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Catalytic Activity and Reusability of Mesoporous Iron Aluminophosphate Catalyst in Pharmacologically Important Organic Transformations
Journal Atoms and Molecules an International Online Journal, Vol-4 (1), pp. 675-681. ISSN-2277-1247 -
Preparation and characterisation of amorphous mesoporous aluminophosphate and metal aluminophosphate as an efficient heterogeneous catalyst for transesterification reaction
Preparation, characterisation of pure aluminophosphate and aluminophosphate modified with different transition metals (V, Fe, Co Ni & Cu) and their catalytic activity in mono/dibenzyl substituted malonates synthesis are explained. The materials were prepared by the coprecipitation method in the absence of any structure-directing species and characterized for their composition, crystalline nature, total surface acidity, specific surface area pore diameter and pore volume by different techniques. Catalytic activity of the materials was investigated in transesterification of diethylmalonate with benzyl alcohol in liquid phase. Pure aluminophosphate resulted only in benzyl ethylmalonate whereas the incorporation of transition metals favored the formation of both benzyl ethylmalonate and dibenzylmalonate. Catalytic activity parallels the surface acidity and mesoporosity of the catalysts. The effect of the molar ratio of reactants, amount of catalyst, and reaction time on the conversion of diethyl malonate and transester yield has been studied. The highest activity of iron aluminophosphate is attributed to its mesoporous nature with uniform pore size distribution, higher surface acidity and surface area. Further, the scope and generality of iron aluminophosphate as a catalyst in the transesterification was studied using various aliphatic, alicyclic and aromatic alcohols. The catalysts could be recycled by retaining most of its initial activity. 2011 Acadie des sciences. Published by Elsevier Masson SAS. All rights reserved. -
A Study on Decision Paralysis in Customers with Special Reference to Placing Order in Restaurant
Owing to the vast number of choices open to customers, they can often feel paralysed in their decision-making. Offering a wide range of options can activate the effect of Decision Paralysis, which delays the client's final decision. The impact of Decision Paralysis can prevail in restaurants. This study reveals the existence of decision paralysis among customers in restaurants when placing an order. The aim is to investigate the prevalence of Decision Paralysis among customers, with particular reference to placing an order in a restaurant and the influence on consumers purchase decisions. A survey questionnaire was rolled out using Google forms to customers who have experienced dining in a restaurant. A total of 416 survey responses were collected for data analysis through the convenience sampling method. It was found that, customer purchase decision has been affected by the decision paralysis effect. It was also found that customers experience a dilemma due to tremendous options or choices in the food sector by the service providers. This study was limited to restaurants and in terms of cuisine, with hotels not being considered. Hence, the main limitation is not being able to generalise the findings of this study to the whole of the food catering sector. The study will benefit both scholars and marketing practitioners in understanding the difficulty a customer faces during purchase decision-making. 2021 Transnational Press London -
Environmental degradation in geopolitical risk and uncertainty contexts for India: A comparison of ecological footprint, CO2 emissions, and load capacity factor
This study assesses the role of geopolitical risk and uncertainty in the degradation of the environment by forming the functions for ecological footprint, CO2 emissions, and load capacity factor for the period 19902019 in India. Besides, the specified function endogenizes economic growth, renewable energy consumption, and natural resource rent as the additional covariates. The use of the autoregressive distributed lag model (ARDL) confirms the long-run relationship between study variables. Further, the dynamic simulations of the autoregressive distributed lag model (DYNARDL) outcomes show that geopolitical risk improves the quality of the environment by reducing the ecological footprint and CO2 emissions. However, it degrades the environment by reducing the load capacity factor. Furthermore, the uncertainty improves the environmental quality by reducing the CO2 emissions and ecological footprint, but the reduced load capacity factor due to uncertainty implies the degradation of environmental quality in India. Given these findings, the study proposes different environmental conservation policies. 2023 Elsevier Ltd -
Towards sustainable resource management: A short and long-run dynamics of mineral production on ecological footprint
The effect of mineral production on ecological footprint is examined in this study while controlling for economic growth, renewable energy consumption, and trade openness as additional determinants for Pakistan. On the empirical front, the study uses the Dynamic Autoregressive Distributed Lag (DYNARDL) simulations for the data collected between 1990 and 2021. The result portrays movement to the long-run equilibrium relationship when considering the ecological footprint as the outcome variable amidst mineral production, economic growth, renewable energy consumption, and trade openness as the covariates. Further, the finding shows temporal dynamics of mineral production on environmental quality with a short-term degradation versus long-term amelioration, which suggests that mineral production can be conducted more sustainably over time with an implication towards taking measures such as technological advancements, improved efficiency, and better waste management practices. Additionally, it failed to find evidence for the conventional Environmental Kuznets Curve, implying a need for policy reevaluation, reassessment of economic development models and accounting for environmental externalities in economic decision-making. Besides, as expected, the outcome demonstrates that using renewable energy lowers the ecological footprint both in long and short terms, which indicates that utilization of renewable energy sources reduces reliance on fossil fuels, resulting in decreased environmental degradation, thereby fostering the need for emphasis on the importance of continued technological innovation in renewable energy technologies to reduce the ecological footprint further. Moreover, it shows that trade openness improves the environmental quality in the short run (worsens it in the long run), thereby highlighting that trade openness may lead to short-term environmental benefits by promoting cleaner technologies and increasing resource efficiency. However, in the long term, trade openness can exacerbate environmental degradation due to economic priorities often taking precedence over environmental concerns. 2024 Elsevier Ltd -
An asymmetric analysis of overall globalization on financial inclusion
Purpose: Financial inclusion is acknowledged as a critical facilitator of the United Nations Sustainable Development Goals agenda for 2030. Therefore, this study aims to examine the asymmetric role of overall globalization on financial inclusion by controlling economic growth, urbanization and population for the selected South Asian countries. Design/methodology/approach: Applying the nonlinear autoregressive distributed lag approach to cointegration explores the impact of overall globalization on financial inclusion in the presence of additional variables like economic growth, urbanization and population in the designed financial inclusion function. Findings: The estimated econometric outcomes show that increasing overall globalization fosters financial inclusion while decreasing overall globalization reduces financial inclusion. Furthermore, a positive (negative) change in economic growth leads to an increase (decrease) in financial inclusion while varying short-run findings. Moreover, both positive and negative changes increase financial inclusion in the long run in connection with urbanization. Although the short-run results are not significant, the study finds that an increase (decrease) in population leads to a decrease (increase) in financial inclusion. Finally, to support the promotion of financial inclusivity throughout South Asia, several policies pertaining to financial inclusion are suggested. Originality/value: To the best of the authors knowledge, this is the first study to examine the asymmetries related to overall globalization on financial inclusion by controlling economic growth, urbanization and population. 2024, Emerald Publishing Limited. -
Income Inequality in Globalization Context: Evidence from Global Data
This paper empirically investigates the relative effectiveness of economic globalization, trade openness, and financial openness on income inequality in low-, middle-, and high-income countries for the panel data over the period from 1991 to 2020 by endogenizing economic growth, urbanization, agriculture, industry, and service sectors value-added as % of GDP as control variables in income inequality function. The results emanating from the panel pooled mean group-autoregressive distributed lag (PMG-ARDL) test provide evidence of a significant long-run relationship among the variables. Interestingly, economic globalization reduces income inequality for high- and middle-income countries and increases it in low-income countries. On the other hand, trade openness reduces income inequality in high- and middle-income countries but increases it for low-income countries. In contrast, financial openness lessens income inequality in low-income countries but increases it for middle- and high-income countries. We find that urbanization increases income inequality in low-, middle- and high-income countries. We also find that economic growth decreases (increases) income inequality in high (middle and low)-income countries. Moreover, it is found that industrial and service sectors output decrease (increases) income inequality in high (middle and low)-income countries, whereas agricultural output improves (deteriorates) income distribution in middle- and low- (high) income countries. In light of these findings, we suggest that the governments of low-income countries need to focus more on improving the level of globalization and trade openness to improve their economic conditions in long run. Both high- and middle-income countries should also improve their financial openness so that effective utilization of overseas finance will flourish their overall economy. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Dual strategy for enhanced photocatalytic degradation of tetracycline: Phosphorus doping and cobalt boride co-catalyst loading on g-C3N4
Despite being promising for the removal of ever-growing pharmaceutical contamination from water, the g-C3N4 photocatalyst still faces roadblocks to implementation due to its intrinsic properties, for example, the limited visible light absorption, reduced charge separation capacity, and low mobility of photo-excited electrons. Doping with non-metals and loading with the co-catalyst is an effective approach to overcome the abovementioned limitations for the g-C3N4 photocatalyst. Herein, both these strategies are integrated in cobalt-boride loaded on phosphorous-doped g-C3N4 (CoB/P-g-C3N4) by facile chemical fabrication routes. Detailed morphological, structural, chemical, and spectroscopic analyses demonstrated that phosphorus doping effectively reduces the bandgap of g-C3N4 to absorb more visible light. Uniformly distributed CoB-nanoparticles create local Schottky barriers that trap photo-generated electrons from g-C3N4 to suppress charge carrier recombination. The optimized CoB/P-g-C3N4 photocatalyst produces ~35 times higher degradation rate constant than the pristine g-C3N4 for the photocatalytic removal of tetracycline antibiotics from water under visible light irradiation. Combining these advantageous features with cost-effective and stable elements, CoB/P-g-C3N4 offers an optimal solution for tuning the intrinsic electronic structure and surface reactivity of g-C3N4, making it highly effective for various photocatalytic applications. 2025 Elsevier Ltd -
Variations in andrographolide content, phytochemical constituents and antioxidant activity of leaves of andrographis paniculata (L.) nees collected from different locations of Southern India
In present study, the samples collected from different locations of Southern India viz., Yellapur Beltargadde, Siddapur, Joida, Ankola, Sirsi Kangod, Yellapur Shalabail, Sirsi Bairumbe, Karwar of Karnataka and Kasaragod from Kerala were analyzed for the andrographolide content, total phenolic and flavonoid content and screened for their antioxidant potential. The A. paniculata leaves were extracted with three different solvents (chloroform, methanol and water) and methanolic extract of Siddapur showed highest (8.82 0.25 mg/g DW) amount of phenolic content whereas, aqueous extract of Ankola (3.00 1.18 mg/g DW) showed the least amount. Chloroform extract of Yellapur Beltargadde village showed highest quantity i.e. 1.87 0.50 mg/g DW of flavonoid content and aqueous extract of Yellapur Beltargadde showed 0.30 0.20 mg/g DW which was least among all the tested samples. The sample collected from Karwar was found to have highest andrographolide content (9.36 0.02 mg/g DW) followed by Yellapur Beltargadde sample with 7.29 0.01 mg/g DW and Sirsi Kasaragod has the lowest contents of 1.54 0.1 mg/g DW when analyzed through HPLC. Among the nine locations, methanol extract from Joida showed highest percentage of scavenging activity (91.95%) followed by methanol extract of Ankola (90.42%) and chloroform extract of Siddapur (77.31%) which was the lowest value of all samples tested. 2021 Chemical Publishing Co.. All rights reserved. -
Ideological preferences versus national integration of India
[No abstract available] -
Financial inclusion in IndiaA progress and challenges
The term Financial Inclusion means the process of access to appropriate financial products and services needed by all sections of society including vulnerable groups such as weaker section and low-income at an affordable cost. It has been a very big challenge for the developing countries for including the people into the financial system. Financial inclusion is emerging as a new paradigm of economic growth that plays major role in driving away the poverty from the country. Financial inclusion is important priority of the country in terms of economic growth and advancement of society. Globally, the financial inclusion is on the rise and from 2014-2017, 515 million adults opened an account with bank and there has been a significant increase in the use of mobile Phones and internet to conduct financial transaction. There was a commendable increase in the financial inclusion and this is predominantly driven by India. Through government initiatives and indicatives taken by the RBI, weaker sections of society and economically poor people were able to access to financial products, services, credit etc. The basic variables for measuring the financial inclusion are bank penetration, credit penetration, number of accounts opened etc. So the present study aims to investigate the progress of financial Inclusion in India through the initiatives taken by the Government of India(GOI) and Reserve Bank of India (RBI). 2019 SERSC. -
Automated segmentation and classification of nuclei in histopathological images
Various kinds of cancer are detected and diagnosed using histopathological analysis. Recent advances in whole slide scanner technology and the shift towards digitisation of whole slides have inspired the application of computational methods on histological data. Digital analysis of histopathological images has the potential to tackle issues accompanying conventional histological techniques, like the lack of objectivity and high variability. In this paper, we present a framework for the automated segmentation of nuclei from human histopathological whole slide images, and their classification using morphological and colour characteristics of the nuclei. The segmentation stage consists of two methods, thresholding and the watershed transform. The features of the segmented regions are recorded for the classification stage. Experimental results show that the knowledge from the selected features is capable of classifying a segmented object as a candidate nucleus and filtering out the incorrectly identified segments. Copyright 2022 Inderscience Enterprises Ltd. -
Apparel shopping styles of young adult consumers in Bangalore
Apparels are one of the most frequently purchased product categories where young adults have the authority to make independent buying decisions, and they also become trendsetters and opinion leaders. Understanding this large segment appropriately is crucial for apparel manufacturers and marketers as they promise longevity of market and exert substantial influence on their parents, peers, as well as their own spending. The present study segmented young adult consumers based on their shopping styles towards purchase of apparels and explored the differences in the shopping styles across demographics such as gender, educational levels, and regional background. The respondents for the study were young adults who belonged to the age group of 18 - 25 years residing in Bangalore, India. The variables under study were eight shopping styles adapted from Sproles and Kendall Consumer Style Inventory- CSI (1986). The study revealed that all the eight shopping styles of the CSI were manifested among young adults in Bangalore; however, the predominant shopping style was the Perfectionist/ High Quality Conscious shopping style. Furthermore, significant differences in the shopping styles of young adults across gender, educational levels, and regional background were found. -
Apparel shopping styles of young adult consumers in Bangalore /
Indian Journal Of Marketing, Vol.46, Issue 2, pp.267-279, ISSN No: 0973-8703. -
Detection of tuberculosis using convolutional neural network with transfer learning
Tuberculosis is sighted as the one of the life causing disease in the recent time. The current research work focus on detection of Tuberculosis using Convolutional Neural Network with Transfer Learning for chest X-ray images. The proposed research work uses two different datasets for detecting Tuberculosis from Chest X-ray images, which is taken from National Institutes of Heaths. During the experimental work, the total sample size used for detecting Tuberculosis is 800 instances. Initially, the image processing techniques were applied to increase the quality of Chest X-ray images. The proposed model uses Convolution Neural Network with transfer learning for the detection of Tuberculosis with 98.7% as accuracy. The proposed model is checked with convolutional neural network without transfer learning. From the experimental evaluation, it is found that the proposed model works better than the Convolution Neural Network without using the transfer learning. 2017, Institute of Advanced Scientific Research, Inc. All rights reserved. -
Down syndrome detection using modified adaboost algorithm
In human body genetic codes are stored in the genes. All of our inherited traits are associated with these genes and are grouped as structures generally called chromosomes. In typical cases, each cell consists of 23 pairs of chromosomes, out of which each parent contributes half. But if a person has a partial or full copy of chromosome 21, the situation is called Down syndrome. It results in intellectual disability, reading impairment, developmental delay, and other medical abnormalities. There is no specific treatment for Down syndrome. Thus, early detection and screening of this disability are the best styles for down syndrome prevention. In this work, recognition of Down syndrome utilizes a set of facial expression images. Solid geometric descriptor is employed for extracting the facial features from the image set. An AdaBoost method is practiced to gather the required data sets and for the categorization. The extracted information is then assigned and used to instruct the Neural Network using Backpropagation algorithm. This work recorded that the presented model meets the requirement with 98.67% accuracy. 2021 Institute of Advanced Engineering and Science. All rights reserved. -
Down syndrome detection using modified ant colony optimization algorithm
Nowadays, the systems related to healthcare are restructured with innovative skills to offer humans more intellectual and proficient healthcare facilities. Various intelligent healthcare systems are exhibited with the help of machine learning and artificial intelligent tools to offer intellectual and expert services. In human body genetic codes are stored in the genes. All of our inherited traits are associated with these genes and are grouped as structures generally called chromosomes. In typical cases, each cell consists of 23 pairs of chromosomes, out of which each parent contributes half. But if a person has a partial or full copy of chromosome 21, the situation is called Down syndrome. It results in intellectual disability, reading impairment, developmental delay, and other medical abnormalities. This paper introduces an intelligent prediction and classification system for healthcare, feature selection based on density with Ant Colony Optimization (ACO) algorithm for Down syndrome (DS). 2021, Engg Journals Publications. All rights reserved. -
Examining the effect of explicit instruction on vocabulary learning and on receptive-productive gap: An experimental study
This research study emphasized the importance of explicit instruction and repeated exposure to the target vocabulary for effective reception and production of new words among the second language learners of English. The purpose of the study was to examine the efficacy of the researcher- created supplementary for the prescribed set of vocabulary in the English language textbook. The study aimed to find out the amount of influence the explicit instruction and repeated exposure to the target vocabulary had on the nature of the receptive- productive gap. A total of sixty-two sixth grade students from a Government school in Tamil Nadu, India, participated in the experimental study which was conducted over a period of three months. The results of the study showed that the explicit instruction and repeated exposure to the target vocabulary had a significant amount of influence on vocabulary knowledge when compared to the conventional way of vocabulary instruction. In the conventional mode of vocabulary instruction, reception of vocabulary was found to have an average of 8% influence on the production knowledge, whereas in the case of the experimental group, it amounted up to 72%. This analysis showed that through explicit instruction and repeated exposure to the target vocabulary the receptive- productive gap is significantly reduced. 2020 JLLS and the Authors - Published by JLLS.