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.

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 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.

A High-Dimensional Test for Multivariate Analysis of Variance Under a Low-Dimensional Factor Structure

In this paper,the problem of high-dimensional multivariate analysis of variance is investigated under a low-dimensional factor structure which violates some vital assumptions on covariance matrix in some existing literature.We propose a new test and derive that the asymptotic distribution of the test statistic is a weighted distribution of chi-squares of 1 degree of freedom under the null hypothesis and mild conditions.We provide numerical studies on both sizes and powers to illustrate performance of the proposed test.

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.

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.

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.

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

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.

Psychometric Properties among Japanese Women Based on the Multidimensional Assessment of Women’s Experience of Childbirth

Aims/Background: Perceived experiences of childbirth are important for mothers as they affect their self-esteem, mother-child interactions, subsequent mother-child bonding, and their desire for another child. This study examined the factor structure and construct validity of Salmon and Drew’s Multidimensional Assessment of Women’s Experience of Childbirth (MAWEC) in Japanese. Design/Methods: This study conducted a questionnaire survey using the Japanese version of the MAWEC and other variables with 759 women with infants in Japan. The participants’ mean (standard deviation [SD], range) age was 31.9 (5.3, 18 - 46) years. A total of 353 (46.5%) participants were primiparous and 384 (50.6%) were multiparous, and 22 (2.9%) did not answer. The data were randomly divided into two groups for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) and separately analyzed the positive- and negative-worded items. I conducted EFA using the maximum-likelihood method with PROMAX rotation from one-through two- and three-factor structures. Different factor structure models were compared in terms of CFAs using, as indicator of goodness-of-fit, chi-square/df, comparative fit index (CFI), and root mean square of error approximation (RMSEA). Results: This study showed that a bifactor model for the MAWEC with four subscales (positive emotion, positive coping, negative emotion, and negative coping) fit the data the best. These four subscales were associated with demographic, obstetric, neonatal, and feeding characteristics. For example, primiparas were more vulnerable to coping aspects of perceived childbirth experiences, including sense of mastery over the delivery process and ability to enjoy the delivery. Gestational age at birth was associated with emotional aspects of perceived childbirth experiences. Conclusion: The Japanese version of the MAWEC consists of four aspects regarding perceived childbirth experience. Perinatal health professionals may examine women’s childbirth experiences from these four perspectives. .

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.

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.

Bainite isothermal transformation of Si–Mn–Mo alloy by phase structure factor calculation under different rare earth contents

The effect of rare earth （RE） on bainite trans- formation mechanism is not yet unified in the academia. Therefore, further studying the effect of RE on bainite transformation mechanism will have important guiding significance for the development of bainite steels. In this paper, using differential dilatometer （DIL805A/D）, heat treatment was performed and C-curve was drawn. The effect of phase structure factor on bainite transformation under two different fractions of RE in Si-Mn-Mo bainite steels was investigated by the empirical electron theory （EET） of solids, molecules, dilatometry, and metallogra- phy. Experimental results show that RE makes Fe-C- RE segregation structural unit of Si-Mn-Mo bainite steels increase, i.e., the values of phase structure factor （na, FDC） increase, and delay bainite transformation due to the drag effect resulting from the segregation of RE ferrite island interphase and the retardation of RE to carbon diffusion in Si-Mn-Mo bainite steels. Beside this, C-curve is shifted to right and down, and microstructures of bainite ferrite and substructures are finer.

A Research on the Flow Characteristics of a Splitter-Based Water Cooling System for Computer Boards

The splitter is an important component of water-based cooling systems used to extract heat from computer boards.In the present study,the flow characteristics of a 16-splitter structure were numerically simulated and compared with experimental results to verify the reliability of the numerical simulation method.Accordingly,the concept of splitter structural coefficients was proposed.Based on the results of this study,we recommend a selection range of 5≤k≤6 for the structure factor k of the splitter;after optimization,the maximum deviation of the splitter outlet flow was reduced from the original value of 100%to 8.3%.

Effect of in ovo folic acid injection on hepatic IGF2 expression and embryo growth of broilers

Background： Insulin-like factor 2（IGF2） plays an important role in embryonic growth process by modulating intermediary metabolism and cell proliferation. Folic acid is involved in one carbon metabolism and contributes to DNA methylation which is related to gene expression. The purpose of this study was to explore whether folic acid could regulate IGF2 expression via epigenetic mechanism and further promote embryonic growth of new-hatched broilers.Methods： In the present study, 360 fertile eggs were selected and randomly assigned to four treatments. On11 embryonic day of incubation（E11）, 0, 50, 100 and 150 μg folic acid were injected into eggs respectively.After hatched, growth performance of broilers were calculated. Hepatic IGF2 expression, methylation level and chromatin structure of promoter region were analyzed.Results： Results have showed that IGF2 expression was up-regulated in 150 μg folic acid group（P 〈 0.05） and other two dose of folic acid did not affect gene expression（P 〉 0.05）. Meanwhile, methylation level of IGF2 promoter were lower in 100 and 150 μg groups, which was consistent with lower expression of DNA methyltransferase1（DNMT1）（P 〈 0.05）. What＇s more, chromatin looseness of IGF2 promoter was higher in 150 μg group than control group（P 〈 0.05）. Further, birth weight（BW）, liver and bursa index of new-hatched chickens in 150 μg folic acid group were higher than the other groups（P 〈 0.05）. There were positive correlations between hepatic IGF2 expression and BW and organs index（P 〈 0.05）.Conclusion： In conclusion, our data have demonstrated that 150 μg folic acid injection on E11 could up-regulate IGF2 expression by modulating DNA hypomethylation and improving chromatin accessibility in the gene promoter region,and ulteriorly facilitate embryonic growth and organ development of broilers.

Community characteristics of macrobenthos in the Huanghe(Yellow River) Estuary during water and sediment discharge regulation

The community characteristics of macrobenthos in the Huanghe（Yellow River） Estuary is influenced by a combination of natural and anthropogenic factors. Here, we investigated short-term changes（1-month） in macrobenthic community structure in response to water and sediment discharge regulation（WSDR） in 2011.Specifically, we sampled the macrobenthos at 18 sampling stations situated at four distances（5, 10, 20, and 40 km）from the mouth of the Huanghe Estuary before（mid-June）, during（early-July）, and after（mid-July） WSDR. The results showed that a total of 73, 72, and 85 species were collected before, during, and after WSDR, respectively.Then, 13, 1, and 16 dominant species were detected at this three periods. Four phyla were primarily detected at all three periods（Annelida, Mollusca, Arthropoda, and Echinodermata）. However, while Mollusca and Annelida were the most important phyla in our study, Echinodermata and Annelida were the most important phyla in 1982,demonstrating major changes to community structure over a 3-decadal period. All stations were of high quality BOPA index before WSDR, whereas two and three stations were of reduced quality BOPA index during and after WSDR, respectively. The results of ABC curves showed that had incurred disturbed conditions after human activities WSDR. Most important of all, multivariate analyses and RDA analysis indicated that the structure of the macrobenthic community was closely linked to environment factors, including that organic content factor caused the distribution of macrobenthic community mostly during WSDR, while water depth after WSDR affected the macro benthos community structure seriously, and during WSDR, the environment factor influencing it was not single, including organic content, sulfide content, Hg and As. These differences may have been due to changes in water transparency negatively impacting the growth and development of macrobenthos, due to specific lifehistory requirements. Our results demonstrate that anthropogenic activity is having both long-term（3 decadal）and short term（1-month） impacts on the structure of the macrobenthic community of the Huanghe Estuary. In conclusion, human activities WSDR influence the habitat environment of macro benthos, including the water temperature, nutrients, bioturbation, and so on. Therefore, we suggest the necessity to strengthen regulations of land-derived organic pollutant input to maintain the ecological balance of the Huanghe Estuary.

The coupling loss factors for non-conservatively coupled structures

The method to calculate the coupling loss factors for non-conservatively coupled structures by using the mobilities of substructures is studied. By using the form of the energy balance equations of conservatively coupled systems, the relationship between the coupling loss factors and the energy ratios in non-conservatively coupled systems is derived. The method to calculate the energy ratios by using the mobilities of substructures is introduced, and experiment verification is carried out. The test data agree well with the predicted results.