751 research outputs found
Robust and Flexible Persistent Scatterer Interferometry for Long-Term and Large-Scale Displacement Monitoring
Die Persistent Scatterer Interferometrie (PSI) ist eine Methode zur Ăberwachung von Verschiebungen der ErdoberflĂ€che aus dem Weltraum. Sie basiert auf der Identifizierung und Analyse von stabilen Punktstreuern (sog. Persistent Scatterer, PS) durch die Anwendung von AnsĂ€tzen der Zeitreihenanalyse auf Stapel von SAR-Interferogrammen. PS Punkte dominieren die RĂŒckstreuung der Auflösungszellen, in denen sie sich befinden, und werden durch geringfĂŒgige Dekorrelation charakterisiert. Verschiebungen solcher PS Punkte können mit einer potenziellen Submillimetergenauigkeit ĂŒberwacht werden, wenn Störquellen effektiv minimiert werden.
Im Laufe der Zeit hat sich die PSI in bestimmten Anwendungen zu einer operationellen Technologie entwickelt. Es gibt jedoch immer noch herausfordernde Anwendungen fĂŒr die Methode. Physische VerĂ€nderungen der LandoberflĂ€che und Ănderungen in der Aufnahmegeometrie können dazu fĂŒhren, dass PS Punkte im Laufe der Zeit erscheinen oder verschwinden. Die Anzahl der kontinuierlich kohĂ€renten PS Punkte nimmt mit zunehmender LĂ€nge der Zeitreihen ab, wĂ€hrend die Anzahl der TPS Punkte zunimmt, die nur wĂ€hrend eines oder mehrerer getrennter Segmente der analysierten Zeitreihe kohĂ€rent sind. Daher ist es wĂŒnschenswert, die Analyse solcher TPS Punkte in die PSI zu integrieren, um ein flexibles PSI-System zu entwickeln, das in der Lage ist mit dynamischen VerĂ€nderungen der LandoberflĂ€che umzugehen und somit ein kontinuierliches Verschiebungsmonitoring ermöglicht. Eine weitere Herausforderung der PSI besteht darin, groĂflĂ€chiges Monitoring in Regionen mit komplexen atmosphĂ€rischen Bedingungen durchzufĂŒhren. Letztere fĂŒhren zu hoher Unsicherheit in den Verschiebungszeitreihen bei groĂen AbstĂ€nden zur rĂ€umlichen Referenz.
Diese Arbeit befasst sich mit Modifikationen und Erweiterungen, die auf der Grund lage eines bestehenden PSI-Algorithmus realisiert wurden, um einen robusten und flexiblen PSI-Ansatz zu entwickeln, der mit den oben genannten Herausforderungen umgehen kann. Als erster Hauptbeitrag wird eine Methode prĂ€sentiert, die TPS Punkte vollstĂ€ndig in die PSI integriert. In Evaluierungsstudien mit echten SAR Daten wird gezeigt, dass die Integration von TPS Punkten tatsĂ€chlich die BewĂ€ltigung dynamischer VerĂ€nderungen der LandoberflĂ€che ermöglicht und mit zunehmender ZeitreihenlĂ€nge zunehmende Relevanz fĂŒr PSI-basierte Beobachtungsnetzwerke hat. Der zweite Hauptbeitrag ist die Vorstellung einer Methode zur kovarianzbasierten Referenzintegration in groĂflĂ€chige PSI-Anwendungen zur SchĂ€tzung von rĂ€umlich korreliertem Rauschen. Die Methode basiert auf der Abtastung des Rauschens an Referenzpixeln mit bekannten Verschiebungszeitreihen und anschlieĂender Interpolation auf die restlichen PS Pixel unter BerĂŒcksichtigung der rĂ€umlichen Statistik des Rauschens. Es wird in einer Simulationsstudie sowie einer Studie mit realen Daten gezeigt, dass die Methode ĂŒberlegene Leistung im Vergleich zu alternativen Methoden zur Reduktion von rĂ€umlich korreliertem Rauschen in Interferogrammen mittels Referenzintegration zeigt.
Die entwickelte PSI-Methode wird schlieĂlich zur Untersuchung von Landsenkung im Vietnamesischen Teil des Mekong Deltas eingesetzt, das seit einigen Jahrzehnten von Landsenkung und verschiedenen anderen Umweltproblemen betroffen ist. Die geschĂ€tzten Landsenkungsraten zeigen eine hohe VariabilitĂ€t auf kurzen sowie groĂen rĂ€umlichen Skalen. Die höchsten Senkungsraten von bis zu 6 cm pro Jahr treten hauptsĂ€chlich in stĂ€dtischen Gebieten auf. Es kann gezeigt werden, dass der gröĂte Teil der Landsenkung ihren Ursprung im oberflĂ€chennahen Untergrund hat. Die prĂ€sentierte Methode zur Reduzierung von rĂ€umlich korreliertem Rauschen verbessert die Ergebnisse signifikant, wenn eine angemessene rĂ€umliche Verteilung von Referenzgebieten verfĂŒgbar ist. In diesem Fall wird das Rauschen effektiv reduziert und unabhĂ€ngige Ergebnisse von zwei Interferogrammstapeln, die aus unterschiedlichen Orbits aufgenommen wurden, zeigen groĂe Ăbereinstimmung. Die Integration von TPS Punkten fĂŒhrt fĂŒr die analysierte Zeitreihe von sechs Jahren zu einer deutlich gröĂeren Anzahl an identifizierten TPS als PS Punkten im gesamten Untersuchungsgebiet und verbessert damit das Beobachtungsnetzwerk erheblich. Ein spezieller Anwendungsfall der TPS Integration wird vorgestellt, der auf der Clusterung von TPS Punkten basiert, die innerhalb der analysierten Zeitreihe erschienen, um neue Konstruktionen systematisch zu identifizieren und ihre anfĂ€ngliche Bewegungszeitreihen zu analysieren
Proceedings of SIRM 2023 - The 15th European Conference on Rotordynamics
It was our great honor and pleasure to host the SIRM Conference after 2003 and 2011 for the third time in Darmstadt. Rotordynamics covers a huge variety of different applications and challenges which are all in the scope of this conference. The conference was opened with a keynote lecture given by Rainer Nordmann, one of the three founders of SIRM âSchwingungen in rotierenden Maschinenâ. In total 53 papers passed our strict review process and were presented. This impressively shows that rotordynamics is relevant as ever. These contributions cover a very wide spectrum of session topics: fluid bearings and seals; air foil bearings; magnetic bearings; rotor blade interaction; rotor fluid interactions; unbalance and balancing; vibrations in turbomachines; vibration control; instability; electrical machines; monitoring, identification and diagnosis; advanced numerical tools and nonlinearities as well as general rotordynamics. The international character of the conference has been significantly enhanced by the Scientific Board since the 14th SIRM resulting on one hand in an expanded Scientific Committee which meanwhile consists of 31 members from 13 different European countries and on the other hand in the new name âEuropean Conference on Rotordynamicsâ. This new international profile has also been
emphasized by participants of the 15th SIRM coming from 17 different countries out of three continents. We experienced a vital discussion and dialogue between industry and academia at the conference where roughly one third of the papers were presented by industry and two thirds by academia being an excellent basis to follow a bidirectional transfer what we call xchange at Technical University of Darmstadt. At this point we also want to give our special thanks to the eleven industry sponsors for their great support of the conference. On behalf of the Darmstadt Local Committee I welcome you to read the papers of the 15th SIRM giving you further insight into the topics and presentations
Comprehensive screening of persistent organic pollutants in industrial wastewater using GC and LC cyclic ion mobility-high resolution mass spectrometry
Industrial chemicals play an important role in all facets of modern society; from flame retardants in electronics and furniture to non-stick coatings in cookware and food packaging. However, despite their extensive applications and many desired benefits, chemicals are sometimes released during their lifecycle resulting in deleterious ecological and human health effects. Industrial wastewater effluents are rich in chemical pollutants, both known and unknown as well as legacy and emerging. In this study, a combination of screening strategies was used to analyze industrial wastewater samples from over 10 sectors in Ontario for halogenated persistent organic pollutants (POPs). Samples were characterized with both gas chromatographic and liquid chromatographic cyclic ion mobility mass spectrometry (GC/LC-cIM-MS) methods.
A novel non-target screening (NTS) technique utilizing GC-cIM-MS, capable of isolating unknown per- and polyfluoroalkyl substances (PFAS) and other halogenated compounds based on the ratio of their mass and collision cross section (CCS) values, was recently developed in our group. When the combined dataset from GC-cIM-MS analysis of the wastewater samples was subjected to this novel filtering strategy, 344 potentially brominated, chlorinated or fluorinated chemical species were identified from the ~27,000 initially present. Following the application of a previously developed script tool (R code) and manual investigation, 44% of these ions were confirmed to be halogenated. Five compounds belonging to frequently detected classes were identified by suspect screening (e.g., polybrominated diphenyl ethers; PBDEs, polychlorinated biphenyls; PCBs, organophosphate flame retardants; OPFRs and perfluorosulfonamides; PFSMs).
Confirmed suspects represented a mere 14% of the halogenated ions (9% intensity) indicating that 86-91% of the halogenated content is truly âunknownâ. A more in-depth look at these unknown ions revealed 19 suspected PFAS including 2 classes that were detected in the environment for the first time. Targeted analyses showed that legacy pollutants such as PBDEs, PCBs, polychlorinated naphthalenes (PCNs) and organochlorine pesticides (OCPs) were either not detected or present at low levels.
For characterization via LC-cIM-MS, wastewater samples were extracted using a tandem solid phase extraction (SPE) technique with weak anion exchange (WAX) and weak cation exchange (WCX) cartridges. LC-cIM-MS experiments revealed the presence of ~50,000 chemical species across all samples and filtering based on CCS and m/z yielded 937 likely brominated, chlorinated or fluorinated compounds. Further data reduction and mass defect analysis led to the discovery of roughly 300 potential PFAS by NTS. Only half of them were matched to a suspect screening database implying that the chemical identities of several PFAS in the Ontario environment are unknown. Multiply charged ions formed during electrospray ionization were found to be non-problematic when filtering data using CCS and m/z. As such, this novel way of data prioritization is a promising approach for PFAS discovery in complex samples when analyzed by LC-ESI-IM-MS. GC-APCI-IM-MS was also found to be a complementary technique for PFAS discovery since comparable numbers were identified using the same workflow
Synthetic Aperture Radar (SAR) Meets Deep Learning
This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports
Impact of highly active immunotherapy on acute and chronic neuroinflammation in aggressive multiple sclerosis
Background: Despite the use of new high efficacy therapies, complete disease remission is elusive in most people with multiple sclerosis (MS). This is particularly relevant for patients affected by aggressive MS, who deal with frequent relapses and accelerated accrual of irreversible disability. No evidence-based criteria exist to guide the choice on the best treatment approach in these patients. It is therefore urgent to collect data on available therapies for aggressive MS, analyzing their onset of action, the intensity of their immunosuppressive effects and their long-term clinical outcomes. Given that chronic, smoldering inflammation behind an intact blood-brain barrier has been identified as one of the most important drivers of disability progression, it is of fundamental importance to evaluate the impact of therapies on compartmentalized chronic neuroinflammation. This is particularly true for newer treatments, including hematopoietic stem cell transplantation (AHSCT), which is currently under investigation as a treatment strategy for aggressive MS.
Aims: Against this background, the overarching aims of this thesis project were to:
1) Assess the clinical and MRI outcomes of patients with aggressive MS treated with different highly
active immunotherapies
2) Investigate the impact of different highly active immunotherapies on chronic inflammation
For the first aim of this project, we performed three different separate studies evaluating the impact of (i) AHSCT, (ii) alemtuzumab and (iii) ocrelizumab on clinical and MRI outcomes in patients presenting an aggressive form of MS. For the second aim, we performed a longitudinal prospective quantitative MRI study evaluating the impact of AHSCT and other highly active therapies on acute and chronic inflammation assessed with quantitative susceptibility mapping (QSM) in aggressive MS patients. Then, aiming at comprehensively detect the smoldering inflammatory component in MS lesions, we performed a combined quantitative MRI study investigating the relationship between axonal integrity, myelin content and iron deposition in the entire spectrum of MS lesions.
Results: First, we showed that AHSCT prevented disability progression and inflammatory disease activity in most patients affected by relapsing-remitting MS and that these effects last for more than a decade. We also demonstrated that AHSCT significantly reduced the risk of relapses and MRI activity, allowing complete disease remission in a higher proportion of patients compared with alemtuzumab. Similar results were observed in patients treated with ocrelizumab, although we observed some evidence of persistent MRI activity in the first year of treatment.
We showed that chronic smoldering inflammation, detected by QSM as paramagnetic rim lesions, is frequent in aggressive MS, being detectable in 80% of patients. Our preliminary results show that chronic active, paramagnetic rim lesions tend to persist over time, despite the use of highly active immunosuppression, including AHSCT. However, we found that some lesions exhibit changes in the intensity and the distribution of QSM signal over time, which could be related, at least in part, to highly active CNS penetrant drugs treatment used in these patients.
Lastly, with a multimodal MRI approach we distinguished different types of MS lesions (hypo-isointense, homogeneous hyperintense, inhomogeneous hyperintense and paramagnetic rim), which were characterized by increasing degrees of axonal and myelin disruption.
Discussion: Aggressive MS is characterized by a great amount of acute and chronic neuroinflammation, which can be detected and monitored in vivo by quantitative MRI. Among high efficacy immunotherapies, AHSCT has the potential to control neuroinflammation allowing long-lasting disease remission
A grammar of Ulwa (Papua New Guinea)
Synopsis:
This book is a grammatical description of Ulwa, a Papuan language spoken by about 600 people living in four villages in the East Sepik Province of Papua New Guinea. Ulwa belongs to the Keram language family. This grammatical description is based on a corpus of recorded texts and elicited sentences that were collected during a total of about twelve months of research carried out between 2015 and 2018. The book aims to detail as many aspects of Ulwa grammar as possible, including matters of phonology, morphology, and syntax. It also contains a lexicon with over 1,400 entries and three fully glossed and translated texts. The book was written with a typologically oriented audience in mind, and should be of interest to Papuan specialists as well as to general linguists. It may be useful to those working on the history or classification of Papuan languages as well as those conducting typological research on any number of grammatical features
Single-cell analysis of cell competition using quantitative microscopy and machine learning
Cell competition is a widely conserved, fundamental biological quality control mechanism. The cell competition assay of MDCK wild-type versus mutant MDCK Scribble-knockdown (ScribKD) relies on a mechanical mechanism of competition, which posits that the emergence of compressing stresses within the tissue at high confluency drive the competitive outcome. According to this mechanism, proliferating wild-type cells out-compete mutant ScribKD cells, resulting in their apoptosis and apical extrusion. Previous studies show that there is an increased division rate of wild-type cells in neighbourhoods with high numbers of ScribKD cells, but what still remains a mystery is whether this is a cause or consequence of
increased apoptosis in the âloserâ cell population. This project also interrogated the competitive assay of wild-type versus RasV12 , which is hypothesized to operate on a biochemical mechanism and results in the apical extrusion (but not apoptosis) of the loser RasV12 population. For both these mechanisms of competition it is still unknown which population of cells are driving the winner/loser outcome. Is the winner cell proliferation prompting the loser cell demise? Or is an autonomous loser elimination prompting a subsequent winner cell proliferation?
In my research, I have employed multi-modal, time-lapse microscopy to image competition assays continuously for several days. These data were then segmented into wild-type or mutant instances using a Convolutional Neural Network (CNN) that can differentiate between the cell types, after which they were tracked across cellular generations using a Bayesian multi-object tracker. A conjugate analysis of fluorescent cell-cycle indicator probes was then utilised to automatically identify key time points of cellular fate commitment using deep-learning image classification. A spatio-temporal analysis was then conducted in order to quantify any correlation between wild-type proliferation and mutant cell demise. For the case of wild-type versus ScribKD , there was no clear evidence for the wild-type cells mitoses directly impacting upon the ScribKD cell apoptotic elimination. Instead, a subsequent analysis found that a more subtle mechanism of pre-emptive, local density increases around the apoptosis site appeared to be determining the eventual ScribKD fate. On the other hand, there was clear evidence of a direct impact of wild-type mitoses on the subsequent apical extrusion and competitive elimination of RasV12 cells. Both of these conclusions agree with the prevailing classification of cell competition types: mechanical interactions are more diffuse and occur over a larger spatio-temporal domain, whereas biochemical interactions are constrained to nearest neighbour cells. The hypothesized density-dependency of ScribKD elimination was further quantified on a single-cell scale by these analyses, as well as a potential new understanding of RasV12 extrusion. Most interestingly, it appears that there is a clear biophysical mechanism to the elimination in the biochemical RasV12 cell competition. This suggests that perhaps a new semantic approach is needed in the field of cell competition in order to accurately classify different mechanisms of elimination
Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling
In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects
Measuring blood flow and pulsatility with MRI: optimisation, validation and application in cerebral small vessel disease
Cerebral small vessel disease (SVD) is the breakdown of the small blood vessels of the brain, leading to many cases of stroke and dementia. The pathophysiology of SVD is largely unknown, although several mechanisms have been suggested. One such mechanism is the role of increased blood flow pulsatility into the brain, caused by vessel stiffening, leading to damage of the microvasculature.
Magnetic resonance imaging (MRI) allows us to non-invasively measure blood flow and velocity using a technique called phase contrast-MRI â traditionally used with 2D slices across the vessel(s) of interest. An advanced form of phase-contrast MRI, known as 4D flow, has emerged in recent years that allows for a volume of data to be acquired, containing velocity information in all directions. However, to keep scan times practical when collecting this amount of data, spatiotemporal resolution has to be sacrificed.
The main aim of this thesis was to assess 4D flowâs capabilities, including comparing it to the more well-established 2D method in healthy volunteers, patients, and phantom experiments, so as to better understand its role in investigating SVD. Another aim was to learn more about the role of flow and pulsatility in SVD development in patients using data acquired in the longitudinal Mild Stroke Study 3 (MSS3).
Firstly, I systematically reviewed studies that have assessed the human brain using 4D flow. Across 61 relevant studies, I found a general consensus for the current use of the technique in this context. I then optimised the Siemens prototype 4D flow sequence (N = 11 healthy volunteers), testing different parameters to find the combination that best balanced scan quality and duration. I then assessed the test-retest repeatability and intra-rater reliability of both 2D and 4D methods (N = 11 healthy volunteers), as well as differences between them. Following this, I performed the same 4D-2D comparison on SVD patients (N = 10). Absolute flow measurements using 4D flow were shown to have moderate repeatability and reliability, while flow pulsatility measurements showed acceptable repeatability and reliability. Furthermore, 2D arterial pulsatility was measured higher than with 4D, while 4D often measured higher flow rates than 2D. 4D flow was shown to be feasible when used on SVD patients, with no noticeable issues caused by potential patient movement.
Flow data analysis from the longitudinal SVD study MSS3 showed that intracranial pulsatility is associated with cross-sectional SVD lesion volume but not longitudinal lesion growth, with stronger associations seen in the arteries of the neck compared to the venous sinuses
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