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Effect of surface charge and other critical parameters on the adsorption of dyes on SLS coated ZnO nanoparticles and optimization using response surface methodology
Adsorption is a possible method with distinct advantages to remediate pollution due to dyes. Sodium Lauryl Sulfate (SLS) coated ZnO nanoparticles were synthesized using the electrochemical method. The final product was dried at different temperatures, 60, 120, 150 and 300 C. The sample dried at 60 C was found to have the maximum SLS coating on its surface providing high negative charge density. This facilitates the adsorption of cationic dyes on its surface through electrostatic attraction. The effect of SLS on the adsorption process was confirmed by comparing it with ZnO without SLS. The effect of important parameters such as amount of adsorbent, concentration of dye, temperature and time on the percentage of adsorption was investigated using Box-Behnken design (BBD) of Response Surface Methodology (RSM). The prepared catalysts were characterized using X-ray diffraction analysis, infrared spectroscopic analysis, scanning electron microscopy, elemental detection analysis, thermogravimetric and zeta potential analysis. Finally, the study was extended to Langmuir and Freundlich isotherms in order to confirm the type of adsorption. The adsorption kinetics studies showed that it obeys pseudo second order kinetics. 2020 Elsevier Ltd. -
Experimental design for optimization of 4-nitrophenol reduction by green synthesized CeO2/g-C3N4/Ag catalyst using response surface methodology
In this study, the enhancement of catalytic activity of ceria when modified with co-catalysts such as graphitic carbon nitride and silver was established. The material was synthesized using phytogenic combustion method, a green alternative to the traditional preparative routes. The catalyst was characterized using XRD, FTIR, SEM, EDX, XPS and TEM techniques. The synergistic effect of the composite CeO2/g-C3N4/Ag was tested for catalytic reduction of 4-nitrophenol in the presence of sodium borohydride. The reaction was carried out at room temperature without any light source or external stirring. The individual and combined effects of four parameters, viz., concentration of 4-NP, amount of catalyst, amount of NaBH4 and time for the reduction of reduction 4-NP were investigated using Box-Behnken design of response surface methodology (RSM). This statistical model was used to optimize the reaction conditions for maximum reduction of 4-NP. The optimum conditions for the reduction reaction are found to be 0.01 mmol/L 4-NP, 15 mg catalyst, 20 mg NaBH4 and 13.7 min time interval. 2020 Chinese Society of Rare Earths -
BoxBehnken design and experimental study of ciprofloxacin degradation over Ag2O/CeO2/g-C3N4 nanocomposites
Abstract: The presence of pharmaceutical residues notably antibiotics in the environment is an increasing concern due to their persistence and toxicity. Developing efficient and eco-friendly methods to eliminate antibiotic residues from water bodies has become a major environmental challenge. CeO2 doped with a heteroatom forms a hybrid structure with g-C3N4 and could serve as an efficient photocatalytic agent. In this study, CeO2/g-C3N4 and Ag2O/CeO2/g-C3N4 hybrid catalysts were prepared for UV light degradation of ciprofloxacin (CIP) antibiotic. The various factors that influence the degradation were experimentally optimized. The kinetics of the degradation was investigated using the LangmuirHinshelwood kinetic model. The effect of three operational parameters influencing the photocatalytic degradation has been evaluated using BoxBehnken design of response surface methodology. The highest degradation of CIP was observed at CIP concentration of 10?g/L with a catalyst amount of 30mg after 2.5h. Efficient charge separation was achieved from the dopant and the existing integrated electric field of the heterojunction showed impressive higher activity. Graphic abstract: [Figure not available: see fulltext.]. 2020, Islamic Azad University (IAU). -
Hierarchically nanostructured ZnO with enhanced photocatalytic activity
Hierarchical nanostructures of ZnO are integrated architectures comprising well-ordered nanoscale subunits and excellent photocatalytic properties. In this study, synthesis of ZnO nanoparticles using methods such as co-precipitation, hydrothermal, thermal decomposition, and electrochemical precipitation yielded microsphere, nanorod, pyramid, and nanopetal-like morphologies, respectively. The catalysts obtained were characterized using XRD, IR, SEM-EDX, UVDRS, TGA, PL, and Zeta potential analysis. The XRD spectra confirmed that all the different morphologies of ZnO have hexagonal wurtzite structures The photocatalytic activity of these nanostructures was determined using a dye degradation study on a model pollutant Methylene Blue (MB) under simulated visible light. The kinetic study of the dye degradation reveals that it obeys pseudo-first-order kinetics with a maximum rate constant of 0.01503 min-1. The nanorod structured ZnO particles prepared by the hydrothermal method showed the best catalytic activity. 2021 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited. -
Phytogenic CeO2-Sm2O3 nanocomposites with enhanced catalytic activity for reduction of 4-nitrophenol
The phytogenic synthesized CeO2-Sm2O3 is a green, efficient and cost-effective catalyst. The CeO2-Sm2O3 composite was characterized using XRD, FTIR, Raman, TGA, UV-DRS, TEM, FE-SEM and EDAX. The synthesized CeO2-Sm2O3 shows a high catalytic activity for the reduction of 4-nitrophenol in the presence of the sodium borohydride under ambient conditions. This CeO2-Sm2O3 nanocomposite catalyst shows good stability and reusability without much loss in conversion efficiency. CeO2-Sm2O3 possess great prospects in the reduction of nitro organic pollutants in water. 2019 IOP Publishing Ltd. -
Machine Learning-Based Imputation Techniques Analysis and Study
Missing values are a significant problem in data analysis and machine learning applications. This study looks at the efficacy of machine learning (ML) - based imputation strategies for dealing with missing data. K-nearest Neighbours (KNN), Random Forest, Support Vector Machines (SVM), and Median/Mean Imputation were among the techniques explored. To address the issue of missing data, the study employs k-nearest neighbors, Random Forests, and SVM algorithms. The dataset's imbalance is considered, and the mean F1 score is employed as an evaluation criterion, using cross-validation to ensure consistent results. The study aims to identify the most effective imputation strategy within ML models, offering crucial insights about their adaptability across various scenarios. The study aims to determine the best plan for data preprocessing in machine learning by comparing approaches. Finally, the findings help to improve our knowledge and application of imputation techniques in real-world data analysis and machine learning. 2024 IEEE. -
On the Hermite and Mathieu Special Characterizations to the Logarithmic ZakharovKuznetsov Equations
In this paper, we find the new travelling wave solutions for several aspects of logarithmic ZakharovKuznetsov (ZK) equations using an efficient technique called the special function method which is composed of Hermite and Mathieu differential equations being novel and special functions. In order to illustrate the efficiency of the projected scheme, we considered four different examples with different cases, namely, logarithmic ZK (log-ZK) equation, logarithmic modified ZK (log-mZK) equation, and logarithmic ZK modified equal width (log-ZK-mEW) equation and logarithmic ZKBenjaminBonaMahony (log-ZKBBM) equation. The behaviour of the obtained results and corresponding consequences are illustrated and captured. Finally, the obtained results confirm that the considered solution procedure can be widely employed to find the solution and also capture some interesting and stimulating consequences. 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
fluorescence diffuse optical tomography : Synthesis characterization and imaging of a novel target specific near infra-red contrast agent for breast cancer detection
Contrast agents are finding profound application in optical imaging of breast cancer for an early detection. In the present work, a novel estrogen receptor (ER) targeted near infra-red fluorescent dye conjugate was synthesized, referred to as Novel Dye Conjugate (nDC) hereafter. nDC is a conjugate of 17and#946;-estradiol with a derivative of indocyanine green dye, bis-1,1-(4-sulfobutyl) indotricarbocyanine-5-carboxylic acid, sodium salt. Structural composition of nDC was validated using Liquid Chromatography Mass Spectrometry (LC-MS) and Hydrogen-1 Nuclear Magnetic Resonance (1H-NMR) technique. MCF-7 and MDA MB 231 Cell lines studies proved the special biding ability of nDC with estrogen receptor positive breast cancer cell lines and its photophysical properties were verified to be in near infrared region (NIR). Similar studies were conducted on ER expressing cancerous tissues like Non-Invasive Ductal Carcinoma, Non-Invasive Lobular Carcinoma, Non-Invasive Adenocarcinoma and Non-Invasive Medullary Carcinoma. In all the above tissues, nuclear level ER binding of nDC was observed leading to the validations of the unique binding properties of the novel dye. Mathematical modeling for tumor to background mapping using nDC was carried out through Fluorescence Diffuse Optical Tomography (FDOT) simulations. Simulation results were also validated using silicone phantom experiments. An array of 8*8 boundary data was collected using frequency domain-FDOT system which was setup indigenously. Commercially available fluorescent dye Indocyanine Green (ICG) was used in the present study for comparative analysis with nDC. When compared to ICG, proposed dye had 1.5-fold higher target to background contrast with respect to fluorescent lifetime in both simulation and phantom studies. Similarly proposed novel dye had a two-fold higher target to background contrast with respect to fluorophore absorption. Above results proved the superiority of nDC compared to ICG on target(tumor) to background ratio enhancement. -
Conjugate of Estradiol and applications thereof /
Patent Number: 201641013646, Applicant: Christ University. -
Group signature based security technique for privacy identity information protection in blockchain /
Patent Number: 202121031204, Applicant: Gauri Arun Varade.
On cryptographic algorithms blockchain is a highlight point dispersed record innovation dependent. By factual techniques, information mining and sociological mining has made clients protection face significant dangers the straightforward and open blockchain record enhanced. -
Conjugate of estradiol and applications thereof /
Patent Number: US 10 , 054 , 602 B2, Applicant: Christ University.
The present invention relates to conjugate of 17-β estradiol with an analog of indocyanine green dye for the detection of cancers. The invention also provides a method of preparation of the conjugate and method of detection of cancer cells. -
Fluorescence diffuse optical tomography: Synthesis, characterization and imaging of a novel target specific near infra-red contrast agent for breast cancer detection /
A paradigm shift is seen for cancer treatment since many decades in developing safe and efficient techniques to prevent, detect, treat and cure cancer worldwide. However, there is still a long way to stabilize the rate of cancer occurrence. Breast cancer is found to be among the top three cancer types in terms of incidence and fifth in terms of mortality. An estimate of 2.1 million new cases of breast cancer was recorded in the International Agency for Research on Cancer [IARC] Report 2018. Close to a half (43.6%) of all breast cancers were diagnosed within the Asia-Pacific region (approximately 911014 cases), with the greatest number of those occurring in China, Japan and Indonesia. Although the prognosis is relatively favorable, at least in more developed countries, early diagnosis is the lifesaver. Diffuse Optical Tomography (DOT) is one of the emerging diagnostic tools for early detection of breast cancer. It uses near infra-red (NIR) light to probe human soft tissues and is capable of continuous monitoring of the patient. DOT is cheaper, compact and uses non-ionizing radiation unlike its counterparts like CT-Scan, Mammogram and PET scan. The potential of DOT can be enhanced by using a NIR exogenous contrast agents, and the system is known as Fluorescence-DOT (FDOT). Indocyanine Green (ICG) is a popular FDA approved dye available in the market which is explored for cancer detection using FDOT. But, with its non-specific nature, there was a need for a specific and functionally orientated dye to further improve the efficacy of FDOT imaging. -
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Early detection of breast cancer using ER specific novel NIR fluorescent dye conjugate: A phantom study using FD-f-DOT system
Fluorescence diffuse optical tomography (f-DOT) is an imaging technique that can quantify the spatial distribution of fluorescent tracers in small animals and human soft tissues. Efficacy of f-DOT imaging can be improved by tagging a functional group to the dye. A novel estrogen receptor (ER) specific near-infrared (NIR) fluorescent dye conjugate was synthesized which can be effectively used for detecting breast cancer tissues at an early stage. Our novel dye, Near Infrared Dye Conjugate-2 (NIRDC-2), is a conjugate of 17?-estradiol with an analogue of Indocyanine Green dye, bis1,1-(4-sulfobutyl) indotricarbocyanine-5-carboxylic acid, sodium salt. Our present study focuses on imaging cylindrical silicone phantoms using Frequency Domain f-DOT system. Background absorption and scattering coefficients were 0.01mm-1 and 1mm-1 respectively. 10?M concentration of NIRDC-2 and Indocyanine Green (ICG) were administered separately into a cylindrical hole (target) of size 8mm diameter in the phantom. In-silico studies were performed to analyze the properties of dyes using experimental data. Absorption coefficient of 0.0002 mm-1 was recovered for the background. Fluorophore absorption coefficient at the target recovered were 0.000173 mm-1 and 0.000408 mm-1 for ICG and NIRDC-2 respectively. In comparison with ICG, our novel dye had a two fold higher target to background contrast. Recovered target position was accurate but size altered. In concurrence with the recovered fluorescent property and the cell lines studies carried out earlier, binding properties of NIRDC-2 makes it a potential probe for the early tumor detection using f-DOT system. COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. -
Assessing the Determinants of Metaverse Adoption for E-Commerce Retailing
The advent of metaverse technology has impacted the retail sector, shaping e-commerce platforms into a new form of metaverse-based online shopping environments. The metaverse e-commerce experience is new to shoppers, making it crucial to comprehend consumer reactions to this technology in the context of retail. This study explores the shopping intention and potential use of the metaverse for shopping using the UTAUT2 model and metaverse-based context-specific antecedents. Using a structured questionnaire, data from 1340 consumers were collected and analyzed through PLS-SEM. The findings indicated that factors such as performance expectancy, effort expectancy, social influence, hedonic motivation, and facilitating conditions influence shopping intention in the e-commerce metaverse. The metaverse-related antecedents, namely, a sense of immersion and imagination, have a positive influence, whereas technological anxiety and perceived security and privacy concerns have a negative impact on e-commerce shopping intention in the metaverse. It was also found that shopping intention influences the potential use of metaverse for shopping and that stickiness to traditional shopping negatively moderates this relationship. This unique research explores consumer buying behavior in the metaverse. It provides marketers, e-commerce managers, designers, and developers of metaverse platforms with the antecedents of the potential use of the metaverse for shopping insights. Consumer policymakers can also draw insights from this study. 2024 The Author(s). Published with license by Taylor & Francis Group, LLC. -
Unveiling virtual interactive marketplaces: Shopping motivations in the Metaverse through the lens of uses and gratifications theory
The emergence of Metaverse has transformed the consumer shopping experience. This novel e-commerce platform offers a fresh approach to shopping, with Generation Z primarily exploring this innovative technology. Our research examines shopping within the Metaverse by developing a model based on the Uses and Gratifications Theory and Metaverse-related factors. A total of 1220 Gen Z consumers were surveyed, and data was collected using a structured questionnaire. Further, analysis of collected data was done using PLS-SEM. The results reveal that information seeking, perceived enjoyment, escapism, social interaction, sense of immersion, and personalization influence the shopping intention in the Metaverse, and perceived risk negatively influences the shopping intention of consumers. Further, shopping intention influences the potential use of Metaverse for shopping, and this relationship is moderated by technological innovativeness. This investigation into the adoption of the Metaverse for retail purposes augments the current Metaverse research and enhances the uses and gratifications theory within the Metaverse domain. Metaverse e-commerce professionals, including managers and developers, can acquire valuable perspectives on consumer shopping tendencies in the Metaverse from this study. 2025 The Author(s) -
Assessing factors influencing intentions to use cryptocurrency payments in the hospitality sector
Purpose: The emergence of cryptocurrency has developed a new payment system that is changing how financial transactions happen in hospitality. Consumers/travelers have started experimenting with cryptocurrency payments in hotels and restaurants. However, extant research is lacking in understanding the consumer adoption intention of cryptocurrency payments. This study investigates the intention to use cryptocurrency payments in the hospitality industry. Design/methodology/approach: The conceptual model in this study is based on the Behavioral Reasoning Theory, and it explores the motivating and deterring factors influencing the adoption of cryptocurrency payments in the hospitality industry. A quantitative survey was conducted among 1,080 consumers to examine and confirm the model, with data being analyzed through the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. Findings: The outcome of this work showed that the reasons for positively influence and reasons against negatively influence consumers attitudes and use intentions. Consumers values of openness to change positively influence the reasons for and do not influence the reasons against and attitude toward the use of cryptocurrency payments. Practical implications: This work contributes to practice by providing insights to customers (users/payee), hospitality managers (investors) and organizations/firms (receiving crypto payments) as well as to financial firms and the government. Originality/value: This research contributes to cryptocurrency payment adoption and behavioral finance literature. The research uniquely provides the adoption and inhibiting factors for cryptocurrency payment in an integrated framework in the hospitality sector. 2024, Emerald Publishing Limited. -
History of gestational diabetes mellitus, self-efficacy and coping in postpartum women: A pilot study
The present study investigates whether the history of gestational diabetes mellitus (GDM) influences self-efficacy and coping among postpartum women. Purposive sampling technique was used to collect data from 100 postpartum women, 50 with a history of GDM and 50 without. The General Perceived Self-Efficacy Scale was used to measure the self-efficacy of the participants. The Brief COPE developed by Carver was used to measure coping. A Mann-Whitney U-test showed postpartum women with a history of GDM are higher in self-efficacy and coping than those without such a history. Even though self-efficacy showed a relationship to coping, the two groups differed in the use of coping strategies. 2018 by the Research Institute of Asian Women, Sookmyung Women's University. All rights reserved. -
Cultural Memory In The Captivity Novels of NA D'Souza Alan Machado
Captivity novels are stories of men and women who were abducted and forcibly taken as captives and subjugated to slavery, usually for religious or political reasons. The research critically engages the captivity novels of Na DSouza and Alan Machado, which vividly evoke the harrowing captivity experience of Mangalore Konkani Catholic community during Tipu Sultans regime. It is alleged that Tipu, after the Second Anglo-Mysore war, wreaked vengeance on Konkani Catholic Christians on suspicion for betraying him and supporting the British. After two hundred years of great silence, the struggle for identity and the quest for history led the post-conflicting community to articulate the contents of the archives into the fabric of a literary composition. The literary works of DSouza and Machado are an essential bridge between generations problematizing history and memory illustrating the events of Great Captivity. The captivity narratives are cultural artefacts of memory that present alternative history of the Mysore Kingdom and revive the memories of the captivity experience of Mangalore Konkani Catholic Christians. The memories of the miseries revived in the writings of DSouza and Machado at the beginning of the twenty first century from the victims point of view expose the gaps in the official records of the Mysore Kingdom and emphasise the community's resilience and cultural significance. These narratives constitute the melancholic representation of the traumatic experience of the community and enable the community of the sufferers to re-live the torments which in turn act as a therapeutic agent. Thus, the imaginative recount of the Great Captivity by DSouza and Machado in the form of novels using memory as a tool challenge the historical construct and call for a legitimate space for the vanquished version in the construction of history. -
Independent partial domination
For p ? (0, 1], a set S ? V is said to p-dominate or par-tially dominate a graph G = (V, E) if|N[S]| |V | ? p. The minimum cardinality among all p-dominating sets is called the p-domination number and it is denoted by ?p(G). Analogously, the independent partial domination (ip(G)) is introduced and studied here independently and in re-lation with the classical domination. Further, the partial independent set and the partial independence number ?p(G) are defined and some of their properties are pre-sented. Finally, the partial domination chain is established as ?p(G) ? ip(G) ? ?p(G) ? ?p(G). L. Philo Nithya et al.