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Impact of chemical reaction on MHD 3D flow of a nanofluid containing gyrotactic microorganism in the presence of uniform heat source/sink
The purpose of current study is to deliberate the effect of chemical reaction on 3D flow and heat transfer of an MHD nanofluid in the vicinity of plate containing gyrotactic microorganism over a elastic surface. Influence of uniform heat source/sink on temparature transfer has been considerd. The governing standard nonlinear system of equalities is resolved numerically via Runge-Kutta method of 45th order based shooting scheme. Role of substantial parameters on flow fields as well as on the, heat, mass and microorganism transportation rates are determined and discussed through ploted graphs. 2018 Walter de Gruyter GmbH, Berlin/Boston. -
Impact of ohmic heating on MHD mixed convection flow of Casson fluid by considering Cross diffusion effect
Present communication aims to discuss the impact of viscous dissipation on MHD flow, heat and mass transfer of Casson fluid over a plate by considering mixed convection. Nonlinear partial differential systems are reduced to the ordinary ones through transformation procedure. The modelled nonlinear systems are computed implementing RKF-45 scheme. Convergent solutions for velocity and temperature and concentration fields are given diagrammatically. The obtained results are compared with published literatures and reasonable agreement is found. It is found that, temperature profile increases by increasing values of Dufour parameter, whereas on opposite trend is observed in concentration profile for increasing values Soret parameter. 2019 B.J. Gireesha et al. -
Exploration of activation energy and binary chemical reaction effects on nano Casson fluid flow with thermal and exponential space-based heat source
Purpose: The purpose of this paper is to explore the effects of binary chemical reaction and activation energy on nano Casson liquid flow past a stretched plate with non-linear radiative heat, and also, the effect of a novel exponential space-dependent heat source (ESHS) aspect along with thermal-dependent heat source (THS) effect in the analysis of heat transfer in nanofluid. Comparative analysis is carried out between the flows with linear radiative heat process and non-linear radiative heat process. Design/methodology/approach: A similarity transformation technique is utilised to access the ODEs from the governed PDEs. The manipulation of subsequent non-linear equations is carried out by a well-known numerical approach called RungeKuttaFehlberg scheme. Obtained solutions are briefly discussed with the help of graphical and tabular illustrations. Findings: The effects of various physical parameters on temperature, nanoparticles volume fraction and velocity fields within the boundary layer are discussed for two different flow situations, namely, flow with linear radiative heat and flow with non-linear radiative heat. It is found that an irregular heat source/sink (ESHS and THS) and non-linear solar radiation play a vital role in the enhancement of the temperature distributions. Originality/value: The problem is relatively original to study the effects of activation energy and binary chemical reaction along with a novel exponential space-based heat source on laminar boundary flow past a stretched plate in the presence of non-linear Rosseland radiative heat. 2019, Emerald Publishing Limited. -
Disentangling homeowner motives for solar PV: Psychometric development, validation and invariance test of the Motivation for Rooftop Solar Adoption Scale
The rooftop photovoltaic (PV) adoption of households is shaped by heterogeneous motives of the household that extend beyond economic calculus, yet prior research often measures these motives using ad hoc or single-item indicators, limiting comparability across studies. This study develops and validates the Motivation for Rooftop Solar Adoption Scale (MRSAS) to disentangle the key motivational dimensions that drives the household PV adoption. Following established scale-development guidance, we generated an initial item pool from theory and recent PV-adoption evidence, assessed content adequacy using a structured Q-sort, and then conducted exploratory factor analysis (N = 295), followed by confirmatory factor analysis (N = 312). Results support a parsimonious 22 item six-factor model with Social Influence, Financial Motivation, Environmental Protectionism, Energy Self-Reliance, Facilitating Conditions, and Technophile Attitude as dimensions. The model exhibits excellent confirmatory model fit along with strong reliability and discriminant validity. Multi-group CFA establishes scalar invariance between adopters and non-adopters, aligning with theory, adopters score higher across all six motivational dimensions. The MRSAS provides a psychometrically robust and transferable tool for profiling why households adopt solar, supporting cumulative theory-building and enabling practitioners to tailor incentives, communication and programme design to the motivations that matter. 2026 The Authors. -
Extended Slash Modified Lindley Distribution to Model Economic Variables Showing Asymmetry
This article introduces a novel probability distribution to model economic variables with high kurtosis and heavy tails showing a decreasing trend. From a mathematical viewpoint, it corresponds to the distribution of the ratio of two independent random variables, one with the modified Lindley distribution and another with the beta distribution. In some sense, it can be described as an extended three-parameter version of the Lindley distribution that has the ability to model data with high kurtosis. After presenting this distribution in more in-depth details, a comprehensive analysis is given, including its associated functions, moments, skewness, and kurtosis characteristics. Furthermore, a parametric estimation work is carried out. A simulation approach is used to validate the performance of the obtained estimates. The applicability of the proposed distribution is demonstrated by fitting real-world data into various socioeconomic scenarios. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Design and Analysis of Reliability Sampling Plans Based on the ToppLeone Generated Weibull Distribution
As part of this study, we design a reliability acceptance sampling plan under the assumption that the lifetime of a product follows the ToppLeone generated Weibull (TLGW) distribution, a model that exhibits structural symmetry in its hazard rate behavior and distributional form. The fundamental procedures for constructing such a plan are described. We compute and tabulate the minimum sample sizes required for given risk criteria using both binomial and Poisson models for the number of failures. We also provide the operating characteristic (OC) values for the proposed sampling plans, and determine the minimum ratios of true mean life to specified mean life needed to satisfy a given producers risk. The role of symmetry in the TLGW distribution is highlighted in its balanced tail properties and shape characteristics, which influence the performance of the acceptance sampling plan. Finally, we illustrate the applicability of the proposed plan with real-world data. 2025 by the authors. -
A Gauss Hypergeometric-Type Model for Heavy-Tailed Survival Times in Biomedical Research
In this study, we introduced and analyzed the SlashLogLogistic (SlaLL) distribution, a novel statistical model developed by applying the slash methodology to loglogistic and beta distributions. The SlaLL distribution is particularly suited for modeling datasets characterized by heavy tails and extreme values, frequently encountered in survival time analyses. We derived the mathematical representation of the distribution involving Gauss hypergeometric and beta functions, explicitly established the probability density function, cumulative distribution function, hazard rate function, and reliability function, and provided clear definitions of its moments. Through comprehensive simulation studies, the accuracy and robustness of maximum likelihood and Bayesian methods for parameter estimation were validated. Comparative empirical analyses demonstrated the SlaLL distributions superior fitting performance over well-known slash-based models, emphasizing its practical utility in accurately capturing the complexities of real-world survival time data. 2025 by the authors. -
A comparative study of bayesian and classical methods for the weighted Lindley distribution under unified hybrid censoring with survival data applications
In survival analysis and reliability engineering, censoring schemes play a crucial role in efficient data collection and analysis. This study investigated the unified hybrid censoring scheme (UHCS), a versatile framework that integrates multiple censoring strategies, to evaluate the suitability of the Weighted Lindley (WL) distribution for modeling lifetime data. Maximum likelihood estimates (MLEs) and their corresponding asymptotic confidence intervals are derived for the parameters of the WL distribution. In the Bayesian framework, parameter estimation was performed under a squared error loss function. A detailed Monte Carlo simulation study was conducted to compare the performance of classical and Bayesian estimators across various sample sizes and censoring schemes. The simulation results revealed that Bayesian estimators consistently yielded lower mean squared errors (MSEs) than their classical counterparts, and the associated credible intervals were generally narrower than the frequentist confidence intervals. To demonstrate the practical applicability of the proposed methods, the analysis was applied to real-world survival datasets. The results highlighted the effectiveness of the WL distribution under UHCS, offering valuable insights for researchers and practitioners in reliability and survival analysis. 2025 the Author(s), licensee AIMS Press. -
A New Versatile Discrete Distribution for Censored Data: Frequentist and Bayesian Methods With Real-Life Applications
This study introduces a novel and highly flexible class of discrete probability distributions tailored to model the diverse monotonic failure-rate patterns frequently observed in stock-market data. The proposed distribution accommodates outliers effectively and serves as a discrete analogue of the exponential law, enabling analysts to derive robust and interpretable insights into market dynamics. Fundamental mathematical characteristics of the distributionsuch as the probability-generating function, mean, and varianceare thoroughly derived. The model is further extended to handle Type-II censored data, enhancing its applicability to real-world scenarios where incomplete observations are common. Parameter estimation is performed using both maximum-likelihood and Bayesian approaches, with a special focus on techniques suitable for censored samples. The performance and reliability of the estimators are examined through extensive simulation studies. To validate the practical utility of the model, it is applied to five real stock-market datasets obtained from Indiastat. The results demonstrate a superior empirical fit, affirming the models relevance in capturing the underlying patterns of financial time series. This distribution provides a valuable tool for analysts and researchers in the fields of financial statistics, risk modeling, and market behavior analysis. 2013 IEEE. -
A Discrete Kumaraswamy Marshall-Olkin Exponential Distribution
Finding new families of distributions has become a popular tool in statistical research. In this article, we introduce a new flexible four-parameter discrete model based on the Marshall-Olkin approach, namely, the discrete Kumaraswamy MarshallOlkin exponential distribution. The proposed distribution can be viewed as another generalization of the geometric distribution and enfolds some important distributions as special cases. Some properties of the new distribution are derived. The model parameters are estimated by the maximum likelihood method, with validation through a complete simulation study. The usefulness of the new model is illustrated via counttype real data sets. 2022. Journal of the Iranian Statistical Society. All Rights Reserved. -
AN ECONOMIC RELIABILITY TEST PLAN BASED ON TRUNCATED LIFE TESTS FOR MARSHALL-OLKIN POWER LOMAX DISTRIBUTION WITH APPLICATIONS
In every competitive enterprise, there has been a resurgence of interest in increasing the quality of products. In this paper, we create new acceptance sampling plans based on truncated life tests for the Marshall-Olkin power Lomax distribution. The minimum sample sizes needed to declare the specified mean life with respect to the newly developed sampling plans are obtained for different values of the model parameters. Besides, the operating characteristic function values, minimum ratios of the true value and the required value of the parameter with a given producer risk are discussed. Moreover, the results are illustrated using numerical examples, and a real data set is considered to illustrate the functioning of the recommended acceptance sampling plans. The result shows that the proposed plan is more adequate compared with other acceptance sampling plans available in the open literature. So, it can be used for industry applications. 2010 Mathematics Subject Classification. 60E05, 62E15, 62F10. 2022, Asia Pacific Academic. All rights reserved. -
On an extension of the two-parameter Lindley distribution
AIM: Lindley distribution has been widely studied in statistical literature because it accommodates several interesting properties. In lifetime data analysis contexts, Lindley distribution gives a good description over exponential distribution. It has been used for analysing copious real data sets, specifically in applications of modeling stress-strength reliability. This paper proposes a new generalized two-parameter Lindley distribution and provides a comprehensive description of its statistical properties such as order statistics, limiting distributions of order statistics, Information theory measures, etc. METHODS: We study shapes of the probability density and hazard rate functions, quantiles, moments, moment generating function, order statistic, limiting distributions of order statistics, information theory measures, and autoregressive models are among the key characteristics and properties discussed. The two-parameter Lindley distribution is then subjected to statistical analysis. The paper uses methods of maximum likelihood to estimate the parameters of the proposed distribution. The usefulness of the proposed distribution for modeling data is illustrated using a real data set by comparison with other generalizations of the exponential and Lindley distributions and is depicted graphically. RESULTS/FINDINGS: This paper presents relevant characteristics of the proposed distribution and applications. Based on this study, we found that the proposed model can be used quite effectively to analyzing lifetime data. CONCLUSIONS: In this article, we proffered a new customized Lindley distribution. The proposed distribution enfolds exponential and Lindley distributions as sub-models. Some properties of this distribution such as quantile function, moments, moment generating function, distributions of order statistics, limiting distributions of order statistics, entropy, and autoregressive time series models are studied. This distribution is found to be the most appropriate model to fit the carbon fibers data compared to other models. Consequently, we propose the MOTL distribution for sketching inscrutable lifetime data sets. 2023 DSR Publishers/The University of Jordan. -
Extended Slash Modified Lindley Distribution to Model Economic Variables Showing Asymmetry
This article introduces a novel probability distribution to model economic variables with high kurtosis and heavy tails showing a decreasing trend. From a mathematical viewpoint, it corresponds to the distribution of the ratio of two independent random variables, one with the modified Lindley distribution and another with the beta distribution. In some sense, it can be described as an extended three-parameter version of the Lindley distribution that has the ability to model data with high kurtosis. After presenting this distribution in more in-depth details, a comprehensive analysis is given, including its associated functions, moments, skewness, and kurtosis characteristics. Furthermore, a parametric estimation work is carried out. A simulation approach is used to validate the performance of the obtained estimates. The applicability of the proposed distribution is demonstrated by fitting real-world data into various socioeconomic scenarios. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
On the discrete weibull marshallolkin family of distributions: Properties, characterizations, and applications
In this article, we introduce a new flexible discrete family of distributions, which accommo-dates wide collection of monotone failure rates. A sub-model of geometric distribution or a discrete generalization of the exponential model is proposed as a special case of the derived family. Besides, we point out a comprehensive record of some of its mathematical properties. Two distinct estimation methods for parameters estimation and two different methods for constructing confidence intervals are explored for the proposed distribution. In addition, three extensive Monte Carlo simulations studies are conducted to assess the advantages between estimation methods. Finally, the utility of the new model is embellished by dint of two real datasets. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Reliability test plan for the marshall-olkin extended inverted kumaraswamy distribution
This paper mainly interested in studying the wider range behavior of the Marshall-Olkin extended inverted Kumaraswamy distribution. The parameters of model are estimated by various estimation methods. A reliability sampling plan is proposed which can save the test time in practical situations. Some tables are also provided for the new sampling plans so that this method can be used conveniently by practitioners. The developed test plan is applied to ordered failure times of software release to provide its importance in industrial applications. 2021 Gnedenko Forum. All right reserved. -
Lyrics of longing: Exploring the role of music in the lived experience of homesickness among college students
The study investigates the multifaceted role of music during homesickness among first-year college students in India. As compared to other mental health outcomes, homesickness is a relatively understudied phenomenon, yet noteworthy due to its direct association with depression and anxiety. Although empirical evidence about music highlights its therapeutic potential for managing stress and anxiety, few studies have explored its role in connection with homesickness. The data for this study were collected through semi-structured interviews with 10 students about their perception of using music during homesickness. Through interpretative phenomenological analysis, the emerging themes pointed to a mixed influence, highlighting the bittersweet nature of music during homesickness. While music validates feelings and boosts confidence and motivation, it also triggers restorative nostalgia and serves as an escape from confronting homesickness. Moreover, native songs fostered an appreciation for ones culture and helped students connect with their roots. The study contributes to understanding how music is a versatile tool for students dealing with homesickness, offering solace and potential challenges. It serves as a guide to future intervention studies that could explore musics long-term influences. Recognising the diverse ways students perceive and respond to music provides valuable insights for developing tailored interventions and support systems. The Author(s) 2024 -
Lyrics of longing: Exploring the role of music in the lived experience of homesickness among college students
The study investigates the multifaceted role of music during homesickness among first-year college students in India. As compared to other mental health outcomes, homesickness is a relatively understudied phenomenon, yet noteworthy due to its direct association with depression and anxiety. Although empirical evidence about music highlights its therapeutic potential for managing stress and anxiety, few studies have explored its role in connection with homesickness. The data for this study were collected through semi-structured interviews with 10 students about their perception of using music during homesickness. Through interpretative phenomenological analysis, the emerging themes pointed to a mixed influence, highlighting the bittersweet nature of music during homesickness. While music validates feelings and boosts confidence and motivation, it also triggers restorative nostalgia and serves as an escape from confronting homesickness. Moreover, native songs fostered an appreciation for ones culture and helped students connect with their roots. The study contributes to understanding how music is a versatile tool for students dealing with homesickness, offering solace and potential challenges. It serves as a guide to future intervention studies that could explore musics long-term influences. Recognising the diverse ways students perceive and respond to music provides valuable insights for developing tailored interventions and support systems. The Author(s) 2024. -
Stable copper nanoparticles as potential antibacterial agent against aquaculture pathogens and human fibroblast cell viability
The developments of green nanotechnology are generating interest of researchers towards synthesis of copper nanoparticles due to their increasing application towards the biomedical field. The utilization of phytochemicals in plant extracts have become a valuable trend in the synthesis of nanoparticles as they possess dual nature of reducing and stabilizing agents. In this work a simple and rapid biosynthesis route for producing stable fenugreek copper nanoparticles (FCuNPs) using Trigonella foenum-graecum is demonstrated and assessed its antibacterial activity against gram negative Vibrio species. The characterization of synthesized FCuNPs was carried out using UVvis spectrophotometer and the SPR of FCuNPs is observed at 350 nm. TEM, HRTEM SAED analysis was done to evaluate the morphology and size of FCuNPs. FTIR spectra of both the plant extract and FCuNPs were recorded in order to study the interaction of phytochemicals with FCuNPs. The antibacterial activity of biosynthesized FCuNPs was tested against V. vulnificus, V. harveyi and V. parahaemolyticus using agar well diffusion technique. Since this method of synthesizing copper nanoparticles does not involve any harmful chemicals, the FCuNPs produced are more biocompatible and were used to evaluate human skin fibroblast cell line by Alamar Blue reduction assay. The outcomes of this report will surely provide a new path in the field of nanotechnology and nano medicine where there is a significant need of antibacterial and cell viability studies. Hence, FCuNPs can be powerful therapeutic materials in numerous biomedical applications, which are to be discovered in the near prospective. 2021 Elsevier Ltd -
Market-Based Strategies for Enhancing Grid Resilience under High Renewable Penetration
The rise in penetration of renewable energy sources (RES), especially wind and solar, presents important challenges to power system operation and electricity markets. Renewables cut emissions and are cheaper in the long run but are intermittent, creating volatility, uncertainty about revenues, and reliability risks. This study analyses the performance of markets in delivering resilience to the grid given high levels of renewables. A grid simulation over 24 hours was then developed in order to study four aspects of the problem; (i) Stability of revenues for the generators, (ii) Reduction in the cost of imbalances as a result of flexibility, (iii) Reliability in terms of Loss of Load Expectation (LOLE), and Energy Not Served (ENS), and (iv) the impact on costs for consumers. Findings show that flexibility participation reduces costs incurred due to imbalance by ? 60%, and resilience mechanisms reduce the effective tariff faced by consumers from 32/kWh to 6.8/kWh. Reliability indices also improve greatly when flexibility and ancillary services markets are introduced. In addition, a Particle Swarm Optimization (PSO) model was applied to find the optimum levels of renewable penetration and flexibility that result in the least total system cost, which correspond to approximately 0.7 for flexibility and approximately 55-65% for renewables. These results point to the economic and technical need for reengineered electricity markets that incorporate flexibility products, ancillary services, and resilience incentives. This dissertation provides a complete methodology of simulation, reliability metrics, and optimization to inform policy makers, system operators, and investors of resilient renewable dominated grids. 2025 IEEE. -
A Novel Hybrid Ensemble Architecture for Stroke Risk Prediction Using Healthcare Data
Stroke is the reason for an alarming number of disabilities worldwide, further emphasising the critical need for early and accurate prediction of risks to inform clinical management. This paper presents a novel hybrid ensemble architecture that leverages the superiority of multiple machine learning models for stroke health risk prediction using health data. In this novel hybridisation, decision tree classifiers belonging to the Random Forest and XGBoost families are effectively combined with support vector machines and a shallow neural network within a Stacked ensemble strategy that uses a hard vote technique. To improve model generalizability and avoid overfitting, feature selection and dimensionality reduction methods like Recursive Feature Elimination (RFE) and Principal Component Analysis (PCA) have been included expertly without compromising performance. After extensive training and testing on a real-world health repository covering a broad range of demographic, lifestyle, and clinical features, the model obtained an outstanding F1-score of 0.9427 and an exemplary ROC-AUC value of 0.9872, much higher than the performance of the individual models. Statistical significance was assessed using the Friedman and Wilcoxon signed-rank test. The model is a strong candidate for incorporation into clinical decision support systems and is fully deployable and EHR-compatible. The Author(s) 2026.