Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially-Aware Language Acquisition

This paper presents a self-supervised method for visual detection of the active speaker in a multi-person spoken interaction scenario. Active speaker detection is a fundamental prerequisite for any artificial cognitive system attempting to acquire language in social settings. The proposed method is intended to complement the acoustic detection of the active speaker, thus improving the system robustness in noisy conditions. The method can detect an arbitrary number of possibly overlapping active speakers based exclusively on visual information about their face. Furthermore, the method does not rely on external annotations, thus complying with cognitive development. Instead, the method uses information from the auditory modality to support learning in the visual domain. This paper reports an extensive evaluation of the proposed method using a large multi-person face-to-face interaction dataset. The results show good performance in a speaker dependent setting. However, in a speaker independent setting the proposed method yields a significantly lower performance. We believe that the proposed method represents an essential component of any artificial cognitive system or robotic platform engaging in social interactions.Comment: 10 pages, IEEE Transactions on Cognitive and Developmental System

Outcome of preoperative radiotherapy in the treatment of cervical cancer with focus on protein expression and dosimetry

Treatment with preoperative intracavitary radiotherapy (ICRT) is used in cervical cancer with the intention to reduce the tumour burden and sterilize microscopic disease in the paracervical tissues. Preoperative ICRT is, however, a controversial treatment regime since it is unclear if addition of ICRT to surgery improves treatment outcome compared to surgery alone. This question constitutes the basis of this thesis. In relation to this issue we have studied clinical, dosimetric and molecular key factors with focus on DNA damage repair signalling molecules of possible importance for radiotherapy sensitivity. One possible way to investigate the potential benefit of preoperative ICRT is to analyze whether complete tumour remission in the surgical specimen after preoperative ICRT is correlated to treatment outcome or not. In paper I we analyzed treatment results after preoperative ICRT in patients with cervical cancer stage IB-IIA. We found a strong correlation between pathologic complete remission (pCR) and survival with a 5-year survival of 95% in patients with pCR compared to 46% in patients with residual tumour (non-pCR) (p<0.0001). These results indicate that the use of preoperative ICRT may contribute to treatment outcome compared to surgery alone. DNA double strand breaks (DNA DSBs) and their repair has in tumour cell lines been linked to radiosensitivity. In paper II we therefore analyzed the expression of proteins related to the DNA-PK repair pathway; DNA-PKcs, Ku70, Ku86, p53, p21 and Mdm-2 in pre-treatment tumour tissue with the aim to find predictive markers for radiotherapy response. Our hypothesis was that high DNA repair capacity in the primary tumour, reflected by a high frequency of cells positive for DNA-PK proteins, would correlate with non-pCR cases. However, we did not find that any of the analyzed proteins were predictive for radiotherapy response. Our hypothesis in paper III was that residual tumours that survived radiotherapy would display a higher frequency of DNA-PK positive cells reflecting a higher capacity to DNA DSB repair compared to their corresponding primary tumours. The expression of DNA-PKcs, Ku70, Ku86, p53, p21 and Mdm-2 proteins was compared in pre- and post-treatment tumour tissue. We found that residual tumours showed an increased frequency of tumour cells positive for DNA-PK complex proteins compared to the frequency in the primary tumour. This result may be interpreted as that radiation causes a selection pressure allowing tumour cells with high DNA-PK expression to survive RT. Biological effective dose (BED) can be used to predict the influence on outcome of different treatment schedules for individual patients. In paper IV we evaluated BED with respect to survival, local control and late toxicity in patients treated either with radiotherapy and surgery or with radiotherapy alone. We found a correlation between BED and treatment outcome for patients treated with radiotherapy alone but not for patients treated with radiotherapy and surgery. No correlations were found between BED and late toxicity from bladder and rectum. In conclusion this thesis illustrates that treatment with preoperative intracavitary radiotherapy may be beneficial for patients with cervical cancer stage IB-IIA. We found that the expression of the DNA-PK complex proteins in primary tumour cannot predict RT response. We did, however, find that the frequency of the DNA-PK complex proteins is higher in residual tumour after ICRT than in corresponding primary tumour. BED cannot be used as a predictive factor for the outcome in patients treated with pre-and postoperative radiotherapy or for the late side effects but does correlate with local control of the tumour and survival in patients treated with RT alone

Reaching Food Security: The legislative challenges of Seed exchange in kind

On the 5th of July 2023, the European Commission presented a new Plant Reproductive Material directive with a general objective of ensuring high quality and diversity that contributes to food security, protects biodiversity, and restores forest ecosystems. The aims are to increase efficiency and promote and support mainly sustainable innovation. In the proposal, there are three Options, Option 1 - Highest degree of flexibility, Option 2 - Balancing flexibility and harmonisation Option 3 - Highest degree of harmonisation, and the legal text is based on Option 2. The objective of this master thesis is to examine the discursive tendencies of food security in the proposal and to discuss how the proposal might challenge and affect small-scale farmers who are exchanging seeds in kind. o What discursive tendencies of food security can be seen in the European Commission’s proposal for a directive on plant reproductive materials? o How does the discourse of food security differentiate between options 1, 2 and 3 in the proposal? The study was carried out firstly by a content analysis to find relevant materials, and then by adding a problematizing dimension, a discourse analysis of sort. To perform the discourse analysis an analytical framework was made, which is based on other researchers' definitions, and is the base of the discourse analysis. Based on the researcher's work, two discourses could be used: Liberal Food Security and Food Sovereignty. By applying the analytical framework to the material, it was possible to see what discourse was most prominent. The results indicate that both Liberal Food Security and Food Sovereignty can be found in the material, however, they do differentiate between the options presented by the European Commission. Liberal Food Security is most prominent in Option 1, but also provides the most flexibility for Food Sovereignty, Liberal Food Security is most prominent in Option 2, but has some tendencies toward Food Sovereignty, and in Option 3 Liberal Food Security is the only discourse of the two that is prominent

Reverse Engineering Psychologically Valid Facial Expressions of Emotion into Social Robots

Social robots are now part of human society, destined for schools, hospitals, and homes to perform a variety of tasks. To engage their human users, social robots must be equipped with the essential social skill of facial expression communication. Yet, even state-of-the-art social robots are limited in this ability because they often rely on a restricted set of facial expressions derived from theory with well-known limitations such as lacking naturalistic dynamics. With no agreed methodology to objectively engineer a broader variance of more psychologically impactful facial expressions into the social robots' repertoire, human-robot interactions remain restricted. Here, we address this generic challenge with new methodologies that can reverse-engineer dynamic facial expressions into a social robot head. Our data-driven, user-centered approach, which combines human perception with psychophysical methods, produced highly recognizable and human-like dynamic facial expressions of the six classic emotions that generally outperformed state-of-art social robot facial expressions. Our data demonstrates the feasibility of our method applied to social robotics and highlights the benefits of using a data-driven approach that puts human users as central to deriving facial expressions for social robots. We also discuss future work to reverse-engineer a wider range of socially relevant facial expressions including conversational messages (e.g., interest, confusion) and personality traits (e.g., trustworthiness, attractiveness). Together, our results highlight the key role that psychology must continue to play in the design of social robots

Graph-Hist: Graph Classification from Latent Feature Histograms With Application to Bot Detection

Neural networks are increasingly used for graph classification in a variety of contexts. Social media is a critical application area in this space, however the characteristics of social media graphs differ from those seen in most popular benchmark datasets. Social networks tend to be large and sparse, while benchmarks are small and dense. Classically, large and sparse networks are analyzed by studying the distribution of local properties. Inspired by this, we introduce Graph-Hist: an end-to-end architecture that extracts a graph's latent local features, bins nodes together along 1-D cross sections of the feature space, and classifies the graph based on this multi-channel histogram. We show that Graph-Hist improves state of the art performance on true social media benchmark datasets, while still performing well on other benchmarks. Finally, we demonstrate Graph-Hist's performance by conducting bot detection in social media. While sophisticated bot and cyborg accounts increasingly evade traditional detection methods, they leave artificial artifacts in their conversational graph that are detected through graph classification. We apply Graph-Hist to classify these conversational graphs. In the process, we confirm that social media graphs are different than most baselines and that Graph-Hist outperforms existing bot-detection models

General equation for Zeno-like effects in spontaneous exponential decay

It was shown that different mechanisms of perturbation of spontaneous decay constant: inelastic interaction of emitted particles with particle detector, decay onto an unstable level, Rabi transition from the final state of decay (electromagnetic field domination) and some others are really the special kinds of one general effect - perturbation of decay constant by dissipation of the final state of decay. Such phenomena are considered to be Zeno-like effects and general formula for perturbed decay constant is deduced.Comment: LaTeX 2.09 file, 11 pages, no figures. Accepted in Physics Letters

Diffusion-Based Co-Speech Gesture Generation Using Joint Text and Audio Representation

This paper describes a system developed for the GENEA (Generation and Evaluation of Non-verbal Behaviour for Embodied Agents) Challenge 2023. Our solution builds on an existing diffusion-based motion synthesis model. We propose a contrastive speech and motion pretraining (CSMP) module, which learns a joint embedding for speech and gesture with the aim to learn a semantic coupling between these modalities. The output of the CSMP module is used as a conditioning signal in the diffusion-based gesture synthesis model in order to achieve semantically-aware co-speech gesture generation. Our entry achieved highest human-likeness and highest speech appropriateness rating among the submitted entries. This indicates that our system is a promising approach to achieve human-like co-speech gestures in agents that carry semantic meaning