Emotional Space Research Articles

“If only he were blind”: Shame, trauma, and dissociation among women with body dysmorphic disorder in physically intimate relationships

ABSTRACT Background Body Dysmorphic Disorder (BDD) involves a debilitating preoccupation with one’s appearance and associated difficulties in social and interpersonal relationships, according to the Diagnostic and Statistical Manual for Mental Disorders (DSM-5). Quantitative research has investigated the severity of relationship difficulties in BDD, while qualitative research has primarily focused on intrapersonal phenomena, although interpersonal difficulties, including with physical intimacy, have frequently emerged from these studies. Aims This study explores how women with BDD make sense of their lived experiences of physical intimacy in the context of current partner relationships. Method Six adult women participated in individual semi-structured interviews. The data was analysed using Interpretative Phenomenological Analysis. Results The analysis generated three superordinate themes: 1) The shame in being seen, 2) Disgust and detachment during intimacy, and 3) A flawed self, unworthy of relationships. Conclusions This study demonstrates how appearance-related concerns filter into the cognitive, behavioural, and emotional intersubjective spaces of physically intimate partnerships. Shame or trauma may be triggered and may be managed through disengagement or dissociation. Clinical implications These findings support calls for a full psychological assessment of the contextual and interpersonal components of BDD, and further suggest that psychological interventions for shame, trauma, and dissociation, such as compassion-focused therapy, imagery rescripting, or body-focused therapies, may be helpful additions to cognitive-behavioural or exposure and response prevention interventions for practitioners working with BDD.

Dream, Bliss, and the Shaping of Emotional Meaning in Beowulf

<i>Dream</i>, <i>Bliss</i>, and the Shaping of Emotional Meaning in <i>Beowulf</i>

Философско-семиотический анализ истории музыкальной знаковости: от XVII до XХ века

The philosophical analysis of the problem of the musical language as a system of special symbolism from the period of the birth of individual composer creativity to the period of the New Time described in the article. This is the first part of the theoretical interpretation of the history of musical symbolism. The philosophical and aesthetic interpretation of the sign structures of the musical language considered to be presented in the context of the evolutionary and historical development on the basis of the methodology of semiosis analysis. Composer's creativity is based on certain techniques and innovative experiments, sometimes on mathematical calculations or on the improvement of existing techniques. Beginning approximately from the 11th-14th centuries, when individual composer creativity was born, and in the epoch of the 17th-20th centuries, reaching its apogee, European composer music produced the highest examples of opus music. This is an autonomous art that sets laws for itself and does not require meaningful injections from the outside - religion or philosophy, from a household or ritual situation, from the lifestyle or everyday experiences of people. The system of autonomous opus music of the twentieth century represents, on the one hand, the absolutization of the artistic specification of the art of sounds, and on the other, the fragility and vulnerability of creativity, isolation from life concreteness or from symbols included in traditional ceremonies, ceremonies, cult life, which often alienates professional opus music from the mass audience makes it incomprehensible and inaccessible. Since music and its language have a sign-symbolic nature, the process of semiosis is the mechanism by which decoding of musical symbolism is possible. Therefore, we are talking about the philosophy of musical semiosis as a process of understanding musical significance in the context of its evolution from its inception to the present day. Musical semiosis is the process of interpreting and structuring musical signs and symbols, as a result of which the open space of human emotions and sense-values is generated. A semi-musical form of musical thinking arises in terms of symbolic and symbolic meaning-making and is a mental construction, interpretation and understanding of musical signs.

‘I Enjoy Having Someone to Rant to, I Feel Like Someone is Listening to Me’: Exploring Emotion in the Use of Qualitative, Longitudinal Diary-Based Methods

Emotions and the emotional labour of researchers have been increasingly recognised in social science disciplines, with many researchers providing personal and reflexive accounts. Such debates are less well recognised in health-related disciplines, particularly public health, who remain at earlier stages of valuing and understanding qualitative research. Drawing on personal experiences and methodological reflections gathered from a qualitative study, undertaken with young people over the course of 16 months during the COVID-19 pandemic in England, UK, the aim of this article is to offer further insight into the impact of researcher emotion, by specifically focussing on longitudinal, diary-based methods. My reflections are framed as three overlapping and intersecting themes. First, that qualitative longitudinal methods (and diary studies in particular) have enormous potential to curate rich emotional narratives. Second, that despite these positives, there are tensions or conflicting dynamics in using a method which helps to explore young people’s emotions but also involves emotional labour for the researcher. Third, that greater attention should be paid to ensuring ethical care for researchers, particularly those engaging with qualitative longitudinal and/or creative methods. Such strategies should not solely rely on self-care and must be considered at institutional or funding body level. To this end, my personal experiences and reflections, as well as those from previous offerings, are used here to underpin a framework for researchers or research teams embarking upon novel qualitative longitudinal methods: 1. Do not underestimate emotional burden. 2. Ensure meaningful debriefing is available. 3. Establish boundaries. 4. Make space for emotion throughout fieldwork as well as during analysis and writing (‘entering and exiting the field’).

Deep Learning-Based Approach for Continuous Affect Prediction From Facial Expression Images in Valence-Arousal Space

Facial emotion recognition has attracted extensive attention from the affective computing community and several approaches have been proposed, mainly providing classification of facial expressions images using a set of discrete emotional labels. The quantification of human emotions from faces has been studied in a continuous 2D emotional space of valence and arousal, that describes the level of pleasantness and the intensity of excitement, respectively. Emotion assessment using valence-arousal computation is a challenging topic with several possible applications in health monitoring, e-learning, mental health diagnosis and monitoring of customer interest. Supervised learning of emotional valence-arousal for continuous affect prediction requires labeled data. However, annotation of facial images with the values for valence and arousal requires training human experts. In this paper, we propose a new and robust approach based on deep learning for continuous affect recognition and prediction. The novelty of our approach is that it maps the discrete labels and a learned facial expression representation to the continuous valence-arousal dimensional space. Given a discrete class of emotion and a facial image, our deep learning-based approach can predict the valence and arousal values accurately. Our proposed approach outperforms existing approaches for arousal and valence prediction on AffectNet dataset and it shows an impressive generalization ability on an unseen dataset for valence prediction.

Значение феномена границы и его социальная трансформация в период первой «волны» COVID-19 и локдауна в России

The Russian lockdown 2020 introduced due to the COVID-19 pandemic pro­duced a number of changes not only in the public health, economic and justice system, but also in the sphere of understanding by society of its own place in so­cial reality. The article deals with the question of transformations in social under­standing of physical space. The authors primarily emphasize the changes of boundary phenomenon in the public perception. During the beginning of COVID-19 pandemic, in the conditions of information deficit and physical clo­sure of borders, Russia found itself in the situation, when the lack of precise knowledges about the events, associated with the global pandemic led to the degradation of established ideas about the surrounding space. The purpose of this article is to highlight the key factors, which led to the qualitative changes in the boundary understanding on the level of the social existence. For the achieve­ment of this goal the authors consecutively solve the following problems: to ana­lyze the types of the boundaries, that have been existing in the public discourse before the lockdown; to follow the process of the new boundaries-understanding genesis and to highlight the main media-factors, that led to the transformations of the boundary-phenomenon in the modern society. The methodical system of this research bases on the analyses of the narrations, existing in the Russian soci­ety short before the lockdown (spring 2020). The special attention was paid to the media background, that had constructed world view of an individual at the pan­demic’s beginning. The authors conclude, that the lockdown not only restricted the physical space for a human, but also influenced in the qualitative way on the human’s spiritual and emotional space perception. From the line, dividing two political entities, the boundary turned into the special bastion, whose func­tion consisted in, first, separation from the unknown space, where there was the danger of COVID-19, second, physic protection from this danger.

An Imaginary of Radical Hope

Many students feel despair when addressing systemic issues of ethical significance, such as climate change, and student despair has been exacerbated by the circumstances of the Covid-19 pandemic. This creates an unwelcoming space for authentic student engagement. To address the problem, we present an imaginary of radical hope, a pedagogical tool informed by trauma, for developing a brave space for class discussion. It is psychologically beneficial to acknowledge negative emotions, clearing the emotional space for students to engage. Therefore, we frame ethics courses with an uncomfortable discussion, asking students to draw from their positionality and share their feelings of hope and despair, related to course material. In this paper, we explain the problem of despair motivating the project, describe the pedagogical and ethical support of our strategy, share the assignment, activity, and examples, and discuss takeaways.

Rhetorical Resistance in Nana Akufo Addo’s Speech

The yoke of suppression upon the Africans by the European countries has left a permanent scar in the minds of African people for ages. The Europeans have not only invaded the African continent physically but also intruded upon its emotional space by creating the division of colonies for nearly hundred years across the vast land. The African continent abounds; massive resources which, from time to time, have perpetually been exploited by the colonizers from the Europe; not for the sake of the continent people but for fulfillment of the colonizers. This has had a knock-on-effect in every stratum of the African societies-be it cultural, social, economic or political. Ghana, the first country to set free in the sub-Saharan region of Africa against the European colonialism now shows its resistance to the foreign aid. Against this backdrop, this paper examines the resistance of the Ghanaian people rhetorically as the political exhortation to its best, in the speech delivered by Ghanaian President, Nana Addo Dankwa Akufo-Addo on Nov. 30, 2017, with the unexpected response to the French President, Emmanuel Macron, subverting the notion of colonial mentality that adheres to the hidden agenda of exploitation in a newer version in the name of financial aid. The president wants the youngsters of the continent to change their perspectives and mindsets of dependency only to use their sweat and toil to turn the African continent itself into a paradise. While analyzing this speech, the researcher employs Aristotelian rhetorical devices: Ethos, Logos and Pathos, and explores the underlying linguistic patterns which contribute to making Nana’s verdict so persuasive and moving to his audience. To the author, the President keeps all balance to bring out his thesis throughout the speech by virtue of both verbal and non-verbal sensitivity of his language and becomes one of the most followed leaders of the world.

Nauczanie przez zachwyt, czyli kilka myśli o edukacji

The article shows the universality of Dr. Jacek Kurek’s conception of teaching through rapture. Originally used in teaching history, this idea can be successfully adapted to lessons of the Polish language, literature and culture. Alicja Podstolec indicates three interpenetrating levels of didactic activity: unusual use of school space, building relationships with students and a congenial atmosphere in classes, and various educational activities that give the teacher the opportunity to implement the principles of teaching through rapture (involving the use of music, literature, and painting to create a space for experience and emotions). Podstolec shows that the idea of experiencing rapture, as conducive to cognition, also works well in the space of Polish language lessons, but should never be a simple duplication of solutions and ideas of other educators.

Artistic and aesthetic principles of German expressive dance in the context of the development of modern dance in the XXI century

The purpose of the article is to identify the artistic and aesthetic features and leading trends in the development of German expressive dance of the first half of the twentieth century. and determine their impact on the development of modern dance in the first decades of the XXI century. Methodology. The system method is applied, thanks to which the peculiarities of German expressive dance are considered; the method of comparative analysis, which helped to identify common and distinctive features in the central concepts of dance K. Joss, M. Wingman, and P. Bausch; method of art history and artistic and stylistic analysis, through which identified and substantiated trends in the development of German modern dance and modern dance). Scientific novelty. The artistic and aesthetic principles of German expressive dance are studied on the basis of the analysis of choreography, aesthetics, and discourse of movement K. Joss, M. Wingman, and P. Bausch; the basic theatrical concepts of the range of emotions of the leading representatives of the German expressive dance motivating physical movement are revealed; determined that P. Bausch, M. Wingman and K. Yosse work with emotional space, which is directly related to physical movement and configures their own unique aesthetics of movement experience - dancers aestheticize the human body, covered and subject to strong emotions. Conclusions. The characteristic interest of German expressionist dance to inconspicuous, accidental, or natural manifestations of corporeality, the focus on violating previously established boundaries of art, the search for innovative ways to approach the chaos of reality, causing the formation of certain models of corporeality, and others. can be clearly seen in the modern dance of the early XXI century – phenomena, representing a unique way of artistic and bodily modeling of the world, become one of the important dancers and generators of current cultural and artistic values ​​and meanings. Key words: German expressive dance, modern dance, artistic and aesthetic principles, K. Joss, M. Wigman, P. Bausch.

Narrating the Human and Singing the Sacred Song: Notes toward an Aesthetic of Biography

Drawing upon the theoretical writings of Tzvetan Todorov and Georg Lukács on the subject of the novel, this essay argues for more widespread recognition of the biography as a literary genre. It frames the genre of biography as a genre of radical incompleteness, discussing the search for verisimilitude and the tendency toward fragmentation in the biographer’s pursuit — a quality that describes not only the biographer’s sources, but also the contingent, broken nature of the intellectual and emotional space that both the biographical subject and the biographer herself inhabit.

Virtual Education for Engaging Gen-Z Students in Meaningful Learning: Its Psychological Impact

Compared to previous generations, Gen-Z has been born into technology, and takes high speed internet, mobile devices and social networking for granted. Being truly digital natives, life online is life itself for this generation. The recent pandemic has brought about forced changes in their physical environment and endangers emotional space. Changes in the learning environment have been imposed at short notice, with virtual education becoming the main mode of learning, instead of being a useful adjunct. This has impacted Generation-Z not only in terms of learning styles but also in terms of psychological wellbeing. . It is difficult to predict how a generation of digital natives would respond to the stress imposed by virtual learning that has been thrust upon them. This article aims to explore the possible psychological impact of virtual learning on Gen-Z and strives to find out how best they can cope up with this abrupt change in learning style.

A multilayer affective computing model with evolutionary strategies reflecting decision-makers’ preferences in process control

Many industrial control problems related to multi-objective optimization, such as controller parameters tuning, often require operators to perform multiple-step interactions without considering the changes of decision-makers’ affective states and quantitative description of decision-makers’ preferences during the interactive decision. Regarding this problem, we developed a multilayer affective computing model (MACM), including three factors: human personality, emotional space, and affective states, to demonstrate the iterative affective computing during the interactions. First, a concise model of affective computing-driven interactive decision-making was built before three submodules involved were described in detail. (1) An affective state recognition method based on facial expressions was presented, providing the basis for obtaining expert affective states during decision-making. (2) An identification method of affective parameters was given, providing an approach to describing personalized affective state-changing rules of different persons. (3) A definition of decision-makers’ preferences in interactive decision-making was specified. In addition, a decision-makers’ preferences mining method was developed by the MACM and an iterative learning control (ILC) strategy. Thus, we proposed affective computing-driven interactive decision-making method, which provided a simplified approach to converting the interactive decision problems based on decision-makers’ preferences to decision issues based on incremental decision vector, along with assisting computers to learn from human experts and perform decision-making automatically in a general sense. Then, two typical process control cases—PI controller tuning for decoupling problem and manipulate vector optimization for batch processes were used to show the correctness and effectiveness of the contributions. Compared with other traditional optimization algorithms without affective state tracking and recognition (fuzzy control, ILC, reinforcement learning, and so on), experimental results indicated that the proposed method could achieve good performance. Finally, this study presented the efficiency and limitations of using this technique for a specific application

Continuous Emotion Recognition with Spatiotemporal Convolutional Neural Networks

Facial expressions are one of the most powerful ways to depict specific patterns in human behavior and describe the human emotional state. However, despite the impressive advances of affective computing over the last decade, automatic video-based systems for facial expression recognition still cannot correctly handle variations in facial expression among individuals as well as cross-cultural and demographic aspects. Nevertheless, recognizing facial expressions is a difficult task, even for humans. This paper investigates the suitability of state-of-the-art deep learning architectures based on convolutional neural networks (CNNs) to deal with long video sequences captured in the wild for continuous emotion recognition. For such an aim, several 2D CNN models that were designed to model spatial information are extended to allow spatiotemporal representation learning from videos, considering a complex and multi-dimensional emotion space, where continuous values of valence and arousal must be predicted. We have developed and evaluated convolutional recurrent neural networks, combining 2D CNNs and long short term-memory units and inflated 3D CNN models, which are built by inflating the weights of a pre-trained 2D CNN model during fine-tuning, using application-specific videos. Experimental results on the challenging SEWA-DB dataset have shown that these architectures can effectively be fine-tuned to encode spatiotemporal information from successive raw pixel images and achieve state-of-the-art results on such a dataset.

An Expatriate’s perspective of India: A study of India- A Wounded Civilization

Expatriate writing, born out of a paradox between movement and resettlement, a sense of belongingness and alienation, has come to occupy a significant position between cultures and countries. It provides fresh perspectives and raises new theoretical formulations. In the process of trying to understand, or rather unravel, it constructs new identities since such creative expressions involve redefining positions and renegotiating boundaries of the emotional and psychological space one can relate to or which one considers his very own. Cultures travel within the psychological realm with the writers living abroad as they shuttle between the physical and psychological paradigms of two different nations. Cultural theories today are being rewritten by such writers who occupy the “in between’ position living on the peripherals of two cultures.

Study of the emotionality of phraseology in general and Turkic linguistics

The article studies human emotions in the emotional and linguacultural space, particularly focused on the study of emotional intensity of phraseology. The author considers the concepts of emotional codes, human feelings and ways of expressing them, and analyzes new approaches to the study of emotionality. The main purpose of the article is to describe the diversity of the emotional content of the word and show the importance of studying the emotional code of the language in modern linguistics and linguocultural context based on Turkic languages. Therefore, since the object is an emotional phraseological units, the focus is on the phraseology that comes with the components of ethno-cultural expressive meaning. The article compares and analyzes phraseological units in the Kazakh, Azerbaijani and Turkish languages ​​and their emotional, discursive, pragmatic meaning. The method of comparing emosems in Turkic languages ​​with their equivalents in other languages ​​is also used. As the result of the work were analyzed the emotional words (phraseology) of the Kazakh and Turkic languages ​​and were revealed their place in the speech act and the significance of scrutinizing these elements. Keywords: Kazakh phraseological units, Turkic phraseological units, phraseological units, emotional intensity of phraseological units, emotionality. &nbsp; &nbsp

Memristive Circuit Design of Brain-Inspired Emotional Evolution Based on Theories of Internal Regulation and External Stimulation.

In this work, a bionic memristive circuit with functions of emotional evolution is proposed by mimicking the emotional circuit in limbic system, which can perform unconscious and conscious emotional evolutions by using theories of internal regulation and external stimulation respectively. Two kinds of memristive models, volatile and non-volatile, play key roles in the process of emotional evolution. That is, the internal regulation is mainly responsible for simulating the unconscious evolution process over time by using the forgetting effect of the volatile memristor. The external stimulation is mainly responsible for using the memristance plasticity of the non-volatile memristor to simulate the evolutionary learning behavior under the action of multi-modal inputs (such as visual, speech and text signals), so as to realize the conscious emotional evolution. A two-dimensional (2D) emotional state space consisted of valence and arousal signals is adopted, the evolution behaviors are performed on the basis of valence and arousal signals in the space, in order to achieve continuous emotional evolution and express the evolved emotions intuitively. Due to the use of memristors, the proposed circuit can realize in-memory computing, which fundamentally avoids the problem of storage wall and constructs a brain-inspired information processing architecture. The simulation results in PSPICE show that a nonlinear mapping relationship between inputs and outputs is constructed through the proposed circuit, which can carry out diversified emotional evolution based on the designed internal regulation and external stimulation evolution circuits.

Mapping Discrete Emotions in the Dimensional Space: An Acoustic Approach

A frequently used procedure to examine the relationship between categorical and dimensional descriptions of emotions is to ask subjects to place verbal expressions representing emotions in a continuous multidimensional emotional space. This work chooses a different approach. It aims at creating a system predicting the values of Activation and Valence (AV) directly from the sound of emotional speech utterances without the use of its semantic content or any other additional information. The system uses X-vectors to represent sound characteristics of the utterance and Support Vector Regressor for the estimation the AV values. The system is trained on a pool of three publicly available databases with dimensional annotation of emotions. The quality of regression is evaluated on the test sets of the same databases. Mapping of categorical emotions to the dimensional space is tested on another pool of eight categorically annotated databases. The aim of the work was to test whether in each unseen database the predicted values of Valence and Activation will place emotion-tagged utterances in the AV space in accordance with expectations based on Russell’s circumplex model of affective space. Due to the great variability of speech data, clusters of emotions create overlapping clouds. Their average location can be represented by centroids. A hypothesis on the position of these centroids is formulated and evaluated. The system’s ability to separate the emotions is evaluated by measuring the distance of the centroids. It can be concluded that the system works as expected and the positions of the clusters follow the hypothesized rules. Although the variance in individual measurements is still very high and the overlap of emotion clusters is large, it can be stated that the AV coordinates predicted by the system lead to an observable separation of the emotions in accordance with the hypothesis. Knowledge from training databases can therefore be used to predict AV coordinates of unseen data of various origins. This could be used to detect high levels of stress or depression. With the appearance of more dimensionally annotated training data, the systems predicting emotional dimensions from speech sound will become more robust and usable in practical applications in call-centers, avatars, robots, information-providing systems, security applications, and the like.

EEG Emotion Recognition via Graph-based Spatio-Temporal Attention Neural Networks.

Emotion recognition based on electroencephalography (EEG) signals has been receiving significant attention in the domains of affective computing and brain-computer interfaces (BCI). Although several deep learning methods have been proposed dealing with the emotion recognition task, developing methods that effectively extract and use discriminative features is still a challenge. In this work, we propose the novel spatio-temporal attention neural network (STANN) to extract discriminative spatial and temporal features of EEG signals by a parallel structure of multi-column convolutional neural network and attention-based bidirectional long-short term memory. Moreover, we explore the inter-channel relationships of EEG signals via graph signal processing (GSP) tools. Our experimental analysis demonstrates that the proposed network improves the state-of-the-art results in subject-wise, binary classification of valence and arousal levels as well as four-class classification in the valence-arousal emotion space when raw EEG signals or their graph representations, in an architecture coined as GFT-STANN, are used as model inputs.

Exploration meets exploitation: Multitask learning for emotion recognition based on discrete and dimensional models

Discrete and dimensional models can be applied to emotion recognition tasks in both psychology and computer science. Both models are advantageous. Specifically, in dimensional models, the differences and similarities between emotions can be easily estimated because of the continuity of numerical vectors used for their representation. In discrete models, core emotions usually have better interpretations, which biologically determine the emotional responses, and their expression and recognition are the same for all individuals regardless of cultural or ethnic differences. However, the problem of building a cooperative mechanism by integrating the advantages of these two models has been ignored for a long time. Therefore, in this work, we introduce an exploration and exploitation mechanism to address this problem. This mechanism not only enables the emotion recognition model to accurately locate simple and discrete emotional anchors in the entire continuous emotion space (exploration) but also encourages it to effectively search for complex and subtle emotional states near the emotional anchors (exploitation). Specifically, we propose a multitask graph neural network (MGNN) to implement this mechanism, introduce a weighting scheme to better balance the exploration and exploitation according to the task-dependent uncertainty, and filter out the key contextual features in different tasks by applying a self-attention mechanism. The experimental results show that our MGNN outperforms advanced methods on the tested datasets.