1,676 research outputs found

    A neuroimaging investigation of bipolar disorder and the neurocognitive effects of 5-HT7 antagonists

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    Bipolar disorder is a psychiatric disorder characterised by pathological mood states, but there is growing recognition of the role of cognitive impairment and dysfunction of emotional processes, which has a profound impact on quality of life. Many people with bipolar disorders exhibit brain volume impairment associated with cognitive dysfunction and an increased risk of dementia. In this thesis, I conducted a systematic review to understand the relationships between mood disorders and the 5-HT7 receptor. The 5-HT7 receptor is related to depression and anxiety, but the relationship between 5-HT7 and mania remains unclear; in addition, sleep and memory were also related to the 5-HT7 receptor. Followed by these findings, in the next two chapters, I examined the effects of 5-HT7 antagonists, using JNJ-18038683, on emotional and cognitive functioning, as well as their neural substrates. I then reported on neuroimaging investigations examining the effects of 5-HT7 antagonists on emotional processing and cognitive function in healthy volunteers to gain insight into their potential mode of action and utility for bipolar disorder. In fMRI analyses, the drug acted on 5-HT7 receptors potentially improving cognitive performance by modulating the function of the Cognitive Control Network in healthy controls. In the above-mentioned chapters, I gained a better understanding of the 5-HT7 antagonist, JNJ-18038683, and the putative promising effects for pharmacological treatments. However, the approach taken has some limitations, including a small sample size, potential participant bias, and a lack of systematic control of medication dose and duration of administration. In addition, in Chapter 5, I explored the brain basis of bipolar disorder and its links to cognitive and emotional dysfunction using a new ‘brain age’ approach. Individuals with bipolar disorder were found to have increased brain age compared to healthy controls. I hope that these findings can be applied to pharmacological treatment for individuals with bipolar disorder, ultimately allowing patients to benefit from the drug in the future

    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

    The Factors Contributing to Patriarchy in Contemporary Rural Bangladesh

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    This study examines factors that have contributed to the persistence of patriarchy in rural Bangladesh. Patriarchy is a social structure and practice in which men have power and privilege over women, subjecting them to various forms of oppression and exploitation. Previous studies have claimed that government and NGO-led development policies promote gender equality by improving women's access to education, microfinance, employment, political representation, and legal protections. Government and NGO-led development initiatives have improved women’s socioeconomic conditions in Bangladesh. However, gender inequality and discrimination against women remain prevalent. I argue that discriminatory cultural practices such as child marriage, dowry, and domestic violence uphold patriarchy, which perpetuates gender inequality in rural Bangladesh. This study employs ethnographic research, unstructured interviews, and participant observation to examine views held by Bangladesh’s rural population regarding discriminatory cultural practices. The findings of this thesis indicate that local sociocultural contexts determine women's empowerment in Bangladesh. Patriarchal gender norms, conservative Islamic views, and social acceptance of gender-based discrimination perpetuate gender inequality in rural Bangladesh. Rural women's economic and social stability is primarily derived from patrilocal marriage, which upholds their subjugation. Moreover, conservative gender norms and discriminatory Muslim personal laws continue to govern Muslim women's family and social status, despite their rising socioeconomic participation. Since 1975, political parties have countered weak electoral legitimacy and justified their hold on political power, by cultivating ties to conservative Islamic groups and emphasising party commitment to Islam, in line with societal norms and expectations. They have sought to maintain a balance between the role of modernisers (i.e., involving women in socioeconomic activities) and the incorporation of gender discrimination into the National Women's Development Policy, family laws, and laws around child marriage and dowry prohibition. In addition, the government refuses to challenge conservative voices that promote child marriage, wedding gifts (typically dowry), and domestic violence. Profit-driven microfinance NGOs and legal system corruption further limit women's protection against such patriarchal traditions. Based on these findings, this thesis argues that locally driven development policies involving conservative Islamic groups can advance gender equality in rural Bangladesh by shifting community support towards the promotion of women's rights

    Collective agency:From philosophical and logical perspectives

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    People inhabit a vast and intricate social network nowadays. In addition to our own decisions and actions, we confront those of various groups every day. Collective decisions and actions are more complex and bewildering compared to those made by individuals. As members of a collective, we contribute to its decisions, but our contributions may not always align with the outcome. We may also find ourselves excluded from certain groups and passively subjected to their influences without being aware of the source. We are used to being in overlapping groups and may switch identities, supporting or opposing the claims of particular groups. But rarely do we pause to think: What do we talk about when we talk about groups and their decisions?At the heart of this dissertation is the question of collective agency, i.e., in what sense can we treat a group as a rational agent capable of its action. There are two perspectives we take: a philosophical and logical one. The philosophical perspective mainly discusses the ontological and epistemological issues related to collective agency, sorts out the relevant philosophical history, and argues that the combination of a relational view of collective agency and a dispositional view of collective intentionality provides a rational and realistic account. The logical perspective is associated with formal theories of groups, it disregards the psychological content involved in the philosophical perspective, establishes a logical system that is sufficiently formal and objective, and axiomatizes the nature of a collective

    30th European Congress on Obesity (ECO 2023)

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    This is the abstract book of 30th European Congress on Obesity (ECO 2023

    Resolving Social Inhibition During Emotion-Focused Therapy for Depression: A Task Analytic Discovery

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    The aim of this study was to create a model of the resolution of social inhibition (SI) during emotion-focused therapy (EFT; Greenberg et al., 1993) for depression. Employing the steps of the discovery phase of a task analysis (Greenberg, 2007), a rational model of the resolution of SI was first developed. Client markers of SI were also conjectured. Following this, performances of the resolution and non-resolution of SI over a course of EFT therapy for depression were observed, using archival data of six clients from clinical trials of EFT for depression (Greenberg & Watson, 1998; Goldman et al., 2006). Resolution was defined as having an SI score on the Inventory of Interpersonal Problems (Horowitz et al., 1988) in the normal range, as indicated by norms, at 18-month follow-up post therapy. The empirical observations were then synthetized with the rational model to create a final rational-empirical model outlining the resolution of SI. The final model identified 6 components: (1) SI Markers; (2) Maladaptive shame and fear expressed by the client’s inhibited self; (3) Client connects SI Agent to painful past original source; (4) A power shift that results in an overcoming of the part of client that perpetuates SI (through expression of assertive anger and hurt/grief, needs for support and acceptance, and deservingness of needs); (5) Client is willing to take risks despite potential hurt/grief; and (6) Increased expression of self-assertion. Theoretical and clinical implications of the findings are considered. Limitations and future research directions are discussed

    “Have patients with chronic skin diseases needs been met?”:A thesis on psoriasis and eczema patient care in dermatology service

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    Background: Common chronic skin diseases such as eczema and psoriasis usually require long term medical care. They are often associated with psychological and metabolic comorbidities, which can impact on patient quality of life (QOL) and on the self-management of these diseases. Regular assessment of patient needs, comorbidities and feedback is a critical step in the development of decision-analytic models. Currently, no intervention is available to regularly assess such patients’ needs and comorbidities and support their involvement in the decision-making and self-management of their morbidity and comorbidities. The aim of this research is to involve the patients in decision making of their care and to support their self-management by the use of a paper questionnaire (study tool) at each consultation. Objective: To explore the acceptability and potential of a self-developed paper questionnaire that constituted a study tool for addressing the needs, comorbidities, and feedback of patients with psoriasis and eczema and supporting their involvement in decision making and self-management of their chronic conditions. Method: A mixed method study was conducted and included a postal survey on adult male and female patients with psoriasis and eczema, using the study tool, which is a paper questionnaire and contains the Dermatology Life Quality Index (DLQI) and seven supplementary open-ended questions to capture patients’ views, feedback, comorbidities, coping status and needs. The survey was followed by semi-structured face-to-face interviews with a sample of the patients who had participated in the survey. The aims of the interviews were two-fold: 1. to gain a deeper understanding of their experience of living with and managing their skin disease; and 2. to gather patient feedback on the service they received as well as their views on using the new study tool or any alternative intervention to address and support their self-management. The final study was a pilot which involved presenting a proposal of an online version of the study tool to a group of healthcare experts asking them to critically review the extent to which the online model responded to patients expressed needs. Results: Of the 114 patients who participated in the postal survey 108 (94.7%) of them expressed physical, metabolic and psychological comorbidities. Stress was identified as the dominant disease-triggering factor in 72 (63%) participants. Thirty-three (28.9%) of participants reported that they could not cope with their chronic illness. Eighteen (15.7%) participants suffered from anxiety, and 12 (10.5%) had depression and suicidal thoughts. Twenty-nine (25%) participants addressed their needs for support at home, and 16 (14%) of them asked for support at work. In the patient feedback section, 21 (18.4%) and 9 (7.8%) participants rated the service they received from their general practitioner (GP) and dermatologist as poor, respectively. In the interviews, all the participants 22 (100%) welcomed the use of the study tool on a regular basis to address their needs, comorbidities and feedback. Nineteen (86.3%) of them suggested that they would prefer using an online version of the tool or patient portal system as a convenient way of remote and interactive communication with the healthcare provider, particularly during the worsening of their skin condition. In the final pilot study, the healthcare experts agreed that the proposed online version of the study tool could be a convenient platform for such patients to support their self-management. They discussed the potential importance of such a tool if it provided them with access to supportive services such as patient information on skin diseases and self-management, access to local mental health service and other relevant psoriasis and eczema patients’ support groups and charities. Conclusion: This novel mixed method research identified knowledge gaps in managing patients with psoriasis and eczema. It provided a new tool that has the potential to regularly engage and assess patients’ unmet needs, comorbidities and feedback. The tool can involve patients in decision-making and offers them the autonomy to disclose heterogeneous needs that may support their self-management. All the interviewees welcomed regular use of the study tool and the majority of them suggested that they would prefer using an online version of the tool if it was available. Future research is needed to assess the impact of the study tool in filling important gaps in patient self-management and in health service improvement

    A Comprehensive Review of Data-Driven Co-Speech Gesture Generation

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    Gestures that accompany speech are an essential part of natural and efficient embodied human communication. The automatic generation of such co-speech gestures is a long-standing problem in computer animation and is considered an enabling technology in film, games, virtual social spaces, and for interaction with social robots. The problem is made challenging by the idiosyncratic and non-periodic nature of human co-speech gesture motion, and by the great diversity of communicative functions that gestures encompass. Gesture generation has seen surging interest recently, owing to the emergence of more and larger datasets of human gesture motion, combined with strides in deep-learning-based generative models, that benefit from the growing availability of data. This review article summarizes co-speech gesture generation research, with a particular focus on deep generative models. First, we articulate the theory describing human gesticulation and how it complements speech. Next, we briefly discuss rule-based and classical statistical gesture synthesis, before delving into deep learning approaches. We employ the choice of input modalities as an organizing principle, examining systems that generate gestures from audio, text, and non-linguistic input. We also chronicle the evolution of the related training data sets in terms of size, diversity, motion quality, and collection method. Finally, we identify key research challenges in gesture generation, including data availability and quality; producing human-like motion; grounding the gesture in the co-occurring speech in interaction with other speakers, and in the environment; performing gesture evaluation; and integration of gesture synthesis into applications. We highlight recent approaches to tackling the various key challenges, as well as the limitations of these approaches, and point toward areas of future development.Comment: Accepted for EUROGRAPHICS 202

    A Framework for Modeling Human Behavior in Large-scale Agent-based Epidemic Simulations

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    Acknowledgements We thank Cuebiq; mobility data is provided by Cuebiq, a location intelligence and measurement platform. Through its Data for Good program, Cuebiq provides access to aggregated mobility data for academic research and humanitarian initiatives. This first-party data is collected from anonymized users who have opted-in to provide access to their location data anonymously, through a GDPR and CCPA compliant framework. To further preserve privacy, portions of the data are aggregated to the census-block group level. For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.Peer reviewedPublisher PD

    Security and Privacy of Resource Constrained Devices

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    The thesis aims to present a comprehensive and holistic overview on cybersecurity and privacy & data protection aspects related to IoT resource-constrained devices. Chapter 1 introduces the current technical landscape by providing a working definition and architecture taxonomy of ‘Internet of Things’ and ‘resource-constrained devices’, coupled with a threat landscape where each specific attack is linked to a layer of the taxonomy. Chapter 2 lays down the theoretical foundations for an interdisciplinary approach and a unified, holistic vision of cybersecurity, safety and privacy justified by the ‘IoT revolution’ through the so-called infraethical perspective. Chapter 3 investigates whether and to what extent the fast-evolving European cybersecurity regulatory framework addresses the security challenges brought about by the IoT by allocating legal responsibilities to the right parties. Chapters 4 and 5 focus, on the other hand, on ‘privacy’ understood by proxy as to include EU data protection. In particular, Chapter 4 addresses three legal challenges brought about by the ubiquitous IoT data and metadata processing to EU privacy and data protection legal frameworks i.e., the ePrivacy Directive and the GDPR. Chapter 5 casts light on the risk management tool enshrined in EU data protection law, that is, Data Protection Impact Assessment (DPIA) and proposes an original DPIA methodology for connected devices, building on the CNIL (French data protection authority) model
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