TY - RPRT A1 - Großmann, Marcel A1 - Homeyer, Tobias T1 - Emulation of Multipath Transmissions in P4 Networks with Kathará T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - Packets sent over a network can either get lost or reach their destination. Protocols like TCP try to solve this problem by resending the lost packets. However, retransmissions consume a lot of time and are cumbersome for the transmission of critical data. Multipath solutions are quite common to address this reliability issue and are available on almost every layer of the ISO/OSI model. We propose a solution based on a P4 network to duplicate packets in order to send them to their destination via multiple routes. The last network hop ensures that only a single copy of the traffic is further forwarded to its destination by adopting a concept similar to Bloom filters. Besides, if fast delivery is requested we provide a P4 prototype, which randomly forwards the packets over different transmission paths. For reproducibility, we implement our approach in a container-based network emulation system called Kathará. KW - P4 KW - multipath KW - emulation KW - Kathará Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322095 ER - TY - RPRT A1 - Riegler, Clemens A1 - Kayal, Hakan T1 - VELEX: Venus Lightning Experiment N2 - Lightning has fascinated humanity since the beginning of our existence. Different types of lightning like sprites and blue jets were discovered, and many more are theorized. However, it is very likely that these phenomena are not exclusive to our home planet. Venus’s dense and active atmosphere is a place where lightning is to be expected. Missions like Venera, Pioneer, and Galileo have carried instruments to measure electromagnetic activity. These measurements have indeed delivered results. However, these results are not clear. They could be explained by other effects like cosmic rays, plasma noise, or spacecraft noise. Furthermore, these lightning seem different from those we know from our home planet. In order to tackle these issues, a different approach to measurement is proposed. When multiple devices in different spacecraft or locations can measure the same atmospheric discharge, most other explanations become increasingly less likely. Thus, the suggested instrument and method of VELEX incorporates multiple spacecraft. With this approach, the question about the existence of lightning on Venus could be settled. T3 - Raumfahrttechnik und Extraterrestrik - 3 KW - Venus KW - Lightning KW - CubeSat KW - Balloon KW - Autorotation Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-282481 ER - TY - JOUR A1 - Wamser, Florian A1 - Seufert, Anika A1 - Hall, Andrew A1 - Wunderer, Stefan A1 - Hoßfeld, Tobias T1 - Valid statements by the crowd: statistical measures for precision in crowdsourced mobile measurements JF - Network N2 - Crowdsourced network measurements (CNMs) are becoming increasingly popular as they assess the performance of a mobile network from the end user's perspective on a large scale. Here, network measurements are performed directly on the end-users' devices, thus taking advantage of the real-world conditions end-users encounter. However, this type of uncontrolled measurement raises questions about its validity and reliability. The problem lies in the nature of this type of data collection. In CNMs, mobile network subscribers are involved to a large extent in the measurement process, and collect data themselves for the operator. The collection of data on user devices in arbitrary locations and at uncontrolled times requires means to ensure validity and reliability. To address this issue, our paper defines concepts and guidelines for analyzing the precision of CNMs; specifically, the number of measurements required to make valid statements. In addition to the formal definition of the aspect, we illustrate the problem and use an extensive sample data set to show possible assessment approaches. This data set consists of more than 20.4 million crowdsourced mobile measurements from across France, measured by a commercial data provider. KW - mobile networks KW - crowdsourced measurements KW - statistical validity Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-284154 SN - 2673-8732 VL - 1 IS - 2 SP - 215 EP - 232 ER - TY - RPRT A1 - Grigorjew, Alexej A1 - Schumann, Lukas Kilian A1 - Diederich, Philip A1 - Hoßfeld, Tobias A1 - Kellerer, Wolfgang T1 - Understanding the Performance of Different Packet Reception and Timestamping Methods in Linux T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - This document briefly presents some renowned packet reception techniques for network packets in Linux systems. Further, it compares their performance when measuring packet timestamps with respect to throughput and accuracy. Both software and hardware timestamps are compared, and various parameters are examined, including frame size, link speed, network interface card, and CPU load. The results indicate that hardware timestamping offers significantly better accuracy with no downsides, and that packet reception techniques that avoid system calls offer superior measurement throughput. KW - packet reception method KW - timestamping method KW - Linux Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322064 ER - TY - THES A1 - Somody, Joseph Christian Campbell T1 - Leveraging deep learning for identification and structural determination of novel protein complexes from \(in\) \(situ\) electron cryotomography of \(Mycoplasma\) \(pneumoniae\) T1 - Tiefenlernen als Werkzeug zur Identifizierung und Strukturbestimmung neuer Proteinkomplexe aus der \(in\)-\(situ\)-Elektronenkryotomographie von \(Mycoplasma\) \(pneumoniae\) N2 - The holy grail of structural biology is to study a protein in situ, and this goal has been fast approaching since the resolution revolution and the achievement of atomic resolution. A cell's interior is not a dilute environment, and proteins have evolved to fold and function as needed in that environment; as such, an investigation of a cellular component should ideally include the full complexity of the cellular environment. Imaging whole cells in three dimensions using electron cryotomography is the best method to accomplish this goal, but it comes with a limitation on sample thickness and produces noisy data unamenable to direct analysis. This thesis establishes a novel workflow to systematically analyse whole-cell electron cryotomography data in three dimensions and to find and identify instances of protein complexes in the data to set up a determination of their structure and identity for success. Mycoplasma pneumoniae is a very small parasitic bacterium with fewer than 700 protein-coding genes, is thin enough and small enough to be imaged in large quantities by electron cryotomography, and can grow directly on the grids used for imaging, making it ideal for exploratory studies in structural proteomics. As part of the workflow, a methodology for training deep-learning-based particle-picking models is established. As a proof of principle, a dataset of whole-cell Mycoplasma pneumoniae tomograms is used with this workflow to characterize a novel membrane-associated complex observed in the data. Ultimately, 25431 such particles are picked from 353 tomograms and refined to a density map with a resolution of 11 Å. Making good use of orthogonal datasets to filter search space and verify results, structures were predicted for candidate proteins and checked for suitable fit in the density map. In the end, with this approach, nine proteins were found to be part of the complex, which appears to be associated with chaperone activity and interact with translocon machinery. Visual proteomics refers to the ultimate potential of in situ electron cryotomography: the comprehensive interpretation of tomograms. The workflow presented here is demonstrated to help in reaching that potential. N2 - Der heilige Gral der Strukturbiologie ist die Untersuchung eines Proteins in situ, und dieses Ziel ist seit der Auflösungsrevolution und dem Erreichen der atomaren Auflösung in greifbare Nähe gerückt. Das Innere einer Zelle ist keine verdünnte Umgebung, und Proteine haben sich so entwickelt, dass sie sich falten und so funktionieren, wie es in dieser Umgebung erforderlich ist; daher sollte die Untersuchung einer zellulären Komponente idealerweise die gesamte Komplexität der zellulären Umgebung umfassen. Die Abbildung ganzer Zellen in drei Dimensionen mit Hilfe der Elektronenkryotomographie ist die beste Methode, um dieses Ziel zu erreichen, aber sie ist mit einer Beschränkung der Probendicke verbunden und erzeugt verrauschte Daten, die sich nicht für eine direkte Analyse eignen. In dieser Dissertation wird ein neuartiger Workflow zur systematischen dreidimensionalen Analyse von Ganzzell-Elektronenkryotomographiedaten und zur Auffindung und Identifizierung von Proteinkomplexen in diesen Daten entwickelt, um eine erfolgreiche Bestimmung ihrer Struktur und Identität zu ermöglichen. Mycoplasma pneumoniae ist ein sehr kleines parasitäres Bakterium mit weniger als 700 proteinkodierenden Genen. Es ist dünn und klein genug, um in grossen Mengen durch Elektronenkryotomographie abgebildet zu werden, und kann direkt auf den für die Abbildung verwendeten Gittern wachsen, was es ideal für Sondierungsstudien in der strukturellen Proteomik macht. Als Teil des Workflows wird eine Methodik für das Training von Deep-Learning-basierten Partikelpicken-Modellen entwickelt. Als Proof-of-Principle wird ein Dataset von Ganzzell-Tomogrammen von Mycoplasma pneumoniae mit diesem Workflow verwendet, um einen neuartigen membranassoziierten Komplex zu charakterisieren, der in den Daten beobachtet wurde. Insgesamt wurden 25431 solcher Partikel aus 353 Tomogrammen gepickt und zu einer Dichtekarte mit einer Auflösung von 11 Å verfeinert. Unter Verwendung orthogonaler Datensätze zur Filterung des Suchraums und zur Überprüfung der Ergebnisse wurden Strukturen für Protein-Kandidaten vorhergesagt und auf ihre Eignung für die Dichtekarte überprüft. Letztendlich wurden mit diesem Ansatz neun Proteine als Bestandteile des Komplexes gefunden, der offenbar mit der Chaperonaktivität in Verbindung steht und mit der Translocon-Maschinerie interagiert. Das ultimative Potenzial der In-situ-Elektronenkryotomographie – die umfassende Interpretation von Tomogrammen – wird als visuelle Proteomik bezeichnet. Der hier vorgestellte Workflow soll dabei helfen, dieses Potenzial auszuschöpfen. KW - Kryoelektronenmikroskopie KW - Tomografie KW - Mycoplasma pneumoniae KW - Deep learning KW - cryo-EM KW - cryo-ET KW - tomography KW - mycoplasma KW - pneumoniae KW - deep learning KW - particle picking KW - membrane protein KW - visual proteomics Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313447 ER - TY - RPRT A1 - Elsayed, Karim A1 - Rizk, Amr T1 - Response Times in Time-to-Live Caching Hierarchies under Random Network Delays T2 - Würzburg Workshop on Next-Generation Communication Networks (WueWoWas'22) N2 - Time-to-Live (TTL) caches decouple the occupancy of objects in cache through object-specific validity timers. Stateof- the art techniques provide exact methods for the calculation of object-specific hit probabilities given entire cache hierarchies with random inter-cache network delays. The system hit probability is a provider-centric metric as it relates to the origin offload, i.e., the decrease in the number of requests that are served by the content origin server. In this paper we consider a user-centric metric, i.e., the response time, which is shown to be structurally different from the system hit probability. Equipped with the state-of-theart exact modeling technique using Markov-arrival processes we derive expressions for the expected object response time and pave a way for its optimization under network delays. KW - Datennetz KW - TTL Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-280843 ER - TY - RPRT A1 - Alfredsson, Rebecka A1 - Kassler, Andreas A1 - Vestin, Jonathan A1 - Pieska, Marcus A1 - Amend, Markus T1 - Accelerating a Transport Layer based 5G Multi-Access Proxy on SmartNIC T2 - Würzburg Workshop on Next-Generation Communication Networks (WueWoWas'22) N2 - Utilizing multiple access technologies such as 5G, 4G, and Wi-Fi within a coherent framework is currently standardized by 3GPP within 5G ATSSS. Indeed, distributing packets over multiple networks can lead to increased robustness, resiliency and capacity. A key part of such a framework is the multi-access proxy, which transparently distributes packets over multiple paths. As the proxy needs to serve thousands of customers, scalability and performance are crucial for operator deployments. In this paper, we leverage recent advancements in data plane programming, implement a multi-access proxy based on the MP-DCCP tunneling approach in P4 and hardware accelerate it by deploying the pipeline on a smartNIC. This is challenging due to the complex scheduling and congestion control operations involved. We present our pipeline and data structures design for congestion control and packet scheduling state management. Initial measurements in our testbed show that packet latency is in the range of 25 μs demonstrating the feasibility of our approach. KW - Datennetz KW - multipath KW - MP-DCCP KW - 5G-ATSSS KW - networking KW - dataplane programming KW - P4 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-280798 ER - TY - JOUR A1 - Bencurova, Elena A1 - Shityakov, Sergey A1 - Schaack, Dominik A1 - Kaltdorf, Martin A1 - Sarukhanyan, Edita A1 - Hilgarth, Alexander A1 - Rath, Christin A1 - Montenegro, Sergio A1 - Roth, Günter A1 - Lopez, Daniel A1 - Dandekar, Thomas T1 - Nanocellulose composites as smart devices with chassis, light-directed DNA Storage, engineered electronic properties, and chip integration JF - Frontiers in Bioengineering and Biotechnology N2 - The rapid development of green and sustainable materials opens up new possibilities in the field of applied research. Such materials include nanocellulose composites that can integrate many components into composites and provide a good chassis for smart devices. In our study, we evaluate four approaches for turning a nanocellulose composite into an information storage or processing device: 1) nanocellulose can be a suitable carrier material and protect information stored in DNA. 2) Nucleotide-processing enzymes (polymerase and exonuclease) can be controlled by light after fusing them with light-gating domains; nucleotide substrate specificity can be changed by mutation or pH change (read-in and read-out of the information). 3) Semiconductors and electronic capabilities can be achieved: we show that nanocellulose is rendered electronic by iodine treatment replacing silicon including microstructures. Nanocellulose semiconductor properties are measured, and the resulting potential including single-electron transistors (SET) and their properties are modeled. Electric current can also be transported by DNA through G-quadruplex DNA molecules; these as well as classical silicon semiconductors can easily be integrated into the nanocellulose composite. 4) To elaborate upon miniaturization and integration for a smart nanocellulose chip device, we demonstrate pH-sensitive dyes in nanocellulose, nanopore creation, and kinase micropatterning on bacterial membranes as well as digital PCR micro-wells. Future application potential includes nano-3D printing and fast molecular processors (e.g., SETs) integrated with DNA storage and conventional electronics. This would also lead to environment-friendly nanocellulose chips for information processing as well as smart nanocellulose composites for biomedical applications and nano-factories. KW - nanocellulose KW - DNA storage KW - light-gated proteins KW - single-electron transistors KW - protein chip Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-283033 SN - 2296-4185 VL - 10 ER - TY - JOUR A1 - Krenzer, Adrian A1 - Makowski, Kevin A1 - Hekalo, Amar A1 - Fitting, Daniel A1 - Troya, Joel A1 - Zoller, Wolfram G. A1 - Hann, Alexander A1 - Puppe, Frank T1 - Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists JF - BioMedical Engineering OnLine N2 - Background Machine learning, especially deep learning, is becoming more and more relevant in research and development in the medical domain. For all the supervised deep learning applications, data is the most critical factor in securing successful implementation and sustaining the progress of the machine learning model. Especially gastroenterological data, which often involves endoscopic videos, are cumbersome to annotate. Domain experts are needed to interpret and annotate the videos. To support those domain experts, we generated a framework. With this framework, instead of annotating every frame in the video sequence, experts are just performing key annotations at the beginning and the end of sequences with pathologies, e.g., visible polyps. Subsequently, non-expert annotators supported by machine learning add the missing annotations for the frames in-between. Methods In our framework, an expert reviews the video and annotates a few video frames to verify the object’s annotations for the non-expert. In a second step, a non-expert has visual confirmation of the given object and can annotate all following and preceding frames with AI assistance. After the expert has finished, relevant frames will be selected and passed on to an AI model. This information allows the AI model to detect and mark the desired object on all following and preceding frames with an annotation. Therefore, the non-expert can adjust and modify the AI predictions and export the results, which can then be used to train the AI model. Results Using this framework, we were able to reduce workload of domain experts on average by a factor of 20 on our data. This is primarily due to the structure of the framework, which is designed to minimize the workload of the domain expert. Pairing this framework with a state-of-the-art semi-automated AI model enhances the annotation speed further. Through a prospective study with 10 participants, we show that semi-automated annotation using our tool doubles the annotation speed of non-expert annotators compared to a well-known state-of-the-art annotation tool. Conclusion In summary, we introduce a framework for fast expert annotation for gastroenterologists, which reduces the workload of the domain expert considerably while maintaining a very high annotation quality. The framework incorporates a semi-automated annotation system utilizing trained object detection models. The software and framework are open-source. KW - object detection KW - machine learning KW - deep learning KW - annotation KW - endoscopy KW - gastroenterology KW - automation Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-300231 VL - 21 IS - 1 ER - TY - JOUR A1 - Kaltdorf, Kristin Verena A1 - Schulze, Katja A1 - Helmprobst, Frederik A1 - Kollmannsberger, Philip A1 - Dandekar, Thomas A1 - Stigloher, Christian T1 - Fiji macro 3D ART VeSElecT: 3D automated reconstruction tool for vesicle structures of electron tomograms JF - PLoS Computational Biology N2 - Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial. KW - Biology KW - Vesicles KW - Caenorhabditis elegans KW - Zebrafish KW - Septins KW - Synaptic vesicles KW - Neuromuscular junctions KW - Computer software KW - Synapses Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-172112 VL - 13 IS - 1 ER -