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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: 201641013646, Applicant: Christ University. -
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. -
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. -
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. -
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. -
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. -
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). -
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 -
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. -
Synthesis of amine functionalized metal organic framework using H2FIPBB ligand for energy storage application /
Patent Number: 202241023295, Applicant: Sruthi Rajasekaran.
The present invention shows the energy storage application of the Mn-Ni@NH2-h2fipbb MOF using the ligand 4,4:hexafluoroisopropylidene bis- benzoic acid (h2fipbb) under mild conditions. The methodology followed was hydrothermal at 120°C with manganese and nickel metal salts along with the ligand in dimethylformamide (DMF). The development of efficient Mn-Ni@NH2-h2fipbb material is suitable for supercapacitance-energy storage applications, which is the future need for various industrial applications. -
Two-dimensional CR2C MXENE decorated with COFE204 nanoparticles for high-performance supercapacitor application /
Patent Number: 202241046374, Applicant: B Shalini Reghunath.
The current innovation shows the cobalt ferrite (CoFe204) decorated on O2C MXene binary composite. This is used as a high-efficiency electrocatalyst for supercapacitor applications in alkaline media. The O2C MXene/CoFe204 binary composite is prepared by etching the O2AIC MAX phase with hydrofluoric acid for 30 min at room temperature, followed by a solvothermal technique using cobalt ferrite nanoparticles. The interlayer spaces of O2C MXene/CoFe204 electrocatalyst improves on introducing CoFe204 nanoparticles between the O2C MXene layers, thereby boosting the capacitance of the composite. -
Bismuth ferrite nanoparticles decorated CR2C MXENE: A highly efficient electrocatalyst for hydrogen evolution /
Patent Number: 202241040877, Applicant: B Shalini Reghunath.
The current invention demonstrates the efficiency of bismuth ferrite/Cr2C MXene binary composite as a highly efficient electrocatalyst for hydrogen evolution reaction in alkaline media. The methodology for preparing O2C MXene is by etching the O2AIC MAX phase with hydrofluoric acid for 30 min at room temperature. Cr2C MXene and bismuth ferrite nanoparticles are mixed under solvothermal conditions to obtain the bismuth ferrite/Cr2C-MXene binary composite. -
Hierarchically porous MN-MOFS composite with RGO as an efficient electrode material for supercapacitor application /
Patent Number: 202241046378, Applicant: Sruthi Rajasekaran.
The present invention shows the energy storage application of the manganese-reduced graphene oxide metal organic frameworks (Mn-rGO MOFs) using the ligand, pyridine 2,6 dicarboxylic acid (PDA), under mild conditions. The methodology followed was hydrothermai at 160°C with manganese sulfate as metal salt, rGO along with the PDA ligand in pyridine, and water as solvent. The development of efficient Mn-rGO MOFs is suitable for supercapacitance energy storage applications, which is the future need for various industrial applications. -
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Sexual Function and Sexual Satisfaction among Non-Working Married Women in Bengaluru
Background: Sexual function and satisfaction are two important components of the sexual health of women. Both are influenced by various external and internal factors over their life cycle. This study aims to explore the factors of sexual function and newlinesatisfaction among non-working married women in Bengaluru using an exploratory newlinesequential research study and highlighting the implications for social work practices. newlineMaterials and Methods: The study has two phases. The first phase was a qualitative newlineexploratory research study that adopted an inductive thematic data analysis. In-depth newlinequalitative interviews were conducted with 11 non-working working married women. The interviews were audio recorded and the transcribed data were analyzed with ATLAS.ti software. The results were presented thematically. The second phase was a newlinecross-sectional survey of 180 non-working married women. The data were collected newlinethrough semi-structured interviews with the Female Sexual Function Index, the New newlineSexual Satisfaction scale, the Psychological Distress Scale, the Subjective Happiness newlinescale, and questions related to socio-demographic details, and health. Descriptive and inferential statistics were carried out and multiple regression analyses were conducted with jamovi v2.3. to find the predictors of both sexual function and satisfaction. Results: In the qualitative phase various factors of sexual function and satisfaction were explored and organized into three global themes. They are Somatic and personal factors, Factors related to the mind, and Situational and extrinsic factors. The quantitative study found that physical, psychological, couples characteristics-related, family, and socio-cultural factors together predict a 17.3% variance in sexual function and a 78.6% variance in sexual satisfaction of women. Conclusion: The study could find positive and negative factors of sexual function and satisfaction. -
Mining and Interpretation of Critical Aspects of Infant Health Status Using Multi-Objective Evolutionary Feature Selection Approaches
The rate of infant mortality (IMR) in a population under one year of age is a marker for infant mortality. It is a major sensitive marker of a community's overall physical health. Protecting the lives of newborns has become a challenging issue in public health, development programs, and humanitarian initiatives. Almost 10.1% infants died in the United States of America (USA) in 2021. Therefore, this paper aims to extract and understand the various influential factors causing infant deaths in the USA. A crowding distance-based multi-objective ant lion optimization (MOALO-CD) is proposed here with statistical evidence for feature selection. The proposed technique is compared with competitive metaheuristic models such as multi-objective genetic algorithm based on crowding distance (MOGA-CD), multi-objective filter approaches, and recursive feature elimination. Various machine learning classifiers are applied to the selected feature subset obtained from MOALO-CD on the USA's infant dataset. Extensive experimental results indicate that the proposed model outperforms the existing metaheuristic approaches in terms of Generational Distance, Inverted Generational Distance, Spread, and Hyper volume. Also, the comparative analysis of various machine learning models reveals that random forest achieves significantly better performance on the feature subset obtained from MOALO-CD. 2013 IEEE. -
An efficient ZnO and Ag/ZnO honeycomb nanosheets for catalytic green one-pot synthesis of coumarins through Knoevenagel condensation and antibacterial activity
This study pioneers the synthesis of porous Ag/ZnO nanosheets, focusing on their role as a catalyst in Knoevenagel condensation. Notably, these nanosheets display exceptional catalytic efficacy and captivating antibacterial properties. The research delves into the Ag/ZnO catalyst's recyclability and proposes a potential reaction mechanism, marking the first comprehensive exploration of Knoevenagel condensation on porous Ag/ZnO nanosheets. Key findings underscore the successful synthesis of coumarin derivatives using various o-hydroxy benzaldehyde and 1,3-dicarbonyl compounds, with nano-Ag/ZnO serving as a catalyst via a monomode microwave-assisted approach. X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy (TEM) and UV-Vis spectroscopy were used in conjunction with other physicochemical methods to characterize the synthesized catalytic samples. The method boasts advantages such as high product yields, brief reaction durations, and the ability to reuse the catalyst for multiple cycles. The Ag/ZnO nanosheets, functioning as an acid catalyst, activate carbonyl groups and facilitate their interaction with methylene-containing active molecules. In addition, antibacterial activity assessments demonstrate the superior effectiveness of Ag/ZnO nanocomposites compared to ZnO nanosheets against Staphylococcus aureus germs. This multifaceted study not only advances catalytic synthesis but also unveils promising biological applications of porous Ag/ZnO nanosheets. 2024 Walter de Gruyter GmbH, Berlin/Boston 2024. -
Node Overlapping Detection for Draggable Node-Based Applications
Node-based interfaces are user interfaces that are based on the concept of nodes, which represent individual units of functionality, and edges, which represent the connections between nodes. In a node-based interface, nodes are connected by edges to form a graph, which represents the data flow and relationships between different parts of the system. The Node overlapping detection technique is only for react flow version 11 and higher. Users having previous versions are not able to use that functionality. To detect the overlapping, based on the output of this library, several user-defined functions can be used to resolve to overlap. It will see the single-pixel overlap. Using this library, users can avoid Node and edge overlapping by creating custom edges. It is a simple JavaScript function currently used for reactjs. In the future, if any other script develops a draggable node-based flowsheet-creating feature, the user can use this library accordingly. 2023 IEEE. -
Consumer ethnocentrism and buying intentions on OTT platforms
This research delves into how OTT platforms are transforming media consumption patterns and explores the role of consumer ethnocentrism in shaping buying behaviors within this context. Through a literature review and quantitative research methodology using a Likert-scale questionnaire, the study investigates the relationship between consumer ethnocentrism, buying intentions, and various influencing factors on OTT platforms. Contrary to expectations, the findings show that consumer ethnocentrism has minimal impact on buying behavior. Instead, factors such as price, content variety, personalized recommendations, cultural alignment, ease of platform usage, familiarity with foreign content, and language preferences are crucial in determining viewers' buying intentions. The chapter concludes by recommending that OTT platforms integrate cultural sensitivities into their strategies to better cater to diverse viewer preferences, thereby enhancing market competitiveness and audience engagement. 2024, IGI Global.