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Dual-mode chemosensor for the fluorescence detection of zinc and hypochlorite on a fluorescein backbone and its cell-imaging applications
Fluorescein coupled with 3-(aminomethyl)-4,6-dimethylpyridin-2(1H)-one (FAD) was synthesized for the selective recognition of Zn2+ over other interfering metal ions in acetonitrile/aqueous buffer (1 : 1). Interestingly, there was a significant fluorescence enhancement of FAD in association with Zn2+ at 426 nm by strong chelation-induced fluorescence enhancement (CHEF) without interrupting the cyclic spirolactam ring. A binding stoichiometric ratio of 1 : 2 for the ligand FAD with metal Zn2+ was proven by a Jobs plot. However, the cyclic spirolactam ring was opened by hypochlorite (OCl?) as well as oxidative cleavage of the imine bond, which resulted in the emission enhancement of the wavelength at 520 nm. The binding constant and detection limit of FAD towards Zn2+ were determined to be 1 104 M?1 and 1.79 ?M, respectively, and the detection limit for OCl? was determined as 2.24 ?M. We introduced here a dual-mode chemosensor FAD having both the reactive functionalities for the simultaneous detection of Zn2+ and OCl? by employing a metal coordination (Zn2+) and analytes (OCl?) induced chemodosimetric approach, respectively. Furthermore, for the practical application, we studied the fluorescence imaging inside HeLa cells by using FAD, which demonstrated it can be very useful as a selective and sensitive fluorescent probe for zinc. 2022 The Royal Society of Chemistry. -
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 -
Dual solutions for unsteady stagnation-point flow of prandtl nanofluid past a stretching/shrinking plate
Dual solutions for the time-dependent flow of a Prandtl fluid containing nanoparticles along a stretching/shrinking surface are presented. The nano Prandtl fluid fills the porous stretching/shrinking surface. The Buongiorno model is employed by accounting Brownian motion and thermophoresis slip mechanisms in the analysis. The relevant nonlinear problem is treated numerically via Runge-Kutta-Fehlberg scheme. The flow profiles are scrutinized with respect to the different governing parameters. Results of this study indicate that the temperature boundary layer thickness increased due to the influence of nanoparticles. 2018 Trans Tech Publications, Switzerland. -
Dual ion specific electrochemical sensor using aminothiazole-engineered carbon quantum dots
A novel electrochemical sensor capable of concurrently detecting Pb2+ and Hg2+ ions has been innovatively engineered. This sensor utilizes the anodic stripping voltammetry technique (ASV) with a composite consisting of carbon quantum dots and aminothiazole (CQD-AT). In this composite, both the carbon quantum dots and aminothiazole contribute significantly to the electroactive surface area, boasting an abundance of functional groups that include oxygen and nitrogen atoms. These functional groups serve as active sites that enhance sensor sensitivity by facilitating the electrostatic interaction-based adsorption of heavy metal ions. Aminothiazole surface is evenly covered with CQDs, which are essential for metal gets reoxidized into metal ions for stripping analysis. Due to this unique modification, the Pb2+ and Hg2+ electrochemical sensor using the CQD-AT composite coated on carbon fiber paper electrode (CQD-AT/CFP) exhibits superior analysis performance such as wide linear range (0.6 1011160 106 M) for Pb2+ and Hg2+ with a limit of detection (LOD) of 3.0 pM and 6.2 pM for Pb2+ and Hg2+. CQD-AT/CFP modified electrode can be considered as a potential material for electrochemical simultaneous determination of Pb2+ and Hg2+ in different water samples. 2023 Elsevier B.V. -
Dual drug co-encapsulation of bevacizumab and pemetrexed clocked polymeric nanoparticles improves antiproliferative activity and apoptosis induction in liver cancer cells
Nanoparticle (NP) enabled approaches have been employed for chemotherapeutic administration due to their capacity to regulate drug release and reduce side effects. Additionally, these methods can use several drugs concurrently and impede the proliferation of cancer cells that have developed resistance. Bevacizumab (BVZ) and pemetrexed (PEM) have demonstrated encouraging outcomes in the treatment and management of cancer. This work investigates the combined antiproliferative efficacy of BVZ and PEM co-loaded PLGA-PEG NPs (BVZ/PEM@PLGA-PEG NPs) against HepG2 liver cancerous cells. The BVZ/PEM@PLGA-PEG exhibited a sphere-shaped and consistent nanosized distribution. In addition, we evaluated the potential mechanisms for inhibiting cell growth and inducing apoptosis using DAPI staining and cell cycle study. The beneficial combined antiproliferative activity and the apoptosis pathway were detected in the HepG2 cells exposed to BVZ/PEM@PLGA-PEG NPs. Our study determined that the combinational drug treatment of BVZ/PEM@PLGA-PEG NPs has a significant effect on promoting the effectiveness of liver cancer treatment. 2024 Wiley Periodicals LLC. -
DTDO: Driving Training Development Optimization enabled deep learning approach for brain tumour classification using MRI
A brain tumour is an abnormal mass of tissue. Brain tumours vary in size, from tiny to large. Moreover, they display variations in location, shape, and size, which add complexity to their detection. The accurate delineation of tumour regions poses a challenge due to their irregular boundaries. In this research, these issues are overcome by introducing the DTDO-ZFNet for detection of brain tumour. The input Magnetic Resonance Imaging (MRI) image is fed to the pre-processing stage. Tumour areas are segmented by utilizing SegNet in which the factors of SegNet are biased using DTDO. The image augmentation is carried out using eminent techniques, such as geometric transformation and colour space transformation. Here, features such as GIST descriptor, PCA-NGIST, statistical feature and Haralick features, SLBT feature, and CNN features are extricated. Finally, the categorization of the tumour is accomplished based on ZFNet, which is trained by utilizing DTDO. The devised DTDO is a consolidation of DTBO and CDDO. The comparison of proposed DTDO-ZFNet with the existing methods, which results in highest accuracy of 0.944, a positive predictive value (PPV) of 0.936, a true positive rate (TPR) of 0.939, a negative predictive value (NPV) of 0.937, and a minimal false-negative rate (FNR) of 0.061%. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Dry Sliding Friction and Wear Performance of HVOF Sprayed WCCo Coatings Deposited on Aluminium Alloy
The tribological behaviour of WCCo Cermet coatings coated on Al6061 alloy was studied in this work. WCCo Cermet coatings have been coated with different thicknesses by changing the amount of the cobalt using HVOF (High velocity oxy fuel technique). The coatings produced have been subjected to microhardness, friction and wear testing. A disc and pin type machine has been used for assessing friction and wears characteristics. The influence on tribological performance of coating thickness and cobalt levels was examined and compared with aluminium alloy. WCCo coating enhanced hardness by 34% and 42% in 100 and 200 micron thicknesses respectively, compared to aluminium alloy. The wear rate and the coefficient of friction are decreased by 48 and 12%, respectively, compared to uncoated aluminium alloy. Both coatings and substrates increase their wear rate and friction coefficient (COF) with the increase in load and sliding speed. Scanning Electron and Confocal microscopy examinations of worn surfaces were carried out to evaluate coating wear processes. 2021, The Institution of Engineers (India). -
Drought PredictionA Comparative Analysis of Supervised Machine Learning Techniques
Drought is a natural phenomenon that puts many lives at risk. Over the last decades, the suicide rate of farmers in the agriculture sector has increased due to drought. Water shortage affects 40% of the world's population and is not to be taken lightly. Therefore, prediction of drought places a significant role in saving millions of lives on this planet. In this research work, six different supervised machine learning (SML) models namely support vector machine (SVM), K-nearest neighbor (KNN), decision tree (DT), convolutional neural networks (CNNs), long short-term memory (LSTM), and recurrent neural networks (RNNs) are compared and analyzed. Three dimensionality reduction techniques principal component analysis (PCA), linear discriminant analysis (LDA), and random forest (RF) are applied to enhance the performance of the SML models. During the experimental process, it is observed that RNN model yielded better accuracy of 88.97% with 11.26% performance enhancement using RF dimensionality reduction technique. The dataset has been modeled using RNN in such a way that each pattern is reliant on the preceding ones. Despite the greater dataset, the RNN model size did not expand, and the weights are observed to be shared between time steps. RNN also employed its internal memory to process the arbitrary series of inputs, which helped it outperform other SML models. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
DROUGHT MITIGATION THROUGH HYDROGEL APPLICATION IN RICE (Oryza sativa L.) CULTIVATION
Sustainability in irrigation is an essential step towards responsible water consumption. In recent years, many studies have sketched climate-resilient agricultural practices to fight drought and uncertain rainfall patterns. Major rain-fed crops such as paddy and wheat require aid when there are abnormal dry spells. To mitigate the loss of crops from such events, superabsorbent polymers can be used. Soils amended with hydrogel or Superabsorbent polymer (SAP) retain moisture during drought to prevent loss of water through evaporation and percolation. This allows the crop to grow with less shock from drought. This study compares rice (Oryza sativa L.) growth rate under application (treatment groups) and non-application (control groups) of hydrogel, considering their high-water requirement. NDLR07 (recently developed) and BPT5204 (local variety) rice varieties were chosen for the current study. Randomized controlled trials were performed for each variety on a control group (NC & BC) and 3 treatment groups with 20% (NT20 & BT20), 40% (NT40 & BT40), and 60% (NT60 & BT60) deficit water supplies respectively. N, T, C refers to seed type, treatment group, control group respectively. Intermittent drought condition was imposed for 14 days to assess the resilience of crops. The water retention capacity of the sandy loam soil was better for treatment groups by 20% than control groups even at an average temperature of 40 ?. Treatment groups continued growing through the drought phase and after, while control groups showed stagnation. Among the tested treatment groups, NT20 had the highest growth among all trials. The results of the study suggested that hydrogel application can help to combat droughts and thereby contribute to sustainable agricultural production by restricting the involvement of climate changes. 2021, Editorial board of Journal of Experimental Biology and Agricultural Sciences. All rights reserved. -
Drones for Crop Monitoring and Analysis
Drones are becoming a vital tool for crop monitoring and analysis in contemporary agriculture. With the use of sophisticated sensors, these unmanned aerial vehicles (UAVs) can gather high-resolution pictures and data, giving farmers real-time insights into the growth and health of their crops. Thanks to technological advancements, drones can now more reliably and effectively collect a variety of data points than previous techniques, including plant health, moisture levels, and insect infestations. Drones are a useful tool for crop monitoring because they enable farmers to identify problems early on, such as nutrient deficits, water stress, and disease outbreaks, and take prompt action to optimize yields and avoid losses. Drones can also swiftly and affordably cover vast tracts of agriculture, giving a thorough picture of crop conditions. Farmers may use the information that drones gather to make educated decisions by choices about fertilization plans, pest control techniques, and irrigation schedules, eventually enhancing crop sustainability and output. Drone technology is projected to play an increasingly bigger role in agriculture as it develops, completely changing how farmers monitor and assess their crops. (Publisher name) (publishing year) all right reserved. -
Driving sustainable development through climate finance in India: A case study of the National Clean Energy Fund (NCEF)
This case study examines the national clean energy fund (NCEF) as a climate finance policy in India. The NCEF was established with the objective of promoting renewable energy projects and sustainable development in the country. The study explores the background and context of climate finance, providing an overview of the NCEF's goals and implementation. The case study analyzes the impact of the NCEF by examining its funding allocations and utilization over the years. It highlights the challenges faced in effectively utilizing the funds, such as administrative hurdles, limited capacity, policy uncertainties, project development barriers, financial constraints, and governance issues. Furthermore, the case study discusses the socio-economic impacts of the NCEF, including job creation, clean energy adoption, and environmental benefits. It also explores the lessons learned from the NCEF implementation, identifying areas for improvement and providing recommendations for enhancing climate finance mechanisms in India. This chapter creates a contribution to renewable energy development in India. 2023, IGI Global. All rights reserved. -
Driving profitable business growth through economical optimization, energy management, and industrial 5.0 innovations
The chapter emphasizes the significance of economic optimization, energy efficiency, and Industrial 5.0 innovations in driving sustainable growth and profitability in today's business landscape. It highlights the strategic allocation of resources to maximize efficiency and minimize costs, using lean management principles, automation, and data analytics. Energy management is crucial for reducing operational costs and mitigating environmental impact, using renewable energy sources and smart technologies. Industrial 5.0, a new era of industrial transformation, combines automation, connectivity, and data exchange, with technologies like artificial intelligence, IoT, and blockchain. 2024, IGI Global. -
Driving Financial Inclusion: Technology as an Indicator of Financial Ecosystem Development During the COVID-19 Pandemic in India
This paper examines Indias level of digital access to financial services as compared to other Asian countries. The study also intends to analyse whether COVID-19 has influenced the usage trend of the selected digital payment indicators in India. Data has been collected from the World Bank Global Findex Database and RBI bulletins. Cross country descriptive analysis was used for studying Indias digital financial access against the other Asian countries. Event study methodology followed by trend analysis was employed to examine whether COVID-19 has impacted the digital payment indicators usage in India. The findings of the study indicated that Indias position in digital financial access needs to be improved. It was further identified that COVID-19 has increased the usage of digital modes for financial transactions in India. There has been a significant increase in the usage volume of mobile banking after the declaration of the pandemic. Govt. can frame its action plans to make use of the opportunity created through the pandemic to improve digital financial access in India. 2022 IGI Global. All rights reserved. -
Drivers of value creation in Indian corporate - An empirical evidence /
International Journal of Applied Business And Economic Research, Vol.15, Issue 22(2), pp. 563-574, ISSN No. 0972-7302. -
Drivers of Rural Non-farm Sector Employment in India, 19832019
Using the national-level employment and unemployment surveys (NSS and PLFS) and the macro-level data for the period 20052019, this article explores the trends and recent growth patterns of rural non-farm sector employment in India. It also examines the micro-level factors determining individuals preference towards non-farm sector jobs and the macro-level factors responsible for the growth of non-farm sector employment in rural India. The main findings of the study suggest that although rural non-farm sector employment is rising in absolute terms, its growth rate has slackened in recent years. While the level of education and skill training, market wage rates and socio-cultural setups are among the key micro-level factors determining farmnon-farm employment choices of rural folks, at the macro-level, the growth of investment in capital goods, the number of factories, investment in infrastructure development and the growth of the manufacturing sector are crucial for the growth of non-farm sector jobs in India. Based on these findings, it is argued that the improvement of human capabilities through increased investment in education and skill, and the growth of non-farm sector employment through the development of rural infrastructure and industrialization measures, are necessary to sustain the structural transformation and to harness the demographic dividend in India. JEL Codes: J01, J21, J43, J64 2024 Research and Information System for Developing Countries & Institute of Policy Studies of Sri Lanka. -
Drivers of Mandatory and Non-Mandatory Internet Corporate Reporting in Public and Private Sector Indian Companies
The papers objective was to measure the drivers of mandatory and non-mandatory internet corporate reporting by public and private sector companies following the internet disclosure compliance of listing and obligation requirement of SEBI under Clause 46. Several drivers, namely firm size, profitability, leverage, liquidity, board size, independence of board, and CEO duality, were used to measure the effectiveness of mandatory and non-mandatory disclosure. A multiple regression model was applied to test the present papers hypotheses. The results of multiple regression revealed that the firms size was exceptionally important for both sectors. In contrast, public sector disclosure was largely impacted by leverage, liquidity, board size, and board independence. In comparison, the private sector disclosure scores were mainly impacted by leverage and board size, although there is no relationship between ICR and firm profitability and CEO duality. In performing separate multivariate regression between the two sectors, many disparities emerged. This disparity showed that public and private sector corporations had quite different firm and governance characteristics of the disclosure. As the first exploratory research to assess the mandate internet disclosure of public and private sector companies in India, it is very informational, specifically for those working on Indian companies regulation, compliance, and research. 2022, Associated Management Consultants Pvt. Ltd. All rights reserved. -
Drivers of Customer Retention: An Introspection Into Indian Retail Customers
There is a wide variety of choices for the modern retail customer including multiple retail formats. The success of the retail establishments has a great reliance of customer retention, which is an essential attribute to achieve profitability. This study takes in to consideration to extract the factors responsible for customer retention which in turn assists in increasing the customer base. The prime objective of the study is to ascertain the influence of customer satisfaction, switching costs and customer loyalty on customer retention. Whereas, the second one is to explore the effect of demographic factors on customer retention. The sample size of this study was 600 respondents who were chosen for the full-fledged study. The statistical techniques used for final analysis were structural equation modelling and regression. The findings subsequent to the statistical analysis and interpretation concluded that customer loyalty, customer satisfaction and switching cost have the strongest effect on customer retention in retails. Customer satisfaction alone is not every time an indicator of customer loyalty. A loyal customer will spread positive word of mouth to other prospective customers about the retail. Occupation of respondent has a major influence on customer retention dimensions. 2021 Management Development Institute. -
Drivers and inhibitors of consumers adoption of AI-driven drone food delivery services
This study sheds light on the determinants of consumers adoption of artificial intelligence-driven drone food delivery service (AI-driven DFDS) using a mixed-methods approach. Interviews with hospitality industry professionals revealed several drivers and inhibitors of AI-driven DFDS adoption. Using these findings, we developed a theoretical model AI-driven DFDS adoption based on the premise of the behavioral reasoning theory and innovation resistance theory. The model was tested using data collected from 1240 consumers. The results suggest that drones relative advantage, perceived ubiquity, social influence, and green image positively influence attitudes and adoption. Risk, usage, and experience barriers have an adverse influence on attitudes and adoption. Consumers openness to new technology has a positive influence on reasons for using AI-driven DFDS. The research makes an important theoretical contribution to research on the adoption of AI-driven DFDS. The study also provides important practical implications for marketers and industry professionals. 2024 Elsevier Ltd -
Drinking straw from coconut leaf: A study of its epicuticular wax content and phenol extrusion properties
Background and Objectives: Plastics are a ubiquitous part of our daily life but now posing a major threat to marine life, animal and human health. More than 50% of the manufactured plastic including straws are being disposed of after single-use. There is an increasing need to mitigate this trend so that the damage could be brought under control. The aim of this research was to develop a compostable, eco-friendly alternative to plastic straws using the leaves of Cocos nucifera L. Materials and Methods: The biochemical properties of 6 varieties of Cocos nucifera L. leaflets were studied in order to screen the most suitable material for making sustainable straws. Epicuticular wax content was analyzed to choose the best variety for preparation of hydrophobic straws. Total antioxidant activity, total tannin content, phenolic and flavonoid content were assayed to evaluate the potential functionality of the leaflets. The phenol extrusion properties of the material were also checked in acidic and normal beverages. Results: Estimation of epicuticular wax and phytochemical analysis in all 6 varieties revealed that all varieties of Cocos nucifera L. leaves provide a potent biomaterial for straw preparation. Silicon 732 was found to be a good adhesive agent for straw preparation. Phenol extrusion assays revealed that there is a negligible difference in the release of phytochemicals before and after dipping of straws in the beverages. Conclusion: The outcome of this research opens up vistas to carry out further research in a hitherto unexplored area of utilizing the leaf of Cocos nucifera in a novel way with far reaching economic and employment implications. 2019 Jyoti Jeena James et al. -
Drill hole surface characterisation of hybrid FRP laminates through statistical analysis
As it is known that the hybrid Fibre Reinforced Polymer (FRP) composite laminate is a recently evolved class of structural material. Hence, the present work deals with secondary processing ability like hole drilling on hard to machine FRP laminate. The influence of drilling attributes on the delamination factor and surface roughness contours are studied for a high thickness hybrid (carbon/glass FRP) laminates. Here, the experimentation was performed utilising Taguchis L27 design of experiments array. Later, on post-drilling, the predominant and optimum variables were studied through taguchi and variance analysis to highlight their contribution on the response functions. Taguchi results indicate that the combination of the 90?tungsten carbide tool, speed of 800 rpm, and rate of feed 50 mm/min gives the best performance concerning the delamination. Also, it was observed that the combination of the 118?tungsten carbide tool, cutting speed of 900 rpm and the rate of feed 60 mm/min give the best performance concerning surface roughness. Whereas, as per ANOVA, the highest percentage contribution factor was concerned to a tool material followed by other factors and analysed data lie with the confidence level of 95%. The work also indicates that tungsten carbide tool yield better results compared to high-speed steel tool. Further, fibre morphology has been studied, which indicates optimal structure with minimal damage. 2020 Engineers Australia.