Mean Interval Length Research Articles

Reliability Estimation under Normal Operating Conditions for Progressively Type-II XLindley Censored Data

This paper assumes constant-stress accelerated life tests when the lifespan of the test units follows the XLindley distribution. In addition to the maximum likelihood estimation, the Bayesian estimation of the model parameters is acquired based on progressively Type-II censored samples. The point and interval estimations of the model parameters and some reliability indices under normal operating conditions at mission time are derived using both estimation methods. Using the Markov chain Monte Carlo algorithm, the Bayes estimates are calculated using the squared error loss function. Simulating the performances of the different estimation methods is performed to illustrate the proposed methodology. As an example of how the proposed methods can be applied, we look at two real-life accelerated life test cases. According to the numerical outcomes and based on some criteria, including the root of the mean square error and interval length, we can conclude that the Bayesian estimation method based on the Markov chain Monte Carlo procedure performs better than the classical methods in evaluating the XLindley parameters and some of its reliability measures when a constant-stress accelerated life test is applied with progressively Type-II censoring.

On reliability estimation of Nadarajah–Haghighi distribution under adaptive type‐I progressive hybrid censoring scheme

AbstractIn this paper, the maximum likelihood and Bayesian estimation methods are considered to estimate the unknown parameters, reliability, and hazard rate functions of the Nadarajah–Haghighi (NH) distribution based on adaptive type‐I progressive hybrid censoring (ATIPHC) scheme. The Bayesian estimation is obtained under the assumption of independent gamma priors. The Bayes estimators cannot be obtained in closed form, therefore Lindley's approximation and Markov chain Monte Carlo (MCMC) method are used to solve this problem. The approximate confidence (ACIs) and credible intervals are also considered. To compare the efficiency of the different proposed estimators, a simulation study is considered and the performance of the different estimators are compared using mean square error (MSE) and interval length criterion. Finally, one real data set is analyzed in order to show how these mentioned estimators can be applied in practice. The simulation and real data analysis showed that the Bayes estimates have the smallest MSEs and the BCIs have the smallest lengths compared to their conventional counterparts.

Allopolyploidization increases genetic recombination in the ancestral diploid D genome during wheat evolution

Genetic recombination produces new allelic combinations, thereby introducing variation for domestication. Allopolyploidization has increased the evolutionary potential of hexaploid common wheat by conferring the advantages of heterosis and gene redundancy, but whether a relationship exists between allopolyploidization and genetic recombination is currently unknown. To study the impact of allopolyploidization on genetic recombination in the ancestral D genome of wheat, we generated new synthetic hexaploid wheats by crossing tetraploid Triticum turgidum with multiple diploid Aegilops tauschii accessions, with subsequent chromosome doubling, to simulate the evolutionary hexaploidization process. Using the DArT-Seq approach, we determined the genotypes of two new synthetic hexaploid wheats with their parents, F2 plants in a diploid population (2x, D1D1 × D2D2) and its new synthetic hexaploid wheat-derived population (6x, AABBD1D1 × AABBD2D2). About 11% of detected SNP loci spanning the D genome of Ae. tauschii were eliminated after allohexaploidization, and the degree of segregation distortion was increased in their hexaploid offspring from the F2 generation. Based on codominant genotypes, the mean genetic interval length and recombination frequency between pairs of adjacent and linked SNPs on D genome of the hexaploid F2 population were 2.3 fold greater than those in the diploid F2 population, and the recombination frequency of Ae. tauschii was increased by their hexaploidization with T. turgidum. In conclusion, allopolyploidization increases genetic recombination of the ancestral diploid D genome of wheat, and DNA elimination and increased segregation distortion also occur after allopolyploidization. Increased genetic recombination could have produced more new allelic combinations subject to natural or artificial selection, helping wheat to spread rapidly to become a major global crop and thereby accelerating the evolution of wheat via hexaploidization.

Stress-Strength Reliability for Exponentiated Inverted Weibull Distribution with Application on Breaking of Jute Fiber and Carbon Fibers.

For the first time and by using an entire sample, we discussed the estimation of the unknown parameters θ1, θ2, and β and the system of stress-strength reliability R=P(Y < X) for exponentiated inverted Weibull (EIW) distributions with an equivalent scale parameter supported eight methods. We will use maximum likelihood method, maximum product of spacing estimation (MPSE), minimum spacing absolute-log distance estimation (MSALDE), least square estimation (LSE), weighted least square estimation (WLSE), method of Cramér-von Mises estimation (CME), and Anderson-Darling estimation (ADE) when X and Y are two independent a scaled exponentiated inverted Weibull (EIW) distribution. Percentile bootstrap and bias-corrected percentile bootstrap confidence intervals are introduced. To pick the better method of estimation, we used the Monte Carlo simulation study for comparing the efficiency of the various estimators suggested using mean square error and interval length criterion. From cases of samples, we discovered that the results of the maximum product of spacing method are more competitive than those of the other methods. A two real‐life data sets are represented demonstrating how the applicability of the methodologies proposed in real phenomena.

Monitoring the Vegetation Dynamics in the Dongting Lake Wetland from 2000 to 2019 Using the BEAST Algorithm Based on Dense Landsat Time Series

The dynamic monitoring and analysis of wetland vegetation play important roles in revealing the change, restoration and reconstruction of the ecosystem environment. The increasing availability of high spatial-temporal resolution remote sensing data provides an unprecedented opportunity for wetland dynamic monitoring and change detection. Using the reconstructed dense monthly Landsat time series, this study focuses on the continuous monitoring of vegetation dynamics in Dongting Lake wetland, south China, in the last two decades (2000–2019) by using the Bayesian estimator of abrupt change, seasonal change, and trend (BEAST) method. Firstly, the flexible spatiotemporal data fusion (FSDAF) model is applied to blend Landsat and moderate-resolution imaging spectroradiometer (MODIS) images on the basis of the input image pair selection strategy named “cross-fusion” to generate the monthly time-series normalized difference vegetation index (NDVI) with the spatial resolution of 30 m. Then, the abrupt changes, trend, and seasonality of the vegetation in the study area as well as the uncertainties of change detection are estimated by the BEAST method. Results show that there is a close relationship between the ground true data and the estimated changepoints. A high overall accuracy (OA) of 87.37% and Kappa coefficient of 0.85 were achieved by the proposed framework. Additionally, the temporal validation got the interval intersection of 86.57% and the absolute difference of mean interval length of 6.8 days. All of the results demonstrate that the vegetation changes in the Dongting Lake wetland varied spatially and temporally in the last two decades, because of extreme weathers and anthropogenic factors. The presented approach can accurately identify the vegetation changes and time of disturbance in both the spatial and temporal domains, and also can retrieve the evolution process of wetland vegetation under the influence of climate changes and human activities. Therefore, it can be used to reveal potential causes of the degradation and recovery of wetland vegetation in subtropical areas.

S6CRISPR GENOME EDITING BASED ISOGENIC INDUCED PLURIPOTENT STEM CELL SYSTEM FOR SCHIZOPHRENIA DISEASE MODELING

Among the solutions to improve the integration of intermittent solar system, solar irradiation prediction is an essential process. This kind of prediction is a highly complex problem and requires highly robust and reliable statistical models for its simulation. The current research is devoted on the implementation of time series formalism which is based on the periodic autoregressive model (PAR) coupled with a power transform (Box–Cox; BC) of data to stabilize variance. A new and robust functional model is proposed based on the prediction intervals approach whose results in term of efficiency (prediction interval coverage probability) and interest (normalized mean interval length) are similar or better than classical prediction tools based on bootstrap utilization. In the deterministic case, the PAR coupled with BC transform gives more mixed results, but for most cases, the classical tools, like persistence, smart persistence, auto-regression, and artificial neural network fail to compete with PAR or PAR-BC models.

Uncertainty‐aware forecast interval for hourly PV power output

A forecast interval is effective for handling the forecast uncertainty in solar photovoltaic systems. In estimating the forecast interval, most available approaches apply an identical policy to all the point forecasts. This results in an inefficient interval (e.g. an unnecessarily wide interval for an accurate forecast). They also adopt a complex model and even require modification of the available deterministic forecasting model, which may adversely affect their application. To overcome these limitations, the authors introduce a forecast uncertainty-aware forecast interval. They calculate a forecast accuracy-related uncertainty metric from an ensemble method based on the dropout technique. The dropout technique is widely used in deep learning models. This implies that the proposed approach can be applied to available deep learning forecasting models without modifying them. Using the uncertainty metric and relevant data of previous forecast results, they estimate the uncertainty-aware forecast interval. Through experiments using real-world data, they first demonstrate the close relation of their uncertainty metric to the forecasting accuracy. Then, they demonstrate that the uncertainty-aware forecast interval reduces the mean interval length by up to 25.7% and decreases the prediction interval coverage probability by 4.07%, compared to available approaches. This illustrates that their approach results in an effective interval.

Prediction intervals for global solar irradiation forecasting using regression trees methods

Abstract A global horizontal irradiation prediction (from 1 h to 6 h) is performed using 2 persistence models (simple and “smart” ones) and 4 machine learning tools belonging to the regression trees methods family (normal, pruned, boosted and bagged). A prediction band is associated to each forecast using methodologies based on: bootstrap sampling and k-fold approach, mutual information, stationary time series process with clear sky model, quantiles estimation and cumulative distribution function. New reliability indexes (gamma index and gamma test) are built from the mean interval length (MIL) and prediction interval coverage probability (PCIP). With such methods and error metrics, good prediction bands are estimated for Ajaccio (France) with a MIL close to 113 Wh/m2, a PCIP reaching 70% and a gamma index lower than 0.9.

Change in Breast Cancer Screening Intervals Since the 2009 USPSTF Guideline.

In 2009, the U.S. Preventive Services Task Force (USPSTF) recommended biennial mammography for women aged 50-74 years and shared decision-making for women aged 40-49 years for breast cancer screening. We evaluated changes in mammography screening interval after the 2009 recommendations. We conducted a prospective cohort study of women aged 40-74 years who received 821,052 screening mammograms between 2006 and 2012 using data from the Breast Cancer Surveillance Consortium. We compared changes in screening intervals and stratified intervals based on whether the mammogram at the end of the interval occurred before or after the 2009 recommendation. Differences in mean interval length by woman-level characteristics were compared using linear regression. The mean interval (in months) minimally decreased after the 2009 USPSTF recommendations. Among women aged 40-49 years, the mean interval decreased from 17.2 months to 17.1 months (difference -0.16%, 95% confidence interval [CI] -0.30 to -0.01). Similar small reductions were seen for most age groups. The largest change in interval length in the post-USPSTF period was declines among women with a first-degree family history of breast cancer (difference -0.68%, 95% CI -0.82 to -0.54) or a 5-year breast cancer risk ≥2.5% (difference -0.58%, 95% CI -0.73 to -0.44). The 2009 USPSTF recommendation did not lengthen the average mammography interval among women routinely participating in mammography screening. Future studies should evaluate whether breast cancer screening intervals lengthen toward biennial intervals following new national 2016 breast cancer screening recommendations, particularly among women less than 50 years of age.

How Have Breast Cancer Screening Intervals Changed Since the 2009 USPSTF Guideline Update?

Abstract Background: Beginning in 2009, the U.S. Preventives Services Task Force (USPSTF) breast cancer screening guidelines recommended biennial mammography screening for women aged 50–74 years, and shared-decision making for women aged 40–49 years. We evaluated changes in screening interval after release of the 2009 recommendations. Methods: We compared screening intervals over the period between 2006 and 2012, expecting that the screening interval would lengthen over this time period, using data from the Breast Cancer Surveillance Consortium on 909,972 screening mammograms among 351,271 women aged 40–89 years. We stratified intervals based on whether the exam at the end of the interval occurred before or after the 2009 USPSTF decision. Differences in mean interval length by woman-level characteristics were compared using linear regression. Results: Contrary to expectations, the mean interval length (in months) minimally decreased after the 2009 USPSTF guideline compared to prior. Among women aged 40–49 years, the mean interval length decreased from 17.3 months to 17.1 months (difference −0.16, 95% confidence interval [CI] -0.30 to -0.01). Similar small reductions were seen for most age groups. The largest decreases in interval length in the post-USPSTF period were observed among women with a first-degree family history of breast cancer (difference −0.68, 95% CI, −0.82–−0.54) or a 5-year breast cancer risk ≥ 2.5% (difference −0.58, 95% CI, −0.73–−0.44). Conclusions: The 2009 USPSTF guideline update did not lengthen the average mammography screening interval among women routinely participating in mammography screening. Future studies should evaluate whether breast cancer screening intervals lengthen towards biennial intervals following new national 2015 breast cancer screening recommendations, particularly among women under 50 years.

Determination of maintenance schedule and process mean of production system

In the literature it is very common to treat the problem of determining the optimal mean of a process (process target) and the optimal preventive maintenance schedule as separate problems. The purpose of this paper is to integrate those decisions and develop a model that finds the optimal selection of process mean and frequency and interval length of preventive maintenance. In developing the model, we assume that the amount of raw material an item receives follows normal distribution. Moreover, a constant-interval preventive maintenance policy is used in this paper. A closed-form solution is obtained when the time to failure of equipment follows a general distribution. Also, sensitivity analysis is conducted on key parameters of the model.

Methods to estimate aboveground wood productivity from long-term forest inventory plots

Forest inventory plots are widely used to estimate biomass carbon storage and its change over time. While there has been much debate and exploration of the analytical methods for calculating biomass, the methods used to determine rates of wood production have not been evaluated to the same degree. This affects assessment of ecosystem fluxes and may have wider implications if inventory data are used to parameterise biospheric models, or scaled to large areas in assessments of carbon sequestration. Here we use a dataset of 35 long-term Amazonian forest inventory plots to test different methods of calculating wood production rates. These address potential biases associated with three issues that routinely impact the interpretation of tree measurement data: (1) changes in the point of measurement (POM) of stem diameter as trees grow over time; (2) unequal length of time between censuses; and (3) the treatment of trees that pass the minimum diameter threshold (“recruits”). We derive corrections that control for changing POM height, that account for the unobserved growth of trees that die within census intervals, and that explore different assumptions regarding the growth of recruits during the previous census interval. For our dataset we find that annual aboveground coarse wood production (AGWP; in Mgha−1year−1 of dry matter) is underestimated on average by 9.2% if corrections are not made to control for changes in POM height. Failure to control for the length of sampling intervals results in a mean underestimation of 2.7% in annual AGWP in our plots for a mean interval length of 3.6years. Different methods for treating recruits result in mean differences of up to 8.1% in AGWP. In general, the greater the length of time a plot is sampled for and the greater the time elapsed between censuses, the greater the tendency to underestimate wood production. We recommend that POM changes, census interval length, and the contribution of recruits should all be accounted for when estimating productivity rates, and suggest methods for doing this.

A Modular Cage System Design for Continuous Medium to Large ScaleIn VivoRearing of Predatory Mites (Acari: Phytoseiidae)

A new stackable modular system was developed for continuousin vivoproduction of phytoseiid mites. The system consists of cage units that are filled with lima beans, Phaseolus lunatus, or red beans,P. vulgaris, leaves infested with high levels of the two-spotted spider mites,Tetranychus urticae. The cage units connect with each other through a connection cup, which also serves for monitoring and collection. Predatory mites migrate upwards to new cage units as prey is depleted. The system was evaluated for production ofPhytoseiulus persimilis. During a 6-month experimental period,20,894.9±10,482.5(mean ± standard deviation) predators were produced per week. The production consisted of4.1±4.6% nymphs and95.9±4.6% adults. A mean of554.5±59.8predatory mites were collected per harvested cage and the mean interval length between harvests was6.57±6.76days. The potential for commercial and experimental applications is discussed.

An Evaluation of Statistical Methods for the Determination of Age of Death Using Dental Root Translucency and Periodontosis

Lamendin and colleagues (1992) proposed to assess age-at-death from root translucency and periodontosis. Several teeth from the same individual were included in their study. In our work, we evaluate the reliability of their formulas without introducing this bias. Our sample was constituted of 214 individuals (114 males and 100 women) selected from the Terry collection (U.S.A.). The R(2) between age and both indicators is equal to 0.33 and 0.08 (p < 0.001). Based on linear regression, the mean of standard error for individual age prediction was equal to 13.67 years, and the mean interval length is equal to 53.89 years. Multinomial logistic regression and Bayesian approach failed to give satisfactory results when classifying the individuals in age categories. Therefore, the use of root translucency and periodontosis may lead to incorrect age-at-death assessment, and it is thus necessary to complement this approach with other techniques to assess age-at-death.

Urn sampling, interval censoring and proportional hazard models

This paper proposes a new distribution-free statistical method for testing hypotheses about covariates for survival data having simultaneously right-, left- and interval-censored survival times. The new test is motivated by the analogue between urn sampling and the Cox’s proportional hazard models. Investigations of the significance levels and power as a function of the proportion of interval-censored observations and interval length show that the test performs well for most censoring situations encountered in practice. Simulation results also suggest that there is negligible loss of power in the practical situation in which the mean interval length for interval-censored observations is less than the mean survival time. This holds even with heavy interval censoring. Comparison with the widely used Mantel’s method for comparing two groups shows that the power of the new method appears to be superior. Furthermore, the test is relatively simple to carry out and generalizes to comparing k populations as well as the testing of general linear hypothesis for arbitrary covariates.

Simultaneous Logit-Based Confidence Intervals for Odds Ratios in 2 × k Classification Tables with a Fixed Reference Level

In this article, we consider the problem of constructing simultaneous confidence intervals for odds ratios in 2 × k classification tables with a fixed reference level. We discuss six methods designed to control the familywise error rate and investigate these methods in terms of simultaneous coverage probability and mean interval length. We illustrate the importance and the implementation of these methods using two {\\sc hiv} public health studies.

Temporal pattern of vocalization type usage in singing sessions of male tyrant flycatchers (Tyranninae)

It has been hypothesized that variation (e.g., of repertoire elements) in prolonged vocalization sessions of passerine birds can serve to minimize habituation by conspecifics. The repertoire of vocalization types limited in suboscine passerines, raising the question of how a limited set of elements can create patterns that minimize habituation. This question was studied by computational analysis of recorded singing sessions of 20 suboscine species from the subfamily Tyranninae, family Tyrannidae (tyrant flycatchers). The recordings of 12 of the species included two or more distinct vocalization types (VTs). In these species, the interval between vocalization units when the VT changed was on average shorter than that when the VT remained the same. In addition, when the VT changed, the mean interval length between successive vocalization units differed depending on which VT preceded the interval and which VT followed it. On the other hand, species with just a single VT in the session analyzed showed a surprisingly high degree of absolute difference between adjacent vocalization units with respect to both the length of the vocalization and percentage of time elapsed until peak amplitude. A change in the rhythm of vocalization accompanying a change in VT provided a potential means of drawing a conspecific listener's attention to the change in VT. The results showed that tyrant flycatchers use temporal patterning to achieve a high level of variety in vocalization sessions despite a limited vocal repertoire.

Practice patterns in the management of patients with esophageal strictures and rings

Only few data exist on the epidemiology and management of esophageal strictures and rings. To study the epidemiology and management of esophageal strictures and rings. Case-control study. Endoscopic data repository of U.S. gastroenterology practices from 1998 to 2003 (Clinical Outcomes Research Initiative). Case subjects included 7287 patients with strictures and 4993 patients with rings. The control group consisted of 124,120 patients without endoscopic evidence of esophageal stenosis. Esophageal dilation. Patient demographics, types and diameters of esophageal dilators, frequency of repeat dilations. Strictures displayed a male predominance, and rings displayed a small female predominance. Compared with the control population, strictures and rings both occurred most frequently in elderly white patients. Dysphagia and reflux were the most common indications for dilation in both conditions. Compared with strictures, rings were treated more often with larger dilators and rubber bougies. One-year rates of repeat dilation for strictures and rings were 13% and 4%, respectively. The mean interval length between repeat dilations was 82 days for strictures and 184 days for rings. Only a limited amount of information about individual patients was retrievable from the electronic database. The variations in the demographic characteristics and the treatment practice allude to differences in the underlying pathophysiology of these 2 benign obstructing lesions of the esophagus.

Pairwise comparisons for proportions estimated by pooled testing

When estimating the prevalence of a rare trait, pooled testing can confer substantial benefits when compared to individual testing. In addition to screening experiments for infectious diseases in humans, pooled testing has also been exploited in other applications such as drug testing, epidemiological studies involving animal disease, plant disease assessment, and screening for rare genetic mutations. Within a pooled-testing context, we consider situations wherein different strata or treatments are to be compared with the goals of assessing significant and practical differences between strata and ranking strata in terms of prevalence. To achieve these goals, we first present two simultaneous pairwise interval estimation procedures for use with pooled data. Our procedures rely on asymptotic results, so we investigate small-sample behavior and compare the two procedures in terms of simultaneous coverage probability and mean interval length. We then present a unified approach to determine pool sizes which deliver desired coverage properties while taking testing costs and interval precision into account. We illustrate our methods using data from an observational HIV study involving heterosexual males who use intravenous drugs.

High-density molecular map of chromosome region harboring stripe-rust resistance genes YrH52 and Yr15 derived from wild emmer wheat, Triticum dicoccoides.

Two stripe-rust resistance genes, YrH52 and Yr15, derived from the Israeli wild emmer wheat, Triticum dicoccoides, have been located on chromosome 1B. The main objectives of the present study were to increase marker density in the vicinity of YrH52 gene by means of AFLP, RAPD and microsatellite markers, to improve the map of another T dicoccoides-derived stripe-rust resistance gene Yr15 using microsatellite markers, and to preliminarily discriminate these two genes. Additional 26 marker loci comprising 20 AFLPs, three RAPDs, and three microsatellites were found to be linked to YrH52 gene. An updated genetic map consisting of 45 marker loci, in the region of YrH52 gene, was constructed with a total map length of 107.7 cm. The mean interval length was 0.96 cm in the region Xgwm359b-P55M53b carrying YrH52 gene. YrH52 was bracketed by Xgwm413 (Nor1 and UBC212a) and Xgwm273a (Xgwm273d) with map distance of 1.3 and 2.7 cm from either side, respectively. Eight additional microsatellite markers were found to be linked with Yr15, and the linkage map of Yr15 gene was thus obviously improved. In the YrH52-mapping population, no crossover was detected in the interval UBC212a (Xgwm413)-Yr15-Nor1, and YrH52 was located distally outside this interval. It may suggest that YrH52 is different from Yr15 even though both of them are derived from T. dicoccoides and are mapped on chromosome 1BS. The large number of molecular makers revealed in the present study would be helpful for the marker-assisted introgression of the T. dicoccoides-derived YrH52 and Yr15 stripe-rust resistance genes into elite cultivars of wheat, and the high-density map would accelerate the map-based cloning of the two genes.