Assisted Therapy in India
The field of animal-assisted therapy is advancing quickly throughout the world gaining popularity as a complementary therapy. Several countries, especially in the East, are still in their nascent phase in utilizing animal-assisted therapy and a more realistic presentation of their status should drive them towards effective initiatives to promote the field. The primary objective of this paper is to throw light on the current scenario of animal-assisted therapy in India. The relevant databases such as Scopus, Google Scholar, Proquest, PubMed, and JSTOR were searched to identify the research literature. The organizational websites, news, and blog articles, as well as institutional repositories, were explored to maximize the evidence. A total of 24 articles were found which included published research articles as well as unpublished conference papers. Results found a dearth of practice and research throughout the country indicating an urgent need to direct steps in promoting the growth of the field. The contemporary issues in the implementation of animal-assisted therapy such as cultural and religious beliefs, lack of awareness, lack of practising organizations and therapists warrant immediate attention. Reducing the research and practice gap alongside focusing on creating awareness, changing public perception, introducing coursework in educational institutions, the publication of evidence-based research will help in the acceptance and growth of this novel therapeutic field. 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Effects of activation energy and chemical reaction on unsteady MHD dissipative DarcyForchheimer squeezed flow of Casson fluid over horizontal channel
The impact of chemical reaction and activation energy plays a vital role in the analysis of fluid dynamics and its thermal properties. The application of the flow of fluid is significantly considered in nuclear reactors, automobiles, manufacturing setups, electronic appliances etc. This study explores the impacts of activation energy and chemical reaction on the magnetohydrodynamic DarcyForchheimer squeezed Casson fluid flow through a porous material across the horizontal channel where the two parallel plates are assumed to be in motion. By using similarity variables, partial differential equations are converted to ordinary differential equations. Numerical method is applied using MATLAB to solve the problems and acquire the data for velocity field, thermal distribution, and concentration distribution. The graphs indicate that fluid velocity and temperature increases as the plates are brought closer. In addition, there was a correlation between a rise in the Hartmann number and a decrease in the fluid's velocity because of the existence of strong Lorentz forces. The temperature and the concentration of the liquid will increase due to the Brownian motion. When the DarcyForchheimer and activation energy parameters are both increased, the velocity and concentration decreases. 2023, The Author(s). -
Identifying the population of T-Tauri stars in Taurus: UVoptical synergy
With the third data release of the Gaia mission, Gaia DR3 with its precise photometry and astrometry, it is now possible to study the behavior of stars at a scale never seen before. In this paper, we developed new criteria to identify T-Tauri stars (TTS) candidates using UV and optical color-magnitude diagrams (CMDs) by combining the GALEX and Gaia surveys. We found 19 TTS candidates and five of them are newly identified TTS in the Taurus molecular cloud (TMC), not cataloged before as TMC members. For some of the TTS candidates, we also obtained optical spectra from several Indian telescopes. We also present the analysis of distance and proper motion of young stars in the Taurus using data from Gaia DR3. We found that the stars in Taurus show a bimodal distribution with distance, having peaks at 130.17-1.241.31 pc and 156.25-5.001.86 pc. The reason for this bimodality, we think, is due to the fact that different clouds in the TMC region are at different distances. We further showed that the two populations have similar ages and proper motion distribution. Using the Gaia DR3 CMD, we showed that the age of Taurus is consistent with 1Myr. 2023, Indian Academy of Sciences.