4,386 research outputs found

    A Spark Of Emotion: The Impact of Electrical Facial Muscle Activation on Emotional State and Affective Processing

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    Facial feedback, which involves the brain receiving information about the activation of facial muscles, has the potential to influence our emotional states and judgments. The extent to which this applies is still a matter of debate, particularly considering a failed replication of a seminal study. One factor contributing to the lack of replication in facial feedback effects may be the imprecise manipulation of facial muscle activity in terms of both degree and timing. To overcome these limitations, this thesis proposes a non-invasive method for inducing precise facial muscle contractions, called facial neuromuscular electrical stimulation (fNMES). I begin by presenting a systematic literature review that lays the groundwork for standardising the use of fNMES in psychological research, by evaluating its application in existing studies. This review highlights two issues, the lack of use of fNMES in psychology research and the lack of parameter reporting. I provide practical recommendations for researchers interested in implementing fNMES. Subsequently, I conducted an online experiment to investigate participants' willingness to participate in fNMES research. This experiment revealed that concerns over potential burns and involuntary muscle movements are significant deterrents to participation. Understanding these anxieties is critical for participant management and expectation setting. Subsequently, two laboratory studies are presented that investigated the facial FFH using fNMES. The first study showed that feelings of happiness and sadness, and changes in peripheral physiology, can be induced by stimulating corresponding facial muscles with 5–seconds of fNMES. The second experiment showed that fNMES-induced smiling alters the perception of ambiguous facial emotions, creating a bias towards happiness, and alters neural correlates of face processing, as measured with event-related potentials (ERPs). In summary, the thesis presents promising results for testing the facial feedback hypothesis with fNMES and provides practical guidelines and recommendations for researchers interested in using fNMES for psychological research

    Speech-based automatic depression detection via biomarkers identification and artificial intelligence approaches

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    Depression has become one of the most prevalent mental health issues, affecting more than 300 million people all over the world. However, due to factors such as limited medical resources and accessibility to health care, there are still a large number of patients undiagnosed. In addition, the traditional approaches to depression diagnosis have limitations because they are usually time-consuming, and depend on clinical experience that varies across different clinicians. From this perspective, the use of automatic depression detection can make the diagnosis process much faster and more accessible. In this thesis, we present the possibility of using speech for automatic depression detection. This is based on the findings in neuroscience that depressed patients have abnormal cognition mechanisms thus leading to the speech differs from that of healthy people. Therefore, in this thesis, we show two ways of benefiting from automatic depression detection, i.e., identifying speech markers of depression and constructing novel deep learning models to improve detection accuracy. The identification of speech markers tries to capture measurable depression traces left in speech. From this perspective, speech markers such as speech duration, pauses and correlation matrices are proposed. Speech duration and pauses take speech fluency into account, while correlation matrices represent the relationship between acoustic features and aim at capturing psychomotor retardation in depressed patients. Experimental results demonstrate that these proposed markers are effective at improving the performance in recognizing depressed speakers. In addition, such markers show statistically significant differences between depressed patients and non-depressed individuals, which explains the possibility of using these markers for depression detection and further confirms that depression leaves detectable traces in speech. In addition to the above, we propose an attention mechanism, Multi-local Attention (MLA), to emphasize depression-relevant information locally. Then we analyse the effectiveness of MLA on performance and efficiency. According to the experimental results, such a model can significantly improve performance and confidence in the detection while reducing the time required for recognition. Furthermore, we propose Cross-Data Multilevel Attention (CDMA) to emphasize different types of depression-relevant information, i.e., specific to each type of speech and common to both, by using multiple attention mechanisms. Experimental results demonstrate that the proposed model is effective to integrate different types of depression-relevant information in speech, improving the performance significantly for depression detection

    Developing International Mindedness through the Arts in the International Baccalaureate (IB) Diploma Programme (DP): An International Survey Design Conducted across all Continents

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    One distinct purpose of international education is to develop greater international understanding and intercultural competences. For the International Baccalaureate, this translates into students developing international mindedness throughout its programmes and courses. However, international mindedness is not measured and the impact of the programmes on the development of international mindedness remains mainly anecdotal. Furthermore, in the Diploma Programme, the choice of Arts courses is optional and the value of an Arts education, or specifically the value of taking a Diploma Programme Arts course in developing international mindedness, is equally unclear. This study investigated the development of international mindedness in students who opted for a Diploma Programme Arts course versus those who did not. The study followed a repeated measures, comparative and mixed-methods research design using a survey tool for data collection. The survey consisted of a quantitative section based on existing surveys and a qualitative section with six open-ended questions. The quantitative data showed an increase in intercultural knowledge and behaviours, while no change in attitudes, and a decrease in values was identified for both student groups, Diploma Programme Arts and Non-Arts-students. Furthermore, there was an increase in intercultural communication skills particularly in Diploma Programme Arts-students. Qualitative data analysis revealed a spectrum of categories of responses. The qualitative data also identified themes in addition to those identified in International Baccalaureate documentation and literature. Recommendations include for the International Baccalaureate Organization to integrate some of the emerging themes in their documentations, for example themes relating to adaptability and interconnectedness, which may also provide an interesting focus for curriculum design. Furthermore, curriculum and programme design should place a greater focus on the development of attitudes and values in the Diploma Programme and a reconsideration of the optionality of the Arts in this context

    A critical sociolinguistic study of diasporization among Hungarians in Catalonia

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    This thesis investigates how contemporary diasporas evolve, how diasporization takes place under the conditions of late modernity, and how language features in this process. By diasporization, I refer to the process(es) in which diasporic groups emerge and individuals start to engage in certain diasporic practices, i.e., social practices that are associated with their ethnic or national origin or with their imagined homeland, or with boundary management in the host-land. The research was an ethnographically informed critical sociolinguistic study of first-generation Hungarians in Catalonia that drew on collaborative methodologies in order to include the emic perspectives of the participants. To capture these perspectives, the research combined many data generating techniques, such as ethnographic field notes, biographical interviews, online focus groups, collection of material evidence, and collaborative interpretation with the key participants in the research.La tesis investiga cómo evolucionan las diásporas contemporáneas y de qué modo se produce la diasporización en las condiciones de la modernidad tardía. Con diasporización me refiero al proceso, o procesos, en los que surgen los grupos diaspóricos y los individuos comienzan a llevar a cabo ciertas prácticas diaspóricas, es decir, prácticas sociales que se asocian a su origen étnico o nacional, su patria imaginada o la gestión de las fronteras en el país de acogida. La tesis toma la forma de estudio crítico informado etnográficamente en personas húngaras en Cataluña de primera generación y se basa en metodologías colaborativas para incluir las perspectivas émicas de las personas participantes. Con el fin de captar estas perspectivas, el estudio combina múltiples técnicas de generación de datos, como por ejemplo las notas de campo etnográficas, las entrevistas biográficas, los grupos focales en línea, la recopilación de rastros materiales y la interpretación colaborativa con las personas participantes clave en el estudio.La tesi investiga com evolucionen les diàspores contemporànies i de quina manera es produeix la diasporització en les condicions de la modernitat tardana. Amb diasporització em refereixo al procés, o processos, en què sorgeixen els grups diaspòrics i els individus comencen a dur a terme certes pràctiques diaspòriques, és a dir, pràctiques socials que s'associen al seu origen ètnic o nacional, la seva pàtria imaginada o la gestió de les fronteres al país d'acollida. La tesi pren forma d'estudi crític informat etnogràficament en persones hongareses a Catalunya de primera generació i es basa en metodologies col·laboratives per incloure les perspectives èmiques de les persones que hi participen. Per captar aquestes perspectives, l'estudi combina múltiples tècniques de generació de dades, com ara les notes de camp etnogràfiques, les entrevistes biogràfiques, els grups focals en línia, la recopilació de rastres materials i la interpretació col·laborativa amb les persones participants clau en l'estudi.Societat de la informació i el coneixemen

    Bias and Fairness in Large Language Models: A Survey

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    Rapid advancements of large language models (LLMs) have enabled the processing, understanding, and generation of human-like text, with increasing integration into systems that touch our social sphere. Despite this success, these models can learn, perpetuate, and amplify harmful social biases. In this paper, we present a comprehensive survey of bias evaluation and mitigation techniques for LLMs. We first consolidate, formalize, and expand notions of social bias and fairness in natural language processing, defining distinct facets of harm and introducing several desiderata to operationalize fairness for LLMs. We then unify the literature by proposing three intuitive taxonomies, two for bias evaluation, namely metrics and datasets, and one for mitigation. Our first taxonomy of metrics for bias evaluation disambiguates the relationship between metrics and evaluation datasets, and organizes metrics by the different levels at which they operate in a model: embeddings, probabilities, and generated text. Our second taxonomy of datasets for bias evaluation categorizes datasets by their structure as counterfactual inputs or prompts, and identifies the targeted harms and social groups; we also release a consolidation of publicly-available datasets for improved access. Our third taxonomy of techniques for bias mitigation classifies methods by their intervention during pre-processing, in-training, intra-processing, and post-processing, with granular subcategories that elucidate research trends. Finally, we identify open problems and challenges for future work. Synthesizing a wide range of recent research, we aim to provide a clear guide of the existing literature that empowers researchers and practitioners to better understand and prevent the propagation of bias in LLMs

    Understanding comparative questions and retrieving argumentative answers

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    Making decisions is an integral part of everyday life, yet it can be a difficult and complex process. While peoples’ wants and needs are unlimited, resources are often scarce, making it necessary to research the possible alternatives and weigh the pros and cons before making a decision. Nowadays, the Internet has become the main source of information when it comes to comparing alternatives, making search engines the primary means for collecting new information. However, relying only on term matching is not sufficient to adequately address requests for comparisons. Therefore, search systems should go beyond this approach to effectively address comparative information needs. In this dissertation, I explore from different perspectives how search systems can respond to comparative questions. First, I examine approaches to identifying comparative questions and study their underlying information needs. Second, I investigate a methodology to identify important constituents of comparative questions like the to-be-compared options and to detect the stance of answers towards these comparison options. Then, I address ambiguous comparative search queries by studying an interactive clarification search interface. And finally, addressing answering comparative questions, I investigate retrieval approaches that consider not only the topical relevance of potential answers but also account for the presence of arguments towards the comparison options mentioned in the questions. By addressing these facets, I aim to provide a comprehensive understanding of how to effectively satisfy the information needs of searchers seeking to compare different alternatives

    Gut-brain interactions affecting metabolic health and central appetite regulation in diabetes, obesity and aging

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    The central aim of this thesis was to study the effects of gut microbiota on host energy metabolism and central regulation of appetite. We specifically studied the interaction between gut microbiota-derived short-chain fatty acids (SCFAs), postprandial glucose metabolism and central regulation of appetite. In addition, we studied probable determinants that affect this interaction, specifically: host genetics, bariatric surgery, dietary intake and hypoglycemic medication.First, we studied the involvement of microbiota-derived short-chain fatty acids in glucose tolerance. In an observational study we found an association of intestinal availability of SCFAs acetate and butyrate with postprandial insulin and glucose responses. Hereafter, we performed a clinical trial, administering acetate intravenously at a constant rate and studied the effects on glucose tolerance and central regulation of appetite. The acetate intervention did not have a significant effect on these outcome measures, suggesting the association between increased gastrointestinal SCFAs and metabolic health, as observed in the observational study, is not paralleled when inducing acute plasma elevations.Second, we looked at other determinants affecting gut-brain interactions in metabolic health and central appetite signaling. Therefore, we studied the relation between the microbiota and central appetite regulation in identical twin pairs discordant for BMI. Second, we studied the relation between microbial composition and post-surgery gastrointestinal symptoms upon bariatric surgery. Third, we report the effects of increased protein intake on host microbiota composition and central regulation of appetite. Finally, we explored the effects of combination therapy with GLP-1 agonist exenatide and SGLT2 inhibitor dapagliflozin on brain responses to food stimuli
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