The relationship between childhood trauma and Internet gaming disorder among college students: A structural equation model

open access journalBackground The aim of this study was to investigate the mechanisms of Internet gaming disorder (IGD) and the associated interaction effects of childhood trauma, depression and anxiety in college students. Methods Participants were enrolled full-time as freshmen at a University in the Hunan province, China. All participants reported their socio-demographic characteristics and undertook a standardized assessment on childhood trauma, anxiety, depression and IGD. The effect of childhood trauma on university students' internet gaming behaviour mediated by anxiety and depression was analysed using structural equation modelling (SEM) using R 3.6.1. Results In total, 922 freshmen participated in the study, with an approximately even male-to-female ratio. A mediation model with anxiety and depression as the mediators between childhood trauma and internet gaming behaviour allowing anxiety and depression to be correlated was tested using SEM. The SEM analysis revealed that a standardised total effect of childhood trauma on Internet gaming was 0.18, (Z = 5.60, 95% CI [0.02, 0.05], P < 0.001), with the direct effects of childhood trauma on Internet gaming being 0.11 (Z = 3.41, 95% CI [0.01, 0.03], P = 0.001), and the indirect effects being 0.02 (Z = 2.32, 95% CI [0.00, 0.01], P = 0.020) in the pathway of childhood trauma-depression-internet gaming; and 0.05 (Z = 3.67, 95% CI [0.00, 0.02], P < 0.001) in the pathway of childhood trauma-anxiety-Internet gaming. In addition, the two mediators anxiety and depression were significantly correlated (r = 0.50, Z = 13.54, 95% CI [3.50, 5.05], P < 0.001). Conclusions The study revealed that childhood trauma had a significant impact on adolescents' Internet gaming behaviours among college students. Anxiety and depression both significantly mediated the relationship between childhood trauma and internet gaming and augmented its negative influence. Discussion of the need to understand the subtypes of childhood traumatic experience in relationship to addictive behaviours is included

Self-Organized Polynomial-Time Coordination Graphs

Coordination graph is a promising approach to model agent collaboration in multi-agent reinforcement learning. It conducts a graph-based value factorization and induces explicit coordination among agents to complete complicated tasks. However, one critical challenge in this paradigm is the complexity of greedy action selection with respect to the factorized values. It refers to the decentralized constraint optimization problem (DCOP), which and whose constant-ratio approximation are NP-hard problems. To bypass this systematic hardness, this paper proposes a novel method, named Self-Organized Polynomial-time Coordination Graphs (SOP-CG), which uses structured graph classes to guarantee the accuracy and the computational efficiency of collaborated action selection. SOP-CG employs dynamic graph topology to ensure sufficient value function expressiveness. The graph selection is unified into an end-to-end learning paradigm. In experiments, we show that our approach learns succinct and well-adapted graph topologies, induces effective coordination, and improves performance across a variety of cooperative multi-agent tasks

Effects of Different Shading Rates on the Photosynthesis and Corm Weight of Konjac Plant

To study the effects of shading level on the photosynthesis and corm weight of konjac plant, the chlorophyll fluorescence parameters, daily variation of relative electron transport rate (rETR), net photosynthetic rate (Pn), and corm weight of konjac plants under different treatments were measured and comparatively analyzed through covered cultivation of biennial seed corms with shade nets at different shading rates (0%, 50%, 70%, and 90%). The results showed that with the increase in shading rate, the maximum photochemical efficiency, potential&nbsp;activity, and non-photochemical quenching of photosystem Ⅱ (PSⅡ) of konjac leaves constantly increased, whereas the actual photosynthetic efficiency, rETR, and photochemical quenching of PSⅡ initially increased and then decreased. This result indicated that moderate shading could enhance the photosynthetic efficiency of konjac leaves. The daily variation of rETR in konjac plants under unshaded treatment showed a bimodal curve, whereas that under shaded treatment displayed a unimodal curve. The rETR of plants with 50% treatment and 70% treatment was gradually higher than that under unshaded treatment around noon. The moderate shading could increase the Pn of konjac leaves. The stomatal conductance and transpiration rate of the leaves under shaded treatment were significantly higher than those of the leaves under unshaded treatment. Shading could promote the growth of plants and increase corm weight. The comprehensive comparison shows that the konjac plants had strong photosynthetic capacity and high yield when the shading rate was 50%-70% for the area

Mechanistic Features of Nanodiamonds in the Lapping of Magnetic Heads

Nanodiamonds, which are the main components of slurry in the precision lapping process of magnetic heads, play an important role in surface quality. This paper studies the mechanistic features of nanodiamond embedment into a Sn plate in the lapping process. This is the first study to develop mathematical models for nanodiamond embedment. Such models can predict the optimum parameters for particle embedment. From the modeling calculations, the embedded pressure satisfies p0=3/2·W/πa2 and the indentation depth satisfies δ=k1P/HV. Calculation results reveal that the largest embedded pressure is 731.48 GPa and the critical indentation depth δ is 7 nm. Atomic force microscopy (AFM), scanning electron microscopy (SEM), and Auger electron spectroscopy (AES) were used to carry out surface quality detection and analysis of the disk head. Both the formation of black spots on the surface and the removal rate have an important correlation with the size of nanodiamonds. The results demonstrate that an improved removal rate (21 nm·min−1) can be obtained with 100 nm diamonds embedded in the plate

Improved active disturbance rejection controller for rotor system of magnetic levitation turbomachinery

The rotor of the magnetic suspension turbomachinery is supported by the magnetic suspension bearing without contact and mechanical friction, which directly drives the high-efficiency fluid impeller. It has the advantages of high efficiency, low noise, less fault and no lubrication. However, the system often has some unknown mutation, time variation, load perturbation and other un-certainties when working, and the traditional Proportion Integration Differentiation (PID) control strategy has great limitations to overcome the above disturbances. Therefore, this paper firstly establishes a mathematical model of the rotor of magnetic levitation turbomachinery. Then, a linear active disturbance rejection controller (LADRC) is presented, which can not only improve the above problems of PID control, but also avoid the complex parameter tuning process of traditional nonlinear active disturbance rejection control (ADRC). However, LADRC is easy to induce the overshoot of the system and cannot filter the given signal. On this basis, an improved LADRC with a fast-tracking differentiator (FTD) is proposed to arrange the transition process of input signals. The simulation results show that compared with the traditional PID controller and single LADRC, the improved linear active disturbance rejection control method with fast tracking differentiator (FTD-LADRC) can better suppress some unknown abrupt changes, time variation and other uncertainties of the electromagnetic bearing-rotor system. At the same time, the overshoot of the system is smaller, and the parameters are easy to be set, which is convenient for engineering application

Comparison of standard and penalized logistic regression in risk model development

OBJECTIVE: Regression models are ubiquitous in thoracic surgical research. We aimed to compare the value of standard logistic regression with the more complex but increasingly used penalized regression models using a recently published risk model as an example. METHODS: Using a standardized data set of clinical T1-3N0 esophageal cancer patients, we created models to predict the likelihood of unexpected pathologic nodal disease after surgical resection. Models were fitted using standard logistic regression or penalized regression (ridge, lasso, elastic net, and adaptive lasso). We compared the model performance (Brier score, calibration slope, C statistic, and overfitting) of standard regression with penalized regression models. RESULTS: Among 3206 patients with clinical T1-3N0 esophageal cancer, 668 (22%) had unexpected pathologic nodal disease. Of the 15 candidate variables considered in the models, the key predictors of nodal disease included clinical tumor stage, tumor size, grade, and presence of lymphovascular invasion. The standard regression model and all 4 penalized logistic regression models had virtually identical performance with Brier score ranging from 0.138 to 0.141, concordance index ranging from 0.775 to 0.788, and calibration slope from 0.965 to 1.05. CONCLUSIONS: For predictive modeling in surgical outcomes research, when the data set is large and the outcome of interest is relatively frequent, standard regression models and the more complicated penalized models are very likely to have similar predictive performance. The choice of statistical methods for risk model development should be on the basis of the nature of the data at hand and good statistical practice, rather than the novelty or complexity of statistical models

Soil Moisture Retrieval Using BuFeng-1 A/B Based on Land Surface Clustering Algorithm

A new land surface clustering algorithm is developed to retrieve soil moisture (SM) using the Global Navigation Satellite System reflectometry (GNSS-R) technique. Data from the BuFeng-1 (BF-1) twin satellites A/B, a pilot mission for the Chinese GNSS-R constellation, is used for SM retrieval. The core concept of the algorithm is to cluster global land areas into different types according to the land properties and calculate the SM type by type, based on the linear relationship between equivalent specular reflectivity and SM. The global comparison between the results and SM product from the Soil Moisture Active Passive mission shows the correlation coefficient (R) is 0.82, and unbiased root mean square error (ubRMSE) is 0.070 cm3·cm-3. The results also show good agreement compared with in situ SM measurements with the mean ubRMSE of 0.036 cm3·cm-3. This study proves that the global SM can be retrieved successfully from the BF-1 mission with the land surface clustering algorithm. By taking full advantage of the similarity of land surface physical properties in different regions, the algorithm provides a practical approach for global SM retrieval using spaceborne GNSS-R data.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 41971377). China Spacesat Company, Ltd. ESA-MOST China Dragon5 Programme (Grant Number: ID.58070) 10.13039/501100003392-Natural Science Foundation of Fujian Province (Grant Number: 2019J01853

Postpartum depression in mothers and fathers: a structural equation model

open access articleBackground Post-partum depression (PPD) is a growing mental health concern worldwide. There is little evidence in the Chinese context of the relationship between paternal PPD and maternal PPD. Given the growing global concerns this relationship requires further exploration. Methods A survey was conducted with 950 total couples from March 2017 to December 2018. The study was conducted using a standardized questionnaire that included basic demographic information, information on the relationship between the mother-in-law and daughter-in-law, marital satisfaction (both maternal and paternal), and PPD symptoms. Structural Equation Modelling (SEM) analysis was used to explore the underlying mechanism for PPD symptoms in mothers and fathers. Results In 4.4% of the couples both the wife and the husband showed depressive symptoms. Maternal marital satisfaction showed a significant mediating effect on paternal PPD (B = -0.114, p < 0.01), and there was a direct effect of maternal PPD on paternal PPD (B = 0.31, p < 0.001). Conclusions This is the first study to investigate the possible correlation between maternal PPD, mother-in-law and daughter-in-law relationship satisfaction, maternal marital satisfaction, paternal marital satisfaction, and paternal PPD. It is important for future PPD interventions to target both maternal and paternal mental health, as well as the mechanisms identified that can lead to PPD