Time Series Analysis and Classification with State-Space Models for Industrial Processes and the Life Sciences

In this thesis the use of state-space models for analysis and classification of time series data, gathered from industrial manufacturing processes and the life sciences, is investigated. To overcome hitherto unsolved problems in both application domains the temporal behavior of the data is captured using state-space models. Industrial laser welding processes are monitored with a high speed camera and the appearance of unusual events in the image sequences correlates with errors on the produced part. Thus, novel classification frameworks are developed to robustly detect these unusual events with a small false positive rate. For classifier learning, class labels are by default only available for the complete image sequence, since scanning the sequences for anomalies is expensive. The first framework combines appearance based features and state-space models for the unusual event detection in image sequences. For the first time, ideas adapted from face recognition are used for the automatic dimension reduction of images recorded from laser welding processes. The state-space model is trained incrementally and can learn from erroneous sequences without the need of manually labeling the position of the error event within sequences. %The limitation to weakly labeled data helps to reduce the labeling effort. In addition, a second framework for the object-based detection of sputter events in laser welding processes is developed. The framework successfully combines for the first time temporal change detection, object tracking and trajectory classification for the detection of weak sputter events. %This is the first time that object tracking is successfully applied to automatic sputter detection. For the application in the life sciences the improvement and further development of data analysis methods for Single Molecule Fluorescence Spectroscopy (SMFS) is considered. SMFS experiments allow to study biochemical processes on a single molecule basis. The single molecule is excited with a laser and the photons which are emitted thereon by fluorescence contain important information about conformational changes of the molecule. Advanced statistical analysis techniques are necessary to infer state changes of the molecule from changes in the photon emissions. By using state-space models, it is possible to extract information from recorded photon streams which would be lost with traditional analysis techniques

Family changes and the willingness to take risks

Economic decisions frequently entail choices in the presence of risk. Decisions to purchase insurance, to save, to invest, and to pursue an education are all choices that may involve some degree of risk, just to name a few. We analyze the impact of changes in family structure on individuals' willingness to take risk (WTR). We find evidence that separating from a partner is associated with an increase in the WTR; while the birth of a first child is associated with a decrease in the WTR. Interestingly, these changes are temporary and the WTR returns to the level observed before the family event within 1–2 years following the event. Married individuals are more risk averse and this does not change with the passage of time of the actual wedding. Providing long term care is also associated with a higher WTR

The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism

Computer vision and other biometrics data science applications have commenced a new project of profiling people. Rather than using 'transaction generated information', these systems measure the 'real world' and produce an assessment of the 'world state' - in this case an assessment of some individual trait. Instead of using proxies or scores to evaluate people, they increasingly deploy a logic of revealing the truth about reality and the people within it. While these profiling knowledge claims are sometimes tentative, they increasingly suggest that only through computation can these excesses of reality be captured and understood. This article explores the bases of those claims in the systems of measurement, representation, and classification deployed in computer vision. It asks if there is something new in this type of knowledge claim, sketches an account of a new form of computational empiricism being operationalised, and questions what kind of human subject is being constructed by these technological systems and practices. Finally, the article explores legal mechanisms for contesting the emergence of computational empiricism as the dominant knowledge platform for understanding the world and the people within it

Das Naturschutzgebiet Aland-Elbe-Niederung – Ausweisung eines NSG zur Umsetzung der Ziele von NATURA 2000

Die EU verabschiedete am 21. Mai 1992 die Richtlinie zur Erhaltung der natürlichen Lebensräume sowie der wildlebenden Tiere und Pflanzen, die sogenannte Fauna-Flora-Habitat-Richtlinie (FFH-Richtlinie). Die Mitgliedsstaaten sind seitdem verpflichtet, ein europaweites Netz von besonderen Schutzgebieten zur Erhaltung der biologischen Vielfalt und zur Förderung einer nachhaltigen Entwicklung aufzubauen. In dieses Natura 2000 genannte Netz sind auch die auf der Grundlage der seit 1979 geltenden EU-Vogelschutzrichtlinie gemeldeten Europäischen Vogelschutzgebiete (EU SPA) integriert. Die reichhaltige Naturausstattung Sachsen-Anhalts ermöglichte die Auswahl von 265 FFH-Gebieten und 32 Vogelschutzgebieten (EU SPA). Die Gebiete wurden als „Gebiete von gemeinschaftlicher Bedeutung der kontinentalen und der atlantischen biogeographischen Region“ im Amtsblatt der EU vom 15.01.2008 veröffentlicht. Nach den Vorgaben der FFH- und Vogelschutzrichtlinie sind die Natura 2000-Gebiete nun als besondere Schutzgebiete national zu sichern. Darüber hinaus sind in den besonderen Schutzgebieten geeignete Maßnahmen zu treffen, um die Verschlechterung der natürlichen Lebensräume und der Habitate der Arten, für die die Gebiete ausgewiesen worden sind, zu vermeiden (vgl. Art. 6, Abs. 2 FFH Richtlinie). Alle erforderlichen Maßnahmen sind an den Ansprüchen der in den jeweiligen Gebieten vorkommenden Lebensraumtypen und Arten auszurichten. Mit dem vorliegenden Sonderheft wird beispielhaft der Verfahrensweg der Ausweisung des Naturschutzgebietes Aland-Elbe-Niederung zur Umsetzung von Natura 2000 im Land Sachsen-Anhalt dokumentiert. Neben der Darstellung der naturräumlichen Situation des Gebietes und seiner naturschutzfachlichen Bedeutung werden insbes. Inhalt und Ablauf des Verwaltungsverfahrens sowie die Lösung der vielfältigen Nutzungskonflikte dargestellt. Dem Heft liegt eine beidseitig bedruckte Schutzgebietskarte des Landes Sachsen-Anhalt im Maßstab 1:250.000 bei. Auf einer Seite sind Schutzgebiete nach internationalem Recht dargestellt. Die zweite Seite der Karte liefert eine aktuelle Zusammenstellung (Stand 31.12.2009) der nach Landesnaturschutzrecht geschützten Gebiete und Objekte. Ein Beiheft mit Namen, Bezeichnung und Größe aller Gebiete komplettiert die Ausgabe

Does retail food diversity in urban food environments influence consumer diets?

The food environment influences consumer diets in significant yet underexplored ways. In this study, we assess the way in which the Nairobi urban food environment—availability, accessibility, affordability, desirability, convenience and marketing—influences the dietary choices and quality of poor urban consumers, by combining market-level diversity scores (MLDS) with household and individual data collected from resource-poor (slum) neighbourhoods in Nairobi, Kenya. We find that urban-poor settings are characterized by a variety of food retail venues, including informal markets such as kiosks, mom-and-pop shops and tabletop vendors, as well as modern retail outlets such as supermarkets. Most of these food outlets predominantly sell unhealthy, highly-processed and energy-dense foods rather than nutritious foods such as vegetables, fruits and animal products. Our analyses show that supermarkets have the highest MLDS, yet they do not significantly influence the diets of resource-poor households. However, a high MLDS among informal retail outlets has a positive association with diet quality; conversely, open-air markets have a negative association. The nutritional status of urban-poor consumers can be improved by promoting the diversification of healthy, nutritious foods across traditional retail outlets and improving accessibility of the outlets to consumers

Microscopic Aquatic Predators Strongly Affect Infection Dynamics of a Globally Emerged Pathogen

Research on emerging infectious wildlife diseases has placed particular emphasis on host-derived barriers to infection and disease. This focus neglects important extrinsic determinants of the host/pathogen dynamic, where all barriers to infection should be considered when ascertaining the determinants of infectivity and pathogenicity of wildlife pathogens [1–3]. Those pathogens with free-living stages, such as fungi causing catastrophic wildlife declines on a global scale [4], must confront lengthy exposure to environmental barriers before contact with an uninfected host [5–8]. Hostile environmental conditions therefore have the ability to decrease the density of infectious particles, reducing the force of infection and ameliorating the impact as well as the probability of establishing an infection [9]. Here we show that, in nature, the risk of infection and infectious burden of amphibians infected by the chytrid fungus Batrachochytrium dendrobatidis (Bd) have a significant, site-specific component, and that these correlate with the microfauna present at a site. Experimental infections show that aquatic microfauna can rapidly lower the abundance and density of infectious stages by consuming Bd zoospores, resulting in a significantly reduced probability of infection in anuran tadpoles. Our findings offer new perspectives for explaining the divergent impacts of Bd infection in amphibian assemblages and contribute to our understanding of ecosystem resilience to colonization by novel pathogens

Mercados informales para reducir la pobreza y para seguridad alimentaria: Explorando opciones políticas en Nicaragua y Honduras

Mucha de la investigación en cadenas de valor y enlaces de mercado generalmente se enfoca en los mercados formales o supermercados, haciendo comparaciones con los mercados tradicionales. Ese tipo de investigaciones podrían generar un sesgo en el diseño de intervenciones políticas hacia inversiones públicas que pueden beneficiar al 10% de los productores más pudientes y el sector privado a los que ellos suplen. Mientras tanto se ha dado poca atención al 90% restante de productores, los mercados tradicionales (o informales, o municipales) donde estos son activos, y los canales de distribución informales que benefician a la clase pobre urbana. Este estudio se realizó en 2015 en Nicaragua y Honduras, con el objetivo de (a) entender los enlaces rural-urbano existentes entre productores pequeños y consumidores pobres de una canasta representativa de productos alimenticios, (b) identificar puntos de apalancamiento para políticas públicas destinadas a mercados tradicionales o informales que puedan aumentar los beneficios tanto para productores rurales como consumidores urbanos, y (c) evaluar si es factible construir modelos de negocio más inclusivos entre actores en mercados tradicionales. Este reporte presenta los resultados encontrados para Nicaragua

Late-Stage Modification of Aminoglycoside Antibiotics Overcomes Bacterial Resistance Mediated by APH(3') Kinases

The continuous emergence of antimicrobial resistance is causing a threat to patients infected by multidrug‐resistant pathogens. In particular, the clinical use of aminoglycoside antibiotics, broad‐spectrum antibacterials of last resort, is limited due to rising bacterial resistance. One of the major resistance mechanisms in Gram‐positive and Gram‐negative bacteria is phosphorylation of these amino sugars at the 3’‐position by O‐phosphotransferases [APH(3’)s]. Structural alteration of these antibiotics at the 3’‐position would be an obvious strategy to tackle this resistance mechanism. However, the access to such derivatives requires cumbersome multi‐step synthesis, which is not appealing for pharma industry in this low‐return‐on‐investment market. To overcome this obstacle and combat bacterial resistance mediated by APH(3’)s, we introduce a novel regioselective modification of aminoglycosides in the 3’‐position via palladium‐catalyzed oxidation. To underline the effectiveness of our method for structural modification of aminoglycosides, we have developed two novel antibiotic candidates overcoming APH(3’)s‐mediated resistance employing only four synthetic steps

Transformer-based out-of-distribution detection for clinically safe segmentation

In a clinical setting it is essential that deployed image processing systems are robust to the full range of inputs they might encounter and, in particular, do not make confidently wrong predictions. The most popular approach to safe processing is to train networks that can provide a measure of their uncertainty, but these tend to fail for inputs that are far outside the training data distribution. Recently, generative modelling approaches have been proposed as an alternative; these can quantify the likelihood of a data sample explicitly, filtering out any out-of-distribution (OOD) samples before further processing is performed. In this work, we focus on image segmentation and evaluate several approaches to network uncertainty in the far-OOD and near-OOD cases for the task of segmenting haemorrhages in head CTs. We find all of these approaches are unsuitable for safe segmentation as they provide confidently wrong predictions when operating OOD. We propose performing full 3D OOD detection using a VQ-GAN to provide a compressed latent representation of the image and a transformer to estimate the data likelihood. Our approach successfully identifies images in both the far- and near-OOD cases. We find a strong relationship between image likelihood and the quality of a model’s segmentation, making this approach viable for filtering images unsuitable for segmentation. To our knowledge, this is the first time transformers have been applied to perform OOD detection on 3D image data.</p