Highly stable CsPbBr3/ PMA perovskite nanocrystals for improved optical performance.

In this study, to address the stability issues, we synthesized a CsPbBr3-coated poly (maleic anhydride-alt-1-octadecene) (CsPbBr3/PMA) using a modified hot-injection method. The CsPbBr3/PMA perovskite nanocrystals (PNCs) exhibited effective green emission at 522 nm with an improved photoluminescence quantum yield (86.8 %) compared to traditional CsPbBr3 PNCs (54.2 %). The ligands in the polymer coating can bond with the uncoordinated Pb and Br ions on the surface of PNCs to minimize surface defects and avoid exposure to the external environment, enhancing the stability of the perovskites. Time-resolved photoluminescence spectra showed longer lifetimes for CsPbBr3/PMA PNCs, while transient absorption measurements provided valuable insights into the intraband hot-exciton relaxation and recombination. We demonstrate the potential application of CSPbBr3/PMA in a down-conversion white-light-emitting diode (LED) by coupling green CsPbBr3/PMA and red K2SiF6:Mn4+ phosphor-coated glass slides onto a 455-nm blue GaN LED. The white LED produced a white light with the International Commission on Illumination color coordinates of (0.323, 0.345), luminous efficiency of 58.4 lm/W, and color rendering index of 83.2. The fabricated, white-LED system obtained a wide color gamut of 125.3 % of the National Television Standards Committee and 98.9 % of Rec. 2020. The findings demonstrate that CsPbBr3/PMA can be an efficient down-conversion material for white LEDs and backlighting.

Sample Size Requirements for Simple and Complex Mediation Models.

Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied researchers tend to use insufficient sample sizes to estimate their models of interest, which might result in unstable and inaccurate estimation of the model parameters including mediation effects. In the present study, sample size requirements were investigated for four frequently used mediation models: one simple mediation model and three complex mediation models. For each model, path and structural equation modeling approaches were examined, and partial and complete mediation conditions were considered. Both the percentile bootstrap method and the multivariate delta method were compared for testing mediation effects. A series of Monte Carlo simulations was conducted under various simulation conditions, including those concerning the level of effect sizes, the number of indicators, the magnitude of factor loadings, and the proportion of missing data. The results not only present practical and general guidelines for substantive researchers to determine minimum required sample sizes but also improve understanding of which factors are related to sample size requirements in mediation models.

A Multilevel Longitudinal Nested Logit Model for Measuring Changes in Correct Response and Error Types.

This article presents a multilevel longitudinal nested logit model for analyzing correct response and error types in multilevel longitudinal intervention data collected under a pretest-posttest, cluster randomized trial design. The use of the model is illustrated with a real data analysis, including a model comparison study regarding model complexity and cluster bias. Two substantive research questions regarding the intervention effect on correct response probability and error patterns are investigated using the proposed model. The recovery of item parameters for the proposed model using two sample size conditions is examined via a simulation study. The accuracy of the parameter estimates is comparable with those found in previous studies for the same family of models, except for the intercept parameters of correct responses. Finally, the impact of ignoring cluster membership in the model on the parameter estimation is also studied by fitting a single-level model to multilevel data. Ignoring cluster membership in the model adversely affects the estimation of intercept parameters in correct and error responses.

Obtaining Fixed Effects for Between-Within Designs in Explanatory Longitudinal Item Response Models Using Mplus.

Between-within designs that include a person group (i.e., a between-subjects factor) and repeated measures of binary responses over time (i.e., a within-subjects factor) are common in educational and psychological research. This software note describes how explanatory item response models can be specified to analyze longitudinal item-level data to detect fixed effects in Mplus for between-within designs. In particular, a necessary parameter transformation is illustrated in detail to obtain the fixed effects in Mplus.

Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF.

A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory (IRT) framework. The goal of the current study is to extend the MIMIC-interaction model for detecting DIF in the context of multidimensional IRT modelling and examine the performance of the multidimensional MIMIC-interaction model under various simulation conditions with respect to Type I error and power rates. Simulation conditions include DIF pattern and magnitude, test length, correlation between latent traits, sample size, and latent mean differences between focal and reference groups. The results of this study indicate that power rates of the multidimensional MIMIC-interaction model under uniform DIF conditions were higher than those of nonuniform DIF conditions. When anchor item length and sample size increased, power for detecting DIF increased. Also, the equal latent mean condition tended to produce higher power rates than the different mean condition. Although the multidimensional MIMIC-interaction model was found to be a reasonably useful tool for identifying uniform DIF, the performance of the model in detecting nonuniform DIF appeared to be questionable.

After Differential Item Functioning Is Detected: IRT Item Calibration and Scoring in the Presence of DIF.

Researchers are commonly interested in group comparisons such as comparisons of group means, called impact, or comparisons of individual scores across groups. A meaningful comparison can be made between the groups when there is no differential item functioning (DIF) or differential test functioning (DTF). During the past three decades, much progress has been made in detecting DIF and DTF. However, little research has been conducted on what researchers can do after such detection. This study presents and evaluates a confirmatory multigroup multidimensional item response model to obtain the purified item parameter estimates, person scores, and impact estimates on the primary dimension, controlling for the secondary dimension due to DIF. In addition, the item response model approach was compared with current practices of DIF treatment such as deleting and ignoring DIF items and using multigroup item response models through simulation studies. The authors suggested guidelines for DIF treatment based on the simulation study results.

Single and Multiple Ability Estimation in the SEM Framework: A Non-Informative Bayesian Estimation Approach.

Latent variable models with many categorical items and multiple latent constructs result in many dimensions of numerical integration, and the traditional frequentist estimation approach, such as maximum likelihood (ML), tends to fail due to model complexity. In such cases, Bayesian estimation with diffuse priors can be used as a viable alternative to ML estimation. The present study compares the performance of Bayesian estimation to ML estimation in estimating single or multiple ability factors across two types of measurement models in the structural equation modeling framework: a multidimensional item response theory (MIRT) model and a multiple-indicator multiple-cause (MIMIC) model. A Monte Carlo simulation study demonstrates that Bayesian estimation with diffuse priors, under various conditions, produces quite comparable results to ML estimation in the single- and multi-level MIRT and MIMIC models. Additionally, an empirical example utilizing the Multistate Bar Examination is provided to compare the practical utility of the MIRT and MIMIC models. Structural relationships among the ability factors, covariates, and a binary outcome variable are investigated through the single- and multi-level measurement models. The paper concludes with a summary of the relative advantages of Bayesian estimation over ML estimation in MIRT and MIMIC models and suggests strategies for implementing these methods.

Altered neuronal nitric oxide synthase expression in the cerebellum of calcium channel mutant mice.

Tottering, rolling Nagoya, and leaner mutant mice all exhibit cerebellar ataxia to varying degrees, from mild (tottering mice) to severe (leaner mice). Collectively, these mice are regarded as tottering locus mutants because each of these mutant mice expresses a different autosomal recessive mutation in the gene coding for the alpha(1A) calcium ion channel protein, which is the pore forming subunit for P/Q-type high voltage activated calcium ion channels. These mutant mice all exhibit varying degrees of cerebellar dysfunction and neuronal cell death. Nitric oxide (NO) is an important messenger molecule in the central nervous system, especially in the cerebellum, and it is produced via the enzyme, nitric oxide synthase (NOS). We investigated expression of neuronal-NOS (n-NOS) in the cerebella of all three mutant mice, as revealed by NADPH-diaphorase (NADPH-d) histochemical staining, quantitation of n-NOS protein using Western blotting and quantitation of n-NOS mRNA using in situ hybridization. The expression of n-NOS mRNA and protein as well as the NADPH-d histochemical reaction were elevated in tottering and rolling Nagoya cerebella. n-NOS mRNA and the NADPH-d histochemical reaction were decreased in the leaner cerebellum, but the leaner mouse n-NOS protein concentration was not significantly different compared to age- and gender-matched controls. These findings suggest that NO may act as an important mediator in the production of the neuropathology observed in these mutant mice.