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A concise route to fused tetrazolo scaffolds through 10-camphor sulfonic acid auto-tandem homogeneous catalysis and mechanistic investigation
10-Camphor sulfonic acid (10-CSA) as an organo-catalyst has gained interest due to its versatile solubility and easiness of handling. This work reports a simple synthetic method through non-classical Biginelli for the construction of tetrazolo pyrimidine (4a-m) and quinazolines (4a?-o?). Azolopyrimidines and quinazolines are of great pharmaceutical importance. Numerous compounds are currently in use for the treatment of different diseases. Therefore their synthesis is industrially inevitable. Employing aldehydes, 1,3-dicarbonyls, and 5-Aminotetrazole, we report eco-friendly, cost-effective catalysis through a tandem reaction catalyzed by the 10-CSA that gave excellent yields, 7095 % for tetrazolo quinazoline and 4576 % tetrazolo pyrimidines respectively. The homonuclear NOESY analysis confirms the selective formation of one isomer. All the compounds are characterised by 1H NMR, 13C NMR, and MS. Investigation of the reaction mechanism by both experimental and theoretical studies provides evidence. Mechanism of the reaction was also explained utilizing the information from mass spectrometry monitoring. DFT calculation carried out at PBEPBE (Perdew-Burke-Ernzerhof) functional and 6-31G (d,p) basis set level of theory of the various intermediates observed supports the experimental evidence. 2023 Elsevier B.V. -
Azole-Based Antibacterial Agents: A Review on Multistep Synthesis Strategies and Biology
This article reviews current multistep synthesis strategies of azole-based antibacterial agents. In recent years, extensive use of chemical agents in treating different diseases resulted in the development of drug resistance. The war on multidrug resistance has resulted in the most significant loss to the worlds economy. Thus, the expansion of development of novel and potential candidates such as azoles and its derivatives is an escalating area in the field of medicinal chemistry. Azole compounds are increasingly being considered necessary in drug discovery paradigms as a number of them serve as lead compounds for the discovery of potent therapeutic agents. They have been used to treat bacterial, fungal, malarial, viral, and other general infections. They have also been known for their anticancer and anti-inflammatory activities. Their efficacy has been attributed to their electron-rich property, resulting in the formation of non-covalent bonds to the receptor proteins. Current research has given us a significant collection of synthetic strategies in the progress of azole compounds. This review article describes the survey of literature regarding multistep synthetic methods in the preparation of azole-based compounds and their antibacterial properties in the last 5 years. 2021 Taylor & Francis Group, LLC. -
An Experimental Investigation on Flexural Strength of Ferrocement Slab Made of Slag Sand Partially Replaced with Iron Ore Tailings
Effective use of slag sand and Iron Ore Tailings and other waste obtained from the manufacturing industry and mining industry like waste foundry sand, will reduce the negative impact on the environment and also will provide opportunities for effective use of natural resources and contribute to sustainability. The aim of this research project is to study the flexural strength of ferrocement slab made of slag sand partially replaced with iron ore tailings with sustainability point of view. Investigation of 48 slab panels of 700mm 300 mm size with thickness 25 mm and 30 mm was conducted using 1 and 2 layers of weld mesh reinforcement casted with different percentage of iron ore tailings. Slabs were tested in Universal Testing Machine, which showed good results with 15% of iron ore tailings. Published under licence by IOP Publishing Ltd. -
Effect of source-substrate distance on the transparent electrode properties of spray pyrolysed aluminium doped zinc oxide thin films
The wide band gap zinc oxide is a potential metal oxide that has been widely used in optoelectronic applications. The zinc oxide thin films demonstrate excellent conductivity and transparency enabling them for transparent electrode applications. The aluminium doping is an efficient route in further improving the conductivity without compromising the transparency and scalable spray pyrolysis is an effective approach in realizing high quality thin films. Our current study focuses on the effects of distance between the substrate and spray nozzle on the structural, morphological, optical, and electrical properties of aluminium doped zinc oxide. Our results suggests that this spray parameter has appreciable impact on the thin film properties and can be optimized for tuning properties. We explain this in detail backed by the characterization of thin films by X-ray diffraction, Atomic Force Microscopy, UVVis-NIR spectroscopy, Photoluminescence and Hall effect measurements. 2021 -
Restructuring Leaner-Centric Approach Framework Through Revised Bloom Taxonomy
The Leaner-Centric Approach, a method of teaching that has stood the test of time, was first introduced in the education system during the times of the Chinese Philosopher Confucius (551BC 479BC) and the teachings of Socrates (469BC-399BC). The old education emphasized students and their tasks based on the instruction given by teachers. Even though the education system was not called learner-centric, it was indeed a learner-centric system that existed then. Later, the teacher-centric approach became essential, and students' participation became very low in the classroom. Because of this, the students' performance was affected. The leaner-centric approach incorporates many activities and methods and increases learner participation. The study focuses on reconstructing the leaner-centric approach in the current scenario by changing the traditional concepts conceived by different teachers. The research also highlights that if a centric approach is followed in the classroom in its true sense, learning will be an unforgettable experience for the students. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Determinants of Food Security in the Gulf Cooperation Council: A Cointegration Approach with an Autoregressive Distributed Lag Model
This paper examines the dynamics of the food import bill for the Gulf Cooperation Council (GCC) during the period 1980 2019 using a co-integration approach of the autoregressive distributed lag (ARDL) model. The study ascertains that the food market in the GCC is highly dependent on imports, which makes it vulnerable to any import disruption. The model confirms that there is a long-term relationship between the food import bill and its dynamics, with an adjustment rate of 37%, indicating that 37% of the deviations from the long-run path are corrected annually. The study demonstrates that in the long run, the food import bill was positively influenced by Gross domestic product (GDP) per capita, exports, inflation, global food prices, and regional instability and negatively influenced by the local production index. Population growth has a significant impact only in the short run. The implications of the findings were discussed, and a food security framework for the GCC has been developed. Engineered Science Publisher LLC 2023. -
Incorporating the metaverse into the green banking revolution: Spearheading the implementation of eco-friendly financial practices
This study aims to explore the awareness and perceptions of green banking among bankers and customers in rural and semi-urban areas of India. A structured questionnaire was employed to gather information from 807 customers and 200 officials of selected commercial banks, utilizing the snowball sampling method. The study utilized chi-square and factor analysis techniques. The chi-square test results revealed an association between educational status and the customer's opinion regarding green banks. Factor analysis derived three key factors influencing the adoption of green banking: convenience and environmental sustainability, financial and technological advantages, and customer retention and prestige. The findings indicate that green banking services provide more benefits to its customers than traditional banking. 2024, IGI Global. -
Brand Loyalty Drivers among Generation Z Fashion Consumers: A Comparative Analysis
Brand loyalty is crucial in the competitive fashion market, particularly among Generation Z. Although previous studies have investigated what drives loyalty, there is still limited evidence from India, particularly about gender differences. This study adopts a context-specific and exploratory approach to examine brand loyalty and its drivers among Generation Z fashion consumers in Bangalore. The study adopts a quantitative research design with a structured questionnaire using a 5-point Likert scale. A sample of 100 Generation Z students in Bangalore was selected using convenience sampling to collect the data. Further descriptive and inferential statistical analyses were conducted using SPSS. The findings show positive associations among brand loyalty, brand awareness, perceived quality, emotional connection, and social influence. Independent-samples t-tests reveal no significant difference in overall brand loyalty between male and female respondents. However, regression analyses indicate that perceived quality and brand awareness are relatively stronger predictors of brand loyalty among male respondents. In contrast, emotional connection is a stronger predictor among female respondents. These findings suggest differences in motivational pathways rather than loyalty intensity. The study suggests that while overall brand loyalty levels are similar across genders, the motivational drivers underlying loyalty differ. These findings are context-specific and exploratory, and their generalizability is limited by convenience sampling and a restricted geographic scope. 2026 Journal of Computers, Mechanical and Management. -
Performance Analysis of Deterministic Finite Automata and Turing Machine Using JFLAP Tool
In real life, the increased data accessing speed and data storage ability is required by most of the machinery fields. However, the real-world problems can be studied effectively with the combination of scientific computational techniques with the mathematical models. Automata theory is known to be the popular mathematical model. Towards most of the software and hardware related applications, the computational methods are analyzed and designed using significant automata theory concepts (likely, pushdown automata (PDA), Turing machines (TMs) and finite automata (FA)). Hence, the conventional lecture-driven style has attracted the reflective preferences of learners using these abstract natured concepts. But the lecture-driven teaching style has less motivated the computer engineering learners. In order to learn automata theory and computational models, we introduce the PDA and TM in a virtual platform. However, this work has motivated the improvement of longitudinal experimental validation and learning using the modern technology. Java Formal Languages and Automata Package (JFLAP) tool is used to write our simulators in JAVA language and the results are obtained from each machine through simulating the input strings. 2021 World Scientific Publishing Company. -
Synthesis and characterization of CeO2/Bi2O3/gC3N4 ternary Z-scheme nanocomposite
An effective and facile phytogenic method was used to prepare CeO2/Bi2O3 and CeO2/Bi2O3/gC3N4 composites using Eichhornia crassipes phytoextract. The synthesized catalysts were characterized using techniques such as XRD, FTIR, UV-DRS, PL, SEM-EDAX, XPS, zeta potential, and TGA. These catalysts showed diverse photocatalytic and optical properties due to the alteration in the bandgap. The synthesized composites exhibited good photocatalytic activity by degrading Malachite green (MG) dye. The increase in the photocatalytic activity could be attributed to the p-n heterojunction of the catalysts with efficient charge separation and strong oxidative ability. The modified photocatalysts showed excellent catalytic activity and reusability under visible light. The superior efficiency and its applications in environmental remediation make these catalysts a potential candidate for photocatalysis. 2020 The American Ceramic Society -
Eco friendly nitration of toluene using modified zirconia
Nitration of toluene has been studied in the liquid phase over a series of modified zirconia catalysts. Zirconia, zirconia- ceria (Zr0.98Ce0.02)O2, sulfated zirconia and sulfated zirconia- ceria were synthesised by co precipitation method and were characterised by X-ray diffraction, BET surface area, Infra red spectroscopy analysis (FTIR), Thermogravimetric analysis (TGA), Scanning Electron Microscopy (SEM), and Energy Dispersive X ray analysis (EDAX). The acidity of the prepared catalysts was determined by FTIR pyridine adsorption study. X-ray diffraction studies reveal that the catalysts prepared mainly consist of tetragonal phase with the crystallite size in the nano range and the tetragonal phase of zirconia is stabilized by the addition of ceria. The modified zirconia samples have higher surface area and exhibits uniform pore size distribution aggregated by zirconia nanoparticles. The onset of sulfate decomposition was observed around 723 K for sulfated samples. The catalytic performance was determined for the liquid phase nitration of toluene to ortho-, meta- and para- nitro toluene. The effect of reaction temperature, concentration of nitric acid, catalyst reusability and reaction time was also investigated. 2013 BCREC UNDIP. -
Modelling and optimization of Rhodamine B degradation over Bi2WO6Bi2O3 heterojunction using response surface methodology
The Bi2O3/Bi2WO6 heterostructures of various compositions are prepared via the surfactant-assisted solgel method, which exhibits enhanced and synergistic photocatalytic activity towards the degradation of Rhodamine B (Rh B) using visible light irradiation. Characterization of these heterostructures has been done using X-ray diffraction, microscopic and spectroscopic methods. The 50% tungstate in bismuth oxide (BWO) nanocomposites having band gap of 2.85eV and an average size of 4080nm shows maximum dye removal up to 87% in 4h compared to pure Bi2O3 and other heterostructures of Bi2O3/Bi2WO6. The reusability studies demonstrate the excellent retention of photocatalytic activity without much loss in activity, implying the stability and efficiency of the prepared catalyst. The degradation of the Rh B dye is modeled mathematically to analyze the interactive effects of the key parameters like the time, amount of catalyst, and dye concentration, and to determine the optimal setting of these parameters to optimize the degradation process using the face-centered Central Composite Design (FC-CCD) of the Response Surface Methodology (RSM) analysis. An accurate full quadratic model has been developed with R2 = 99.41%. The sensitivity of the degradation was evaluated at all levels of the key parameters. At 0.1g of catalyst amount, it was found that the increment of the catalyst amount would be suitable for improved degradation as compared to allowing more time for the degradation. The maximum degradation was obtained for a dye concentration of 5ppm, and 0.1g catalyst for 4h. 2022, King Abdulaziz City for Science and Technology. -
Water Purification Using Subnanostructured Photocatalysts
Visible light is an abundant resource, and photocatalysts absorb this light and use it to energize chemical reactions. Of the many types of reactions that are catalyzed by photocatalysts, wastewater purification is an important area. Photocatalysis is an economical, eco-friendly, and sustainable method of purifying water, a precious resource for which need is increasing while availability is shrinking. Of the several types of photocatalytic materials available, atomically dispersed metals and metal oxides appear to be the most promising. In conventional materials, the efficiency of utilization of active photocatalytic material is rather poor because only a small fraction of those present on the surface can serve as active materials. As the particle size decreases, this efficiency increases. In this respect, subnanometric catalysts such as single-site heterogeneous catalysts, atomically dispersed catalysts, and single-atom catalysts have distinct advantages when compared with their bulk and nanometric counterparts. The challenges in preparing stable single-atom catalysts have largely been overcome, and several methods are now available for their preparation. Many atomically dispersed photocatalytic materials have been synthesized, and many new insights have been gained, unlocking the tremendous potential in purifying wastewater by utilizing solar radiation. The aspects of higher activity, improved selectivity, economical use of materials, and a better understanding of the structure-activity relationship offered by subnanometric photocatalysts have been explored in this chapter. 2020 American Chemical Society. -
Challenges and Issues in Health Care and Clinical Studies Using Deep Learning
Deep learning is a subset of machine learning, which has more than three layers of neural networks. Neural networks resemble the functioning of human behavior in nature. These neural networks are capable of producing results with single layers, but multiple layers help in producing accurate results with increased precision rate. Deep learning supports a number of artificial intelligence (AI)-based applications and services, which helps in increased automated devices, data analysis, and many more physical tasks in various fields. Deep learning technology has become part of human day-to-day life. It is involved in every aspect of daily routine like voice-based searches, operating a device, baking transactions, and many more. Deep learning allows the healthcare industry to examine data quickly without compromising accuracy. Deep learning uses mathematical models designed to work almost like the human brain. Multiple layers of networking and technology enable unmatched computing capability and the ability to traverse and analyze through vast sets of data that would have previously been lost, forgotten, or missed. 2024 Taylor & Francis Group, LLC. -
Classification of fibroid using novel fully connected CNN with back propagation classifier (NFCCNNBP)
In this phase, we utilize features extracted from a prior stage to classify uterine fibroids. We employ a predefined dataset with feature values as our training set for a novel classifier called the "Novel Fully Connected CNN with Back Propagation Classifier."This classifier learns from the training set. We then put this method to the test with new images not included in the training dataset. Its primary objective is to assess the extent of infection across the entire uterine surface. Through the adoption of a Convolutional Neural Network (CNN) combined with Back Propagation (BP), we have achieved an impressive accuracy rate of 98.3% for predictions. When we compare this accuracy to existing classifiers like Fuzzy Logic, Naive Bayes, and SVM, our proposed model, NFCCNNBP, outperforms them significantly. 2024 Author(s). -
Impact of Digital Wallets Usage on Digital Banking Experience
The aim of this study is to explore the influence the digital wallets on digital banking experience of the bank customers. The study used e-wallet literacy scale constructs as independent variables and digital banking experience as dependent variable in order to identify the impact of digital wallets on digital baking experience of the bank customers. The primary data was collected from 300 bank customers who are using the digital wallet provided by the bank or any other third-party digital wallet. Structure equation modeling was executed to explore the influence of digital wallets on digital banking experience. The results indicate that Purchase Transactions (PT) and Investment Transactions (IT) are having high influence on digital banking experience followed by Fund Transfer Transactions (FTP), Method of Payment (MOP) having moderate impact, and finally, Credit Payment Transactions (CPT) and Bill Payment Transactions (BPT) are having low influence on digital banking experience. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
A Study on the Influence of Personality Traits on Entrepreneurial intentio
Pacific Business Review International, Vol. 9, Issue 5. pp. 12-19, ISSN No. 0974-438X -
A Study on the Influence of personality traits on entrepreneurial intention among working professionals in the Indian technical organizations
Pacific Business Review International, Vol. 9, Issue 5, pp. 12-19, ISSN 097X-438X -
Diabetic retinopathy detection via deep learning based dual features integrated classification model
Background: The primary recognition of diabetic retinopathy (DR) is a pivotal requirement to prevent blindness and vision impairment. This deadly condition is identified by highly qualified professionals by examining colored retinal images. Objective: The physical diagnostics for this condition was time-consuming and prone to fault. The development of computer-vision based intelligent systems has develop a main research area to effectually diagnosis the pathologies from an image. Methods: In this research, a novel Deep learning based Dual Features Integrated classification (DD-FIC) framework is designed to detect the DR from a color retinal image. Initially, the fundus images are denoised by Wavelet integrated Retinex (WIR) algorithm to remove the noise artifacts which provide high contrast image. This DD-FIC model contains two phases of feature extraction module to evaluation of several retinal areas. Initially, global features of the fundus image are retrieved by the assist of attention fused efficient model, whereas the attention module dynamically highlights the important features. Afterwards, the segmented retinal vessels data is converted into features for learning the local features. Results: Finally, the collective of features is processed into the Random Forest based feature selection model for the optimal prediction with five different classes using multi-class support vector machine (MCSVM). The efficacy of the proposed DD-FIC framework is estimated by Kaggle dataset with the detection accuracy of 98.6%. Conclusions: The proposed framework rises the accuracy of 1.54%, 3.65%, 13.79% and 6.28% for Multi-channel CNN, CNN, VGG NiN and Shallow CNN respectively. The Author(s) 2024.