Search

There are two begomoviruses, tomato leaf curl New Delhi virus (ToLCNDV) and bitter gourd yellow mosaic virus (BgYMV) infecting bitter gourd in India. An extensive survey conducted from 2019 to 2022 clearly established that infection by ToLCNDV is more predominant (92.43%) than BgYMV (44%). The ToLCNDV isolates infecting bitter gourd shared only 88% identity in the DNA-A component with other ToLCNDV isolates and were found to be a distinct variant. The predicted amino acid sequence of the viral proteins, replication initiation protein, coat protein, and the symptom determinant protein in the study isolates are markedly different. Especially the RCR motif I and RCR motif III are different from other geminiviruses. Infectivity of cloned components of one of the isolates ToLCNDV-BG NP was demonstrated in bitter gourd. Recombination analysis clearly revealed that the study isolates are recombinants with the major parent predicted as squash leaf curl Yunnan virus (GenBank Accession Number: MK064241) and the minor parent as ToLCNDV from Pakistan (GenBank Accession Number: AM747291). Due to distinct genomic features and less than 90% identity with the majority of ToLCNDV isolates, the study isolates deserve to be raised to the status of a distinct strain, designated as ToLCNDV-BG. [ABSTRACT FROM AUTHOR]

Background: The rising demand for food production along with the concerns regarding the injudicious use of chemicals in pest management has paved way for the alternatives that could promise sustainable pest management. Bacillus thuringiensis Berliner (Bt), a soil bacterium, is a potential biopesticide with its ability to produce crystal toxins that are insecticidal in nature. Main body: This article provides an insight into the diverse Bt toxins and their applications as biopesticides in pest management. The selective action of Bt towards target organism is based on its specific interactions with the insect gut receptors. The significance of Bt in the management of lepidopteran, coleopteran, hemipteran, dipteran and nematode pests of crops and livestock through its mode of action is extensively reviewed. Conclusion: Besides being a promising pest control option, the challenges faced through resistance development, variation in susceptibility across species and non-target effects of Bt are also discussed. Proactive approaches and multiple modes of action can mitigate this issue. [ABSTRACT FROM AUTHOR]

In this paper, we introduce weighted fractional generalized cumulative past entropy of a nonnegative absolutely continuous random variable. Various properties of the proposed weighted fractional measure are studied, including some bounds and stochastic orders. A connection between the proposed measure and the left-sided Riemann-Liouville fractional integral is established. Further, the proposed measure is studied for the proportional reversed hazard rate model. Next, a nonparametric estimator of the weighted fractional generalized cumulative past entropy is proposed based on empirical distribution function. Various examples with a real-life data set are considered for illustrative purpose. A validation of the proposed measure is provided using the logistic map and some applications are also discussed. Weighted fractional generalized cumulative paired entropy is proposed and some of its properties are explored. Finally, large-sample properties of the proposed empirical estimator are studied. [ABSTRACT FROM AUTHOR]

In Takagi and Sugeno (T-S) fuzzy fault tree analysis (FFTA), the construction of T-S fuzzy gates relies too much on expert experience, which will result in inevitable subjective errors. In order to overcome this disadvantage, a new method was proposed in which the construction of T-S gates no longer relies solely on historical data and expert experience but is also determined by the importance of the basic events to the top event. In the proposed method, fault degrees were described as fuzzy numbers; fault probabilities were described as fuzzy possibilities. The importance index of basic events can be solved through the analysis of the fuzzy fault tree model by Monte Carlo (MC) simulation. The proposed method is suitable for systems where exact information on the fault probabilities of the components and the magnitude of failure and effect on the system are not available. The concept and calculation method of T-S probability importance was presented. Finally, the proposed method is applied to analyze the reliability of the NC turret seal subsystem, the accuracy of the method is verified by comparing with the methods based on traditional FFTA and T-S FFTA, and the weak points of the system are obtained by importance analysis, which will provide data for system fault diagnosis and preventive maintenance. [ABSTRACT FROM AUTHOR]

Conditional specification of distributions is a developing area with several applications. In the finite discrete case, a variety of compatible conditions can be derived. In this paper, we revisit a rank–based criterion for identifying compatible distributions corresponding to complete conditional specification, including the case with zeros under the finite discrete set up. Based on this, we primarily focus on the compatibility of two conditionals (under the finite discrete set-up) in which incomplete specification on either or both the conditional matrices are present. Compatibility in the general case are also briefly discussed. The proposed methods are finally illustrated with several examples. [ABSTRACT FROM AUTHOR]

In this paper, the general proportional mean past lifetime frailty model is considered, from which the unconditional cumulative distribution and density functions of the lifetime variable are derived. Dependency between the two variables are studied. Stochastic comparisons are made through which it is shown that some well-known stochastic orderings between two frailty variables carry over to the corresponding lifetime variables. The effects of baseline variable and the frailty variable on the proposed frailty model are studied. The relative mean past lifetime ordering is introduced and some relative ordering between two lifetime random variables with different frailty variables are studied. Also a simulation study is given to illustrate some results. [ABSTRACT FROM AUTHOR]

We obtain simple non-parametric estimators of Gini-based covariance, correlation and regression coefficients. We then establish the consistency and asymptotic normality of the proposed estimators. We provide an explicit formula for finding the asymptotic variance of the estimators. We also discuss jackknifed versions of the proposed estimators for reducing the bias of the estimators in case of small sample sizes. Finally, we evaluate the finite-sample performance of these estimators through on Monte Carlo simulations from a bivariate Pareto distribution. [ABSTRACT FROM AUTHOR]

The non-central Wishart and inverted Wishart distributions are studied in this work under elliptical models; some distributional results are based on some generalizations of the well-known Kummer relations, which leds us to determine that some moments have a polynomial representation. Then the non-central and "studentized Wishart" distributions are derived in a general setting. After some generalizations, including the so called non-central generalized inverted Wishart distribution, the classical results based on Gaussian models are derived here as corollaries. [ABSTRACT FROM AUTHOR]

It is well known that inference for the generalized Pareto distribution (GPD) is a difficult problem since the GPD violates the classical regularity conditions in the maximum likelihood method. For parameter estimation, most existing methods perform satisfactorily only in the limited range of parameters. Furthermore, the interval estimation and hypothesis tests have not been studied well in the literature. In this article, we develop a novel framework for inference for the GPD, which works successfully for all values of shape parameter k. Specifically, we propose a new method of parameter estimation and derive some asymptotic properties. Based on the asymptotic properties, we then develop new confidence intervals and hypothesis tests for the GPD. The numerical results are provided to show that the proposed inferential procedures perform well for all choices of k. [ABSTRACT FROM AUTHOR]

Skew-normal/independent distributions provide an attractive class of asymmetric heavy-tailed distributions to the usual symmetric normal distribution. We use this class of distributions here to derive a robust generalization of sinh-normal distributions (Rieck in Statistical analysis for the Birnbaum–Saunders fatigue life distribution, 1989), we then propose robust nonlinear regression models, generalizing the Birnbaum–Saunders regression models proposed by Rieck and Nedelman (Technometrics 33:51–60, 1991) that have been studied extensively. The proposed regression models have a nice hierarchical representation that facilitates easy implementation of an EM algorithm for the maximum likelihood estimation of model parameters and provide a robust alternative to estimation of parameters. Simulation studies as well as applications to a real dataset are presented to illustrate the usefulness of the proposed model as well as all the inferential methods developed here. [ABSTRACT FROM AUTHOR]

Mechanisms underlying anxiety disorders remain elusive despite the discovery of several associated genes. We constructed the protein–protein interaction networks (interactomes) of six anxiety disorders and noted enrichment for striatal expression among common genes in the interactomes. Five of these interactomes shared distinctive overlaps with the interactomes of genes that were differentially expressed in two striatal compartments (striosomes and matrix). Generalized anxiety disorder and social anxiety disorder interactomes showed exclusive and statistically significant overlaps with the striosome and matrix interactomes, respectively. Systematic gene expression analysis with the anxiety disorder interactomes constrained to contain only those genes that were shared with striatal compartment interactomes revealed a bifurcation among the disorders, which was influenced by the anterior cingulate cortex, nucleus accumbens, amygdala and hippocampus, and the dopaminergic signaling pathway. Our results indicate that the functionally distinct striatal pathways constituted by the striosome and the matrix may influence the etiological differentiation of various anxiety disorders. [ABSTRACT FROM AUTHOR]

In actuarial science, it is often of interest to compare stochastically extreme claim amounts from heterogeneous portfolios. In this regard, in the present work, we compare the smallest order statistics arising from two heterogeneous portfolios in the sense of the usual stochastic, hazard rate, reversed hazard rate and likelihood ratio orderings. We also consider the multiple-outlier model and obtain some ordering results. It is assumed that the portfolios belong to the general exponentiated location-scale model. The results obtained here are based on vector majorization of parameters and multivariate chain majorization with heterogeneity in different parameters. For the purpose of illustration, the derived results are applied to some well known distributions. Various examples and counterexamples are also provided. Finally, a simulation study is conducted to validate some of the results established here. [ABSTRACT FROM AUTHOR]

Health monitoring of an aero-engine assumes importance in the light of primary requirements of flight safety and reliability. This paper proposes a novel, simple method for monitoring aircraft engine health using Whale Optimization Algorithm based Artificial Neural Network (WOANN) technique, for analyzing the data downloaded from the health and usage monitoring system (HUMS) of a military aircraft. The actual engine data recorded during 47 different flights of eight different engines (of the same type) have been considered in this work. Thirteen engine parameters have been used to determine and monitor the health of the engine. The efficiency of the WOANN technique for engine health monitoring, is compared with that of three other common machine learning algorithms: Probabilistic based Neural Network (PNN), K-Nearest Neighbour (KNN), and Back propagation based Artificial Neural Network (BPANN). The results show that WOANN algorithm classifies and predicts engine health far more accurately as compared to PNN, KNN and BPANN. The values obtained for the metrics of Accuracy, Error, False Positive Rate, F1 score, Mathews Correlation Coefficient, Specificity, Kappa coefficient are found to be the best for WOANN algorithm. The WOANN achieved overall prediction accuracy of 95%, thus presenting itself as a very useful tool for day-to-day monitoring of aircraft engine health using the data downloaded from the aircraft's HUMS. [ABSTRACT FROM AUTHOR]

Here, we describe taxonomical composition, as well as seasonal and diel dynamics of airborne microbial communities in West Siberia. A total of 78 airborne biomass samples from 39 time intervals were analysed, within a temperature range of 48 °C (26 °C to − 22 °C). We observed a 5–170-fold decrease in DNA yield extracted from the airborne biomass in winter compared to summer, nevertheless, yielding sufficient material for metagenomic analysis. The airborne microbial communities included Actinobacteria and Proteobacteria, Ascomycota and Basidiomycota fungi as major components, as well as some Streptophyta plants. In summer, bacterial and fungal plant pathogens, and wood-rotting saprophytes were predominant. In winter, Ascomycota moulds and cold-related or stress environment bacterial species were enriched, while the fraction of wood-rotting and mushroom-forming Basidiomycota fungi was largely reduced. As recently reported for the tropical climate, the airborne microbial communities performed a diel cycle in summer, however, in winter diel dynamics were not observed. [ABSTRACT FROM AUTHOR]

Bivariate records have many application in different fields such as hydrology, economy, finance and weather forecasting; see, for example, the works of Bayramoglu (Metrika 79:725–747, 2016) and Kemalbay and Bayramoglu (Turk J Math 43:1474–1491, 2019). It should be noted that there are various definitions of bivariate records. In this paper, we discuss the concept of north-east bivariate records, originally proposed by Arnold et al. (Records, Wiley, New York, 1998). Even though the concept was introduced more than two decades ago, no serious research has been made on it due to its complexity. In the present paper, we obtain distributional and limit results for the north-east bivariate records. We also discuss generation techniques for these bivariate records. [ABSTRACT FROM AUTHOR]

An accelerated life test (ALT) is commonly used in reliability studies of high quality products. A step-stress experiment is one such ALT that is often used in practice. In this paper, we develop exact inference based on likelihood-ratio test for a simple step-stress model with exponential lifetimes under Type-II censoring. We consider both unrestricted and order-restricted maximum likelihood estimators (MLEs) for this purpose. We also derive the exact power function of this test, which we then use for designing an optimal step-stress testing experiment. By using a similar approach, we extend these results to other forms of censoring. Monte Carlo simulations are then carried out to evaluate the performance of the inferential methods developed here. Finally, an illustrative example is presented for demonstrating all the inferential results. [ABSTRACT FROM AUTHOR]

The optimal design of a k-level step-stress accelerated life-testing (ALT) experiment with unequal duration steps under Type-I hybrid censoring scheme for a general log-location-scale lifetime distribution is discussed here. Censoring is allowed only at the change-stress point in the final stage. Based on the cumulative exposure model, the determination of the optimal choice for Weibull, lognormal and log-logistic lifetime distributions are considered by minimization of the asymptotic variance of the maximum likelihood estimate of the pth percentile of the lifetime at the normal operating condition. Numerical results show that for these lifetime distributions, the optimal k-step-stress ALT design with unequal duration steps under Type-I hybrid censoring scheme reduces just to a 2-step-stress ALT design. [ABSTRACT FROM AUTHOR]

Due to its flexibility, gamma distribution is commonly used for lifetime data analysis in reliability and survival studies, and especially in one-shot device testing data. In the study of such data, inducing more failures by accelerated life tests is a common practice, to obtain more lifetime information within a relatively short period of time. In this paper, we develop weighted minimum density power divergence estimators, as a natural extension of the classical maximum likelihood estimator, in the analysis of one-shot device testing data, under accelerated life tests based on gamma lifetime distribution. Wald-type test statistics, based on these estimators, are also developed. Through a Monte Carlo simulation study, the suggested estimators and tests are shown to be robust alternatives to the maximum likelihood estimators and the classical Wald tests based on them. Finally, these procedures are applied to a mice tumor toxicological data for illustrative purpose. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the existence and uniqueness of the maximum likelihood estimates (MLEs) of the parameters of Laplace Birnbaum–Saunders distribution based on Type-I, Type-II and hybrid censored samples. We first derive the relationship between the MLEs of the two parameters and then discuss the monotonicity property of the profile likelihood function. Numerical iterative procedure is then discussed for determining the MLEs of the parameters. Finally, for illustrative purpose, we analyze one real data from the literature and present some graphical illustrations of the approach. [ABSTRACT FROM AUTHOR]

In this paper, based on combined Type-II censored samples, an exponential form for the underlaying distributions is considered for estimating the unknown parameters using the maximum likelihood and Bayesian methods. Three loss functions are used to derive the Bayesian estimators. Also, the Bayesian prediction for the order statistics from a future sample is calculated. Moreover, the results of the exponential and Pareto distributions are presented as illustrative examples. Finally, for illustrating all the inferential methods discussed in this paper, Monte Carlo simulation and data analysis for the exponential distribution are presented. [ABSTRACT FROM AUTHOR]

For two independent sequences of independent and identically distributed exponential random variables with different scale parameters based on observed lower-joint records, inter-record times, and record indicators. The conditional maximum likelihood estimators are considered as well as various interval estimators. A simulation method is given to efficiently generate these lower-joint records which is utilized in a Monte Carlo study of the coverage probabilities of the interval estimators. [ABSTRACT FROM AUTHOR]

In this paper, upon using the known expressions for the Best Linear Unbiased Estimators (BLUEs) of the location and scale parameters of the Laplace distribution based on a progressively Type-II right censored sample, we derive the exact moment generating function (MGF) of the linear combination of standard Laplace order statistics. By using this MGF, we obtain the exact density function of the linear combination. This density function is then utilized to develop exact marginal confidence intervals (CIs) for the location and scale parameters through some pivotal quantities. Next, we derive the exact density of the BLUEs-based quantile estimator and use it to develop exact CIs for the population quantile. A brief mention is made about the reliability and cumulative hazard functions and as to how exact CIs can be constructed for these functions based on BLUEs. A Monte Carlo simulation study is then carried out to evaluate the performance of the developed inferential results. Finally, an example is presented to illustrate the point and interval estimation methods developed here. [ABSTRACT FROM AUTHOR]

In this paper, we consider a competitive scenario and assume the initial number of competing causes to undergo a destruction after an initial treatment. This brings in a more realistic and practical interpretation of the biological mechanism of the occurrence of tumor since what is recorded is only from the undamaged portion of the original number of competing causes. Instead of assuming any particular distribution for the competing cause, we assume the competing cause to follow a Conway–Maxwell Poisson distribution which brings in flexibility as it can handle both over-dispersion and under-dispersion that we usually encounter in count data. Under this setup and assuming a Weibull distribution to model the time-to-event, we develop the expectation maximization algorithm for such a flexible destructive cure rate model. An extensive simulation study is carried out to demonstrate the performance of the proposed estimation method. Finally, a melanoma data is analyzed for illustrative purpose. [ABSTRACT FROM AUTHOR]

Let $$X_{1},\ldots , X_{n}$$ be lifetimes of components with independent non-negative generalized Birnbaum-Saunders random variables with shape parameters $$\alpha _{i}$$ and scale parameters $$\beta _{i},~ i=1,\ldots ,n$$ , and $$I_{p_{1}},\ldots , I_{p_{n}}$$ be independent Bernoulli random variables, independent of $$X_{i}$$ 's, with $$E(I_{p_{i}})=p_{i},~i=1,\ldots ,n$$ . These are associated with random shocks on $$X_{i}$$ 's. Then, $$Y_{i}=I_{p_{i}}X_{i}, ~i=1,\ldots ,n,$$ correspond to the lifetimes when the random shock does not impact the components and zero when it does. In this paper, we discuss stochastic comparisons of the smallest order statistic arising from such random variables $$Y_{i},~i=1,\ldots ,n$$ . When the matrix of parameters $$(h({\varvec{p}}), {\varvec{\beta }}^{\frac{1}{\nu }})$$ or $$(h({\varvec{p}}), {\varvec{\frac{1}{\alpha }}})$$ changes to another matrix of parameters in a certain mathematical sense, we study the usual stochastic order of the smallest order statistic in such a setup. Finally, we apply the established results to two special cases: classical Birnbaum-Saunders and logistic Birnbaum-Saunders distributions. [ABSTRACT FROM AUTHOR]

In this article, we consider the problem of predicting survival times of units from the exponential distribution which are censored under a simple step-stress testing experiment. Progressive Type-II censoring are considered for the form of censoring. Two kinds of predictors-the maximum likelihood predictors (MLP) and the conditional median predictors (CMP)-are derived. Some numerical examples are presented to illustrate the prediction methods developed here. Using simulation studies, prediction intervals are generated for these examples. We then compare the MLP and the CMP with respect to mean squared prediction error and the prediction interval. [ABSTRACT FROM AUTHOR]

In this paper, we propose three simple closed form estimators for a class of log-symmetric distributions on $${\mathbb {R}}^{+}$$ . The proposed methods make use of some key properties of this class of distributions. We derive the asymptotic distributions of these estimators. The performance of the proposed estimators are then compared with those of the maximum likelihood estimators through Monte Carlo simulations. Finally, some illustrative examples are presented to illustrate the methods of estimation developed here. [ABSTRACT FROM AUTHOR]

In this work, we propose several different confidence interval methods based on ranked-set samples. First, we develop bootstrap bias-corrected and accelerated method for constructing confidence intervals based on ranked-set samples. Usually, for this method, the accelerated constant is computed by employing jackknife method. Here, we derive an analytical expression for the accelerated constant, which results in reducing the computational burden of this bias-corrected and accelerated bootstrap method. The other proposed confidence interval approaches are based on a monotone transformation along with normal approximation. We also study the asymptotic properties of the proposed methods. The performances of these methods are then compared with those of the conventional methods. Through this empirical study, it is shown that the proposed confidence intervals can be successfully applied in practice. The usefulness of the proposed methods is further illustrated by analyzing a real-life data on shrubs. [ABSTRACT FROM AUTHOR]

In this paper, a weak version of the joint reversed hazard rate order, useful for stochastic comparison of non-independent random variables, has been defined and discussed. In particular, some relationships between the joint weak reversed hazard rate order and the usual reversed hazard rate order are established when the underlying copulas are symmetric. [ABSTRACT FROM AUTHOR]

In start-up demonstration testing, the performance of the unit on successive start-ups is taken into account and several different types of decision criteria (most of them are inspired by the theory of runs and scans) for accepting or rejecting the unit have been introduced. Although the use of a start-up demonstration test assumes the existence of units of lower quality, when the estimation of the respective probability comes up, there is still much work to be done. Therefore, in this paper, we study binary start-up demonstration tests, assuming that we have at hand two different types of units with potentially different probabilities of successful start-up. In this case, the waiting time distributions are expressed as two-component mixture models and their identifiability is discussed. Finally, an estimation method based on the EM algorithm for the model parameters is described and some numerical examples are presented to illustrate the methods developed here. [ABSTRACT FROM AUTHOR]

In this paper, we develop the steps of the expectation maximization algorithm (EM algorithm) for the determination of the maximum likelihood estimates (MLEs) of the parameters of the destructive exponentially weighted Poisson cure rate model in which the lifetimes are assumed to be Weibull. This model is more flexible than the promotion time cure rate model as it provides an interesting and realistic interpretation of the biological mechanism of the occurrence of an event of interest by including a destructive process of the initial number of causes in a competitive scenario. The standard errors of the MLEs are obtained by inverting the observed information matrix. An extensive Monte Carlo simulation study is carried out to evaluate the performance of the developed method of estimation. Finally, a known melanoma data are analyzed to illustrate the method of inference developed here. With these data, a comparison is also made with the scenario when the destructive mechanism is not included in the analysis. [ABSTRACT FROM AUTHOR]

In this paper, we develop exact nonparametric inference for quantiles of the population based on the sequence of k -record values, conditionally on the corresponding observed inter- k -record times, to increase the precision of inference, as compared to nonparametric unconditional procedures. The effect of including the additional information contained in the inter- k -record times is evaluated by means of an empirical study. The conditional tolerance and prediction intervals for a future k -record from another independent sequence are obtained as well. A real data set is also used to illustrate the inferential results developed here. [ABSTRACT FROM AUTHOR]

In this paper, we propose two moment-type estimation methods for the parameters of the generalized bivariate Birnbaum-Saunders distribution by taking advantage of some properties of the distribution. The proposed moment-type estimators are easy to compute and always exist uniquely. We derive the asymptotic distributions of these estimators and carry out a simulation study to evaluate the performance of all these estimators. The probability coverages of confidence intervals are also discussed. Finally, two examples are used to illustrate the proposed methods. [ABSTRACT FROM AUTHOR]

The univariate logistic distribution and its properties and applications have been studied quite extensively in the literature. Some generalizations as well as multivariate extensions of it have also been proposed for greater flexibility in modeling univariate and multivariate data. In this paper, we construct three different types of generalized bivariate logistic type distributions through conditional specification, and discuss some of their properties. Finally, we use a data set to fit the proposed models for the purpose of illustration. [ABSTRACT FROM AUTHOR]

Empirical phi-divergence test statistics have demostrated to be a useful technique for the simple null hypothesis to improve the finite sample behavior of the classical likelihood ratio test statistic, as well as for model misspecification problems, in both cases for the one population problem. This paper introduces this methodology for two-sample problems. A simulation study illustrates situations in which the new test statistics become a competitive tool with respect to the classical z test and the likelihood ratio test statistic. [ABSTRACT FROM AUTHOR]

Cure rate models offer a convenient way to model time-to-event data by allowing a proportion of individuals in the population to be completely cured so that they never face the event of interest (say, death). The most studied cure rate models can be defined through a competing cause scenario in which the random variables corresponding to the time-to-event for each competing causes are conditionally independent and identically distributed while the actual number of competing causes is a latent discrete random variable. The main interest is then in the estimation of the cured proportion as well as in developing inference about failure times of the susceptibles. The existing literature consists of parametric and non/semi-parametric approaches, while the expectation maximization (EM) algorithm offers an efficient tool for the estimation of the model parameters due to the presence of right censoring in the data. In this paper, we study the cases wherein the number of competing causes is either a binary or Poisson random variable and a piecewise linear function is used for modeling the hazard function of the time-to-event. Exact likelihood inference is then developed based on the EM algorithm and the inverse of the observed information matrix is used for developing asymptotic confidence intervals. The Monte Carlo simulation study demonstrates the accuracy of the proposed non-parametric approach compared to the results attained from the true correct parametric model. The proposed model and the inferential method is finally illustrated with a data set on cutaneous melanoma. [ABSTRACT FROM AUTHOR]

We investigate the problem of testing equality and inequality constraints on regression coefficients in linear models with multivariate power exponential (MPE) distribution. This distribution has received considerable attention in recent years and provides a useful generalization of the multivariate normal distribution. We examine the performance of the power of the likelihood ratio, Wald and Score tests for grouped data and in the presence of regressors, in small and moderate sample sizes, using Monte Carlo simulations. Additionally, we present a real example to illustrate the performance of the proposed tests under the MPE model. [ABSTRACT FROM AUTHOR]

In this paper, we compare the largest order statistics arising from independent heterogeneous Weibull random variables based on the likelihood ratio order. Let $$X_{1},\ldots ,X_{n}$$ be independent Weibull random variables with $$X_{i}$$ having shape parameter $$0<\alpha \le 1$$ and scale parameter $$\lambda _{i}$$ , $$i=1,\ldots ,n$$ , and $$Y_{1},\ldots ,Y_{n}$$ be a random sample of size n from a Weibull distribution with shape parameter $$0<\alpha \le 1$$ and a common scale parameter $$\overline{\lambda }=\frac{1}{n}\sum \nolimits _{i=1}^{n}\lambda _{i}$$ , the arithmetic mean of $$\lambda _{i}^{'}s$$ . Let $$X_{n:n}$$ and $$Y_{n:n}$$ denote the corresponding largest order statistics, respectively. We then prove that $$X_{n:n}$$ is stochastically larger than $$Y_{n:n}$$ in terms of the likelihood ratio order, and provide numerical examples to illustrate the results established here. [ABSTRACT FROM AUTHOR]

In this paper, we carry out a theoretical study of the correlation coefficients between exponential order statistics and their monotonicity properties. Then, aided by a Monte Carlo simulation study, we make some conjectures about the correlation structure of order statistics from a larger class of distributions. [ABSTRACT FROM AUTHOR]

In this paper, we establish the stochastic ordering of median from an exchangeable trivariate normal vector based on the strength of the correlation coefficient. Specifically, by considering two exchangeable trivariate normal vectors with different correlation coefficients, we show that the absolute value of the median in the vector with smaller correlation coefficient is stochastically smaller than the absolute value of the median in the vector with larger correlation coefficient. We prove this result by utilizing skew-normal distributions. [ABSTRACT FROM AUTHOR]

Bacillus thuringiensis is a major source of insecticidal genes imparting insect resistance in transgenic plants. Level of expression of transgenes in transgenic plants is important to achieve desirable level of resistance against target insects. In order to achieve desirable level of expression, rice chloroplast transit peptide sequence was fused with synthetic cry2AX1 gene to target its protein in chloroplasts. Sixteen PCR positive lines of rice were generated by Agrobacterium mediated transformation using immature embryos. Southern blot hybridization analysis of T transgenic plants confirmed the integration of cry2AX1 gene in two to five locations of rice genome and ELISA demonstrated its expression. Concentration of Cry2AX1 in transgenic rice events ranged 5.0-120 ng/g of fresh leaf tissue. Insect bioassay of T transgenic rice plants against neonate larvae of rice leaffolder showed larval mortality ranging between 20 and 80 % in comparison to control plant. Stable inheritance and expression of cry2AX1 gene was demonstrated in T progenies through Southern and ELISA. In T progenies, the highest concentration of Cry2AX1 and mortality of rice leaffolder larvae were recorded as 150 ng/g of fresh leaf tissue and 80 %, respectively. The Cry2AX1 expression even at a very low concentration (120-150 ng/g) in transgenic rice plants was found effective against rice leaffolder larvae. [ABSTRACT FROM AUTHOR]

In this paper, we present several useful mixture representations for the reliability function of the inactivity time of systems with heterogeneous components based on order statistics, signatures and mean reliability functions. Some stochastic comparisons of inactivity times between two systems are discussed. These results form nice extensions of some existing results for the case when the components are independent and identically distributed. [ABSTRACT FROM AUTHOR]