How does firm heterogeneity information impact the estimation of embodied carbon emissions in Chinese exports?

Using an augmented Chinese input–output table in which information about firm ownership and type of traded goods are explicitly reported, we show that ignoring firm heterogeneity causes embodied CO2 emissions in Chinese exports to be overestimated by 20% at the national level, with huge differences at the sector level, for 2007. This is because different types of firm that are allocated to the same sector of the conventional Chinese input–output table vary greatly in terms of market share, production technology and carbon intensity. This overestimation of export-related carbon emissions would be even higher if it were not for the fact that 80% of CO2 emissions embodied in exports of foreign-owned firms are, in fact, emitted by Chinese-owned firms upstream of the supply chain. The main reason is that the largest CO2 emitter, the electricity sector located upstream in Chinese domestic supply chains, is strongly dominated by Chinese-owned firms with very high carbon intensity.

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems.

A Model of Emotion as Patterned Metacontrol

Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1.

The morphofunctional approach to emotion modelling in robotics

In this conceptual paper, we discuss two areas of research in robotics, robotic models of emotion and morphofunctional machines, and we explore the scope for potential cross-fertilization between them. We shift the focus in robot models of emotion from information-theoretic aspects of appraisal to the interactive significance of bodily dispositions. Typical emotional phenomena such as arousal and action readiness can be interpreted as morphofunctional processes, and their functionality may be replicated in robotic systems with morphologies that can be modulated for real-time adaptation. We investigate the control requirements for such systems, and present a possible bio-inspired architecture, based on the division of control between neural and endocrine systems in humans and animals. We suggest that emotional epi- sodes can be understood as emergent from the coordination of action control and action-readiness, respectively. This stress on morphology complements existing research on the information-theoretic aspects of emotion.

A linked data approach to sentiment and emotion analysis of twitter in the financial domain

Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked Data approach for modelling sentiment and emotions about financial entities. We aim at integrating sentiment information from different communities or providers, and complements existing initiatives such as FIBO. The ap- proach has been validated in the semantic annotation of tweets of several stocks in the Spanish stock market, including its sentiment information.

Onyx: A Linked Data approach to emotion representation

Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on lexical resources and emotion analysis services. It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with the Lexicon Model for Ontologies (lemon), a popular RDF model for representing lexical entries. This approach also means a new and interesting way to work with different theories of emotion. As part of this work, Onyx has been aligned with EmotionML and WordNet-Affect.

Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Emotion transplantation through adaptation in HMM-based speech synthesis

This paper proposes an emotion transplantation method capable of modifying a synthetic speech model through the use of CSMAPLR adaptation in order to incorporate emotional information learned from a different speaker model while maintaining the identity of the original speaker as much as possible. The proposed method relies on learning both emotional and speaker identity information by means of their adaptation function from an average voice model, and combining them into a single cascade transform capable of imbuing the desired emotion into the target speaker. This method is then applied to the task of transplanting four emotions (anger, happiness, sadness and surprise) into 3 male speakers and 3 female speakers and evaluated in a number of perceptual tests. The results of the evaluations show how the perceived naturalness for emotional text significantly favors the use of the proposed transplanted emotional speech synthesis when compared to traditional neutral speech synthesis, evidenced by a big increase in the perceived emotional strength of the synthesized utterances at a slight cost in speech quality. A final evaluation with a robotic laboratory assistant application shows how by using emotional speech we can significantly increase the students’ satisfaction with the dialog system, proving how the proposed emotion transplantation system provides benefits in real applications.

Measuring emotion: the long and short of it

Estudio de la eficiencia en la reducción del número de términos empleados en los léxicos de respuesta emocional del consumidor: aplicación en cerveza

Embodied Religion and Liberal Society: The Obstacle of De Facto Established Religion

Recent scholarship suggests that religion should be conceived in terms of embodied social practices as much as (if not more than) a set of systematic beliefs. Such accounts of religion, I will argue, raise problems that have not been adequately treated in current discussion of the role of religion in liberal society.

Cultural universals: Measuring the semantic structure of emotion terms in English and Japanese

Research is presented on the semantic structure of 15 emotion terms as measured by judged-similarity tasks for monolingual English-speaking and monolingual and bilingual Japanese subjects. A major question is the relative explanatory power of a single shared model for English and Japanese versus culture-specific models for each language. The data support a shared model for the semantic structure of emotion terms even though some robust and significant differences are found between English and Japanese structures. The Japanese bilingual subjects use a model more like English when performing tasks in English than when performing the same task in Japanese.

Constructing a Neuroscientific Pastoral Theology of Fear and Hope

Contemporary therapeutic circles utilize the concept of anxiety to describe a variety of disorders. Emotional reductionism is a detriment to the therapeutic community and the persons seeking its help. This dissertation proposes that attention to the emotion of fear clarifies our categorization of particular disorders and challenges emotional reductionism. I propose that the emotion of fear, through its theological relationship to hope, is useful in therapeutic practice for persons who experience trauma and PTSD. I explore the differences between fear and anxiety by deconstructing anxiety. Through this process, I develop four categories which help the emotion of fear stand independent of anxiety in therapy. Temporality, behaviors, antidote and objects are categories which distinguish fear from anxiety. Together, they provide the impetus to explore the emotion of fear. Understanding the emotion of fear requires an examination of its neurophysiological embodiment. This includes the brain structures responsible for fear production, its defensive behaviors and the evolutionary retention of fear. Dual inheritance evolutionary theory posits that we evolved physically and culturally, helping us understand the inescapability of fear and the unique threats humans fear. The threats humans react to develop through subjective interpretations of experience. Sometimes threats, through their presence in our memories and imaginations, inhibit a person's ability to live out a preferred identity and experience hope. Understanding fear as embodied and subjective is important. Process theology provides a religious framework through which fear can be interpreted. In this framework, fear is developed as an adaptive human response. Moreover, fear is useful to the divine-human relationship, revealing an undercurrent of hope. In the context of the divine-human relationship fear is understood as an initial aim which protects a person from a threat, but also preserves them for novel future relationships. Utilizing a "double-listening" stance, a therapist hears the traumatic narrative and counternarratives of resistance and resilience. These counternarratives express an orientation towards hopeful futures wherein persons thrive through living out a preferred identity. A therapeutic practice incorporating the emotion of fear will utilize the themes of survival, coping and thriving to enable persons to place their traumatic narrative within their meaning systems.

The Vernacular Discourse of the "Arab Spring:" An Analysis of the Visual, the Embodied, and the Textual Rhetorics of the Karama Revolution

The Vernacular Discourse of the "Arab Spring" is a project that bridges the divide between the East and the West by offering new readings to Arab subjectivities. Through an analysis of the "Arab Spring" through the lens of vernacular discourse, it challenges the Euro-Americo-centric legacies of Orientalism in Western academia and the new wave of extremism in the Arab world by offering alternative representations of Arab bodies and subjectivities. To offer this new reading of the "Arab Spring," it explores the foundations of critical rhetoric as a theory and a practice and argues for a turn towards a critical vernacular discourse. The turn towards critical vernacular discourse is important as it urges the analyses of different artifacts produced by marginalized groups in order to understand their perspectives that have largely been foreclosed in traditional cultural studies research. Building on embodied/performative critical rhetoric, the vernacular discourses of the Arab revolutionary body examines other forms of knowledge productions that are not merely textual; more specifically, through data gathered in the Lhbib Bourguiba, Tunisia. This analysis of the political revolutionary body unveils the complexity underlining the discussion around issues of identity, agency and representation in the Middle East and North Africa, and calls for a critical study towards these issues in the region beyond the binary approach that has been practiced and applied by academics and media analysts. Hence, by analyzing vernacular discourse, this research locates a method of examining and theorizing the dialectic between agency, citizenry, and subjectivity through the study of how power structure is recreated and challenged through the use of the vernacular in revolutionary movements, as well as how marginalized groups construct their own subjectivities through the use of vernacular discourse. Therefore, highlighting the political prominence of evaluating the Arab Spring as a vernacular discourse is important in creating new ways of understanding communication in postcolonial/neocolonial settings.

Using Emotion to Foster Acceptance: A Treatment Approach for Family Therapists Working with Transgender Adolescents and their Families

Currently, there is limited research and clinical focus on family therapy with transgender adolescents. When an adolescent discloses his/her transgender identity to his/her family, the family can experience an array of emotions, such as fear, distrust, anger, and sadness, along with confusion and invalidating behavior that can threaten secure attachment among family members. The purpose of this paper is to present a family therapy treatment approach for therapists working with transgender adolescents that is both culturally sensitive to the needs of these families as well as based on a systemic family therapy model. Emotionally Focused Family Therapy (EFFT) is a systemic model that is grounded in attachment theory and focuses on using emotion as a key tool in restructuring problematic relational patterns and fostering more secure family bonds. Through the use of a hypothetical case study, this paper aims at illustrating how EFFT can help family members process feelings related to the transgender identity of an adolescent family member and restore their attachment in a manner that strengthens family relationships and bonds.

Exploring How AFFECT (A Family Focused Emotion Communication Training) and Self Psychology Are Mutually Enhancing

This paper implicitly advocates for a rapprochement between psychodynamic and behavioral approaches to psychotherapy, by exploring the similarities and differences between self psychology and A Family Focused Emotion Communication Training (AFFECT), a behavioral parent training model. Self psychology, a theory with broad applicability, has been applied to several modalities besides behavioral ones. Generally speaking, self psychology and AFFECT are both relational approaches to psychotherapy that emphasize the impact of parent responsiveness, more specifically empathic attunement, on a child's emotional development and emotion regulation. Differentiating aspects of each model are identified to enhance the other model. AFFECT has relevance for pushing self psychology theory more in the direction of operations, which has implications for enhancing the research potential of self psychology, as well as for the training of the self-psychologist. Conversely, self psychology has relevance for coaching the parent with low self-esteem and decreased self-efficacy in AFFECT, which has potential implications for AFFECT treatment outcomes.