413 research outputs found

    Design, Integration, and Field Evaluation of a Robotic Blossom Thinning System for Tree Fruit Crops

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    The US apple industry relies heavily on semi-skilled manual labor force for essential field operations such as training, pruning, blossom and green fruit thinning, and harvesting. Blossom thinning is one of the crucial crop load management practices to achieve desired crop load, fruit quality, and return bloom. While several techniques such as chemical, and mechanical thinning are available for large-scale blossom thinning such approaches often yield unpredictable thinning results and may cause damage the canopy, spurs, and leaf tissue. Hence, growers still depend on laborious, labor intensive and expensive manual hand blossom thinning for desired thinning outcomes. This research presents a robotic solution for blossom thinning in apple orchards using a computer vision system with artificial intelligence, a six degrees of freedom robotic manipulator, and an electrically actuated miniature end-effector for robotic blossom thinning. The integrated robotic system was evaluated in a commercial apple orchard which showed promising results for targeted and selective blossom thinning. Two thinning approaches, center and boundary thinning, were investigated to evaluate the system ability to remove varying proportion of flowers from apple flower clusters. During boundary thinning the end effector was actuated around the cluster boundary while center thinning involved end-effector actuation only at the cluster centroid for a fixed duration of 2 seconds. The boundary thinning approach thinned 67.2% of flowers from the targeted clusters with a cycle time of 9.0 seconds per cluster, whereas center thinning approach thinned 59.4% of flowers with a cycle time of 7.2 seconds per cluster. When commercially adopted, the proposed system could help address problems faced by apple growers with current hand, chemical, and mechanical blossom thinning approaches

    Vision-based safe autonomous UAV landing with panoramic sensors

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    The remarkable growth of unmanned aerial vehicles (UAVs) has also raised concerns about safety measures during their missions. To advance towards safer autonomous aerial robots, this thesis strives to develop a safe autonomous UAV landing solution, a vital part of every UAV operation. The project proposes a vision-based framework for monitoring the landing area by leveraging the omnidirectional view of a single panoramic camera pointing upwards to detect and localize any person within the landing zone. Then, it sends this information to approaching UAVs to either hover and wait or adaptively search for a more optimal position to land themselves. We utilize and fine-tune the YOLOv7 object detection model, an XGBooxt model for localizing nearby people, and the open-source ROS and PX4 frameworks for communications and drone control. We present both simulation and real-world indoor experimental results to demonstrate the capability of our methods

    Microbial Community Composition and Competitive Dynamics Within Squid Symbioses

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    Animals evolved surrounded by bacteria, resulting in widespread symbioses in which host and symbiont often form specialized partnerships that are essential for host development, reproduction, or survival. During host-colonization, bacteria are often forced together within a physical space, providing opportunities for competitive and cooperative interactions that ultimately shape the microbial community within a given host. The first three chapters of this dissertation use the light organ symbiont Vibrio fischeri as a model bacterium for studying these complex microbial interactions. V. fischeri encodes a strain-specific T6SS, a contact-mediated killing mechanism found broadly distributed among host-associated bacteria. I designed a microscopy workflow to quantify contact-dependent competition at the single-cell level and applied this technique to study competitive interactions between lethal and non-lethal V. fischeri strains in vitro. Then, I used this assay in combination with a subcellular biomechanical model for T6SS to investigate killing dynamics within lethal-lethal interactions. This study revealed that strains with the ability to activate T6SS more quickly under host-like conditions outcompete slower-activating strains, even if both isolates are lethal. In addition to T6SS, V. fischeri encodes both conserved and strain-specific mechanisms for horizontal gene transfer (HGT). Using an experimental evolution assay designed to detect transfer of selectable chromosomal markers, I found that V. fischeri exchanges chromosomal DNA in coculture in a manner inconsistent with any HGT mechanism that has been previously described in V. fischeri. Although squid light organs represent an important model for bacterial interactions, we currently lack a fundamental understanding of the natural microbial community across other squid body sites. In the final chapter of this dissertation, I characterized the microbial community of mantle, gill, sub-mantle tissue, and accessory nidamental glands of wild-caught Lolliguncula brevis squid using a combination of culture-based techniques, microscopy, and amplicon sequencing. I found that L. brevis hosts multiple species of culturable Vibrios, a core community of Bradyrhizobium that is conserved across body sites, and a surprisingly diverse gill community. Taken together, this dissertation provided new tools for evaluating interactions between symbiotic bacteria, and also introduced L. brevis as an exciting system that warrants further study into the complexity of squid microbiomes.Doctor of Philosoph

    Augmented reality (AR) for surgical robotic and autonomous systems: State of the art, challenges, and solutions

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    Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human-robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future

    Enabling Multi-LiDAR Sensing in GNSS-Denied Environments: SLAM Dataset, Benchmark, and UAV Tracking with LiDAR-as-a-camera

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    The rise of Light Detection and Ranging (LiDAR) sensors has profoundly impacted industries ranging from automotive to urban planning. As these sensors become increasingly affordable and compact, their applications are diversifying, driving precision, and innovation. This thesis delves into LiDAR's advancements in autonomous robotic systems, with a focus on its role in simultaneous localization and mapping (SLAM) methodologies and LiDAR as a camera-based tracking for Unmanned Aerial Vehicles (UAV). Our contributions span two primary domains: the Multi-Modal LiDAR SLAM Benchmark, and the LiDAR-as-a-camera UAV Tracking. In the former, we have expanded our previous multi-modal LiDAR dataset by adding more data sequences from various scenarios. In contrast to the previous dataset, we employ different ground truth-generating approaches. We propose a new multi-modal multi-lidar SLAM-assisted and ICP-based sensor fusion method for generating ground truth maps. Additionally, we also supplement our data with new open road sequences with GNSS-RTK. This enriched dataset, supported by high-resolution LiDAR, provides detailed insights through an evaluation of ten configurations, pairing diverse LiDAR sensors with state-of-the-art SLAM algorithms. In the latter contribution, we leverage a custom YOLOv5 model trained on panoramic low-resolution images from LiDAR reflectivity (LiDAR-as-a-camera) to detect UAVs, demonstrating the superiority of this approach over point cloud or image-only methods. Additionally, we evaluated the real-time performance of our approach on the Nvidia Jetson Nano, a popular mobile computing platform. Overall, our research underscores the transformative potential of integrating advanced LiDAR sensors with autonomous robotics. By bridging the gaps between different technological approaches, we pave the way for more versatile and efficient applications in the future

    Augmented Reality (AR) for Surgical Robotic and Autonomous Systems: State of the Art, Challenges, and Solutions

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    Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human–robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future

    Nanobubble Technology for the Removal of MIB and Geosmin From Drinking Water

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    The presence of taste and odor (T&O) compounds in drinking water has been historically a major challenge for water utilities. They are difficult to remove using conventional water treatment processes, a combination of coagulation, flocculation, sedimentation, filtration, and chlorination. However, activated carbon (AC) adsorption, advanced oxidation processes, and biofiltration can be effective. The seasonal nature of T&O events makes it difficult to justify installing dedicated treatment technologies. Additionally, incorporating these technologies into existing water treatment plants can be expensive and require significant upgrades. Therefore, water utilities are always interested in exploring new approaches to minimize the occurrence and removal of T&O compounds in drinking water. Nanobubbles (NBs) can provide innovative solutions to T&O problems in water supplies and water treatment. The main objectives of this dissertation were to conduct a comprehensive investigation to systematically examine (i) the characterization and stability of oxygen and ozone NBs in typical freshwater and drinking water treatment conditions and ii) the removal efficiency and mechanisms of geosmin and 2-methylisoborneol (MIB), the major and most common T&O compounds in freshwaters, by NBs. First, the stability of oxygen NBs was investigated under the representative key natural water chemistry conditions and constituents, including pH, Ca2+, Na+, natural organic matter (NOM) and temperature. The half-lives of oxygen NBs followed the order Ca2+ \u3c Na+ \u3c pH 3 \u3c high SUVA254 NOM \u3c pH 5 \u3c 30 ◦C. Calcium was the most influential parameter significantly decreasing NBs levels among all parameters investigated. The main disappearance pathway of the negatively charged oxygen NBs in water was found to be coalescence, which was promoted greatly by cations (i.e., Ca2+, Na+ and low pH) and adsorption of NOM with high aromaticity onto the surface of oxygen NBs. The impact of higher temperatures became more noticeable after longer storage periods, where higher temperatures increase the kinetic energy of oxygen NBs, making them more likely to collide and coalesce. Therefore, when oxygen NBs are released or used in freshwater, high calcium, high SUVA254 NOM, and low pH would significantly reduce their availability and residence times. Second, removal of geosmin and MIB from water by oxygen NBs was investigated. Initially, comparisons of nitrogen, air, and oxygen NBs showed higher removal percentages of geosmin and MIB as the oxygen content in NBs increased. Using oxygen NBs, volatilization was the dominant mechanism for the removal of geosmin (~40%) and MIB (~20%), while oxidation by reactive oxygen species (ROS) brought additional removal of up to 15%. The formation of hydroxyl (•OH) radicals was promoted when NBs were mixed with microbubbles (MBs). Formation of singlet oxygen and superoxide radicals did not appear to play a role for removal of target compounds by oxygen NBs. Alkalinity decreased the removal percentages of both geosmin and MIB by scavenging •OH radicals and inhibiting the oxidative removal pathway, while pH in the range of 3 to 10 had no significant impact on the geosmin and MIB removal. Geosmin and MIB removals were higher at higher temperatures due to increased volatilization and oxidative processes, where they decreased in the presence of either NOM or hardness. Under all tested conditions, geosmin removal efficiency was consistently higher than MIB due to the difference in their physicochemical properties (i.e., hydrophobicity or Log Kow, Henry’s law constant, functional groups, and steric hindrance of the MIB structure). Overall, the use of oxygen NBs resulted in less than 15% enhancement in removal of geosmin and MIB through the oxidative pathway. Third, the characterization of ozone NBs, their stability and •OH radical formation from ozone decomposition were examined under freshwater conditions. Ozone NBs were more stable than oxygen NBs because of their higher negative surface charge (i.e., −32.0 mV and −23.6 mV, respectively). Ozone NBs generated at a higher dissolved ozone concentration (12.5 mg/L) exhibited greater stability (and higher negative surface charge) than those generated at a lower dissolved ozone concentration (1 mg/L) during long-term storage, which showed that ozone NBs generation conditions affect their stability and physicochemical properties. The stability of ozone NBs (generated at 12.5 mg/L dissolved ozone) were investigated under different pH, NOM, alkalinity, calcium, and temperature of freshwater conditions, for an extended storage time (i.e., 255 days). The half-lives of ozone NBs followed the order of 3 mM Ca2+ \u3c pH 3 \u3c high SUVA254 NOM (4.1 L/mg.m) \u3c pH 7 \u3c pH 9, while the effects of carbonate (or alkalinity) and temperature on the stability of ozone NBs were insignificant. Thus, ozone NBs would be stable for up to several months in natural waters depending on the water hardness and aromaticity of NOM. The formation of •OH radicals in ozone NBs solutions was 2 – 3 times higher than conventional ozonation during the same reaction time. A rapid disappearance of ozone NBs in the presence of 3 mM Ca2+ led to almost no additional •OH radical formation and the overall concentration of •OH radicals in that solution was comparable to conventional ozonation. The presence of carbonate ions lowered the formation of •OH radicals, but it was not enough to stop the continuous generation of radicals. However, NBs concentrations were not affected by the presence of carbonate in the background water. Fourth, the removal efficiencies of geosmin and MIB were investigated by ozone NBs and compared side-by-side with conventional ozonation. The primary mechanism of geosmin and MIB removal by both conventional ozonation and ozone NBs was oxidative degradation via •OH radicals. Ozone NBs were more effective at removing geosmin and MIB (i.e., 80% and 73%, respectively) than conventional ozonation (i.e., 69% and 54%, respectively) in a 10-minute contact time at 20°C in distilled and deionized (DDI) water, which was due to the higher •OH radical formation in ozone NB water. Furthermore, in natural waters, ozone NBs maintained its performance with 85% and 74% removal of geosmin and MIB, respectively, which is more than 10% higher than conventional ozone at 20 ᵒC. Increasing temperature from 20 to 30 ᵒC enhanced the removal efficiencies of geosmin and MIB for ozone NBs (i.e., up to 15 %) and conventional ozonation (up to 6%) in DDI and natural waters. Reducing the initial ozone dose from 1.0 (O3/DOC= 0.43 mg/mg) to 0.5 mg/L (O3/DOC= 0.22 mg/mg) at 20 ᵒC widened the gap in removal efficiencies (i.e., up to 20%) between ozone NBs and conventional ozonation in natural water, demonstrating that the effectiveness of ozone NBs was less impacted by lowering the ozone dose. This can be explained by the presence of the same amount of ozone NBs in solutions for 0.5 and 1.0 mg/L ozone even though ozone level was reduced. While the addition of calcium (300 mg/L as CaCO3) reduced the ozone NBs concentration, it did not impact the geosmin and MIB removal by ozone NBs. On the other hand, the presence of background alkalinity (250 mg/L as CaCO3) decreased the removal efficiencies of geosmin and MIB, but its impact on ozone NBs (i.e., 7-10%) was less than conventional ozonation (11-13%). Lastly, bromate formation in the presence of 250 µg/L bromide was not significantly different between ozone NBs and conventional ozone, and the bromate level was below the USEPA regulatory limit of 10 µg/L. The results showed that the use of ozone NBs is more efficient and performs better than conventional ozonation during water treatment, which will reduce the cost and the environmental impact of the treatment process. Overall, this research showed that oxygen NBs will be more effective for oxygen transfer applications (e.g., aeration) especially in low hardness waters with long term stability of oxygen NB, while the oxidative capabilities of oxygen NBs are rather much less important due to lower amount of ROS (mainly •OH) formation. On the other hand, ozone NBs, with their •OH formation, are more effective in the abiotic degradation of organic compounds than conventional ozonation. Ozone NBs, depending on the generation conditions, carry a higher negative surface charge than oxygen NBs, giving them longer stability in water, except increasing calcium levels significantly reduce both NBs stability

    Giardia duodenalis – deciphering barrier break down in human, organoid-derived duodenal monolayers

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    Das Protozoon Giardia duodenalis ist eine der Hauptursachen für infektiöse Magen-Darm-Erkrankungen. Die zugrundeliegenden Pathomechanismen sind jedoch nach wie vor unklar. Um die Pathogenität G. duodenalis‘ untersuchen zu können, wird ein Modellsystem benötigt, dass die Komplexität des Darmepithels widerspiegelt. Diese Arbeit zeigt die Etablierung eines Zellkultursystems auf der Basis von organoid-abgeleiteten Epithelien unter Verwendung von filter-basierten Zellkultureinsätzen. Wir haben Protokolle für die Etablierung von organoid-basierten Zellkulturen (ODMs) vier verschiedener Wirte zoonotischer Protozoen unter Verwendung eines einzigen Protokolls erstellt. Die Charakterisierung zeigte, dass das Modellsystem erfolgreich die Polarisierung des Darmepithels nachahmt, aus mehreren Zelltypen besteht und eine Infektion ermöglicht. Der Schwerpunkt der Arbeit lag auf der Analyse der durch G. duodenalis induzierten Barrierestörung in ODMs auf Transkriptions-, Protein- und Funktionsebene. Die Infektion von humanen duodenalen Zellen führte zu einem Verlust der epithelialen Barrierefunktion. Mit Hilfe des transepithelialen elektrischen Widerstandes und Dextran Flux wurde eine Erhöhung der Barrieredurchlässigkeit beobachtet. Die Hemmung von zuvor in immortalisierten Zellmodellen beschriebenen Reaktionswegen konnte die Barrierefunktion nicht wiederherstellen. Stattdessen konnten Veränderungen der Ionenhomöostase sowie den Zusammenbruch der zonula occludens nachgewiesen werden. Der beobachtete Phänotyp konnte auf die Aktivierung des cAMP/PKA/CREB-Signalwegs, als einen von mehreren kausalen Faktoren, zurückgeführt werden. Hier zeigen wir die Etablierung eines aus Organoiden abgeleiteten Modells, das die Untersuchung von G. duodenalis Infektionen in vitro ermöglicht. Mit unserem Modell konnten wir eine neue Reihenfolge von Ereignissen entschlüsseln, die einen der Faktoren während symptomatischer Giardiasis darstellt.The protozoan Giardia duodenalis is a one of the major causes of gastrointestinal illness. Underlying pathomechanisms remain unclear. An in vitro model system that also mimics the complexity of intestinal epithelium is needed to allow pathogenicity studies. This thesis shows the establishment of a cell culture system based on organoid-derived epithelia using permeable cell culture inserts. We have provided guidelines on the establishment of organoid-derived monolayers (ODMs) of four different hosts of zoonotic protozoa using a single protocol. Characterization showed that the model system successfully mimics intestinal polarization, is composed of multiple cell types and allows for infection with multiple protozoan parasites. As the main focus of the thesis, analysis of G. duodenalis-induced barrier breakdown in ODMs was performed on transcriptional, protein and functional level. Infection of human duodenal, organoid-derived monolayers resulted in a time- and dose-dependent breakdown of epithelial barrier function. Barrier permeability increases were observed ranging from ions to macromolecules as measured by transepithelial electrical resistance and Dextran flux. Inhibition of previously proposed key pathogen-induced pathways observed in immortalized cell models did not rescue barrier dysfunction. We could instead show changes in ion homeostasis, and tight junctional breakdown. While none of the previously proposed effector pathways appeared to be responsible, we could pin-point the observed phenotype to activation of the cAMP/PKA/CREB signaling pathway, as one of the factors of the multifactorial barrier breakdown. The establishment of an organoid-derived infection model is shown, allowing the study of in vitro Giardia duodenalis infections. Using this model, we could decipher a new series of events that may be one of the factors causing the intestinal barrier breakdown observed in symptomatic Giardiasis

    Content-aware approach for improving biomedical image analysis: an interdisciplinary study series

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    Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity
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