228 research outputs found
sj-docx-1-han-10.1177_15589447221141482 – Supplemental material for Pain Control and Satisfaction With Peripheral Nerve Blocks for Upper Extremity Surgery
No full textSupplemental material, sj-docx-1-han-10.1177_15589447221141482 for Pain Control and Satisfaction With Peripheral Nerve Blocks for Upper Extremity Surgery by Caroline M. Wu, Cyril S. Gary, Kristin E. Karim, Kavya K. Sanghavi, Michael S. Murphy, J. Todd Hobelmann and Aviram M. Giladi in HAND</p
Buddhaghosa
No full textThis entriy is about Buddhaghosa or Buddhaghosacarya, a poet of unknown date known for being the author of the Padyacudamani (The Crest-Jewel of Verses), a Sanskrit mahakavya (great kavya) or sargabandha (canto composition) poem
Bivariate Step-Stress Accelerated Life Tests for the Kavya–Manoharan Exponentiated Weibull Model under Progressive Censoring with Applications
No full textA new three-parameter survival model is proposed using the Kavya–Manoharan (KM) transformation family and the exponentiated Weibull (EW) distribution. The shapes of the pdf for the new model can be asymmetric and symmetric shapes, such as unimodal, decreasing, right-skewed and symmetric. In addition, the shapes of the hrf for the suggested model can be increasing, decreasing, constant and J-shaped. Statistical properties are obtained: quantile function, mode, moments, incomplete moments, residual life time, reversed residual life time, probability weighted moments, order statistics and entropy. We discuss the maximum likelihood estimation for the model. The relevance and flexibility of the model are demonstrated using two real datasets. The distribution is very flexible, and it outperforms many known distributions, such as the three-parameter exponentiated Weibull, the modified Weibull model, the Kavya–Manoharan Weibull, the extended Weibull, the odd Weibull inverse Topp–Leone and the extended odd Weibull inverse Nadarajah–Haghigh model. A bivariate step-stress accelerated life test based on progressive type-I censoring (PTIC) using the model is presented. This pattern is noticed when a particular number of lifetime test units are routinely eliminated from the test at the conclusion of each post-test period of time. Minimizing the asymptotic variance of the MLE of the log of the scale parameter at design stress under PTIC yields an expression for the ideal test plan under PTIC
Exploring New Horizons: Advancing Data Analysis in Kidney Patient Infection Rates and UEFA Champions League Scores Using Bivariate Kavya–Manoharan Transformation Family of Distributions
No full textIn survival analyses, infections at the catheter insertion site among kidney patients using portable dialysis machines pose a significant concern. Understanding the bivariate infection recurrence process is crucial for healthcare professionals to make informed decisions regarding infection management protocols. This knowledge enables the optimization of treatment strategies, reduction in complications associated with infection recurrence and improvement of patient outcomes. By analyzing the bivariate infection recurrence process in kidney patients undergoing portable dialysis, it becomes possible to predict the probability, timing, risk factors and treatment outcomes of infection recurrences. This information aids in identifying the likelihood of future infections, recognizing high-risk patients in need of close monitoring, and guiding the selection of appropriate treatment approaches. Limited bivariate distribution functions pose challenges in jointly modeling inter-correlated time between recurrences with different univariate marginal distributions. To address this, a Copula-based methodology is presented in this study. The methodology introduces the Kavya–Manoharan transformation family as the lifetime model for experimental units. The new bivariate models accurately measure dependence, demonstrate significant properties, and include special sub-models that leverage exponential, Weibull, and Pareto distributions as baseline distributions. Point and interval estimation techniques, such as maximum likelihood and Bayesian methods, where Bayesian estimation outperforms maximum likelihood estimation, are employed, and bootstrap confidence intervals are calculated. Numerical analysis is performed using the Markov chain Monte Carlo method. The proposed methodology’s applicability is demonstrated through the analysis of two real-world data-sets. The first data-set, focusing on infection and recurrence time in kidney patients, indicates that the Farlie–Gumbel–Morgenstern bivariate Kavya–Manoharan–Weibull (FGMBKM-W) distribution is the best bivariate model to fit the kidney infection data-set. The second data-set, specifically that related to UEFA Champions League Scores, reveals that the Clayton Kavya–Manoharan–Weibull (CBKM-W) distribution is the most suitable bivariate model for fitting the UEFA Champions League Scores. This analysis involves examining the time elapsed since the first goal kicks and the home team’s initial goal
Classical and Bayesian Inference for the Kavya–Manoharan Generalized Exponential Distribution under Generalized Progressively Hybrid Censored Data
No full textThis manuscript focuses on the statistical inference of the Kavya–Manoharan generalized exponential distribution under the generalized type-I progressive hybrid censoring sample (GTI-PHCS). Different classical approaches of estimation, such as maximum likelihood, the maximum product of spacing, least squares (LS), weighted LS, and percentiles under GTI-PHCS, are investigated. Based on the squared error and linear exponential loss functions, the Bayes estimates for the unknown parameters utilizing separate gamma priors under GTI-PHCS have been derived. Point and interval estimates of unknown parameters are developed. We carry out a simulation using the Monte Carlo algorithm to show the performance of the inferential procedures. Finally, real-world data collection is examined for illustration purposes
AMPA Receptor Surface Expression Is Regulated by S-Nitrosylation of Thorase and Transnitrosylation of NSF
Get PDFUmanah et al. show that the S-nitrosylation of Thorase and the transnitrosylation of NSF are responsible for NMDAR-activated trafficking of AMPARs underlying synaptic plasticity. © 2020 The Author(s)
The regulation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) trafficking affects multiple brain functions, such as learning and memory. We have previously shown that Thorase plays an important role in the internalization of AMPARs from the synaptic membrane. Here, we show that N-methyl-D-aspartate receptor (NMDAR) activation leads to increased S-nitrosylation of Thorase and N-ethylmaleimide-sensitive factor (NSF). S-nitrosylation of Thorase stabilizes Thorase-AMPAR complexes and enhances the internalization of AMPAR and interaction with protein-interacting C kinase 1 (PICK1). S-nitrosylated NSF is dependent on the S-nitrosylation of Thorase via trans-nitrosylation, which modulates the surface insertion of AMPARs. In the presence of the S-nitrosylation-deficient C137L Thorase mutant, AMPAR trafficking, long-term potentiation, and long-term depression are impaired. Overall, our data suggest that both S-nitrosylation and interactions of Thorase and NSF/PICK1 are required to modulate AMPAR-mediated synaptic plasticity. This study provides critical information that elucidates the mechanism underlying Thorase and NSF-mediated trafficking of AMPAR complexes. © 2020 The Author(s)1
Statistical Inference for the Kavya–Manoharan Kumaraswamy Model under Ranked Set Sampling with Applications
No full textIn this article, we introduce a new extension of the Kumaraswamy (Ku) model, which is called the Kavya Manoharan Kumaraswamy (KMKu) model. The shape forms of the pdf for the KMKu model for various values of parameters are similar to the Ku model. It can be asymmetric, such as bathtub, unimodal, increasing and decreasing. In addition, the shape forms of the hrf for the KMKu model can be bathtub, U-shaped, J-shaped and increasing. Several statistical and computational properties were computed. Four different measures of entropy were studied. The maximum likelihood approach was employed to estimate the parameters for the KMKu model under simple and ranked set sampling. A simulation experiment was conducted in order to calculate the model parameters of the KMKu model utilizing simple and ranked set sampling and show the efficiency of the ranked set sampling more than the simple random sampling. The KMKu has more flexibility than the Ku model and other well-known models, and we proved this using three real-world data sets
Improving Quality of Lead Data of Customer Relationship Management in M-Commerce
Get PDFAbstract: In the present growing trend of mobile computing, technologies, applications mainly focus on mobile ecommerce (m-commerce) and the mobile Web. As the mobile commerce market grows, Customer relationship management (CRM) is one of the major applications that incorporates the present marketing standard of relationship management (RM) and supports in acquisition, understanding requirements, and maintaining long-term relationships with customers. Expanding the CRM applications to mobile devices is increasingly becoming a major goal for organizations to optimize their workforce. To obtain a successful and desired outcome, quality of acquired data has a major impact on the organization's productivity. Hence the quality of data constitute the basis for major decisions of organization's operational and strategic levels which intern leads to positive growth of organizations. In order to tackle the above issue, we have proposed a novel quality model for customer lead data. Some of the activities are defined to analyse the performance of system with respect to time, data quality, reliability. This framework needs a feasible implementation module in the near future for improving quality of CRM lead data in m-commerce
Design and Fabrication Of Continuous Peeling Machine for Bananas
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Buddhaghosa’s Padyacudamani: A Medieval Mahakavya on the Life of the Buddha
No full textThe Padyacudamani is a Sanskrit mahakavya narrating the life and feats of the “historical” Buddha. Its dating and place of origin are uncertain, and nothing is known about its author, Buddhaghosa (merely a namesake of the celebrated Buddhist scholar). The one certain thing about the Padyacudamani is its considerable poetic value, highly praised by A.K. Warder in his Indian Kavya Literature. Despite such authoritative commendation and the several intriguing peculiarities that characterize the poem, it has received but scant attention in contemporary scholarly research. This paper aims to provide an overview of the Padyacudamani and of its most interesting features
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