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Spectroscopic, crystal structure and DFT-assisted studies of some nickel(II) chelates of a heterocyclic-based NNO donor aroylhydrazone: in vitro DNA binding and docking studies
Five new nickel(II) complexes have been synthesised with an NNO donor tridentate aroylhydrazone (HFPB) employing the chloride, nitrate, acetate and perchlorate salts, and all the complexes are physiochemically characterized. Elemental analyses suggested stoichiometries as Ni(FPB)(NO3)]2H2O (1), [Ni(HFPB)(FPB)]Cl (2), [Ni(FPB)(OAc)(DMF)] (3), [Ni(FPB)(ClO4)]DMF (4), [Ni(FPB)2] (5). Aroylhydrazone is found coordinating in deprotonated iminolate form in four of the complexes (1, 3, 4, 5) however in one case (complex 2), two aroylhydrazone moieties are binding to the metal centre in the neutral and anionic forms. The structure of the bisligated complex 5, found using single crystal X ray diffraction studies confirmed that the metal has a distorted octahedral N4O2 coordination environment, with each of the two deprotonated ligands coordinating through the pyridine nitrogen, imino-hydrazone nitrogen and the enolate oxygen of the hydrazone moiety. To compare and study, the electronic interactions and stabilities of the metal complexes, various quantum chemical parameters were calculated. Moreover, Hirshfeld surface analysis was carried out for complex 5 to determine the intermolecular interactions. The biophysical attributes of the ligand and complex5 have been investigated with CT-DNA and experimental outcomes show that the Ni(II) complex exhibited higher binding propensity towards DNA as compared to ligand. Furthermore, to specifically understand the type of interactions of the metal complexes with DNA, molecular docking studies were effectuated. In addition, the electronic and related reactivity behaviors of the ligand and five Ni(II) complexes were studied using B3LYP/631 + + G**/LANL2DZ level. As expected, the obtained results from Natural Bond Orbital (NBO) computations displayed that the resonance interactions (n ? ?* and ? ? ?*) play a determinant role in evaluating the chemical attributes of the reported compounds. Graphical abstract: (Figure presented.). The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. -
Spectrum of corona products based on splitting graphs
Let G be a simple undirected graph. Three new corona products of graphs based on splitting graph of G are defined. The adjacency spectra of the three new graphs based on splitting graph of G are determined. The number of spanning trees and the Kirchoff index of the new graphs are determined using their nonzero Laplacian eigenvalues. 2023 World Scientific Publishing Company. -
Speculative investment decisions in cryptocurrency: a structural equation modelling approach
Cryptocurrency markets are inclined towards speculative usage due to the inherent high risk of financial loss and the potential for substantial gains during transaction completion. In response to this phenomenon, this study represents the inaugural effort to explore the influence of variables such as subjective norms, domain knowledge, impulsive investment tendencies, and self-control on decisions related to speculative investments. Utilising structural equation modelling with a dataset of 367 responses in India, the study is the first of its kind. The research reveals that subjective norms and domain knowledge play a significant role in influencing impulsive investment and self-control. Additionally, impulsive investment exhibits significant associations with decisions involving speculative investments. This insight underscores the complexity wherein individuals, despite exercising self-control, may still engage in speculative decisions that lead to adverse consequences. The findings have practical implications for investors and regulators, offering valuable insights into investment behaviours within the cryptocurrency realm. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Speech to text conversion and summarization for effective understanding and documentation
Speech, is the most powerful way of communication with which human beings express their thoughts and feelings through different languages. The features of speech differs with each language. However, even while communicating in the same language, the pace and the dialect varies with each person. This creates difficulty in understanding the conveyed message for some people. Sometimes lengthy speeches are also quite difficult to follow due to reasons such as different pronunciation, pace and so on. Speech recognition which is an inter disciplinary field of computational linguistics aids in developing technologies that empowers the recognition and translation of speech into text. Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same. The research work presented in this paper describes an easy and effective method for speech recognition. The speech is converted to the corresponding text and produces summarized text. This has various applications like lecture notes creation, summarizing catalogues for lengthy documents and so on. Extensive experimentation is performed to validate the efficiency of the proposed method. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Spherulitic crystallization of ?-In2Te3 by physical vapour deposition
Different morphologies of indium telluride (In2Te3) including novel spherulites were crystallized using the physical vapour deposition (PVD) method, by varying the difference in the growth and source zone temperature (?T) of a dual zone horizontal furnace assembled indigenously. Whiskers and kinked needles of In2Te3were grown at ?T = 250 K and 300 K respectively, maintaining the growth zone at 500 C. At high supersaturation (? T = 400 K), spherulitic crystals were obtained. The stoichiometric composition of these crystals has been confirmed using energy dispersive analysis by x-rays (EDAX). The structure of ?-In2Te3 spherulitic crystals is identified as zinc blende with lattice parameter a = 6.159 from x-ray diffraction (XRD) studies. The scanning electron microscope (SEM) images revealed the radial structure of the grown spherulites. The growth mechanism for the spherulitic crystallization of ?-In2Te3 crystals has been discussed based on the theoretical models. Copyright 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. -
Spider Monkey Crow Optimization Algorithm with Deep Learning for Sentiment Classification and Information Retrieval
The epidemic increase in online reviews' growth made the sentiment classification a fascinating domain in academic and industrial research. The reviews assist several domains, which is complicated to gather annotated training data. Several sentiment classification methodologies are devised for performing the sentiment analysis, but retrieval of information is not accurately performed, less effective, and less convergence speed. In this paper, we propose a sentiment paper proposes a sentiment classification model, namely Spider Monkey Crow Optimization algorithm (SMCA), for training the deep recurrent neural network (DeepRNN). In this method, the telecom review is employed to remove stop words and stemming to eliminate inappropriate data to minimize user's seeking time. Meanwhile, the feature extraction is performed using SentiWordNet to derive the sentiments from the reviews. The extracted SentiWordNet features and other features, like elongated words, punctuation, hashtag, and numerical values, are employed in the DeepRNN for classifying sentiments. To retrieve the required review, the Fuzzy K-Nearest neighbor (Fuzzy-KNN) is employed to retrieve the review based on a distance measure. With rigorous assessments and experimentation, it is observed that the proposed SMCA-based DeepRNN performs better in terms of accuracy of 97.7%, precision of 95.5%, recall of 94.6%, and F1-score 96.7%, respectively. 2013 IEEE. -
Spiking neural network with blockchain for tampered image detection using forensic steganography images
Accurate tools are required to acknowledge misleading images in order to maintain image legitimacy, and these tools must allow for legal operations on images. Additionally, after posting their images to the Internet, image owners lose rights over the images because there are no measures in place to safeguard them from misuse. One of the most well-liked techniques for addressing copyright disputes is the use of steganography technologies. The embedded steganography images can, sadly, be easily altered or deleted. To address this problem, this work presents the spiking neural network (SNN) with blockchain for tampered image detection utilizing forensic steganography images. Forensic steganography images that have been altered can be found with this SNN. Using steganography images from the database, SNN is trained in this model. The blockchain stores the owners access policies. The Python platform is used to implement the proposed strategy. F-measure, specificity, accuracy, precision, recall false positive rate (FPR), and false negative rate (FNR) are used to gauge how well the proposed approach performs. When compared to state-of-the-art approaches, the proposed approach obtained an impressive rise of 98.65%, in classification accuracy. 2024 Institute of Advanced Engineering and Science. All rights reserved. -
Spirocyclic isatin-derivative analogues: Solvation, structural, electronic, topological, reactivity properties, and anti-leukaemic biological evaluation
The present work investigates, via computational methods, three spirocyclic isatin derivatives with ?-methylene-?-butyrolactone cores, whose synthesis, experimental data and structural-activity relationships have been reported, to compare their properties and biological action. DFT (Density Functional Theory) studies, including geometry optimisation, FMO Analysis, theoretical UV spectral analysis, NBO and NLO studies, are performed using Gaussian 09 W with a standard basis set. The IEFPCM model is employed to investigate the solvent effect on the reactivity and stability of the compounds. Topological analyses are also performed, including ELF, LOL, RDG and charge transfer studies. ADME profiling is performed using SwissADME online tool. Anti-leukaemic target proteins are selected and docked with the title compounds to understand their suitability to act against leukaemic conditions. 2023 Elsevier B.V. -
Spontaneous hydrogen production using gadolinium telluride
Developing materials for controlled hydrogen production through water splitting is one of the most promising ways to meet current energy demand. Here, we demonstrate spontaneous and green production of hydrogen at high evolution rate using gadolinium telluride (GdTe) under ambient conditions. The spent materials can be reused after melting, which regain the original activity of the pristine sample. The phase formation and reusability are supported by the thermodynamics calculations. The theoretical calculation reveals ultralow activation energy for hydrogen production using GdTe caused by charge transfer from Te to Gd. Production of highly pure and instantaneous hydrogen by GdTe could accelerate green and sustainable energy conversion technologies. 2023 -
Spoofing Face Detection Using Novel Edge-Net Autoencoder for Security
Recent security applications in mobile technologies and computer systems use face recognition for high-end security. Despite numerous security tech-niques, face recognition is considered a high-security control. Developers fuse and carry out face identification as an access authority into these applications. Still, face identification authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized user. In the existing spoofing detection algorithm, there was some loss in the recreation of images. This research proposes an unobtrusive technique to detect face spoofing attacks that apply a single frame of the sequenced set of frames to overcome the above-said problems. This research offers a novel Edge-Net autoencoder to select convoluted and dominant features of the input diffused structure. First, this pro-posedmethodistestedwiththeCross-ethnicityFaceAnti-spoofing (CASIA), Fetal alcohol spectrum disorders (FASD) dataset. This database has three models of attacks: distorted photographs in printed form, photographs with removed eyes portion, and video attacks. The images are taken with three different quality cameras: low, average, and high-quality real and spoofed images. An extensive experimental study was performed with CASIA-FASD, 3 Diagnostic Machine Aid-Digital (DMAD) dataset that proved higher results when compared to existing algorithms. 2023, Tech Science Press. All rights reserved. -
SPP1, a potential therapeutic target and biomarker for lung cancer: functional insights through computational studies
NIH reported 128 different types of cancer of which lung cancer is the leading cause of mortality. Globally, it is estimated that on average one in every seventeen hospitalized patients was deceased. There are plenty of studies that have been reported on lung cancer draggability and therapeutics, but yet a protein that plays a central specific to cure the disease remains unclear. So, this study is designed to identify the possible therapeutic targets and biomarkers that can be used for the potential treatment of lung cancers. In order to identify differentially expressed genes, 39 microarray datasets of lung cancer patients were obtained from various demographic regions of the GEO database available at NCBI. After annotating statistically, 6229 up-regulated genes and 10324 down-regulated genes were found. Out of 17 up-regulated genes and significant genes, we selected SPP1 (osteopontin) through virtual screening studies. We found functional interactions with the other cancer-associated genes such as VEGF, FGA, JUN, EGFR, and TGFB1. For the virtual screening studies,198 biological compounds were retrieved from the ACNPD database and docked with SPP1 protein (PDBID: 3DSF). In the results, two highly potential compounds secoisolariciresinol diglucoside (-12.9 kcal/mol), and Hesperidin (-12.0 kcal/mol) showed the highest binding affinity. The stability of the complex was accessed by 100 ns simulation in an SPC water model. From the functional insights obtained through these computational studies, we report that SPP1 could be a potential biomarker and successive therapeutic protein target for lung cancer treatment. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
SPREADING RELIGION AND CULTURE THROUGH INTERNET MEMES
This paper delves into the use of Internet memes as a means of spreading religion and ethical values in modern society. With the rise of the Internet and social media, memes have gained popularity as a form of shared content with the ability to convey meaningful messages. The research evaluates the prevalence and impact of memes in religious and ethical contexts. Through this research, the authors present their viewpoint after mulling over the findings of authors like Limor Shifman. The study asserts that memes can facilitate discussions, promote religious literacy, reinforce beliefs, and instil ethical values. Additionally, it anticipates that religious and ethical memes may influence individuals' actions in their daily lives. This research is significant as it examines the potential of memes to serve as a contemporary tool for spreading religion and ethics in a digital world. 2023 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore),. -
Sprouting in Seeds Aided by Nitrogen Sourced from Ammonia Fumes Leached from Aluminum Dross
Nitrogen and water are nutrients essential for the sprouting of seeds and healthy growth of plants. The seeds derive nitrogen from ammonia (NH3), found in ammonium hydroxide commonly added as manure to the soil. In a materials synthesis process, NH3 gas was released when Aluminum-dross (Al-dross), a hazardous industrial foundry waste was beneficiated to extract useful materials (metallic Al, oxides of Al and Mg, etc.) from the waste. Chemical tests, SEM with EDS and XRD were used to characterize sieved black Al-dross (starting raw material) before and after the beneficiation process. Al-dross also contained significant quantities of aluminum nitride (AlN). When treated with an aqueous media (plain or carbonated water), the AlN reacted to release NH3 gas fumes. This work explored the potential of using this gas to act as a source of nitrogen to accelerate the sprouting of seeds and plant germination. Vegetable and fruit seeds were sown in the soil that was directly infused with the NH3 released from Al-dross for two hours, followed by several (8 to 12) hours of self-diffusion time for homogeneous distribution of the gas in the soil. Five pairs of soils (untreated regular and NH3 fumes treated soils) were prepared under similar conditions. 5 different vegetable and fruit seedlings were planted in these pairs of soils. The germination patterns and growth of the sprouts with time were observed. The seeds that preferred an alkaline environment for germination (e.g., ridge gourd and watermelon seeds) sprouted early and in good health in the NH3 treated soil. Seeds preferring acidic soils did not germinate well in NH3 fume-infused soils. The experiments confirmed the viability of the novel concept, where the waste ammonia fumes released from Al-dross could be favorably generated and used in a controlled manner to promote sprouting of certain agricultural seedlings. 2023 Elsevier Ltd. All rights reserved. -
Sputter deposited tungsten oxide thin films and nanopillars: Electrochromic perspective
Tungsten oxide (WO3) thin films and nano pillars were grown on FTO and corning substrates by using DC magnetron sputtering. Structural properties, surface morphology, optical properties, and electrochromic properties were systematically characterized by using SEM, XRD, UVVis Spectrometer, and Electrochemical Analyser respectively. Increased oxygen partial pressure resulted a rise in the optical transmittance from 72% to 89% at a wavelength of 600 nm. Moreover, coloration efficiency was also found to vary with partial pressures for both planar and glad from 30.48 cm2C-1 to 78.36 cm2C-1. We observe that glad deposited nano pillars showing higher coloration efficiency as compared to the planar thin film. The coloration efficiency found for the planar thin film and nano pillars at optimized partial pressure are 37.04 cm2C-1 and 78.36 cm2C-1 respectively. A strong influence of oxygen partial pressure and surface to volume ratio has been observed on the coloration efficiency, which can play a major role in the electrochromic application. 2022 Elsevier B.V. -
SR-Mine: Adaptive Transaction Compression Method for Frequent Itemsets Mining
Extraction of frequent itemsets is a key step in association rule mining. Frequent Pattern (FP) mining from a very large dataset is still a challenging research problem. The basic frequent itemset algorithms are Apriori and FP-growth. FP-growth uses Frequent Pattern Tree (FP-tree) to store the database information in a compressed form. A large number of research papers have been proposed as an improvement of the basic frequent itemset mining algorithms. Several researchers have proposed modifications to existing data structures as well as new data structures to improve the mining process. A new method, Size Reduced Mining (SR-Mine), is proposed to speed up the FP-tree creation. The proposed work is implemented with the basic FP-growth algorithm and with the other two recent algorithms based on FP-tree. The three modified algorithms have been tested with standard datasets and compared with the original algorithms. The proposed method can be applied with the frequent itemset mining algorithms which consider each transaction one by one to construct a data structure for mining. The experimental results show that the proposed method can improve the performance of the mining. 2021, King Fahd University of Petroleum & Minerals. -
Stability Analyses of BrinkmanBard Convection in Hybrid-Nanoliquid Saturated-Porous Medium Using Local Thermal Non-equilibrium Model
This paper carries out linear and weakly non-linear stability analyses of natural convection in a Newtonian hybrid-nanoliquid saturated porous medium. The Boussinesq approximation is assumed to be valid in the study, and a two-phase energy model is used. The weighted residual Galerkin technique is employed to obtain the expression for the Rayleigh number and Lorenz model by using a truncated double Fourier series solution. The quadratic non-linear Lorenz model is solved numerically by using the RungeKuttaFehlberg method. Water is considered as a carrier liquid, and copper and alumina nanoparticles are considered with dilute concentration. Linear stability analysis reveals the onset of convection prepones in a hybrid nanoliquid-saturated porous medium. The amount of heat transport is maximum in a hybrid nanoliquid saturated porous medium and minimum in a liquid-saturated porous medium. Local thermal non-equilibrium situation ceases at higher rates of interphase heat transfer coefficient. The assumption of local thermal non-equilibrium is prominent in hybrid nanoliquid saturated porous medium. The results of the hybrid-nanoliquid channel, a hybrid nanoliquid saturated porous medium with the local thermal assumption, are presented as a limiting case of the study. 2024, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Stability and statistical analysis on melting heat transfer in a hybrid nanofluid with thermal radiation effect
The dual solutions for the stagnation point flow in a cobaltCeO2/kerosene hybrid nanofluid with melting heat transfer and thermal radiation are analyzed. The partial differential equations are solved by the conversion of the partial differential equations into nonlinear ordinary differential equations by utilizing suitable scaling group transformations. Numerical solutions are obtained by employing the built-in function in the MATLAB software (bvp4c). Physically recoverable solutions are found employing stability analysis. The factor variables of interest (melting parameter, the nanoparticle volume fraction of cobalt and CeO2) are then further analyzed by utilizing the sensitivity analysis (based on the response surface methodology model) for heat transfer rate, as well as the skin friction coefficient. It is found that the heat transfer and skin friction tend to be significantly higher in a hybrid nanofluid due to the radiation and melting heat transfer. The lower branch is found to be unstable, whereas the upper branch is found to be stable. Also, the heat transfer rate and skin friction coefficient are found to be negatively sensitive toward the melting parameter. The model in this study can be applied for microscopic propulsion systems and the nano-electromechanical systems integrated with a nano-based system. IMechE 2021. -
STABILITY IN CHAOS: IMPACT OF MONETARY, FISCAL, AND FIRM CHARACTERISTICS ON INVESTOR SENTIMENT IN ASIAN EMERGING MARKETS
This study investigates the impact of firm characteristics, monetary policies, and fiscal policies on investor sentiment, specifically focusing on market volatility and trading volume in six Asian emerging markets during the pre-pandemic and pandemic periods. Using panel data regression on a sample of 5,619 firms between 2015 and 2023, this study analyses the distinct roles of firm-specific factors and macroeconomic policies in shaping market behaviour during periods of economic instability. The findings reveal that firm characteristics such as capital structure and payout policies consistently drive both volatility and trading volume. Monetary policies, particularly interest rates and money supply, showed heightened significance during the pandemic, while fiscal policies, though largely insignificant pre-pandemic, became more relevant during the crisis. The study's results provide critical insights for policymakers and investors on the dynamic interplay between firm-level and macroeconomic factors during crisis periods, emphasising the need for coordinated policy responses. 2024, Universiti Malaysia Sarawak. All rights reserved. -
Stability of porous medium convection in polarized dielectric fluids with non-classical heat conduction
International Journal of Mathematical Archive Vol.4, Issue 4, pp.136-144, ISSN No. 2229-5046 -
Stability Testing and Restoration of a DEIG-Based Wind Power Plant with Indirect Grid Control Strategies
In the current scenario, because of government policies, environmental factors, and technological improvements, there is a rapid growth in renewable energy sector. The emphasis is to obtain better system performance by effective resource utilization and providing security and reliability. This paper discusses the design and implementation of indirect grid control of a wind power plant by controlling the parameters in both grid and rotor side converters. The proposed system consists of Doubly Excited Induction Generator (DEIG) with Wind turbine system (WTS) and Mechanical and Electrical Power Controlling Systems (MPCS-EPCS). Various transmission line faults (symmetrical and asymmetrical faults) incur power imbalances in power grid. The developed MPCS and EPCS are helpful to perform grid monitoring and controlling under different types of faulty conditions. The MPCS monitors the effective source utilization and EPCS helpful for matching the grid energy levels under normal and faulty conditions. Modification in the converter topologies to minimize the impact of adverse effects of faults on the DEIG-WTS and to improve resiliency in the power grid is also discussed. To improve the stability and enhancing resource utilization to improve the efficiency of the overall system with the enhancement of fault voltage ride-through capability in DEIG-WTS under fault conditions are also considered. The stability of the system is tested under steady-state and dynamic-state conditions by applying faulty conditions in MATLAB/Simulink environment. 2023 IETE.