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Catalytic potential of fluorescein under visible light irradiation: Enabling single-pot open flask synthesis of novel pyrazolyl methanesulfonamides
This groundbreaking study introduces a novel and efficient method for synthesizing a range of substituted pyrazolyl methanesulfonamides through a five-component cyclocondensation reaction. This reaction incorporates five different components, such as ethyl acetoacetate, hydrazine, dimedone, benzaldehydes, substituted phenyl acetonitriles, and methyl sulfonyl chloride was made to react under visible light irradiation, with fluorescein serving as an effective catalyst and ethanol as solvent for 30 mintues. This method offers significant advantages, including simplified handling, higher yields of target products with shorter reaction times, and easier purification processes. We successfully synthesized around 15 novel pyrazolyl methanesulfonamide derivatives with high efficiency. Comprehensive spectral characterization confirmed the structural integrity and purity of these derivatives, demonstrating the robustness and versatility of this approach. Facilitated by visible light and utilizing fluorescein as a bio-friendly catalyst, this methodology is both green and sustainable. This innovative approach not only streamlines the synthesis of pyrazolyl methanesulfonamides but also holds considerable promise for advancing research and applications in fields such as medicinal chemistry and materials science. 2024 The Author(s) -
Elevating pyrrole derivative synthesis: a three-component revolution
Pyrrole is an essential chemical with considerable relevance as a pharmaceutical framework for many biologically necessary medications. The growing demand for biologically active compounds calls for a simple one-pot method for generating novel pyrrole derivatives. Nots surprisingly, several multicomponent reactions (MCRs) aim to synthesize pyrrole derivatives. However, this review presents the three-component synthesis of pyrrole derivatives, highlighting the significance of multicomponent reaction in synthesizing eclectic multi-functionalised pyrrole covering the selected literature on the three-component synthesis of substituted pyrrole from 2016 to late 2023. Furthermore, this article classifies the reactions based on the starting material with functional groups involved in the pyrrole ring formation. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Consumer preference towards private label brands with reference to retail apparel in India
As majority of the present day consumers are considering brands as an important element in their choice of decision making while purchasing, it is pertinent that sellers should capitalize on the type of brands they are offering to consumers. Both private labels and global brands have their own advantages and disadvantages over each other mainly in terms of pricing and quality factors. However, the main motive the consumers are looking forward is to buy a product which would effectively satisfy their requirements. If they find a product which satisfies their needs effectively, they buy it irrespective of whether it is a private label or a global brand. Even the price of the product may not be a major factor in such a case. This study focused on the preference and intention among consumers towards buying of private label products, especially retail apparel products. This study examined the causal relationships between six antecedents of customer perceived preference identified in this study as fashion consciousness, attitude, store image, price, quality, and store loyalty with regard to the purchase intention of private label brand apparels. The model was evaluated using data collected from 292 customers from different malls in Bangalore in 2016-17. The findings revealed that customers attitude played a significant role in their purchase behaviour towards private label brand apparels. 2019, Associated Management Consultants Pvt. Ltd. All Rights Reserved. -
Effect of food insecurity on the cognitive problems among elderly in India
Background: Food Insecurity (FI) is a crucial social determinant of health, independent of other socioeconomic factors, as inadequate food resources create a threat to physical and mental health especially among older person. The present study explores the associations between FI and cognitive ability among the aged population in India. Methods: To measure the cognitive functioning we have used two proxies, word recall and computational problem. Descriptive analysis and multivariable logistic regression was used to understand the prevalence of word recall and computational problem by food security and some selected sociodemographic parameters. All the results were reported at 95% confidence interval. Results: We have used the data from the first wave of longitudinal ageing study of India (LASI), with a sample of 31,464 older persons 60 years and above. The study identified that 17 and 5% of the older population in India experiencing computational and word recall problem, respectively. It was found that respondents from food secure households were 14% less likely to have word recall problems [AOR:0.86, 95% CI:0.310.98], and 55% likely to have computational problems [AOR:0.45, 95% CI:0.290.70]. We also found poor cognitive functioning among those experiencing disability, severe ADL, and IADL. Further, factors such as age, education, marital status, working status, health related factors were the major contributors to the cognitive functioning in older adults. Conclusion: This study suggest that food insecurity is associated with a lower level of cognition among the elderly in India, which highlight the need of food policy and interventional strategies to address food insecurity, especially among the individuals belonging to lower wealth quintiles. Furthermore, increasing the coverage of food distribution may also help to decrease the burden of disease for the at most risk population. Also, there is a need for specific programs and policies that improve the availability of nutritious food among elderly. 2021, The Author(s). -
Skin cancer classification using machine learning for dermoscopy image
Skin cancer is highly ambiguous and difficult to identify and cure in the last stage. To increase the survival rate, it is important to recognize the stages of skin cancer for effective treatment. The main aim of the paper is to classify the various stages of skin cancer using dermoscopy images from the data repository of ISIC and PH2. The data is pre -processed with the help of median filter and wiener filter for removing the noise. Segmentation is processed using Watershed and Morphological. After the segmentation, features were extracted using Grey Level Co-occurrence Matrix (GLCM), Color, Geometrical shapes in order to improve the accuracy of dermoscopy image. Finally, the dataset is classified with some popular methods like KNN with 89%, Ensemble with 84% and SVM works better than the other two methods by giving the highest accuracy of 92%. BEIESP. -
Students Satisfaction with Remote Learning During the COVID-19 Pandemic: Insights for Policymakers
Purpose: This study aimed to learn more about the factors influencing student happiness and involvement in remote learning in Indian higher education institutions (HEIs). The study aims to assist administrators, strategists, and politicians in efficiently dealing with educations new normal. Methodology: The study used a quantitative research approach to fulfill the research aims. A sample of 546 students from various Indian HEIs was chosen, and data were gathered using standardized questionnaires. Structural equation modeling, confirmatory factor analysis, and importance-performance analysis (IPA) were used to calculate the student satisfaction index and examine the impact of various factors. Findings: The findings of this study revealed that institutional and faculty support emerged as the most influential factor impacting students satisfaction through remote learning. It also highlighted the need for HEIs to redesign the assessment process and evaluation techniques to adapt to the remote learning environment. Practical Implications: The findings of this study indicated the practical consequences for administrators, strategists, and policymakers at Indian HEIs. It was advised that improving institutional and teacher support should be a major concern in order to improve student happiness in remote learning situations. Furthermore, redesigning assessment procedures and evaluation processes may improve learning outcomes and student engagement. Originality: This study contributed to the existing body of knowledge by specifically investigating the factors influencing student satisfaction in remote learning within Indian HEIs. The findings shed light on the unique challenges and opportunities the shift to remote education presented. They offered valuable insights for managing and improving the quality of education during and beyond the pandemic. 2023, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Sigmoidal Particle Swarm Optimization for Twitter Sentiment Analysis
Social media, like Twitter, is a data repository, and people exchange views on global issues like the COVID-19 pandemic. Social media has been shown to influence the low acceptance of vaccines. This work aims to identify public sentiments concerning the COVID-19 vaccines and better understand the individuals sensitivities and feelings that lead to achievement. This work proposes a method to analyze the opinion of an individuals tweet about the COVID-19 vaccines. This paper introduces a sigmoidal particle swarm optimization (SPSO) algorithm. First, the performance of SPSO is measured on a set of 12 benchmark problems, and later it is deployed for selecting optimal text features and categorizing sentiment. The proposed method uses TextBlob and VADER for sentiment analysis, CountVectorizer, and term frequency-inverse document frequency (TF-IDF) vectorizer for feature extraction, followed by SPSO-based feature selection. The Covid-19 vaccination tweets dataset was created and used for training, validating, and testing. The proposed approach outperformed considered algorithms in terms of accuracy. Additionally, we augmented the newly created dataset to make it balanced to increase performance. A classical support vector machine (SVM) gives better accuracy for the augmented dataset without a feature selection algorithm. It shows that augmentation improves the overall accuracy of tweet analysis. After the augmentation performance of PSO and SPSO is improved by almost 7% and 5%, respectively, it is observed that simple SVM with 10-fold cross-validation significantly improved compared to the primary dataset. 2023 Tech Science Press. All rights reserved. -
An Anomaly Detection Framework for Twitter Data
An anomaly indicates something unusual, related to detecting a sudden behavior change, and is also helpful in detecting irregular and malicious behavior. Anomaly detection identifies unusual events, suspicious objects, or observations that differ significantly from normal behavior or patterns. Discrepancies in data can be observed in different ways, such as outliers, standard deviation, and noise. Anomaly detection helps us understand the emergence of specific diseases based on health-related tweets. This paper aims to analyze tweets to detect the unusual emergence of healthcare-related tweets, especially pre-COVID-19 and during COVID-19. After pre-processing, this work collected more than 44 thousand tweets and performed topic modeling. Non-negative matrix factorization (NMF) and latent Dirichlet allocation (LDA) were deployed for topic modeling, and a query set was designed based on resultant topics. This query set was used for anomaly detection using a sentence transformer. K-means was also employed for clustering outlier tweets from the cleaned tweets based on similarity. Finally, an unusual cluster was selected to identify pandemic-like healthcare emergencies. Experimental results show that the proposed framework can detect a sudden rise of unusual tweets unrelated to regular tweets. The new framework was employed in two case studies for anomaly detection and performed with 78.57% and 70.19% accuracy. 2022 by the authors. -
The rise of new age social media influencers and their impact on the consumers' reaction and purchase intention
The internet revolution and digitisation have created innovative platforms and spokespersons for brands beyond traditional media. The marketing landscape for brands and customers is evolving towards a more personal and authentic approach; adopting various social media platforms and influencers creates more brand engagement. Influencers are the new third-party endorsers, catering to and recommending products to their loyal community of followers. The influencer and their fans/followers are a brands new storytellers. However, selecting the right influencer for a brands promotional strategy requires careful consideration of several factors. This paper aims to study the impact/effect of these variables, namely, endorsers credibility and corporate credibility, on consumers attitudes towards the brand and its impact on purchase intention, with respect to the millennial era. In the present study, 14 Likert-based questions were designed, asking the respondents to rank their choice of agreement on a scale of 1 to 5. The results were obtained through statistical analysis, including measuring the relationship between variables using confirmatory factor analysis and regression techniques. And the study found that corporate credibility has a significantly higher impact (approximately 90%) than individual endorsements (including those by celebrities) in enhancing customers brand perception. Copyright 2024 Inderscience Enterprises Ltd. -
Determinants of Hand Washing Practices among Adolescents in India Findings from CNNS Data, 2016-18
The study attempts to assess the effect of socioeconomic determinants on access to Good Handwashing Practices (GHP) among the adolescent population in India. The Comprehensive National Nutrition Survey (CNNS), 2016-18 dataset is used to identify the predictor and outcome variable for the study. Binary logistic regression established the adolescents age and sex, mothers schooling, wealth index, and the region as a significant predictor for GHP. The study revealed that gender, age, caste, education, individual household wealth, and the region has a significant association with adolescent hand-washing practices, where economic conditions drive the individual practice of handwashing more than the behavioural aspect. It requires government intervention to improve sanitation and water facilities to accelerate hand-washing among adolescents in India. 2022 Tata Institute of Social Sciences. All rights reserved. -
Evaluation of Flow Resistance using Multi-Gene Genetic Programming for Bed-load Transport in Gravel-bed Channels
Evaluation of flow resistance is necessary for the computation of conveyance capacity in open channels. The significance of the friction factor in channels with bedload conditions is paramount. The response of flow resistance in gravel-bed channels in bedload transport conditions is distinct from that of a fixed bed. The paper studies the different empirical approaches in the literature to determine the friction factor under bedload transport conditions and proposes an expression by genetic programming for the same. Various hydraulic and geometric parameters affect flow resistance in the bedload transport condition. The present study includes bed slope, relative submergence depth, aspect ratio, Reynolds number, and Froude number as influencing factors for such flow conditions. A wide range of experimental datasets is employed to determine the effect of these influencing parameters and develop a customised single expression for the friction factor. The experimental data set has also been moderated for sidewall corrections. The predictability of the proposed model is compared to various empirical equations from the literature. Unlike the existing models, the proposed model provides a more extensive expression for effectively predicting the friction factor for a wide range of datasets. The conveyance capacity of a river is validated from the estimated value of friction factor, as compared to other standard models. The developed Multi-Gene Genetic Programming (MGGP) model reasonably predicts discharge in the rivers, signifying that the model can competently be applied to field study within the specified range of parameters. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Digital image correlation (DIC) for measuring strain in brick masonry specimen using Ncorr open source 2D MATLAB program
This micro-article is focused on the application of DIC in measuring strain for a 2D structural element like brick masonry specimen. Conventional techniques of strain measurements involve devices like strain gauges, LVDTs, dial gauges and extensometers. Even though Commercial DIC packages are available and have been widely used to perform DIC, these setups are quite expensive. In this study a simple DSLR camera along with Ncorr, an open source 2D MATLAB program is used to perform the DIC. Results have also been obtained experimentally by using conventional measuring devices and compared with that of DIC. The results obtained through DIC is well in agreement with that of experiments, and the difference in strain at failure was observed to be 4.7%. Furthermore, the results of this study should encourage researchers to adopt this technique in studies of behaviour and structural health monitoring of brick masonry specimens. 2019 The Authors -
Environmentally conscious synthesis of novel pyrano[2,3-d]pyrimidines via ternary deep eutectic solvents
Pyrano[2,3-d]pyrimidine and its analogues have gained considerable courtesy because of their diverse biological functions and wide-ranging applications, from pharmaceutical agents to essential natural pigments. However, synthesising pyrano[2,3-d]pyrimidine with multiple reactants is challenging and requires advanced green chemistry solutions. This study investigates the generation of thirteen new pyrano[2,3-d]pyrimidine analogues through a single-step, open-flask, multicomponent reaction (MCR) strategy involving aldehydes, phenylhydrazine, ethyl acetoacetate, and barbituric acid via deep eutectic solvents (DES). These DESs serve as environmentally friendly alternatives to traditional solvents. A ternary deep eutectic solvent (TDES) was evaluated for its catalytic solvent activity among ten different formulations. TDES-7 (5 mL) demonstrated the best performance, achieving 95 % product formation within 30 min at room temperature. Its remarkable catalytic activity and ability to produce high yields across multiple reaction cycles make it a standout choice for this application. The collaboration between MCR and TDES underscores an important blend of two significant green aspects, demonstrating their potential to achieve a green and productive sustainable synthesis method with an noble E-factor of 0.1236. 2024 Elsevier B.V. -
Novel heterocyclic thiosemicarbazones derivatives as colorimetric and "turn on" fluorescent sensors for fluoride anion sensing employing hydrogen bonding
(Chemical Equation Presented) Two novel heterocyclic thiosemicarbazone derivatives have been synthesized, and characterized, by means of spectroscopic and single crystal X-ray diffraction methods. Their chromophoric-fluorogenic response towards anions in competing solvent dimethyl sulfoxide (DMSO) was studied. The receptor shows selective recognition towards fluoride anion. The binding affinity of the receptors with fluoride anion was calculated using UV-visible and fluorescence spectroscopic techniques. 2013 Elsevier B.V. All rights reserved. -
Effects of dark matter on the upper bound mass of neutron stars
Observations have indicated that we do not see neutron stars (NS) of mass near the theoretical upper limit as predicted. Here we invoke the role of dark matter (DM) particles in star formation, and their role in lowering the mass of remnants eventually formed from these stars. Massive stars can capture DM particles more effectively than the lower mass stars, thus further softening the equation of state of the remnant neutron stars. We also look at the capture of DM particles by the NS, which could further soften the upper mass limit of NS. The admixture of DM particles would be higher at earlier epochs (high z). 2020 Elsevier B.V. -
Revisiting Cournot Duopoly Model An Experimental Study
Journal of the Institute for Research in Social Sciences and Humanities, Vol-6 (1&2), pp. 151-170. ISSN-0973-3353 -
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. -
The Role of Major-Sport Event Cricket with Respect to Consumer Perception and Attitude Towards Ambush Marketing
International Journal of Business and Management Invention, Vol-2 (10), pp. 76-81. ISSN-2319-801X -
Can co-creating in CSR initiatives influence loyal customers? Evidence from the banking industry
Consumers are increasingly pressing organizations to adapt meaningful corporate social responsibility (CSR) initiatives and seek avenues for co-creation. Study to investigate if CSR can help co-creation significantly contributes to the competitive advantage of banks. Many previous pieces of research have recognized CSR as a strategic imperative that may help businesses to build consumer loyalty. To address gaps in the literature based on the social identity theory and theory of social exchange, this article investigates the impact of CSR on consumer loyalty while considering the mediation effect of co-creation. The data were collected in India, and the sample contained 520 customers of banks. Partial least squares-structural equation modeling was used to test the hypothesis. The study findings show that CSR, directly and indirectly, impacts consumer loyalty through co-creation. The current study's findings aid banking institutions in determining how to design and implement strategies based on CSR and co-creation that could eventually result in consumer loyalty. 2023 ERP Environment and John Wiley & Sons Ltd. -
Does perceived corporate social responsibility improve customer engagement? - An empirical evidence from Indian banks
In recent years, banks are trying to embed their corporate social responsibility (CSR) and societal outreach initiatives into their strategic process to improve their competitive advantage and performance. A previous study reveals that CSR initiatives and efforts of the banks will likely to positively influence the customers attitudes toward that bank and generate favourable behavioural outcomes. This study will provide a deeper investigation of whether the perceived CSR discriminate against the customer engagement level in the bank. This paper attempts to measure the discriminating power of CSR towards customer engagement. Maignan and Ferrells (2004) scale was used to ascertain the corporate social responsibility, and for measuring customer engagement, the Gallop scale (2001) was used. Primary data was collected through a simple random sampling technique from 612 customers across different banks. The discriminant analysis was carried out to find out the discriminating power of CSR towards customer engagement. Discriminating function model results exactly predicting customer engagement level based on the CSR initiatives. The findings are supportive and helpful for the banks in formulating effective CRM Strategy to satisfy and engage their customer at a high level through effectively articulated CSR plans and policies. 2024 Inderscience Publishers. All rights reserved.