Parental Psychological Control and Internet Gaming Disorder Tendency:A Moderated Mediation Model of Core Self-Evaluation and Intentional Self-Regulation

Internet gaming disorder(IGD)among junior high school students is an increasingly prominent mental health concern.It is important to look for influences behind internet gaming disorder tendency(IGDT)in the junior high school student population.The present study aimed to reveal the explanatory mechanisms underlying the association between parental psychological control(PPC)and internet gaming disorder tendency among junior high school students by testing the mediating role of core self-evaluation(CSE)and the moderating role of intentional self-regulation(ISR).Participants in present study were 735 Chinese junior high school students who completed offline self-report questionnaires on parental psychological control,core self-evaluation,intentional self-regulation,and Internet gaming disorder tendency.Analyses were conducted via mediation and moderated mediation.The results showed that:(1)Parental psychological control was positively related to junior high school students’Internet gaming disorder tendency.Core self-evaluation,and intentional self-regulation were negatively related to junior high school students’Internet gaming disorder tendency,respectively.(2)Core self-evaluation partially mediated the relationship between parental psychological control and junior high school students’Internet gaming disorder tendency.(3)Intentional self-regulation moderated the association between parental psychological control and Internet gaming disorder tendency,as well as the relationships between parental psychological control and core self-evaluation and core self-evaluation and Internet gaming disorder tendency in the mediated model.Based on these findings,we believe that there is a need to weaken parental psychological control,strengthen junior high school students’core self-evaluation and intentional self-regulation,and to recognize the important role of parents as well as their children’s personal positive traits in the healthy development of junior high school students.

Effect of Family Cohesion on Depression of Chinese College Students in the COVID-19 Pandemic: Chain Mediation Effect of Perceived Social Support and Intentional Self-Regulation

Individuals’perceptions,attitudes,and patterns of getting along with family members are important factors influencing Chinese people’s self-evaluation.The aim of this study was to investigate the effect of family cohesion on depression and the role of perceived social support and intentional self-regulation in this association.A hypothesized model of the association of family cohesion,perceived social support,intentional self-regulation,and depression was examined.A convenience sampling method was used to survey 1,180 college students in Yunnan Province using self-report.Data were collected using the Family Cohesion Scale,the Perceived Social Support Scale,the Intentional Self-Regulation Scale,and the Center for Epidemiological Studies Depression Scale.The findings revealed low to moderate correlation between the variables studied.College students’family cohesion was a negative predictor of their depression.This association was also mediated by the knock-on effect of perceived social support and intentional self-regulation.These findings show how family cohesion affects college students’depressive status.Specifically,these results help demonstrate the importance of family cohesion,perceived social support,and intentional self-regulation in optimizing students’depression,which in turn can promote better psychological states.

Intentional and unintentional impacts of anaesthesia： insights from experiments in pain and injury

The study of brain function in the presence of pain and injury is a rapidly expanding field of experimental research.Clinically,the presence of pain and injury is often accompanied by reports of behavioural change and altered cognition.Even in a highly controlled environment such as the surgical operating theatre postoperative behavioural changes including posttraumatic stress disorder,depression,chronic fatigue,

Intentional replantation combined root resection therapy for the treatment of typeⅢradicular groove with two roots:A case report

BACKGROUND A radicular groove is an anatomic malformation that usually initiates at the central fossa,extending along the root at varying lengths and depths and predisposes the involved tooth to a severe periodontal defect.Severe grooves that extend to the root apex often lead to complex combined periodontal-endodontic lesions.They are a serious challenge for doctors to diagnose and treat.CASE SUMMARY In this report,we described a patient with a maxillary lateral incisor with a deep palatogingival groove with two roots,which led to complex combined periodontal-endodontic lesions.Suggested treatment modalities included curettage of the affected tissues,elimination of the groove by grinding and/or sealing with a variety of filling materials,and surgical procedures.In this case,a combination of endodontic therapy,intentional replantation,and root resection were used,which resulted in periodontal/periradicular healing after 12 mo.CONCLUSION Intentional replantation and root resection offer a predictable procedure and should be considered a viable treatment modality for the management of palatogingival grooves,especially for two-rooted teeth.

Results of an Intentional Introduction of Artemia sinica in the High-Altitude Tibetan Lake Dangxiong Co:On a Base of Surveys in 2011 and 2013

1 Introduction The human population is projected to reach 9200million by 2050.A fundamental question for science is whether it is possible to increase food production to meet the demands of a human population of that magnitude.It’s possible only to increase an aquaculture production.Cultivation of fish/shrimp larvae is a bottleneck in a cultivation of the different organisms.Live food

Management of type IIIb dens invaginatus using a combination of root canal treatment,intentional replantation,and surgical therapy:A case report

BACKGROUND TypeⅢb dens invaginatus(DI)with a lateral canal located at the mid-third of the root is rarely reported.Here,we report a rare case of typeⅢb DI in the left upper anterior tooth with a lateral canal that led to persistent periodontitis.CASE SUMMARY A 15-year-old female patient presented with a chief complaint of pain associated with recurrent labial swelling in the area of the left anterior tooth.A diagnosis of typeⅢb DI and chronic periodontitis was made.Intentional replantation was performed after conventional endodontic treatment failed.After 6 mo,the patient was asymptomatic,but a sinus tract was observed.Cone-beam computed tomography images showed bone loss in the mesial of the mid-root.Based on methylene blue staining and microscopy images,the lateral foramen located at the middle third of the root was surgically treated.After 3 years of follow-up,the clinical findings and radiographic assessment presented a favorable prognosis of bone healing without root absorption or ankylosis.CONCLUSION TypeⅢb DI with a lateral canal can be successfully treated by root canal treatment,intentional replantation,and surgical therapy.

Mathematical Nanotechnology: Quantum Field Intentionality

Considering the finite actions of a field on the matter and the space which used to infiltrate their quantum reality at level particle, methods are developed to serve to base the concept of “intentional action” of a field and their ordered and supported effects (synergy) that must be realized for the “organized transformation” of the space and matter. Using path integrals, these transformations are decoded and their quantum principles are shown.

A Post-colonialism Approach to Intentional Mistranslation-Comparative Study of Two English Versions of Shuo Ren

Mistranslation has always been received with negative reactions among the translation community for a long time.Post-colonial translation theory forms an intersection with translatology and brings translation studies from linguistics to the hidden factors such as politics,cultures and aesthetics that influence the formation of translations.From the perspective of post-colonial translation theory,this article makes comparisons with intentional mistranslation among the two English versions of Shuo Ren,and analyzes the causes that affect the intentional mistranslation of different translators.In conclusion,translators in strong cultures may misuse intentional mistranslation to“dump”their own culture,political views,or religious beliefs,so as to promote cultural aggression against the colonized or former colonial countries.In addition,domestic translators should adopt appropriate intentional mistranslation to ensure more acceptance and spreading of Chinese culture in the world.

To What Extent are Intentional and Incidental Approaches Effective Ways of Learning Vocabulary?

Vocabulary learning and teaching usually consists of two components, namely, intentional vocabulary acquisition and incidental vocabulary acquisition. Indeed,intentional learning and incidental learning have their own characteristics and advantages, and thus they may play unequal roles in learners' vocabulary acquisition. This essay will compare intentional and incidental vocabulary acquisition approaches as well as explore to what extent these two approaches are effective.

L2 Vocabulary Acquisition Through Reading——Incidental Learning and Intentional Learning

二语词汇习得过程中主要涉及到两种不同的方法:直接学习和间接学习。本文通过调查中国非英语专业学习者在阅读语境中词汇习得现象,发现在间接学习的基础上增加直接学习对学习者不同知识层面(从认知到运用)的词汇习得能力的提高和词汇记忆有很大帮助。英语学习者的水平在产出性词汇附带习的得中起到很大作用。

Resilience-oriented intentional islanding of reconfigurable distribution power systems

The participation of distributed energy resources in the load restoration procedure,known as intentional islanding,can significantly improve the distribution system reliability.Distribution system reconfiguration can effectively alter islanding procedure and thus provide an opportunity to supply more demanded energy and reduce distribution system losses.In addition,high-impact events such as hurricanes and earthquakes may complicate the procedure of load restoration,due to the disconnection of the distribution system from the upstream grid or concurrent component outages.This paper presents a two-level method for intentional islanding of a reconfigurable distribution system,considering high-impact events.In thefirst level,optimal islands are selected according to the graph model of the distribution system.In the second level,an optimal power flow(OPF)problem is solved to meet the operation constraints of the islands by reactive power control and demand side management.The proposed problem in the first level is solved by a combination of depth first search and particle swarm optimization methods.The OPF problem in the second level is solved in DIgSILENT software.The proposed method is implemented in the IEEE 69-bus test system,and the results show the validity and effectiveness of the proposed algorithm.

Load Shedding and Restoration for Intentional Island with Renewable Distributed Generation

Due to the high penetration of renewable distributed generation(RDG),many issues have become conspicuous during the intentional island operation such as the power mismatch of load shedding during the transition process and the power imbalance during the restoration process.In this paper,a phase measurement unit(PMU)based online load shedding strategy and a conservation voltage reduction(CVR)based multi-period restoration strategy are proposed for the intentional island with RDG.The proposed load shedding strategy,which is driven by the blackout event,consists of the load shedding optimization and correction table.Before the occurrence of the large-scale blackout,the load shedding optimization is solved periodically to obtain the optimal load shedding plan,which meets the dynamic and steady constraints.When the blackout occurs,the correction table updated in real time based on the PMU data is used to modify the load shedding plan to eliminate the power mismatch caused by the fluctuation of RDG.After the system transits to the intentional island seamlessly,multi-period restoration plans are generated to optimize the restoration performance while maintaining power balance until the main grid is repaired.Besides,CVR technology is implemented to restore more loads by regulating load demand.The proposed load shedding optimization and restoration optimization are linearized to mixed-integer quadratic constraint programming(MIQCP)models.The effectiveness of the proposed strategies is verified with the modified IEEE 33-node system on the real-time digital simulation(RTDS)platform.

Three-stage method for intentional controlled islanding of power systems

Controlled islanding of power system is an emer-gency control to stop the propagation of disturbances and to avoid blackouts. This paper presents a three-stage method for intentional controlled islanding of power systems. It enables to search out reasonable islanding cutsets, which have the minimum load-generation imbalance or the minimal power flow disruption, without low-voltage problems. In the first stage, a self-adaptive graph simplification algorithm is proposed to obtain a two-terminal graph as a suitable islanding cutset search area from the original power network graph model. In the second stage, an islanding cutset search algorithm is designed to find all of islanding cutsets, including the minimum load-generation imbalance cutset, in the two-terminal graph. In the third stage, an islanding scheme checking algorithm is developed to examine the outputs of stage two. It uses the depth first search algorithm to determine reasonable islanding cutsets without low-voltage problems. The IEEE30-bus system and the IEEE 118-bus system are utilized to demonstrate the proposed method. The simulation results show its validity and accuracy in large-scale power systems.

Improving innovation and entrepreneurship education in higher institutions: the impact of "Mass Entrepreneurship and Innovation" education on undergraduates' entrepreneurial intentions

The exploration of the way"mass entrepreneurship and innovation"(MEI)education influences students'aspirations to become entrepreneurs has grown into an important area of analysis in studies related to higher education.This research intends to examine the consequences of MEI education on students'tendency towards entrepreneurship,and to put forward methods for augmenting the teaching of innovation and entrepreneurship in private higher educational establishments.To achieve this objective,questionnaires and semi-structured interviews were employed in the study,which involved a total of 197 students and five education experts.The statistical analysis of the questionnaire data revealed that MEI education was positively related to students'entrepreneurial intentions,and that both entrepreneurial experience and family entrepreneurial background played moderating roles in this relationship.The interview findings indicated that private universities could enhance educational reforms by designing talent training programs,developing diversified curricula,and developing more professional entrepreneurial platforms to encourage students'entrepreneurial intentions.This study offers fresh insights for improving and perfecting the mechanism of innovation and entrepreneurship education in private universities.

Unintentional Injury Mortality Among Children Under Five Years--China,2006−2017

What is already known about this topic?Unintentional injuries among children aged under five years is still a serious public health problem in China.Epidemiological characteristics of under-five unintentional injury are reported in single provinces and cities for China but not nationally based on the Disease Surveillance Points(DSPs)dataset.What is added by this report?Unintentional injury mortality rates for under-five decreased substantially between 2006 and 2017 in China,with the decrease occurring primarily for males and rural children.Children living in rural areas and males had higher unintentional injury mortality rates than children in urban areas and females.The major fatal types of under-five unintentional injury were drowning and road injury.What are the implications for public health practice?Further interventions need to be taken in accordance with the main types of unintentional injuries,especially effective prevention strategies used in other countries or recommended by the World Health Organization(WHO).Even with equal access to injury prevention and control services for different sexes,policy efforts should focus on higher-risk populations,especially children aged under five years who are males or reside in rural areas.

Cardiovascular health awareness,risk perception,behavioural intention and INTERHEART risk stratification among middle-aged adults in Malaysia

Objective:To investigate the interrelationship between cardiovascular health awareness,risk perception,behavioural intention,and INTERHEART risk stratification in a middle-aged adult population in Malaysia.Methods:A cross-sectional survey with convenience sampling was conducted during November 2022 and January 2023.Participants completed validated questionnaires assessing cardiovascular health awareness,risk perception of cardiovascular diseases,behavioural intention towards adopting healthy habits,and INTERHEART risk stratification score(IHRS)based on established risk factors.A total of 602 respondents were included in the final analysis.Data were analysed with independent t-test/one-way ANOVA or Mann-Whitney/Kruskal-Wallis to test the differences,Pearson correlation or linear regression test to analyze the association of independent and dependent variables.Results:There was a significant positive correlation between medical knowledge related to cardiovascular disease(CVD)and knowledge related to CVD risk prevention,risk perception,behavioural intention and IHRS(P<0.05,Pearson correlation).Notably,individuals with higher IHRS tended to have lower knowledge related to CVD and CVD risk prevention,risk perception,and behavioural intention.Males,laborers,active/former smokers,individuals with lower household income and educational levels,those involved in occupations not related to the healthcare sector,and those who did not receive the CVD health brochure or are unaware of health self-assessment tools are likely to have lower levels of knowledge,risk perception,and poorer behavioural intention regarding cardiovascular health(P<0.05,one-way ANOVA).While educational level,smoking status,awareness about CVD poster,self-assessment tools were repeatedly significantly associated with knowledge related to CVD and CVD risk prevention,risk perception,behavioral intention and/or IHRS(P<0.05,linear regression).Conclusions:These findings underscore the importance of promoting cardiovascular health awareness and risk perception among middle-aged adults to foster positive BI and reduce CVD risk.Tailored interventions targeting specific risk factors identified by INTERHEART may enhance risk stratification accuracy and facilitate targeted preventive strategies.

CBA: multi source fusion model for fast and intelligent target intention identification

How to mine valuable information from massive multisource heterogeneous data and identify the intention of aerial targets is a major research focus at present. Aiming at the longterm dependence of air target intention recognition, this paper deeply explores the potential attribute features from the spatiotemporal sequence data of the target. First, we build an intelligent dynamic intention recognition framework, including a series of specific processes such as data source, data preprocessing,target space-time, convolutional neural networks-bidirectional gated recurrent unit-atteneion (CBA) model and intention recognition. Then, we analyze and reason the designed CBA model in detail. Finally, through comparison and analysis with other recognition model experiments, our proposed method can effectively improve the accuracy of air target intention recognition,and is of significance to the commanders’ operational command and situation prediction.

KGTLIR:An Air Target Intention Recognition Model Based on Knowledge Graph and Deep Learning

As a core part of battlefield situational awareness,air target intention recognition plays an important role in modern air operations.Aiming at the problems of insufficient feature extraction and misclassification in intention recognition,this paper designs an air target intention recognition method(KGTLIR)based on Knowledge Graph and Deep Learning.Firstly,the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism.Meanwhile,the accuracy,recall,and F1-score after iteration are introduced to dynamically adjust the sample weights to reduce the probability of misclassification.After that,an intention recognition model based on Knowledge Graph is constructed to predict the probability of the occurrence of different intentions of the target.Finally,the results of the two models are fused by evidence theory to obtain the target’s operational intention.Experiments show that the intention recognition accuracy of the KGTLIRmodel can reach 98.48%,which is not only better than most of the air target intention recognition methods,but also demonstrates better interpretability and trustworthiness.

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

Heterogeneous information fusion recognition method based on belief rule structure

To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.