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A Cross-sectional Study on Factors Associated with Sexual Satisfaction Among Non-working Married Women in Bengaluru
Background: Sexual satisfaction is a complex concept influenced by physical, psychological and socio-cultural factors. However, there is a lack of research on what determines sexual satisfaction among non-working married women in India. This gap hinders our understanding of how traditional gender roles, economic dependence and cultural norms affect the sexual well-being of this group. This study aims to explore the factors associated with sexual satisfaction among non-working married women in Bengaluru, India. Materials and Methods: A cross-sectional survey was conducted among 180 non-working married women. Data were collected using the New Sexual Satisfaction Scale, the Psychological Distress Scale, the Subjective Happiness Scale and a self-prepared questionnaire on various factors related to sexual satisfaction. Descriptive statistics and multiple regression were used to analyse the data. Results: Factors significantly associated with non-working womens sexual satisfaction include physical factors (menstrual health difficulties, reproductive health issues and urogenital problems), psychological factors (psychological distress and subjective happiness) and socio-cultural factors (education, knowledge of sexual health at the time of marriage, type of marriage, age, age difference between couples and duration of marital life). Family-related factors (type of family, family pressure for children and exhausting household work) and couple-related characteristics (spouses smoking/drinking patterns and relationship with the spouse) were also significant. Together, these factors explained 78.6% of the variability in sexual satisfaction among non-working married women. Conclusion: The findings highlight the need for health interventions to promote healthy lifestyles and suggest changes in sexual health practices. They also indicate the need for training health professionals to address the sexual health aspects of women. Further longitudinal studies with larger samples are required to better understand the relationship between these predictors and sexual satisfaction. 2025 The Author(s). This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). -
Some improper injective coloring parameters of graphs
Any vertex coloring protocol of a graph can be viewed as a random experiment of assigning colors to the vertices, whose random variable is defined as the number of vertices assigned a specific color in that coloring. Based on this idea, the statistical parameters of mean and variance have been extended to chromatic mean and chromatic variance for various proper vertex colorings of graphs in the literature. In this paper, the ideas of chromatic mean and chromatic variance of graphs concerning their improper injective coloring are introduced and determined for certain standard graphs. World Scientific Publishing Company. -
Eco-friendly packaging in fashion and retail: Aligning style with sustainability
The chapter identifies gaps in current research, particularly in developing countries, and calls for further studies on consumer perceptions, economic feasibility, and innovations in packaging materials and technologies. Future research directions are proposed, focusing on consumer trust in sustainability claims, cost-benefit analyses of eco-friendly packaging, and the development of new biodegradable alternatives. Overall, the chapter serves as a critical resource for understanding the challenges and opportunities in advancing sustainable packaging practices in the fashion and retail sectors, emphasizing the necessity of collaborative efforts to foster environmental stewardship and encourage environmentally friendly consumption habits. 2025, IGI Global Scientific Publishing. All rights reserved. -
A Study on Robust Feature Selection Methods Using LASSO, LASSO Variants and Ridge Regression in Sports
Regularization tools like Lasso have made a substantial progresses in regression modelling, particularly to high-dimensional data and multicollinear data. Whereas Ridge regression uses L2 regularization to address the problem of multicollinearity, Lasso uses L1 regularization to conduct regression and feature selection together. The weaknesses of Lasso under correlated predictors have inspired the creation of a number of improved variants. The present paper will do a comparative analysis of simple Lasso, Ridge and Lasso extensions like Elastic Net, Adaptive Lasso, Group Lasso and Relaxed Lasso on real-world sports data, with special focus on a new implementation of the improved Relaxed Lasso that involves three optimization strategies: systematic grid search, extended lambda sequences, and nested cross-validation structures. The comparison has been done in terms of feature selection, resistance to outliers, and prediction accuracy on Ice Hockey, Cricket, and NBA data. Various measures of errors are used to analyze models: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Coefficient of Determination (R2 ). The results have shown that the Enhanced Relaxed Lasso performs best regarding improvements in performance especially in cricket data and still serves as a competitive data in different sporting scenarios. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
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. -
Research Initiative on Sustainable Education System: Model of Balancing Green Computing and ICT in Quality Education
Green Computing Practices (GCP) convey the revolutionary changes of the modern education system. The education system is transforming into a hybrid mode of operations in effective teaching and learning procedure. In the modern era, computer devices are playing a foremost role in performing ICT based teaching and learning (ICT-BTL). The GCP and ICT-BTL are the creative and innovative practices that can ensure the eco-friendly enactment and safeguard from various harmful environmental impacts. The motive of projecting the present research outcome is to address the impact of GCP on ICT-BTL activities. The creative and innovative practices of ICT-BTL support the implementation of GCP towards a sustainable education system. A sustainable education system interconnects the teachers, learners, institutions, and industrial experts through eco-friendly electronic and computer devices that ensure maximum efficiency in education with minimum environmental impacts. 2022 IEEE. -
E-Development and Sustainable Management Education for Effective Leadership and Sustainable Society
Electronic development is the process of systematic evolution for mankind and society at large that ensures the overall progress of the electronic mode of learning, education, healthcare, society, and corporate governance. The main objective of the chapter was to address the impacts of e-development and sustainable management education for effective leadership that leads to constructing a sustainable society. The required data were collected both from primary and secondary sources. Primary data were collected from 120 respondents. The secondary data sources included official websites. The study is empirical and various statistical tools like mean, standard deviation, and t-test were executed for data analysis. The results of the research study were indicated the high degree and low degree of contribution from e-development and sustainable management education are not significant between effective leadership and sustainable society. E-development can be effective for creating a sustainable society with the goal setting of improving effective leadership skills. Copyright 2022, IGI Global. -
Level of green computing based management practices for digital revolution and new india
The reality is staring us in the form of global warming, climate changes and air-quality degradation. This reality constitutes an increasing zone on the strategic front. These strategic changes need necessarily to be responded through employees of an organization. Against this backdrop, the Green Information Technology and Green HRM have emerged as a sequel to rapid degradation of our planet due to human activities. Therefore, incorporating the environmentally friendly practices through IT practices, recruitment, training and performance management functions constitute important components of Green IT and HRM. Green information technology is the revolutionary initiatives especially for human resources management practices that lead to digital life towards sustainable society. Keeping this practical and emergent context in view, the present study makes an attempt to develop a framework for assessing the level of green HRM practices actually prevailing in Indian organizations. The requisite data were collected from original sources and clarified with existing sources. The results of the study led to the inference that Information Technology and HRM practices of promoting individual performance needs fine-tuning because any green initiative has necessarily to be a collective exercise by all concerned. BEIESP. -
Impact of blended education system on outcome-based learning and sector skills development
An effective education system transforms the teaching and learning process into innovative idea generation and independent working ability. A blended education system is the representation of effective education that connects the teachers, students, and educational institutions for content development, delivery of effective teaching methods, and choice-based learning. The motive for initiating the research work was to address the demand for outcome-based learning in society that can fulfill the sector-wise human resource requirements and sector skill development. A blended education system helps to design effective courses and degrees with the capacity of choosing subjects, lectures, and teachers either in online or offline mode of education. The system may also assist in preparing the learning pattern like classroom-based learning, internship-based learning, or learning through project works. The researchers identified the dependent and independent variables with the help of expert opinion. The questionnaire was designed with all relevant questions based on the variables and refined through a pilot study. The research outcomes are described by understanding the nature of quantitative data using statistical tools like frequency distribution, t-test, and ANOVA test with the connectivity of qualitative data and the reality of social issues. 2023 IEEE. -
The future of business management with the power of distributed systems and computing
Distributed systems and computing have emerged as key technologies for businesses seeking to improve their operations, decision-making, and customer experience. In this chapter, we examine the potential of distributed systems and computing for the future of business management. We analyze the key characteristics and advantages of distributed systems and computing for business management, including improved scalability, flexibility, and availability, as well as increased efficiency and reduced costs. We also discuss the various applications of distributed systems and computing in business management, including inventory management, supply chain optimization, customer relationship management, financial management and accounting, data analytics, decision-making, and collaboration and communication. We also explore the emerging trends and technologies in distributed systems and computing, including edge computing, blockchain, and artificial intelligence, and their potential implications for the future of business management. Furthermore, we discuss the opportunities for research and innovation in the field of distributed systems and computing, including the development of new algorithms and protocols, the exploration of novel applications, and the investigation of the social and ethical implications of distributed systems and computing. In conclusion, distributed systems and computing offer a powerful set of tools for businesses seeking to enhance their performance and competitiveness in the digital age. However, the adoption of distributed systems and computing also entails a range of challenges and risks that must be addressed through careful planning and management. By embracing the potential of distributed systems and computing while also addressing its challenges, businesses can position themselves for success in the increasingly interconnected and digital world of the future. 2024 John Wiley & Sons Ltd. All rights reserved. -
GASP XXIII: A Jellyfish Galaxy as an Astrophysical Laboratory of the Baryonic Cycle
With MUSE, Chandra, VLA, ALMA, and UVIT data from the GASP program, we study the multiphase baryonic components in a jellyfish galaxy (JW100) with a stellar mass 3.2 1011 M o hosting an active galactic nucleus (AGN). We present its spectacular extraplanar tails of ionized and molecular gas, UV stellar light, and X-ray and radio continuum emission. This galaxy represents an excellent laboratory to study the interplay between different gas phases and star formation and the influence of gas stripping, gas heating, and AGNs. We analyze the physical origin of the emission at different wavelengths in the tail, in particular in situ star formation (related to H?, CO, and UV emission), synchrotron emission from relativistic electrons (producing the radio continuum), and heating of the stripped interstellar medium (ISM; responsible for the X-ray emission). We show the similarities and differences of the spatial distributions of ionized gas, molecular gas, and UV light and argue that the mismatch on small scales (1 kpc) is due to different stages of the star formation process. We present the relation H?-X-ray surface brightness, which is steeper for star-forming regions than for diffuse ionized gas regions with a high [O i]/H? ratio. We propose that ISM heating due to interaction with the intracluster medium (either for mixing, thermal conduction, or shocks) is responsible for the X-ray tail, observed [O i] excess, and lack of star formation in the northern part of the tail. We also report the tentative discovery in the tail of the most distant (and among the brightest) currently known ULX, a pointlike ultraluminous X-ray source commonly originating in a binary stellar system powered by either an intermediate-mass black hole or a magnetized neutron star. 2019. The American Astronomical Society. All rights reserved. -
Aza-Michael addition of 1,2-diazoles to structurally diverse enones: Efficient methods toward ?-amino ketones
An efficient and mild protocol was realized using 1,2-diazoles and related heterocycles with cyclic and acyclic enones in presence of T3P (2,4,6-tripropyl-1,3,5,2,4,6-trioxatriphosphorinane-2,4,6-trioxide) toward the regioselective formation of N-cycloalkyl heterocycles at room temperature. The developed reaction conditions showcased good selectivity over a wide range of 1,2-diazoles and enones by delivering N-cycloalkyl heterocycles in excellent yields. 2020 Wiley Periodicals LLC. -
P(III)-Mediated Cascade C-N/C-S Bond Formation: A Protocol towards the Synthesis of N,S-Heterocycles and Spiro Compounds
A P(III)-mediated entry towards construction of C?N/C?S bond has been devised. The developed heterocyclization method was exercised for the synthesis of a diverse range of N,S-heterocycles and related spiro molecules. P(NMe2)3 revealed the maximum efficacies under the aerobic reaction conditions and a spectrum of bis-nucleophiles, and isothiocyanates were tolerated well to serve the access of manifold immense molecules. (Figure presented.). 2020 Wiley-VCH GmbH -
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Synthesis of Thiazines, Thiazinones and N-Cycloalkyl Azoles Via Novel Synthetic Routes
Heterocyclic building blocks have gained the utmost importance in recent past on the newlineaccount of their significance in biological and pharmaceutical fields. Among these newlinenitrogen and sulphur containing heterocyclic building blocks such as thiazines, newlinethiazinones and N-cycloalkyl heterocyclic motifs hold an important role in medicinal newlinechemistry. Thiazine cores are used for the treatment of various life threating diseases newlinelike cancer, cardiovascular and fabry diseases. Drugs containing thiazinone cores were used to treat Parkinson, Alzheimer s and various neuro degenerative diseases. Ncycloalkyl azole motifs are used to treat various life threating cancers like neck, lung, prostate, breast etc. As per the literature review, synthesis of these motifs are done using multi steps and harsh conditions, which limited the substrate scope. In this thesis we describe our studies on development of one pot, mild condition for newlinesynthesis of thiazinone cores using P(NMe2)3 (HMPT). We had developed HMPT [P(NMe2)3] mediated reactions towards synthesis of Carbon-Nitrogen/Carbon-Sulphur bond. The developed methodology was extended for thiazine cores as well. This new synthetic methodology is useful to synthesize various N, S-heterocycles including the novel spiro molecules. HMPT reagent under the mild and aerobic reaction conditions provided the access for many manifold immense molecules. Molecular docking studies were conducted for the synthesized compounds considering MOA-B inhibitors as target. MOA-B inhibitor motifs were approved for the treatment of Parkinson illness. The synthesized thiazine and thiazinone molecules showed good binding affinity in molecular docking studies conducted. We had developed a new strategy using T3P (1-Propanephosphonic anhydride, ~ 50 % wt, in EA solution) mediated synthetic procedure for the synthesis of N-cycloalkyl newlineazoles. -
Bayesian and Non-Bayesian Parameter Estimation for the Bivariate Odd Lindley Half-Logistic Distribution Using Progressive Type-II Censoring with Applications in Sports Data
The Bivariate Odd Lindley Half-Logistic (BOLiHL) distribution with progressive Type-II censoring provides a powerful statistical tool for analyzing dependent data effectively. This approach benefits society by enhancing engineering systems, improving healthcare decisions, and supporting effective risk management, all while optimizing resources and minimizing experimental burdens. In this paper, the likelihood function derived under progressive Type-II censoring is generalized for the BOLiHL distribution. The well-known maximum likelihood estimation method and Bayesian estimation are applied to evaluate the parameters of the distribution. A study utilizing simulation techniques is performed to evaluate the performance of the estimators, using statistical analysis metrics for censored observations under a progressive Type-II censoring scheme with varying sample sizes, failure times, and censoring schemes. Additionally, a real dataset is studied to validate the proposed model, delivering impactful analyses for practical applications. 2025 by the authors. -
Predicting nitrous oxide contaminants in Cauvery basin using region-based convolutional neural network
Nitrous oxide (N2O) in riverbeds affects hydrological processes by contributing to the greenhouse effect, indicating poor water quality, disrupting biogeochemical cycling, and linking to eutrophication. Elevated N2O levels signal environmental issues, impacting aquatic life and necessitating precise forecasting for effective environmental management and reduced greenhouse gas emissions. Precisely forecasting nitrous oxide (N2O) emissions from riverbeds is paramount for effective environmental management, given its significant potency as a greenhouse gas. This study focuses on the difficulties related to spatial feature extraction and modeling accuracy in predicting N2O in riverbeds in Tamil Nadu. To address the obstacles, the research suggests utilizing the Deep Learning Based Prediction of Nitrous Oxide Contaminants (DL-PNOC), which studies the N2O contaminants in water using Region-based Convolutional Neural Network (RCNN) for spatial feature extraction, to predict nitrous oxide contaminants. The study is centered on the Cauvery River Basin located in Tamil Nadu, where the emission of N2O is a matter of environment. The outcomes encompass the specialized N2O contaminant model for riverbeds and the implementation of RCNN achieves precise N2O forecasting. The DL-PNOC approach combines a contaminant model with RCNN deep learning techniques to capture spatial characteristics and predict N2O pollutants accurately. Furthermore, using the River Bed Dynamics Simulator reinforces the dependability of the findings. The DL-PNOC approach has exhibited encouraging results, as evidenced by the following metrics: a high IoU of 88.66%, precision of 88.96%, recall of 90.03%, F1 score of 89.22%, and low RMSE and MAE values of 9.14% and 7.59%, respectively. The findings highlight the efficacy of the DL-PNOC approach in precisely forecasting N2O pollutants in river sediments. 2024 Elsevier B.V.