Factor Structure and Longitudinal Invariance of the CES-D across Diverse Residential Backgrounds in Chinese Adolescents

Background:Valid and reliable measures of depressive symptoms are crucial for understanding risk factors,outcomes,and interventions across rural and urban settings.Despite this need,the longitudinal invariance of these measures over time remains understudied.This research explores the structural components of the Center for Epidemiological Studies Depression Scale(CES-D)and examines its consistency across various living environments and temporal stability in a cohort of Chinese teenagers.Method:In the initial phase,1,042 adolescents furnished demographic details and undertook the CES-D assessment.After a three-month interval,967 of these participants repeated the CES-D evaluation.The study employed Confirmatory factor analysis(CFA)to scrutinize the scale’s structural integrity.We investigated factorial invariance by conducting a twopronged CFA:one comparing urban vs.rural backgrounds,and another contrasting the results from the initial assessment with those from the follow-up.Results:The CES-D demonstrated adequate reliability in both rural and urban high school student samples.The preliminary four-factor model applied to the CES-D demonstrated a good fit with the collected data.Invariance tests,including multigroup analyses comparing rural and urban samples and longitudinal assessments,confirmed the scale’s invariance.Conclusions:The results suggest that the CES-D serves as a reliable instrument for evaluating depressive symptoms among Chinese adolescents.Its applicability is consistent across different living environments and remains stable over time.

Research on the Influence Factors and Struction of University Teachers Leader-Member Exchange

The leader - member exchange theory is one of the leading and the hot topic in recent years of the study of Western leaders. Structural studies of LMX factors have important theoretical and practical value in college teachers. In this paper, the ＂impact factor structure of university teachers LMX Questionnaire＂ for four universities 808 subjects was investigated. By exploratory factor analysis and confirmatory factor analysis, it found that the structure of university teachers LMX factors includes five dimensions： values, attitudes up, personality characteristics, switching behavior, objective situations. The questionnaire has good reliability and validity.

Factor input structure,environmental policies,and the export quality upgrade:a perspective of heterogeneity

In the analysis of how environmental regulation affects the comparative advantage of trade,existing literature ignores industry's inherent heterogeneity, which draws remarkably different conclusions. In view of this, the paper analyzed the mechanism of environmental regulation on the export quality of different industries from the perspective of factor input structure heterogeneity. Based on the panel data of China's manufacturing industry, the paper used the system generalized method of moments method to examine the heterogeneity influence of environmental regulation on manufacturing export quality. The study found that, first, environmental regulation affected the export quality upgrade of the manufacturing sector through offset effect and compensation effect, and the direction of the impact would mainly depend on the industry's factor input structure. Second, for industries with larger fixed-asset investment(FAI) ratio in the factor input structure, the current environmental regulation policy was not conducive to the export quality upgrading of the industries. However, there was a significant U-shaped dynamic relationship between them. As environmental regulations became stricter, when regulatory stringency went beyond the inflection point, the policy would promote the upgrading of export quality. But for industries with smaller proportion of FAI, environmental regulation exerted a favorable impact on the export quality upgrade, following a J-shaped marginal growth curve.Third, for industries with different factor input structure, their export quality had been effectively upgraded as expected by factors like human capital investment, independent R&D, technology introduction, and foreign direct investment; but raising per capita capital stock and expanding enterprise size did not produce significant direct impact on export quality upgrade. These conclusions remained robust after using different measurement methods and replacing with other variables. Therefore, this paper suggests that governments should take industry heterogeneity into consideration and formulate differentiated hierarchical environmental policies.Besides, they should strengthen the enforcement of the current environmental regulation policies. By doing so, enterprises are forced to improve their technology and product quality so that they can better cope with rising compliance costs, eliminate backward industries, and resolve excess capacity. In this way, the economic structure would be transformed and upgraded from the supply side.

Revising Space Groups from Simulated SHELXfcf Structure Factors. More Examples of Incorrect Space Groups, an Example of a Chemically-Incorrect Structure and the Special Case of Pgl to PRevisions

The structure factors of any crystal structure can be simulated from its atomic coordinates (and temperature factors) in a SHELXL-97 run on a dummy hkl in which only the scale factor is refined. The squares of the structure factors are retrieved from the fcf, and such simulated data are used in the revision of the space groups of several incorrectly-refined crystal structures. Two cases, a P1 to P1 revision and a chemically-incorrect structure that is refined in a correct space group, are discussed.

Rock mass structural recognition from drill monitoring technology in underground mining using discontinuity index and machine learning techniques

A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

SEISMIC RANDOM VIBRATION ANALYSIS OF STOCHASTIC STRUCTURES USING RANDOM FACTOR METHOD

Seismic random vibration analysis of stochastic truss structures is presented. A new method called random factor method is used for dynamic analysis of structures with uncertain parameters, due to variability in their material properties and geometry. Using the random factor method, the natural frequencies and modeshapes of a stochastic structure can be respectively described by the product of two parts, corresponding to the random factors of the structural parameters with uncertainty, and deterministic values of the natural frequencies and modeshapes obtained by conventional finite element analysis. The stochastic truss structure is subjected to stationary or non-stationary random earthquake excitation. Computational expressions for the mean and standard deviation of the mean square displacement and mean square stress are developed by means of the random variable＇s functional moment method and the algebra synthesis method. An antenna and a truss bridge are used as practical engineering examples to illustrate the application of the random factor method in the seismic response analysis of random structures under stationary or non-stationary random earthquake excitation.

Excitation spectrum and structure factor of a two-component Bose-Einstein condensate in different hyperfine states

The elementary excitation spectrum of a two-component Bose-Einstein condensate in different hyperfine states is obtained by Green＇s function method. It is found to have two branches. In the long wave-length limit, the two branches of the excitation spectrum are reduced to one phonon excitation and one single-particle excitation. The single-particle one has an energy gap. When the energy gap exists, we study the Landau critical velocity and the depletion of the condensate. With the obtained Green＇s functions, we calculate the structure factor of a two-component condensate. It is found that the static structure factor comprises only the branch of the phonon excitation and the single-particle excitation makes no contribution to the structure factor.

Effects of three-body interaction on dynamic and static structure factors of an optically-trapped Bose gas

We investigate how three-body interactions affect the elementary excitations and dynamic structure factor of a Bose- Einstein condensate trapped in a one-dimensional optical lattice. To this end, we numerically solve the Gross-Pitaevskii equation and then the corresponding Bogoliubov equations. Our results show that three-body interactions can change both the Bogoliubov band structure and the dynamical structure factor dramatically, especially in the case of the two-body interaction being relatively small. Furthermore, when the optical lattice is strong enough, the analytical results, combined with the sum-rule approach, help us to understand that： the effects of three-body interactions on the static structure Ihctor can be significantly amplified by an optical lattice. Our predictions should be observable within the current Bragg spectroscopy experiment.

Temperature Dependence of the Static Structure Factor of the Non－simple Liquid Metal， Cd

Report a calculation or the static structure factors at any temperature for the non-simple liquid metal Cd by the method or model parameter based on the hard sphere cluster(HSC)model.In comparison with available experimental data,the theoretical results are in good agreement with experiments.

Network autoregression model with grouped factor structures

Network autoregression and factor model are effective methods for modeling network time series data.In this study,we propose a network autoregression model with a factor structure that incorporates a latent group structure to address nodal heterogeneity within the network.An iterative algorithm is employed to minimize a least-squares objective function,allowing for simultaneous estimation of both the parameters and the group structure.To determine the unknown number of groups and factors,a PIC criterion is introduced.Additionally,statistical inference of the estimated parameters is presented.To assess the validity of the proposed estimation and inference procedures,we conduct extensive numerical studies.We also demonstrate the utility of our model using a stock dataset obtained from the Chinese A-Share stock market.

Factor-structure of economic growth in E-commerce

In order to analyze the factors having effect on economic growth of E commerce, the economic growth process of E commerce is divided into three stages; growth stage, stabilization stage and re growth stage. These three different stages are analysed using several economic growth theories, a set of factor structure is proposed for each stage of the economic growth process of E commerce.

Domain Structure of the Selenocysteine-specific Translation Factor SelB in Prokaryotes

Translation factor SelB is the key component for the specific decoding of UGA codons with selenocysteine at the ribosome. SelB binds selenocysteyl-tRNASec, guanine nucleotides and a secondary structure of the selenoprotein mRNA following the UGA at the 3' side. A comparison of the amino acid sequences of SelB species from E. coli,Desulfomicrobium baculatum, Clostridium thermoaceticum and Haemophilus influenzae showed that the proteins consist of at least four structural domains from which the Nterminal three are well conserved and share homology with elongation factor Tu whereas the C-terminal one is more variable and displays no similarity to any protein known. With the aid of the coordinates of EF-Tu the N-terminal part has been modelled into a 3D structure which exhibits intriguing features concerning its interaction with guanine nucleotides and other components of the translational apparatus. Cloning and expression of fragments of SelB and biochemical analysis of the purified truncated proteins showed that the C-terminal 19 kDa protein fragment is able to specifically bind to the selenoprotein mRNA. SelB, thus, is a translation factor functionally homologous to EF-Tu hooked up to the mRNA with its C-terminal end. The formation by SelB of a quaternary complex in vivo has been proven by overexpression of truncated genes of SelB and by demonstration that fragments comprising the mRNA or the tRNA binding domain inhibit selenocysteine insertion

Factor Structure and Measurement Invariance of the Prenatal Attachment Inventory: A Study among Japanese Pregnant Women

Background: Maternal emotional tie towards a foetus is a predictor of later maternal and child’s mental health. Methods: A questionnaire survey was conducted among 539 first trimester women. It included the Prenatal Attachment Inventory (PAI), Relationship Questionnaire (RQ), and Edinburgh Postnatal Depression Scale (EPDS). The factor structure models derived from exploratory factor analyses were compared by confirmatory factor analyses. Results: A three-factor bifactor model of the PAI was bet fit to the data. The omega coefficients and explained common variance suggested that the influences of three group factors were not negligible. The scores of the three subscales (derived from the three factors) were differently associated with age, gestation week, and adult attachment styles (derived from RQ). They were, however, not correlated with the EPDS scores. Conclusion: The PAI has a model of three groups and one general factor with an excellent fit to the data. The three subscales have construct validity too.

New Factor to Characterize Mechanism of “Strong Column-Weak Beam” of RC Frame Structures

Most reinforced concrete(RC)frame structures did not achieve the "strong column-weak beam" failure mode in recent big earthquakes, resulting in a large number of casualties and significant property loss. To deal with this serious problem, a new column-beam relative factor was proposed to characterize the relative yield situation of column ends and beam ends. By limiting the column-beam relative factor, RC frame structures could achieve the "strong column-weak beam" failure mode under the excitation of strong ground motions. The limit values of column-beam relative factor were calculated, analyzed and verified by using structural simulation models for corner columns in the bottom story of structures, which are destroyed most seriously in earthquakes. The results show that the limit values should be analyzed under bi-directional ground motion and with different axial compression ratios of columns. The peak ground acceleration(PGA)of ground motions has no significant effect on the limit values, while the type of strong ground motions has a significant effect on the limit values.

The sustainability and transition of economic growth in China:from a perspective of factor structure

After more than 20 years＇ high speed growth, the sustainable growth of Chinese economy faces serious limitation of resources and factors now and in the future. In order to maintain the economic growth. China has to trans-form the way of economic growth, Based on the analysis on the related theories of economic growth and the structural transformation in factors of production, this paper proposes that the transformation of the economic growth way has to impel the optimization and the promotion of the utilization structure of factors of production. Finall.v, based on the analysis of the necessity to change the pattern of economic growth, this paper proposes＇ the strategic measures to promote the continuous economic growth and the transformation of patterns of economic growth.

Dealing with Multicollinearity in Factor Analysis: The Problem, Detections, and Solutions

Multicollinearity in factor analysis has negative effects, including unreliable factor structure, inconsistent loadings, inflated standard errors, reduced discriminant validity, and difficulties in interpreting factors. It also leads to reduced stability, hindered factor replication, misinterpretation of factor importance, increased parameter estimation instability, reduced power to detect the true factor structure, compromised model fit indices, and biased factor loadings. Multicollinearity introduces uncertainty, complexity, and limited generalizability, hampering factor analysis. To address multicollinearity, researchers can examine the correlation matrix to identify variables with high correlation coefficients. The Variance Inflation Factor (VIF) measures the inflation of regression coefficients due to multicollinearity. Tolerance, the reciprocal of VIF, indicates the proportion of variance in a predictor variable not shared with others. Eigenvalues help assess multicollinearity, with values greater than 1 suggesting the retention of factors. Principal Component Analysis (PCA) reduces dimensionality and identifies highly correlated variables. Other diagnostic measures include the condition number and Cook’s distance. Researchers can center or standardize data, perform variable filtering, use PCA instead of factor analysis, employ factor scores, merge correlated variables, or apply clustering techniques for the solution of the multicollinearity problem. Further research is needed to explore different types of multicollinearity, assess method effectiveness, and investigate the relationship with other factor analysis issues.

Modeling the Synergetic Effect of Various Factors on Chloride Transport in Nonsaturated Concrete

Diffusion has been systematically described as the main mechanism of chloride transport in reinforced concrete（RC） structure, especially when the concrete is in a saturated state. However, the single mechanism of diffusion is not able to describe the actual chloride ingress in the nonsaturated concrete. Instead, it is dominated by the interaction of diffusion and convection. With the synergetic effects of various factors taken into account, this study aimed to modify and develop an analytical convection- diffusion coupling model for chloride transport in nonsaturated concrete. The model was verified by simulation of laboratory tests and field measurement. The results of comparison study demonstrate that the analytical model developed in this study is efficient and accurate in predicting the chloride profiles in the nonsaturated concrete.

The Role of the Native Language in Second Language Acquisition

The role that a learner＇s native language plays in his or her second language acquisition （SLA） has been the focus of many researchers in the past few decades. The article provides a brief review of the literature on the importance and the factors of native language influence in SLA.

Calculation and Analysis of Valence Electron Structure of Mo_2C and V_4C_3 in Hot Working Die Steel

Taking the hot working die steel （HWDS） 4Cr3Mo2NbVNi as an example, the phase electron structures （PES） and the biphase interface electron structures （BIES） of Mo2C and V4 C3 , which are two kinds of important carbides precipitated during tempering in steel were calculated, on the basis of the empirical electron theory of solids and molecules and the improved TFD theory. The influence of Mo2 C and V4 C3 on the mechanical properties of HWDS has been analyzed at electron structure level, and the fundamental reason that the characteristic of the PES and the BIES of carbides decides the behavior of them has been revealed.

OUT-OF-PLANE COMPRESSIVE PROPERTIES OF HEXAGONAL PAPER HONEYCOMBS

The compressive behaviour of paper honeycombs is studied by means of an experimental analysis. Experiment results show how geometry aspects of hexagonal paper honeycombs, e.g. the height of paper honeycomb, the thickness and length of honeycomb cell-wall, the drawing ratio of hexagonal honeycomb, affect the compressive properties of the paper honeycombs. It is in good agreement with the theory model. The constraint factor K of the critical buckling stress is mainly determined by the length of honeycomb cell-wail. It can be described as K=1.54 for B type paper honeycombs and K=3.32 for D type paper honeycombs. The plateau stress is the power exponent function of the thickness to length ratio of honeycomb cell-wall, and the experiment results show that the constant is 13.2 and the power exponent is 1.77. The research results can be used to characterize and improve efficiently the compressive properties of paper honeycombs.