Exploiting the conceptual space in hybrid recommender systems: a semantic-based approach

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, octubre de 200

Fear Classification using Affective Computing with Physiological Information and Smart-Wearables

Mención Internacional en el título de doctorAmong the 17 Sustainable Development Goals proposed within the 2030 Agenda and adopted by all of the United Nations member states, the fifth SDG is a call for action to effectively turn gender equality into a fundamental human right and an essential foundation for a better world. It includes the eradication of all types of violence against women. Focusing on the technological perspective, the range of available solutions intended to prevent this social problem is very limited. Moreover, most of the solutions are based on a panic button approach, leaving aside the usage and integration of current state-of-the-art technologies, such as the Internet of Things (IoT), affective computing, cyber-physical systems, and smart-sensors. Thus, the main purpose of this research is to provide new insight into the design and development of tools to prevent and combat Gender-based Violence risky situations and, even, aggressions, from a technological perspective, but without leaving aside the different sociological considerations directly related to the problem. To achieve such an objective, we rely on the application of affective computing from a realist point of view, i.e. targeting the generation of systems and tools capable of being implemented and used nowadays or within an achievable time-frame. This pragmatic vision is channelled through: 1) an exhaustive study of the existing technological tools and mechanisms oriented to the fight Gender-based Violence, 2) the proposal of a new smart-wearable system intended to deal with some of the current technological encountered limitations, 3) a novel fear-related emotion classification approach to disentangle the relation between emotions and physiology, and 4) the definition and release of a new multi-modal dataset for emotion recognition in women. Firstly, different fear classification systems using a reduced set of physiological signals are explored and designed. This is done by employing open datasets together with the combination of time, frequency and non-linear domain techniques. This design process is encompassed by trade-offs between both physiological considerations and embedded capabilities. The latter is of paramount importance due to the edge-computing focus of this research. Two results are highlighted in this first task, the designed fear classification system that employed the DEAP dataset data and achieved an AUC of 81.60% and a Gmean of 81.55% on average for a subjectindependent approach, and only two physiological signals; and the designed fear classification system that employed the MAHNOB dataset data achieving an AUC of 86.00% and a Gmean of 73.78% on average for a subject-independent approach, only three physiological signals, and a Leave-One-Subject-Out configuration. A detailed comparison with other emotion recognition systems proposed in the literature is presented, which proves that the obtained metrics are in line with the state-ofthe- art. Secondly, Bindi is presented. This is an end-to-end autonomous multimodal system leveraging affective IoT throughout auditory and physiological commercial off-theshelf smart-sensors, hierarchical multisensorial fusion, and secured server architecture to combat Gender-based Violence by automatically detecting risky situations based on a multimodal intelligence engine and then triggering a protection protocol. Specifically, this research is focused onto the hardware and software design of one of the two edge-computing devices within Bindi. This is a bracelet integrating three physiological sensors, actuators, power monitoring integrated chips, and a System- On-Chip with wireless capabilities. Within this context, different embedded design space explorations are presented: embedded filtering evaluation, online physiological signal quality assessment, feature extraction, and power consumption analysis. The reported results in all these processes are successfully validated and, for some of them, even compared against physiological standard measurement equipment. Amongst the different obtained results regarding the embedded design and implementation within the bracelet of Bindi, it should be highlighted that its low power consumption provides a battery life to be approximately 40 hours when using a 500 mAh battery. Finally, the particularities of our use case and the scarcity of open multimodal datasets dealing with emotional immersive technology, labelling methodology considering the gender perspective, balanced stimuli distribution regarding the target emotions, and recovery processes based on the physiological signals of the volunteers to quantify and isolate the emotional activation between stimuli, led us to the definition and elaboration of Women and Emotion Multi-modal Affective Computing (WEMAC) dataset. This is a multimodal dataset in which 104 women who never experienced Gender-based Violence that performed different emotion-related stimuli visualisations in a laboratory environment. The previous fear binary classification systems were improved and applied to this novel multimodal dataset. For instance, the proposed multimodal fear recognition system using this dataset reports up to 60.20% and 67.59% for ACC and F1-score, respectively. These values represent a competitive result in comparison with the state-of-the-art that deal with similar multi-modal use cases. In general, this PhD thesis has opened a new research line within the research group under which it has been developed. Moreover, this work has established a solid base from which to expand knowledge and continue research targeting the generation of both mechanisms to help vulnerable groups and socially oriented technology.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: David Atienza Alonso.- Secretaria: Susana Patón Álvarez.- Vocal: Eduardo de la Torre Arnan

Super-resolution imaging of cell-surface Sonic hedgehog multimolecular signalling complexes

Sonic hedgehog is a fascinating protein with great responsibility over the formation and upkeep of our bodies. It is widely studied, not least because dysregulation of the Shh signalling pathway leads to repercussions on human health, such as contraction of cancer. Gaining an understanding of its signalling mechanism is central to inventing preventative measures and treatments against this disease. This thesis focuses on the study of the spatial organisation of Shh multimolecular signalling complexes on the surface of producing cells, and those dispatched in the vicinity of those cells, using high-resolution optical imaging beyond the diffraction limit. With un-precedented resolution, the differences in organisation of Shh pre- and post-release from the surface were characterised, and the influence of the lipid modifications of Shh, namely choles-terol and palmitate, investigated. The main findings were that both lipid adducts are necessary for large-scale multimerisation, but not for the formation of small, sub-diffraction limit oligomers. Together with data I collected about the profile of the clusters’ size distributions, I find that electrostatic interactions between the molecules may be the engine driving the multimerisation process. Furthermore, the role of lipid modifications may, at least in part, be to retain Shh on the surface while multimerisation proceeding according to the law of mass action builds upon the small oligomer nucleation sites prepared presumably by the electrostatic interactions in the first place. Other, more indirect lines of evidence again based on the profile of the multimer size distribution insinuated that Shh complexes may not undergo any proteolytic modifications prior to release – contrary to some reports in the literature. The results presented in this thesis are the fruits of a completely fresh and innovative approach to examining Shh, which for the first time delivers concrete dimensional details about the elusive structure of the Shh multimer.Open Acces

Smart Sensors for Healthcare and Medical Applications

This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare

The application of genomic technologies to cancer and companion diagnostics.

This thesis describes work undertaken by the author between 1996 and 2014. Genomics is the study of the genome, although it is also often used as a catchall phrase and applied to the transcriptome (study of RNAs) and methylome (study of DNA methylation). As cancer is a disease of the genome the rapid advances in genomic technology, specifically microarrays and next generation sequencing, are creating a wave of change in our understanding of its molecular pathology. Molecular pathology and personalised medicine are being driven by discoveries in genomics, and genomics is being driven by the development of faster, better and cheaper genome sequencing. The next decade is likely to see significant changes in the way cancer is managed for individual cancer patients as next generation sequencing enters the clinic. In chapter 3 I discuss how ERBB2 amplification testing for breast cancer is currently dominated by immunohistochemistry (a single-gene test); and present the development, by the author, of a semi-quantitative PCR test for ERBB2 amplification. I also show that estimating ERBB2 amplification from microarray copy-number analysis of the genome is possible. In chapter 4 I present a review of microarray comparison studies, and outline the case for careful and considered comparison of technologies when selecting a platform for use in a research study. Similar, indeed more stringent, care needs to be applied when selecting a platform for use in a clinical test. In chapter 5 I present co-authored work on the development of amplicon and exome methods for the detection and quantitation of somatic mutations in circulating tumour DNA, and demonstrate the impact this can have in understanding tumour heterogeneity and evolution during treatment. I also demonstrate how next-generation sequencing technologies may allow multiple genetic abnormalities to be analysed in a single test, and in low cellularity tumours and/or heterogenous cancers. Keywords: Genome, exome, transcriptome, amplicon, next-generation sequencing, differential gene expression, RNA-seq, ChIP-seq, microarray, ERBB2, companion diagnostic

Design, Mathematical Modelling, Construction and Testing of Synthetic Gene Network Oscillators to Establish Roseobacter Clade Bacteria and the Protozoan Trypanosoma brucei as Synthetic Biology Chassis.

The aim of this project is to establish Roseobacter marine bacteria and Trypanosoma brucei (T. brucei) protozoa as synthetic biology chassis. This work addresses the gap within synthetic biology resulting from the limited choice of host cells available for use in practice. This was done by developing synthetic bacterial and trypanosomal genetic regulatory networks (GRNs) which function as an oscillator as well as by developing the necessary protocols and set-ups to allow for the analysis of GRN dynamics within the host. Roseobacter clade bacteria are naturally found in diverse oceanic habitats and have an important ecological role in balancing global carbon levels. This makes Roseobacter an ideal chassis for future efforts to apply synthetic biology to bioremediation and geo-engineering challenges. The aim of this investigation was to establish straight-forward molecular biology procedures in Roseobacter bacteria followed by characterisation and modelling of an E. coli oscillator in Roseobacter. Results showed that Roseobacter synthetic biology is non-trivial. Protozoa are exploited as host cells for industrial production of biotherapeutics due to fast doubling times and host proteins’ mammalian-like post-translational glycosylation. As an established model organism for studying protozoa, T. brucei provided a test case for establishing synthetic biology in this phylum for the first time. T. brucei is highly divergent from eukaryotes commonly used in synthetic biology and possesses a sophisticated genomic machinery to evade host immune systems. The establishment of standard synthetic biology approaches in mathematical modelling and gene network design in T. brucei will underpin application of synthetic biology to enhance the industrial capability of the protozoa as a chassis and to probe its pathobiology. This investigation involved design and assembly of a Goodwin oscillator, followed by characterisation and modelling of the network and the development of a novel experimental set-up for live-cell imaging of single motile trypanosomes. Results showed that T. brucei is a promising novel synthetic biology chassi