Preliminary Exploration of the Mental Health Education Competency Survey of Primary and Middle School Head Teachers

Despite a recent focus on the mental health of students, primary and middle school mental health education in China has been hampered by a lack of resources fand inadequate professional training. This study assessed the mental health education competency of primary and middle school head teachers using the Mental Health Education Competency Questionnaire, a measure based on data from documentary analysis, behavioral event interviews (BEIs), and expert judgment. Factor, reliability, and validity analysis of this questionnaire were conducted. Through these analyses, seven structural dimensions of mental health education competency were found: mental health education skill, career growth, personality charm, occupational tendency, achievement feature, student perspective, and professional knowledge. This questionnaire will improve hiring and evaluation processes and, therefore, improve mental health education

Peer Victimization and Depressive Symptoms Among Rural-to-Urban Migrant Children in China: The Protective Role of Resilience

Peer victimization can have a profound effect on children’s wellbeing and is a known risk factor for depression in childhood. Migrant children experience peer victimization at higher rates than non-migrant peers; however, limited research has examined psychological factors that may serve to reduce depression risk for this group. In particular, no studies have yet investigated whether resilience, including personal characteristics, and a strong social support network, may moderate the relationship between peer victimization and depressive symptoms for migrant children. This study utilized a latent interaction model to examine the effect of resilience on the relationship between peer victimization and depressive symptoms among 721 rural-to-urban migrant children in Beijing, China. Results indicated that peer victimization was positively associated with depressive symptoms. Resilience was found to be a protective factor for depressive symptoms and also mitigated the effects of peer victimization on depressive symptoms. Exploratory analyses suggest that enrollment in private migrant schools may be linked with poorer psychosocial outcomes for Chinese migrant children. Strengthening the internal resilience and social supports for all migrant children may be an effective strategy to lower their risk for depression. Implications for intervention are discussed

Peer Victimization and Depressive Symptoms Among Rural-to-Urban Migrant Children in China: The Protective Role of Resilience

Peer victimization can have a profound effect on children’s wellbeing and is a known risk factor for depression in childhood. Migrant children experience peer victimization at higher rates than non-migrant peers; however, limited research has examined psychological factors that may serve to reduce depression risk for this group. In particular, no studies have yet investigated whether resilience, including personal characteristics, and a strong social support network, may moderate the relationship between peer victimization and depressive symptoms for migrant children. This study utilized a latent interaction model to examine the effect of resilience on the relationship between peer victimization and depressive symptoms among 721 rural-to-urban migrant children in Beijing, China. Results indicated that peer victimization was positively associated with depressive symptoms. Resilience was found to be a protective factor for depressive symptoms and also mitigated the effects of peer victimization on depressive symptoms. Exploratory analyses suggest that enrollment in private migrant schools may be linked with poorer psychosocial outcomes for Chinese migrant children. Strengthening the internal resilience and social supports for all migrant children may be an effective strategy to lower their risk for depression. Implications for intervention are discussed

Dependent-Chance Goal Programming for Water Resources Management under Uncertainty

Without sufficient data, consulting experts is a good way to quantify unknown parameters in water resources management which will result in human uncertainty. The aim of this paper is to introduce a new tool-uncertainty theory to deal with such uncertainty which is treated as uncertain variable with uncertainty distribution. And a dependent-chance goal programming (DCGP) model is provided for water resources management under such circumstance. In the model uncertain measure is used to measure possibility that an event will occur which is maximized by minimizing the deviation (positive or negative deviation) from target of objective event under a given priority structure. In the end, the developed model is applied to a numerical example to illustrate the effectiveness of the model. The result obtained contributes to the desired water-allocation schemes for decision-markers

Preparation of Iron-nickel Alloy Nanostructures via Two Cationic Pyridinium Derivatives as Soft Templates

In this paper, crystalline iron-nickel alloy nanostructures were successfully prepared from two cationic pyridinium derivatives as soft templates in solution. The crystal structure and micrograph of FeNi alloy nanostructures were characterized by X-ray diffraction, scanning electron microscopy and transmission electron microscopy, and the content was confirmed by energy-dispersive spectrometry. The results indicated that the as-prepared nanostructures showed slightly different diameter ranges with the change of cationic pyridinium derivatives on the surface. The experimental data indicated that the adsorption of cationic pyridinium compounds on the surface of particles reduces the surface charge, leading to an isotropic distribution of the residual surface charges. The magnetic behaviours of as-prepared FeNi alloy nanostructures exhibited disparate behaviours, which could be attributed to their grain sizes and distinctive structures. The present work may give some insight into the synthesis and character of new alloy nanomaterials with special nanostructures using new soft templates

Laboratory Study on Improving Recovery of Ultra-Heavy Oil Using High-Temperature-Resistant Foam

After multiple rounds of steam huff-and-puff processes, an ultra-heavy oil reservoir is prone to excessive steam injection pressure, large heat loss, small sweep range of steam, and steam channeling, thus severely affecting the effective utilization of the oil reservoir. To solve these problems, one-dimensional and three-dimensional (3D) physical simulation tools were used to study the plugging performance of high-temperature composite foams by adding tanning extract and alkali lignin under the influence of some factors such as the reservoir temperature, salinity of formation water, and injection methods. The ultra-heavy oil used in the experiment comes from Shengli Oilfield. Under the condition of surface degassing, the viscosity of ultra-heavy oil could reach 145169 mPa.s at 60 °C. The experimental results show that the foam can produce a synergistic effect with both gel systems, indicating that the gel increases the stability of the foam. The foam can transfer more gel into the high-permeability formation, which can efficiently control the foam. The 3D physical simulation experiments indicated that both the systems enhance the recovery of heavy oil reservoir and reduce its moisture content significantly using steam injection. The method involving tannin extract foam and steam injection increased the recovery by 20% compared to the foam involving only steam injection. The method involving alkali lignin foam and steam injection increased the recovery by 11%

A trading optimization model for virtual power plants in day-ahead power market considering uncertainties

Background: The day-ahead power market is an important part of the spot market. In the day-ahead market, participants make short-term forecasts of the load and output to propose the bidding curve more precisely. As energy aggregators that have regulatory resources, virtual power plants (VPPs) need to consider the uncertainty of distributed renewable energy output when participating in power market transactions.Methods: This paper analyzes the uncertainty and built an optimization model for VPP in day-ahead power market considering the uncertainty from both inner parts and the market environment. To verify the model, a simulation study is ran.Results: And the study results show the following: 1) the forecasting model is more efficient than the traditional algorithm in terms of accuracy, and 2) the confidence levels are not fully positive with the benefit of VPPs.Discussion: Improving the confidence level could reduce the uncertainty brought by renewable energy, but could also cause conservative trading behavior and affect the consumption of renewable energy