Evaluating the Efficacy of correlation-based Meta-Analytic Structural Equation Modeling Under Different Patterns of Missing Correlations

Missing correlations often happen in the primary correlation matrices and create major problems for the performance of meta-analytic structural equation modeling (MASEM). In current literature, methodological investigation regarding the performance of MASEM methods paired with a large proportion of missing data is limited. This simulation study was designed to investigate the impacts of missing conditions on the correlation-based MASEM performance, utilizing weighted-covariance generalized least squares (W-COV GLS) with pairwise deletion (PD), W-COV GLS with multiple imputation (MI), and two-stage structural equation modeling (TSSEM) to pool the correlation matrices. Specifically, impacts of the study number (k), the within study sample size (n), the proportion of missing correlations (pm), and the proportion of studies reported full matrices (pf) on the performance of MASEM results were explored, with two different factorial models. Conditions where the correlation-based MASEM could produce accurate parameter estimations were identified. The results showed that larger sample size (i.e., k and n) and greater proportion of full matrices (pf) improve model fits, reduce bias in parameter estimates and their standard errors, and decrease the type I error rate. Whereas, the missing proportion (pm) has an inverse function on model fits, parameter and standard error estimates, and type I error rates. W-COV GLS with MI is superior than the other two methods with most missing conditions, but W-COV GLS with PD tends to perform better than W-COV GLS with MI when the missing proportion is extremely small paired with a large proportion of full matrices under the model with unequal factor loadings. Moreover, the outcomes demonstrated the necessity of including at least one study with full correlation matrices in the study pool for TSSEM and W-COV GLS with PD. Suggestions for future research were also described

A comprehensive analysis of Fermi Gamma-Ray Burst Data: IV. Spectral lag and Its Relation to Ep Evolution

The spectral evolution and spectral lag behavior of 92 bright pulses from 84 gamma-ray bursts (GRBs) observed by the Fermi GBM telescope are studied. These pulses can be classified into hard-to-soft pulses (H2S, 64/92), H2S-dominated-tracking pulses (21/92), and other tracking pulses (7/92). We focus on the relationship between spectral evolution and spectral lags of H2S and H2S-dominated-tracking pulses. %in hard-to-soft pulses (H2S, 64/92) and H2S-dominating-tracking (21/92) pulses. The main trend of spectral evolution (lag behavior) is estimated with $\log E_p\propto k_E\log(t+t_0)$ (${\hat{\tau}} \propto k_{\hat{\tau}}\log E$), where $E_p$ is the peak photon energy in the radiation spectrum, $t+t_0$ is the observer time relative to the beginning of pulse $-t_0$, and ${\hat{\tau}}$ is the spectral lag of photons with energy $E$ with respect to the energy band $8$-$25$ keV. For H2S and H2S-dominated-tracking pulses, a weak correlation between $k_{{\hat{\tau}}}/W$ and $k_E$ is found, where $W$ is the pulse width. We also study the spectral lag behavior with peak time $t_{\rm p_E}$ of pulses for 30 well-shaped pulses and estimate the main trend of the spectral lag behavior with $\log t_{\rm p_E}\propto k_{t_p}\log E$. It is found that $k_{t_p}$ is correlated with $k_E$. We perform simulations under a phenomenological model of spectral evolution, and find that these correlations are reproduced. We then conclude that spectral lags are closely related to spectral evolution within the pulse. The most natural explanation of these observations is that the emission is from the electrons in the same fluid unit at an emission site moving away from the central engine, as expected in the models invoking magnetic dissipation in a moderately-high-$\sigma$ outflow.Comment: 58 pages, 11 figures, 3 tables. ApJ in pres

A Feasible Algorithm for Designing Biorthogonal Bivariate Vector-valued Finitely Supported Wavelets

AbstractWavelet analysis has been developed a new branch for over twenty years. The concept of vector-valued binary wavelets with two-scale dilation factor associated with an orthogonal vector-valued scaling function is introduced. The existence of orthogonal vector-valued wavelets with two-scale is discussed. A necessary and sufficient condition is provided by means of vector-valued multiresolution analysis and paraunitary vector filter bank theory. An algorithm for constructing a sort of orthogonal vector-valued wavelets with compact support is proposed, and their orthogonal properties are investigated

Multi-innovation stochastic gradient algorithms for dual-rate sampled systems with preload nonlinearity

AbstractSince the stochastic gradient algorithm has a slower convergence rate, this letter presents a multi-innovation stochastic gradient algorithm for a class of dual-rate sampled systems with preload nonlinearity. The basic idea is to transform the dual-rate system model into an identification model which can use dual-rate data by using the polynomial transformation technique. A simulation example is provided to verify the effectiveness of the proposed method

Overexpression of BplERD15 enhances drought tolerance in Betula platyphylla Suk

In this study, we report the cloning and functional characterization of an early responsive gene, BplERD15, from Betula platyphylla Suk to dehydration. BplERD15 is located in the same branch as Morus indica Linnaeus ERD15 and Arabidopsis Heynh ERD15 in the phylogenetic tree built with ERD family protein sequences. The tissue-specific expression patterns of BplERD15 were characterized using qRT-PCR and the results showed that the transcript levels of BplERD15 in six tissues were ranked from the highest to the lowest levels as the following: mature leaves (ML) \u3e young leaves (YL) \u3e roots (R) \u3ebuds (B) \u3eyoung stems (YS) \u3emature stems (MS). Multiple drought experiments were simulated by adding various osmotica including polyethylene glycol, mannitol, and NaCl to the growth media to decrease their water potentials, and the results showed that the expression of BplERD15 could be induced to 12, 9, and 10 folds, respectively, within a 48 h period. However, the expression level of BplERD15 was inhibited by the plant hormone abscisic acid in the early response and then restored to the level of control. The BplERD15 overexpression (OE) transgenic birch lines were developed and they did not exhibit any phenotypic anomalies and growth deficiency under normal condition. Under drought condition, BplERD15-OE1, 3, and 4 all displayed some drought tolerant characteristics and survived from the drought while the wild type (WT) plants withered and then died. Analysis showed that all BplERD15-OE lines had significant lower electrolyte leakage levels as compared to WT. Our study suggests that BplERD15 is a drought-responsive gene that can reduce mortality under stress condition