Attachment Styles and Traumatic Responses: Exploring the Impact of Parental Interaction on Child Development and Coping Mechanisms

This article explores the intricate relationship between attachment styles formed during early childhood and the subsequent responses to traumatic events, particularly the death of a parent. Drawing on the theoretical framework of attachment theory and incorporating contemporary research, the paper discusses how parental interactions shape the neural circuitry of infants and children, influencing their ability to form secure or insecure attachments. These attachment styles, in turn, play a critical role in determining the child’s coping mechanisms when faced with trauma. This paper focuses on trying to understand how attachment theory is connected to the reaction to trauma with a highlight on the four major styles of attachments which are secure, anxious, avoidant, and disorganized to mention but a few, and how they influence stress and adversity in children. Attachment theory holds that human beings’ ability to form affectional bonds in infancy determines their patterns of relatedness across the life cycle. The type of attachment that is secure usually supports healthy adaptation and good coping mechanisms regardless of the trauma in the childhood of the child. While secure attachment mostly facilitates favorable trauma-related outcomes, anxious or avoidant attachment can exacerbate or alter the responses. The caregiving system that is avoidant attachment has implications of autonomous self-functioning which has features of suppression of the emotional response and poor search for emotional support during stress. From the principles of developmental psychology and trauma theory, the paper also focuses on the major significance of the child’s early caregivers’ interactions that define the resilience and vulnerability factor. This knowledge is therefore critical in designing specific interventions based on the improvement of coping behaviors and emotional regulatory systems of children who have been exposed to trauma. Finally, we have the synthesis of new knowledge about the role of secure attachment relationships as its fundamental element in shaping adaptive traumatization and psychological development. The article also delves into the physiological processes involved in emotional regulation and the role of cortisol in disrupting attachment. Finally, the implications of these findings for therapeutic interventions and the challenges of addressing prolonged grief and traumatic responses in clinical settings are considered.

Effect of emotion management and nursing on patients with painless induced abortion after operation

BACKGROUND With an estimated 121 million abortions following unwanted pregnancies occurring worldwide each year,many countries are now committed to protecting women’s reproductive rights.AIM To analyze the impact of emotional management and care on anxiety and contraceptive knowledge mastery in painless induced abortion(IA)patients.METHODS This study was retrospective analysis of 84 patients with IA at our hospital.According to different nursing methods,the patients were divided into a control group and an observation group,with 42 cases in each group.Degree of pain,rate of postoperative uterine relaxation,surgical bleeding volume,and postoperative bleeding volume at 1 h between the two groups of patients;nursing satisfaction;and mastery of contraceptive knowledge were analyzed.RESULTS After nursing,Self-Assessment Scale,Depression Self-Assessment Scale,and Hamilton Anxiety Scale scores were 39.18±2.18,30.27±2.64,6.69±2.15,respectively,vs 45.63±2.66,38.61±2.17,13.45±2.12,respectively,with the observation group being lower than the control group(P<0.05).Comparing visual analog scales,the observation group was lower than the control group(4.55±0.22 vs 3.23±0.41;P<0.05).The relaxation rate of the cervix after nursing,surgical bleeding volume,and 1-h postoperative bleeding volumes were 25(59.5),31.72±2.23,and 22.41±1.23,respectively,vs 36(85.7),42.39±3.53,28.51±3.34,respec tively,for the observation group compared to the control group.The observation group had a better nursing situation(P<0.05),and higher nursing satisfaction and contraceptive knowledge mastery scores compared to the control group(P<0.05).CONCLUSION The application of emotional management in postoperative care of IA has an ideal effect.

Implicit Knowledge, Explicit Knowledge and Interaction in the College English Teaching

In each act or process of knowledge, all components can be classified into two kinds: tacit (implicit) components and focal (explicit) components. This article, first of all introduces the terms of implicit knowledge, explicit knowledge and their distinctions in the process of English language learning and then provides interactive instruction design to improve learners' communicative competence.

Knowledge-enriched joint-learning model for implicit emotion cause extraction

Emotion cause extraction(ECE)task that aims at extracting potential trigger events of certain emotions has attracted extensive attention recently.However,current work neglects the implicit emotion expressed without any explicit emotional keywords,which appears more frequently in application scenarios.The lack of explicit emotion information makes it extremely hard to extract emotion causes only with the local context.Moreover,an entire event is usually across multiple clauses,while existing work merely extracts cause events at clause level and cannot effectively capture complete cause event information.To address these issues,the events are first redefined at the tuple level and a span-based tuple-level algorithm is proposed to extract events from different clauses.Based on it,a corpus for implicit emotion cause extraction that tries to extract causes of implicit emotions is constructed.The authors propose a knowledge-enriched jointlearning model of implicit emotion recognition and implicit emotion cause extraction tasks(KJ-IECE),which leverages commonsense knowledge from ConceptNet and NRC_VAD to better capture connections between emotion and corresponding cause events.Experiments on both implicit and explicit emotion cause extraction datasets demonstrate the effectiveness of the proposed model.

Interpreting and Extracting Open Knowledge for Human-Robot Interaction

A more natural way for non-expert users to express their tasks in an open-ended set is to use natural language. In this case,a human-centered intelligent agent/robot is required to be able to understand and generate plans for these naturally expressed tasks. For this purpose, it is a good way to enhance intelligent robot's abilities by utilizing open knowledge extracted from the web, instead of hand-coded knowledge. A key challenge of utilizing open knowledge lies in the semantic interpretation of the open knowledge organized in multiple modes, which can be unstructured or semi-structured, before one can use it.Previous approaches used a limited lexicon to employ combinatory categorial grammar(CCG) as the underlying formalism for semantic parsing over sentences. Here, we propose a more effective learning method to interpret semi-structured user instructions. Moreover, we present a new heuristic method to recover missing semantic information from the context of an instruction. Experiments showed that the proposed approach renders significant performance improvement compared to the baseline methods and the recovering method is promising.

A Method of Multimodal Emotion Recognition in Video Learning Based on Knowledge Enhancement

With the popularity of online learning and due to the significant influence of emotion on the learning effect,more and more researches focus on emotion recognition in online learning.Most of the current research uses the comments of the learning platform or the learner’s expression for emotion recognition.The research data on other modalities are scarce.Most of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on data.Because of the need for other modal research data,we construct a synchronous multimodal data set for analyzing learners’emotional states in online learning scenarios.The data set recorded the eye movement data and photoplethysmography(PPG)signals of 68 subjects and the instructional video they watched.For the problem of ignoring the instructional videos on learners and ignoring the knowledge,a multimodal emotion recognition method in video learning based on knowledge enhancement is proposed.This method uses the knowledge-based features extracted from instructional videos,such as brightness,hue,saturation,the videos’clickthrough rate,and emotion generation time,to guide the emotion recognition process of physiological signals.This method uses Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM)networks to extract deeper emotional representation and spatiotemporal information from shallow features.The model uses multi-head attention(MHA)mechanism to obtain critical information in the extracted deep features.Then,Temporal Convolutional Network(TCN)is used to learn the information in the deep features and knowledge-based features.Knowledge-based features are used to supplement and enhance the deep features of physiological signals.Finally,the fully connected layer is used for emotion recognition,and the recognition accuracy reaches 97.51%.Compared with two recent researches,the accuracy improved by 8.57%and 2.11%,respectively.On the four public data sets,our proposed method also achieves better results compared with the two recent researches.The experiment results show that the proposed multimodal emotion recognition method based on knowledge enhancement has good performance and robustness.

Implications of The Gift of the Magi for Moral Education of Teenagers From the Perspective of Interaction Ritual Chains

Adolescence is a pivotal moment in shaping one’s character and holds great implications for one’s values and personal growth.The Gift of the Magi by O.Henry portrays how an ordinary young couple in difficult financial circumstances managed to show their love for each other,eulogizing truth,goodness,and beauty in humanity.We conducted a thorough examination of the significance of moral values conveyed in The Gift of the Magi for teenager education using the“situation-emotion-symbol”model that is based on Randall Collins’theory of interaction ritual chains in order to establish an interaction ritual chain model for moral education of teenagers.Our study reveals that situated cognition is useful in constructing the focus of attention for the moral education of teenagers;that shared emotion is the driving force for achieving moral education of teenagers;and that symbolic connections help teenagers put the virtues they’ve learned from The Gift of the Magi into action and provides effective measures that can significantly contribute to the cultivation and implementation of moral education among teenagers.

First Time Demonstration of the Quantum Interference Effect during Integration of Cognition and Emotion in Children

Quantum cognition is a scientific approach to cognitive phenomena which makes use of the mathematical formalism of quantum theory. Quantum interference effect constitutes one of this theory’s main tenets and has been repeatedly demonstrated experimentally, in the last decade, in adult subjects. In the present paper, we aim to demonstrate, for the first time, the existence of thequantum interference effect on children during an experiment involving an integration of cognition and emotion. Our positive results consolidate the presuppositions of quantum cognition, enlarging its field of application to children’s mental apparatus and evidence the important question to consider the quantum model in the current investigated question of the interaction of cognition and emotion in children at neurological and psychological levels.

Applying Nearpod to the Teaching Chinese as a Second Language Class to Enhance Interactions and Collaborations in the Secondary Schools

The quick spread of the epidemic since 2019 together with fast advancing of technology has exposed teachers to online education,including Teaching Chinese as a Second Language(TCSL)classrooms.Some Chinese as a Second Language(CSL)teachers were reluctant to utilize technology tools in their teaching due to the lack of technological knowledge.Thus,this study designed a CSL curriculum with the lens of the TPACK framework(Technological Pedagogical Content Knowledge).Nearpod was specifically adopted as a web-based technology tool to support the teaching Chinese language due to its powerful functions provided.Nearpod allows teachers to design interactive activities in multiple ways to facilitate interactions and collaboration in the CSL learning process.This paper aimed to help Chinese teachers improve their understanding of how to effectively integrate technology into CSL teaching.Chinese teachers will develop a deeper comprehension of distance teaching from the perspectives of technology,pedagogy,and content knowledge,enhance students’deeper learning,and promote interaction and collaboration in L2 class.The effective use of the technology can develop language skills in a meaningful context knowledge with the guidance of pedagogical content knowledge.

Information and Knowledge Flows in the Network of the Education through Work for Family Health Program

The Education through Work for Family Health Program (PET Saúde, in Portuguese) created by the Ministries of Education and Health is a proposal to integrate service, learning and community. The goal of PET Saúde is to foster the formation of learning groups within the Family Health Strategy scope. While being studied at the city of Feira de Santana, the program was structured with one coordinator and eleven tutorial groups, distributed in 27 family health offices, which constituted a social network where the construction and knowledge diffusion occur. This article proposes the analysis of the information and knowledge flows of this network through the social networks analysis. This study highlights the play of PET Saúde’s coordinator in the processes of organization and articulation as central vertex of the network, and some scholars in the articulation of different tutorial groups. The results show a fragmentation in the PET Saúde network when the coordinator vertex is removed, whereas 5 components are generated where 4 tutorial groups appear isolated.

A novel speech emotion recognition algorithm based on combination of emotion data field and ant colony search strategy

In order to effectively conduct emotion recognition from spontaneous, non-prototypical and unsegmented speech so as to create a more natural human-machine interaction; a novel speech emotion recognition algorithm based on the combination of the emotional data field （EDF） and the ant colony search （ACS） strategy, called the EDF-ACS algorithm, is proposed. More specifically, the inter- relationship among the turn-based acoustic feature vectors of different labels are established by using the potential function in the EDF. To perform the spontaneous speech emotion recognition, the artificial colony is used to mimic the turn- based acoustic feature vectors. Then, the canonical ACS strategy is used to investigate the movement direction of each artificial ant in the EDF, which is regarded as the emotional label of the corresponding turn-based acoustic feature vector. The proposed EDF-ACS algorithm is evaluated on the continueous audio）＇visual emotion challenge （AVEC） 2012 dataset, which contains the spontaneous, non-prototypical and unsegmented speech emotion data. The experimental results show that the proposed EDF-ACS algorithm outperforms the existing state-of-the-art algorithm in turn-based speech emotion recognition.

EVOLUTIONARY GAME OF DYNAMIC KNOWLEDGE EXCHANGING IN KNOWLEDGE INTERACTION

Characteristics of knowledge exchanging behavior among individual agents in a knowledge dynamic interaction system are studied by using the game theory. An analytic model of evolutionary game of continuous dynamic knowledge interaction behavior is founded based on the structure of the evolutionary game chain. Possible evolution trends of the model are discussed. Finally, evolutionary stable strategies （ESSs） of knowledge transactions among individual agents in the knowledge network are identified by simulation data. Stable charicteristics of ESS in a continuous knowledge exchanging team help employee to communicate and grasp the dynamic regulation of shared knowledge.

A Facial Expression Emotion Recognition Based Human-robot Interaction System

A facial expression emotion recognition based human-robot interaction(FEER-HRI) system is proposed, for which a four-layer system framework is designed. The FEERHRI system enables the robots not only to recognize human emotions, but also to generate facial expression for adapting to human emotions. A facial emotion recognition method based on2D-Gabor, uniform local binary pattern(LBP) operator, and multiclass extreme learning machine(ELM) classifier is presented,which is applied to real-time facial expression recognition for robots. Facial expressions of robots are represented by simple cartoon symbols and displayed by a LED screen equipped in the robots, which can be easily understood by human. Four scenarios,i.e., guiding, entertainment, home service and scene simulation are performed in the human-robot interaction experiment, in which smooth communication is realized by facial expression recognition of humans and facial expression generation of robots within 2 seconds. As a few prospective applications, the FEERHRI system can be applied in home service, smart home, safe driving, and so on.

Impress of intergenerational emotional support on the depression in non-cohabiting parents

BACKGROUND Mental health is one of the important dimensions of health,while depression is an important indicator of mental health evaluation.AIM To investigate the association between intergenerational emotional support and depression of non-cohabiting parents(≥45 years old)in China.METHODS We used the fourth wave data from the China Health and Retirement Longitudinal Study(2015).The data was made up of ten main modules,the associated two datasets,and five constructed datasets.The first step is to select the corresponding module data according to the purpose of this study.Moreover,the data of the six modules are integrated by the unique ID code and we choose depression and non-cohabiting items as the selection conditions.4810 samples were selected,which mainly included data on intergenerational emotional support and the individual scores on depressive symptoms.RESULTS The average age of 4810 respondents was(60.56±14.613)years old.Females were accounted for more than half of the samples(52.6%).74.0%respondents from rural areas and approximately 63.3%of the participants had a chronic disease.The mean value of the CESD-10 score was 13.06(SD5.225).Both faces to face and phone contacts were protective factors on depression symptoms in the mid-aged and seniors in China(P<0.05).In terms of the frequency of face to face contact,the more frequently you met your parents,the lower your parents'depressive score was.Also,phone contact variable results are displayed as a positive correlation completely between inter-generational contacts from children and depressive symptoms in non-cohabiting parents in China.Children’s education level and income level were also reducing the risk of depression in noncohabiting parents.However,gender,children’s numerous,chronic disease and chronic disease number were the risk factors.CONCLUSION Intergenerational emotional support is associated with depressive symptoms in non-cohabiting parents in China.However,the relationship was also affected by other variables.

EP-Bot: Empathetic Chatbot Using Auto-Growing Knowledge Graph

People occasionally interact with each other through conversation.In particular,we communicate through dialogue and exchange emotions and information from it.Emotions are essential characteristics of natural language.Conversational artificial intelligence is an integral part of all the technologies that allow computers to communicate like humans.For a computer to interact like a human being,it must understand the emotions inherent in the conversation and generate the appropriate responses.However,existing dialogue systems focus only on improving the quality of understanding natural language or generating natural language,excluding emotions.We propose a chatbot based on emotion,which is an essential element in conversation.EP-Bot(an Empathetic PolarisX-based chatbot)is an empathetic chatbot that can better understand a person’s utterance by utilizing PolarisX,an autogrowing knowledge graph.PolarisX extracts new relationship information and expands the knowledge graph automatically.It is helpful for computers to understand a person’s common sense.The proposed EP-Bot extracts knowledge graph embedding using PolarisX and detects emotion and dialog act from the utterance.Then it generates the next utterance using the embeddings.EP-Bot could understand and create a conversation,including the person’s common sense,emotion,and intention.We verify the novelty and accuracy of EP-Bot through the experiments.

Study of the affective interaction in college English teaching

Affect plays a significant role in college English teaching and learning, in which teachers, learners, tasks and contexts or environments interact with each other, developing a system of affective interaction. In the system, the teacher is a facilitator and mediator and the learner is the subject of English learning. In a harmonious and friendly classroom environment, with the knowledge transmission blending in well with the cultivation of affect, attitudes and values, students＇ cognitive and emotional development can be promoted. The experimental results of the present study indicated that students in the affective college English classroom did significantly better （p〈 .05） in cognition than before. Furthermore, the analyses of the two surveys showed that attention to affective interaction in college English teaching helped students enhance their interest in college English learning, cross-cultural awareness, self-confidence, interpersonal intelligence, and so forth. Therefore, our conclusion is that attention to affective interaction in college English classroom teaching is conducive to students＇ personal growth and a more holistic development.

The Internet Catalyzes Tech Innovation and Economic Growth

“Internet Plus”in recent years,has gained traction among universities,research institutes and even the corporate world.The Internet,enabling fast and interactive data transmission in real-time,has facilitated the openness and sharing of knowledge,the commercialization of academic achievements,and the development of platforms for academic exchanges.

Discussion on the Expression of emotional appeal of consumer in Food Packaging Design

As the rapid development of modem society and the commodity economy, goods of each enterprise must through the competition to sales of commodities in the market have a foothold. Now the product packaging design requires not only simple packaging. but need to highlight the design sense, using a different visual language to convey product information to consumers, will also promise to consumers is conveyed. To the consumer＇s emotional experience as the main design starting point, only the value of the product itself into the purchase value of consumers, so as to reflect the role and value of the design. Now we are facing the problem is how to promote the sale of products through the design of product packaging, so that consumers have a strong desire to buy.

A discussion of the emotive element of knowledge service practice:An empirical study at the Chinese Academy of Sciences

With the arrival of the information age, research activities focused on the practice and approaches of knowledge services are on a marked increase as evidenced in the publications of social sciences. According to a social network analysis on knowledge service related literature, it reveals that information and knowledge workers often fail to take such an important element as the functional role of an emotive engagement into consideration in their study of knowledge services. It has increasingly become an issue of high profile with the rapid development of digital libraries and their web-based knowledge services in China and anywhere else in the world. In order to have a clearer understanding about issues involved in knowledge servicing so as to maximize the effectiveness and efficiency of digital libraries in their knowledge service performance, the author has conducted surveys for seven times on the online information seeking behavior of graduate students at the Chinese Academy of Sciences with such research methods as questionnaires, interviews and natural observations during September 2006-June 2009. The research result has showed the emotive element has an important role in the user's information seeking behavior and in knowledge services practice. Therefore, knowledge services rendered may be more effective by adding the emotiveness-oriented communication element into such practice. This paper recommends that such an emotiveness-oriented communication approach should be carefully studied and factored into libraries' knowledge services practice.