Automated image analysis systems to quantify physical and behavioral attributes of biological entities

All life forms in nature have physical and behavioral attributes which help them survive and thrive in their environment. Technologies, both within the areas of hardware systems and data processing algorithms, have been developed to extract relevant information about these attributes. Understanding the complex interplay of physical and behavioral attributes is proving important towards identifying the phenotypic traits displayed by organisms. This thesis attempts to leverage the unique advantages of portable/mobile hardware systems and data processing algorithms for applications in three areas of bioengineering: skin cancer diagnostics, plant parasitic nematology, and neglected tropical disease. Chapter 1 discusses the challenges in developing image processing systems that meet the requirements of low cost, portability, high-throughput, and accuracy. The research motivation is inspired by these challenges within the areas of bioengineering that are still elusive to the technological advancements in hardware electronics and data processing algorithms. A literature review is provided on existing image analysis systems that highlight the limitations of current methods and provide scope for improvement. Chapter 2 is related to the area of skin cancer diagnostics where a novel smartphone-based method is presented for the early detection of melanoma in the comfort of a home setting. A smartphone application is developed along with imaging accessories to capture images of skin lesions and classify them as benign or cancerous. Information is extracted about the physical attributes of a skin lesion such as asymmetry, border irregularity, number of colors, and diameter. Machine learning is employed to train the smartphone application using both dermoscopic and digital lesion images. Chapter 3 is related to the area of plant parasitic nematology where automated methods are presented to provide the nematode egg count from soil samples. A new lensless imaging system is built to record holographic videos of soil particles flowing through microscale flow assays. Software algorithms are written to automatically identify the nematode eggs from low resolution holographic videos or images captured from a scanner. Deep learning algorithm was incorporated to improve the learning process and train the software model. Chapter 4 is related to the area of neglected tropical diseases where new worm tracking systems have been developed to characterize the phenotypic traits of Brugia malayi adult male worms and their microfilaria. The worm tracking algorithm recognizes behavioral attributes of these parasites by extracting a number of features related to their movement and body posture. An imaging platform is optimized to capture high-resolution videos with appropriate field of view of B. malayi. The relevance of each behavioral feature was evaluated through drug screening using three common antifilarial compounds. The abovementioned image analysis systems provide unique advantages to the current experimental methods. For example, the smartphone-based software application is a low-cost alternative to skin cancer diagnostics compared to standard dermoscopy available in skin clinics. The lensless imaging system is a low-cost and high-throughput alternative for obtaining egg count densities of plant parasitic nematodes compared with visual counting under a microscope by trained personnel. The B. malayi worm tracking system provides an alternative to available C. elegans tracking software with options to extract multiple parameters related to its body skeleton and posture

Uneindeutiges vereindeutigen – Zur sprachlichen Hervorbringung nicht-binärer Geschlechtsidentität [Disambiguating the Ambiguous – On the Linguistic Constitution of Non-Binary Gender Identity]

Die Praktik des Verortens kann als zentrale soziale Praktik betrachtet werden, durch die eine Person zeichenhaft ihre eigene Identität sowie eine bestimmte Wirklichkeit hervorbringt. Der Beitrag geht der Frage nach, wie sich Personen mit nicht-binärer Geschlechtsidentität verorten und welche sprachlichen Mittel sie dabei verwenden. Dazu werden mittels korpus- und textlinguistischer Methoden Beiträge von und an nicht-binäre(n) Personen analysiert

Die physiologische Funktion von TRPC6 in Endothelzellen und glatten Muskelzellen der Lunge

Das Ziel der vorliegenden Arbeit war es, die molekularen Mechanismen der hypoxischen pulmonalen Vasokonstriktion in präkapillären pulmonalen arteriellen glatten Muskelzellen (PASMC) sowie des Ischämie-Reperfusionsschadens in den Endothelzellen (LEC) der Säugerlunge zu untersuchen. Da beide fundamentale Mechanismen in TRPC6-defizienten Mäusen nicht mehr auftreten, mussten ihnen eine TRPC6-Aktivierung zugrunde liegen. Zur Aufklärung der Mechanismen auf zellulärer Ebene wurden zuerst PASMC und LEC isoliert und durch Bindung charakteristischer Antikörper identifiziert. Die Identifikation von Signalkomponenten in beiden Zelltypen gelang außerdem durch die Messung der Erhöhung der intrazellulären Ca2+-Konzentration nach Perfusion eines hypoxischen Puffers. Durch Applikation spezifischer pharmakologischer Inhibitoren und Indikatoren gelang es schließlich, Hinweise zum Ablauf der Signaltransduktionskaskaden zu sammeln. In PASMC wird während des sogenannten „priming“ durch eine geringe Rezeptoraktivierung eine basale Konzentration an Diacylglycerin, dem physiologischen Aktivator von TRPC6, gebildet, die jedoch durch die Aktivität von DAG-abbauenden DAG-Kinasen so reduziert wird, dass eine TRPC6-Aktivierung nicht möglich ist. Nach Applikation von Hypoxie führt eine postulierte Erhöhung der reaktiven Sauerstoffradikale in der Zelle jedoch zu einer Inhibition von DAG-Kinasen, zur DAG-Akkumulation und zur TRPC6-Aktivierung. In PASMC werden durch den folgenden Na+-Einstrom spannungsabhängige Ca2+-Kanäle vom L-Typ aktiviert, die den eigentlichen Ca2+-Einstrom zur Zellkontraktion einleiten. In LEC konnte eine ähnliche Signaltransduktionskaskade identifiziert werden, auch wenn hier die Notwendigkeit eines „primings“ nicht geklärt werden konnte und der Ca2+-Einstrom durch TRPC6-Kanäle verläuft, da keine spannungsabhängigen Calciumkanäle vom L-Typ exprimiert werden. Zusammenfassend lässt sich also sagen, dass der TRPC6- Kanal einen wichtigen pharmakologischen Angriffspunkt für beide Signaltransduktionskaskaden darstellt

TSC2OpenX - Realisierung einer Werkzeugkette zur Simulation abstrakter Verkehrsszenarien

For the development of autonomous vehicles, extensive testing is crucial to ensure their safety. Testing on public roads or proving grounds is not only time-consuming and expensive but can easily lead to damaged property or personal injury in dangerous traffic scenarios. To accommodate for these problems, vehicle manufacturers have turned to digitally simulating traffic scenarios. Traffic Sequence Charts (TSC), a visual description language with formal semantics, can be used to elegantly describe these scenarios. However, the specification of a traffic scenario as an "abstract scenario" using TSC cannot be read directly by simulators. In this thesis, a tool chain is presented which maps TSCs into a language that is understood by simulators and thus enables TSCs to be properly simulated

New methods of removing debris and high-throughput counting of cyst nematode eggs extracted from field soil

The soybean cyst nematode (SCN), Heterodera glycines, is the most damaging pathogen of soybeans in the United States. To assess the severity of nematode infestations in the field, SCN egg population densities are determined. Cysts (dead females) of the nematode must be extracted from soil samples and then ground to extract the eggs within. Sucrose centrifugation commonly is used to separate debris from suspensions of extracted nematode eggs. We present a method using OptiPrep as a density gradient medium with improved separation and recovery of extracted eggs compared to the sucrose centrifugation technique. Also, computerized methods were developed to automate the identification and counting of nematode eggs from the processed samples. In one approach, a high-resolution scanner was used to take static images of extracted eggs and debris on filter papers, and a deep learning network was trained to identify and count the eggs among the debris. In the second approach, a lensless imaging setup was developed using off-the-shelf components, and the processed egg samples were passed through a microfluidic flow chip made from double-sided adhesive tape. Holographic videos were recorded of the passing eggs and debris, and the videos were reconstructed and processed by custom software program to obtain egg counts. The performance of the software programs for egg counting was characterized with SCN-infested soil collected from two farms, and the results using these methods were compared with those obtained through manual counting

Watch Dog for a Plant House

The determination in selecting this project is to reduce the effects by the attributes of the nature on the plants. The proposed project we will help the user to check and maintain all the essential things like temperature, moisture in air, water content in soil and salinity in the soil required for an optimal growth of a plant. The Plant House maintenance by the user in a dynamical process is the goal of our project. In the existing system there should be a person in-charge in the room where the trees are planted and grown, to check the temperature and the other attributes which are to be maintained. To reduce the human presence in the process, in the existing system we construct a Greenhouse application which will respond to the changes in the attributes of the environment. The optimal growing environment of the different plants are stored in to the database. The application consists of a main home page where we can see the different room, if the user need to add a room he can add it. The user is recommended to enter required values for the Temperature, Humidity, Water, Fertilizer, Plant Bed, and Lightning, which are the essential needs for a plant growth. Sensors are maintained by the user, values which should match with the optimal values of the plant given by the user in the database. The fields can also be updated and also the room can also be deleted

A Cadaveric Pilot Study

This study investigates the adhesion capacity of a polyglycolic acid- (PGA-) hyaluronan scaffold with a structural modification based on a planar polymer (PM) surface in a cadaver cartilage defect model. Two cadaver specimens were used to serially test multiple chondral matrices. In a cadaver hip model, cell free polymer-based cartilage implants with a planar bioinspired PM surface (PGA-PM-scaffolds) were implanted arthroscopically on 10 mm × 15 mm full- thickness femoral hip cartilage lesions. Unprocessed cartilage implants without a bioinspired PM surface were used as control group. The cartilage implants were fixed without and with the use of fibrin glue on femoral hip cartilage defects. After 50 movement cycles and removal of the distraction, a rearthroscopy was performed to assess the outline attachment and integrity of the scaffold. The fixation techniques without and with fibrin fixation showed marginal differences for outline attachment, area coverage, scaffold integrity, and endpoint fixation after 50 cycles. The PGA-PM-scaffolds with fibrin fixation achieved a higher score in terms of the attachment, integrity, and endpoint fixation than the PGA-scaffold on the cartilage defect. Relating to the outline attachment, area coverage, scaffold integrity, and endpoint fixation, the fixation with PGA-PM-scaffolds accomplished significantly better results compared to the PGA-scaffolds . PGA-PM-scaffolds demonstrate increased observed initial fixation strength in cadaver femoral head defects relative to PGA-scaffold, particularly when fibrin glue is used for fixation