Structural Analysis and Adsorption Studies of (PbO, MgO) Metal Oxide Nanocomposites for Efficient Methylene Blue Dye Removal from Water.

In the present work, magnesium oxide (MgO) and lead oxide (PbO) nanoparticles were prepared by the co-precipitation method. Their structural parameters and morphology were investigated using XRD, HRTEM, and FTIR. The formation of the phases was seen to have small average crystallite sizes and an orthorhombic crystal structure for both MgO and PbO nanoparticles. The results of HR-TEM showed irregularly shaped nanoparticles: quasi-spherical or rod-like shapes and spherical-like shapes for MgO and PbO nanoparticles, respectively. The produced nanoparticles' size using X-ray diffraction analysis was found to be 17 nm and 41 nm for MgO and PbO nanoparticles, respectively. On the other hand, it was observed from the calculations that the optical band gap obeys an indirect allowed transition. The calculated values of the band gap were 4.52 and 4.28 eV for MgO and PbO NPs, respectively. The MB was extracted from the wastewater using the prepared composites via absorption. Using a variety of kinetic models, the adsorptions were examined. Out of all the particles, it was discovered that the composites were best. Furthermore, of the models currently under consideration, the pseudo-second-order model best fit the degradation mechanism. The resultant composites could be beneficial for degrading specific organic dyes for water purification, as well as applications needing a wider optical band gap.

The quasi-xgamma frailty model with survival analysis under heterogeneity problem, validation testing, and risk analysis for emergency care data.

Frailty models are important for survival data because they allow for the possibility of unobserved heterogeneity problem. The problem of heterogeneity can be existed due to a variety of factors, such as genetic predisposition, environmental factors, or lifestyle choices. Frailty models can help to identify these factors and to better understand their impact on survival. In this study, we suggest a novel quasi xgamma frailty (QXg-F) model for the survival analysis. In this work, the test of Rao-Robson and Nikulin is employed to test the validity and suitability of the probabilistic model, we examine the distribution's properties and evaluate its performance in comparison with many relevant cox-frailty models. To show how well the QXg-F model captures heterogeneity and enhances model fit, we use simulation studies and real data applications, including a fresh dataset gathered from an emergency hospital in Algeria. According to our research, the QXg-F model is a viable replacement for the current frailty modeling distributions and has the potential to improve the precision of survival analyses in a number of different sectors, including emergency care. Moreover, testing the ability and the importance of the new QXg-F model in insurance is investigated using simulations via different methods and application to insurance data.

Improved estimation of population variance in stratified successive sampling using calibrated weights under non-response.

This paper introduces a new method to estimate the population variance of a study variable in stratified successive sampling over two occasions, while accounting for random non-response. The method uses a logarithmic type estimator and leverages information from a highly positively correlated auxiliary variable. The paper also presents calibrated weights for the new estimator and examines its properties through numerical and simulation studies. The results indicate that the suggested estimator is more effective than the standard estimator for estimating the population variance.

Improved estimation of population distribution function using twofold auxiliary information under simple random sampling.

In this article, our main aim is to suggest enhanced families of estimators for estimating the population distribution function (DF) using twofold auxiliary evidence within the framework of simple random sampling. Numerical analysis is performed on four different actual data sets. The precision of the estimators is further investigated exhausting a simulation study. As equated with existing estimators, the suggested families of estimators have minimum mean square error (MSE) and higher percentage relative efficiency (PRE). The succeeding recommended family of estimators outperforms the first family of estimators across all data sets. These are positive indicators of its performance. The theoretical result shows that the recommended family of estimators performs better than the existing estimators. The extent of improvement in efficiency is noteworthy, indicating the superiority of the suggested estimators in terms of minimum MSE.

A new Topp-Leone Kumaraswamy Marshall-Olkin generated family of distributions with applications.

We aim in this paper to propose a novel class of distributions that was created by merging the Topp-Leone distribution and the Generated families of Kumaraswamy and Marshall-Olkin. Its cumulative distribution function characterizes it and includes rational and polynomial functions. In particular, the following desirable properties of the new family are presented: Shannon entropy, order statistics, the quantile power series, and several associated measures and functions. Then, using a specific family member identified before, we create a parametric statistical model with the basic distribution being the inverse exponential distribution. Finally, a thorough investigation has been made to implement this new distribution with three data sets: the glass fibers data set, the glass Alumina data set and the hailing times data set. In comparison to six prominent competitors, the new model performs favorably on all statistical tests and criteria that were examined.

A general class of improved population variance estimators under non-sampling errors using calibrated weights in stratified sampling.

This paper proposes a new calibration estimator for population variance within a stratified two-phase sampling design. It takes into account random non-response and measurement errors, specifically applying this method to estimate the variance in Gas turbine exhaust pressure data. The study integrates additional information from two highly positively correlated auxiliary variables to develop a general class of estimators tailored for the stratified two-phase sampling scheme. The properties of these estimators, in terms of their biases and mean square errors, have been thoroughly examined and extensively analyzed through numerical and simulation studies. Furthermore, the calibrated weights of the strata are derived. The proposed estimators outperform the natural estimator of population variance. Finally, suitable recommendations have been made for survey statisticians intending to apply these findings to real-life problems.

Enhancing mean estimators in median ranked set sampling with dual auxiliary information.

When measuring the research variable is complicated, expensive, or problematic, median ranked set sampling (MRSS) is often utilized since it is straightforward to rank the components using a low-cost sorting criterion. Using this sampling scheme, many authors considered the problem of population mean estimation with a single auxiliary variable in order to obtain more precised estimators than the traditional ratio type regression estimators. In this article, we extend their ideas based on regression approach using two auxiliary variables and introduce a new regression-type estimator along with its theoretical expression of minimum mean square error (MSE). The suggested estimator's applicability is demonstrated using both simulated and real-world data sets.

Statistical inferences under step stress partially accelerated life testing based on multiple censoring approaches using simulated and real-life engineering data.

Evaluating the lifespan distribution of highly reliable commodities under regular use is exceedingly difficult, time consuming, and extremely expensive. As a result of its ability to provide more failure data faster and at a lower experimental cost, accelerated life testing has become increasingly important in life testing studies. In this article, we concentrate on parametric inference for step stress partially life testing utilizing multiple censored data based on the Tampered Random Variable model. Under normal stress circumstances, the lifespan of the experimental units is assumed to follow the Nadarajah-Haghighi distribution, with and being the shape and scale parameters, respectively. Maximum likelihood estimates for model parameters and acceleration factor are developed using multiple censored data. We build asymptotic confidence intervals for the unknown parameters using the observed Fisher information matrix. To demonstrate the applicability of the different methodologies, an actual data set based on the timings of subsequent failures of consecutive air conditioning system failures for each member of a Boeing 720 jet aircraft fleet is investigated. Finally, thorough simulation studies utilizing various censoring strategies are performed to evaluate the estimate procedure performance. Several sample sizes were studied in order to investigate the finite sample features of the considered estimators. According to our numerical findings, the values of mean squared errors and average asymptotic confidence intervals lengths drop as sample size increases. Furthermore, when the censoring level is reduced, the considered estimates of the parameters approach their genuine values.

Modified generalized Weibull distribution: theory and applications.

This article presents and investigates a modified version of the Weibull distribution that incorporates four parameters and can effectively represent a hazard rate function with a shape resembling a bathtub. Its significance in the fields of lifetime and reliability stems from its ability to model both increasing and decreasing failure rates. The proposed distribution encompasses several well-known models such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh, and modified Weibull distributions. The paper derives key mathematical statistics of the proposed distribution, including the quantile function, moments, moment-generating function, and order statistics density. Various mathematical properties of the proposed model are established, and the unknown parameters of the distribution are estimated using different estimation techniques. Furthermore, the effectiveness of these estimators is assessed through numerical simulation studies. Finally, the paper applies the new model and compares it with various existing distributions by analyzing two real-life time data sets.

Quality of Resuscitative Care Provided to an Infant With Abusive Head Trauma in Community Emergency Departments: An In Situ, Prospective, Simulation-Based Study.

OBJECTIVES: Abusive head trauma (AHT) is a very common and serious form of physical abuse, and a major cause of mortality and morbidity for young children. Early Recognition and supportive care of children with AHT is a common challenge in community emergency department (CEDs). We hypothesized that standardized, in situ simulation can be used to measure and compare the quality of resuscitative measures provided to children with AHT in a diverse set of CEDs. METHODS: This prospective, simulation-based study measured teams' performance across CEDs. The primary outcome was overall adherence to AHT using a 15-item performance assessment checklist based on the number of tasks performed correctly on the checklist. RESULTS: Fifty-three multiprofessional teams from 18 CEDs participated in the study. Of 270 participants, 20.7% were physicians, 65.2% registered nurses, and 14.1% were other providers. Out of all tasks, assessment of airway/breathing was the most successfully conducted task by 53/53 teams (100%). Although 43/53 teams (81%) verbalized the suspicion for AHT, only 21 (39.6%) of 53 teams used hyperosmolar agent, 4 (7.5%) of 53 teams applied cervical spine collar stabilization, and 6 (11.3%) of 53 teams raised the head of the bed. No significant difference in adherence to the checklist was found in the CEDs with an inpatient pediatric service or these with designated adult trauma centers compared with CEDs without. Community emergency departments closer to the main academic center outperformed CEDs these that are further away. CONCLUSIONS: This study used in situ simulation to describe quality of resuscitative care provided to an infant presenting with AHT across a diverse set of CEDs, revealing variability in the initial recognition and stabilizing efforts and provided and targets for improvement. Future interventions focusing on reducing these gaps could improve the performance of CED providers and lead to improved patient outcomes.

Improving Pediatric Readiness and Clinical Care in General Emergency Departments: A Multicenter Retrospective Cohort Study.

OBJECTIVE: To evaluate the impact of a collaborative initiative between general emergency departments (EDs) and the pediatric academic medical center on the process of clinical care in a group of general EDs. STUDY DESIGN: This retrospective cohort study assessed the process of clinical care delivered to critically ill children presenting to 3 general EDs. Our previous multifaceted intervention included the following components: postsimulation debriefing, designation of a pediatric champion, customized performance reports, pediatric resources toolkit, and ongoing interactions. Five pediatric emergency care physicians conducted chart reviews and scored encounters using the Pediatric Emergency Care Research Network's Quality of Care Implicit Review Instrument, which assigns scores between 5 and 35 across 5 domains. In addition, safety metrics were collected for medication, imaging, and laboratory orders. RESULTS: A total of 179 ED encounters were reviewed, including 103 preintervention and 76 postintervention encounters, with an improvement in mean total quality score from 23.30 (SD 5.1) to 24.80 (4.0). In the domain of physician initial treatment plan and initial orders, scores increased from a mean of 4.18 (0.13) to 4.61 (0.15). In the category of safety, administration of wrong medications decreased from 28.2% to 11.8% after the intervention. CONCLUSION: A multifaceted collaborative initiative involving simulation and enhanced pediatric readiness was associated with improvement in the processes of care in general EDs. This work provides evidence that innovative collaborations between academic medical centers and general EDs may serve as an effective strategy to improve pediatric care.

Improvement of Pediatric Advanced Airway Management in General Emergency Departments After a Collaborative Intervention Program.

BACKGROUND: In general emergency departments, advanced airway management of pediatric patients who are critically ill has been associated with increased adverse events given the varying exposure to pediatric patients and limited resources. Previous studies have shown significant improvement of simulated pediatric airway management in general emergency departments. The aim of this retrospective study was to determine the effect of an in situ simulation-based collaborative intervention program on the actual care of pediatric airway management in general emergency departments. METHODS: This was a retrospective study of pediatric subjects who were critically ill and required intubation at a diverse set of general emergency departments before referral to the academic medical center. The primary outcome was the quality of clinical care measured by adherence to best practices via a critical action checklist. Secondary outcomes included tracheal intubation associated adverse events and clinical outcomes. RESULTS: A total of 135 pediatric subjects (48 pre- and 87 post-intervention) who were transferred to the academic medical center from 9 general emergency departments between May 2014 and August 2019 were included in the analysis. The use of a cuffed endotracheal tube improved, from 44% to 72% (P = .001), whereas there was no significant change in the appropriate endotracheal tube size. Overall, severe tracheal intubation associated adverse events decreased, from 18.8% to 9.2% (P = .03), and post-intubation cardiac arrest events decreased, from 6.3% to 0% (P = .02). CONCLUSIONS: A simulation-based collaborative intervention program led to improvement in pediatric airway management and subject outcomes in general emergency departments. This model demonstrated the transfer of improvement from a simulated setting to a clinical setting and may be targeted in other clinical settings.