Information Retrieval for Multivariate Research Data Repositories

In this dissertation, I tackle the challenge of information retrieval for multivariate research data by providing novel means of content-based access. Large amounts of multivariate data are produced and collected in different areas of scientific research and industrial applications, including the human or natural sciences, the social or economical sciences and applications like quality control, security and machine monitoring. Archival and re-use of this kind of data has been identified as an important factor in the supply of information to support research and industrial production. Due to increasing efforts in the digital library community, such multivariate data are collected, archived and often made publicly available by specialized research data repositories. A multivariate research data document consists of tabular data with $m$ columns (measurement parameters, e.g., temperature, pressure, humidity, etc.) and $n$ rows (observations). To render such data-sets accessible, they are annotated with meta-data according to well-defined meta-data standard when being archived. These annotations include time, location, parameters, title, author (and potentially many more) of the document under concern. In particular for multivariate data, each column is annotated with the parameter name and unit of its data (e.g., water depth [m]). The task of retrieving and ranking the documents an information seeker is looking for is an important and difficult challenge. To date, access to this data is primarily provided by means of annotated, textual meta-data as described above. An information seeker can search for documents of interest, by querying for the annotated meta-data. For example, an information seeker can retrieve all documents that were obtained in a specific region or within a certain period of time. Similarly, she can search for data-sets that contain a particular measurement via its parameter name or search for data-sets that were produced by a specific scientist. However, retrieval via textual annotations is limited and does not allow for content-based search, e.g., retrieving data which contains a particular measurement pattern like a linear relationship between water depth and water pressure, or which is similar to example data the information seeker provides. In this thesis, I deal with this challenge and develop novel indexing and retrieval schemes, to extend the established, meta-data based access to multivariate research data. By analyzing and indexing the data patterns occurring in multivariate data, one can support new techniques for content-based retrieval and exploration, well beyond meta-data based query methods. This allows information seekers to query for multivariate data-sets that exhibit patterns similar to an example data-set they provide. Furthermore, information seekers can specify one or more particular patterns they are looking for, to retrieve multivariate data-sets that contain similar patterns. To this end, I also develop visual-interactive techniques to support information seekers in formulating such queries, which inherently are more complex than textual search strings. These techniques include providing an over-view of potentially interesting patterns to search for, that interactively adapt to the user's query as it is being entered. Furthermore, based on the pattern description of each multivariate data document, I introduce a similarity measure for multivariate data. This allows scientists to quickly discover similar (or contradictory) data to their own measurements

LIFE-SHARE Project: Developing a Digitisation Strategy Toolkit

This poster will outline the Digitisation Strategy Toolkit created as part of the LIFE-SHARE project. The toolkit is based on the lifecycle model created by the LIFE project and explores the creation, acquisition, ingest, preservation (bit-stream and content) and access requirements for a digitisation strategy. This covers the policies and infrastructure required in libraries to establish successful practices. The toolkit also provides both internal and external resources to support the service. This poster will illustrate how the toolkit works effectively to support digitisation with examples from three case studies at the Universities of Leeds, Sheffield and York

Identifying emotions in opera singing: implications of adverse acoustic conditions

The expression of emotion is an inherent aspect in singing, especially in operatic voice. Yet, adverse acoustic conditions, as, e. g., a performance in open-air, or a noisy analog recording, may affect its perception. State-of-the art methods for emotional speech evaluation have been applied to operatic voice, such as perception experiments, acoustic analyses, and machine learning techniques. Still, the extent to which adverse acoustic conditions may impair listeners’ and machines’ identification of emotion in vocal cues has only been investigated in the realm of speech. For our study, 132 listeners evaluated 390 nonsense operatic sung instances of five basic emotions, affected by three noises (brown, pink, and white), each at four Signal-to-Noise Ratios (-1 dB, -0.5 dB, +1 dB, and +3 dB); the performance of state-of-the-art automatic recognition methods was evaluated as well. Our findings show that the three noises affect similarly female and male singers and that listeners’ gender did not play a role. Human perception and automatic classification display similar confusion and recognition patterns: sadness is identified best, fear worst; low aroused emotions display higher confusion

Switchable Signaling Molecules for Media Modulation: Fundamentals, Applications, and Research Directions

Although visionary applications of molecular communication (MC), such as long-term continuous health monitoring by cooperative in-body nanomachines, have been proposed, MC is still in its infancy when it comes to practical implementation. In particular, long-term experiments and applications face issues such as depletion of signaling molecules (SMs) at the transmitter (TX) and inter-symbol interference (ISI) at the receiver (RX). To overcome these practical challenges, a new class of SMs with switchable states seems to be promising for future MC applications. In this work, we provide an overview of existing switchable SMs, and classify them according to their properties. Furthermore, we highlight how switchable SMs can be utilized as information carriers for media modulation. In addition, we present theoretical and experimental results for an end-to-end MC system employing the green fluorescent protein variant "Dreiklang" (GFPD) as switchable SM. Our experimental results show, for the first time, successful information transmission in a closed-loop pipe system using media modulation. Finally, we discuss media modulation specific challenges and opportunities.Comment: 7 pages, 6 figures. This work has been accepted for publication in IEEE Communications Magazin

Identification of Neural Mechanisms in First Single-Sweep Analysis in oVEMPs and Novel Normative Data

Background: Bone-conducted (BC) VEMPs provide important tools for measuring otolith function. However, two major drawbacks of this method are encountered in clinical practice—small n10 amplitude and averaging technique. In this study, we present the results of a new VEMP setup measuring technique combined with a novel single-sweep analysis. Methods: The study included BC oVEMP data from 92 participants for the evaluation of normative data using a novel analysis technique. For evaluating test-retest reliability, the intraclass correlation coefficient (ICC) was used. Results: We found significant n10 amplitude differences in single-sweep analyses after the first and second measurements. Thereby, mathematical analyses of the head movement did not show any differences in the first or second measurements. The normative n10 amplitude was 20.66 µV with an asymmetric ratio (AR) of 7%. The new value of late shift difference (LSD) was 0.01 ms. The test retest-reliability showed good to excellent ICC results in 9 out of 10 measurements. Conclusions: Our results support a phenomenon in single-sweep analysis of the first stimuli independent of head movement and signal morphology. Furthermore, the values obtained with the new measurement method appear to be more sensitive and may allow an extended diagnostic range due to the new parameter LSD

AVEC 2017--Real-life depression, and affect recognition workshop and challenge

The Audio/Visual Emotion Challenge and Workshop (AVEC 2017) “Real-life depression, and affect” will be the seventh competition event aimed at comparison of multimedia processing and machine learning methods for automatic audiovisual depression and emotion analysis, with all participants competing under strictly the same conditions. .e goal of the Challenge is to provide a common benchmark test set for multimodal information processing and to bring together the depression and emotion recognition communities, as well as the audiovisual processing communities, to compare the relative merits of the various approaches to depression and emotion recognition from real-life data. .is paper presents the novelties introduced this year, the challenge guidelines, the data used, and the performance of the baseline system on the two proposed tasks: dimensional emotion recognition (time and value-continuous), and dimensional depression estimation (value-continuous)

Immunothrombotic Dysregulation in COVID-19 Pneumonia is Associated with Respiratory Failure and Coagulopathy

Background: SARS-CoV-2 infection causes severe pneumonia (COVID-19), but the mechanisms of subsequent respiratory failure and complicating renal and myocardial involvement are poorly understood. In addition, a systemic prothrombotic phenotype has been reported in COVID-19 patients. Methods: A total of 62 subjects were included in our study (n=38 patients with RT-PCR confirmed COVID-19 and n=24 non-COVID-19 controls). We performed histopathological assessment of autopsy cases, surface-marker based phenotyping of neutrophils and platelets, and functional assays for platelet, neutrophil functions as well as coagulation tests. Results: We provide evidence that organ involvement and prothrombotic features in COVID-19 are linked by immunothrombosis. We show that in COVID-19 inflammatory microvascular thrombi are present in the lung, kidney, and heart, containing neutrophil extracellular traps associated with platelets and fibrin. COVID-19 patients also present with neutrophil-platelet aggregates and a distinct neutrophil and platelet activation pattern in blood, which changes with disease severity. Whereas cases of intermediate severity show an exhausted platelet and hyporeactive neutrophil phenotype, severely affected COVID-19 patients are characterized by excessive platelet and neutrophil activation compared to healthy controls and non-COVID-19 pneumonia. Dysregulated immunothrombosis in SARS-CoV-2 pneumonia is linked to both ARDS and systemic hypercoagulability. Conclusions: Taken together, our data point to immunothrombotic dysregulation as a key marker of disease severity in COVID-19. Further work is necessary to determine the role of immunothrombosis in COVID-19

Accumulation of mutations in antibody and CD8 T cell epitopes in a B cell depleted lymphoma patient with chronic SARS-CoV-2 infection

Antibodies against the spike protein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can drive adaptive evolution in immunocompromised patients with chronic infection. Here we longitudinally analyze SARS-CoV-2 sequences in a B cell-depleted, lymphoma patient with chronic, ultimately fatal infection, and identify three mutations in the spike protein that dampen convalescent plasma-mediated neutralization of SARS-CoV-2. Additionally, four mutations emerge in non-spike regions encoding three CD8 T cell epitopes, including one nucleoprotein epitope affected by two mutations. Recognition of each mutant peptide by CD8 T cells from convalescent donors is reduced compared to its ancestral peptide, with additive effects resulting from double mutations. Querying public SARS-CoV-2 sequences shows that these mutations have independently emerged as homoplasies in circulating lineages. Our data thus suggest that potential impacts of CD8 T cells on SARS-CoV-2 mutations, at least in those with humoral immunodeficiency, warrant further investigation to inform on vaccine design