Leibniz University Hannover
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Entwicklung eines neuartigen Sensors für Bioprozesse mit Mikroalgen
No full textMicroalgae are well-known photosynthetic microorganisms used as cell factories for the production of relevant biotechnological compounds. Despite the interesting characteristics attributed to microalgae, their industrial-scale production still struggles with scale-up problems and economic feasibility. One important bottleneck is the lack of suitable online sensors for the reliable monitoring of biological parameters in microalgae bioprocesses. Software sensors provide an approach to improving the monitoring of those process parameters that are difficult to quantify directly and are therefore only indirectly accessible. Their use aims to improve the productivity of microalgal bioprocesses through better monitoring, control and automation, according to the current demands of industrial digitalization. The present research describes the development of a non-invasive online multispectral UV–Vis sensor integrating transmission, sidescatter, and backscatter measurement modes, its evaluation in the performance of biomass and pigment estimation, and the development of different software sensors based on machine learning techniques able to predict microalgae biomass. Biomass estimation using C. vulgaris, showed that online sidescatter and opacity measurements at 780 nm described positive correlations (r > 0,98) and R2 > 0,98 against offline spectrophotometer measurements. N. oculata biomass estimation also showed excellent performance for online sidescatter, opacity, and absorbance measurements against the reference method. However, the chlorophyll and carotenoid estimations could presumably only be measured in C. vulgaris and not in N. oculata under the conditions studied. Ridge regression (RR), support vector regression (SVR), and feedforward neural network (FNN) were used to develop several software sensors. Two individual software sensors based on FNN predicted biomass growth (g/L) of C. vulgaris and Nannochloropsis sp. with validation values of MAE = 0,0463, MSE = 0,0031, R2 = 0,99 and MAE = 0,0062, MSE = 0,0092, R2 = 0,98, respectively. In addition, a software sensor using FNN called “union model” was developed to accurately predict and monitor microalgae biomass growth for both species, either individually or together. This provides the potential to monitor the biomass growth of C. vulgaris and/or Nannochloropsis sp. in a laboratory or production facility in real time. This research demonstrates the feasibility of developing smart technologies to improve the monitoring and digitalization of microalgae bioprocesses
Assessing sit-to-stand motion execution using 6D IMUs only - A proof of concept
No full textIn diesem Artikel schlagen wir einen Proof of Concept für die Verwendung von 6D-IMUs zur Bewertung der Korrektheit der Sit-to-Stand-Bewegung (STS) vor, einer kritischen Aufgabe in der Rehabilitation nach einem Schlaganfall. Dazu wurden gesunde Personen angewiesen, Bewegungsmuster nach einem Schlaganfall nachzuahmen, um ein relevantes Modell für das Verhalten nach einem Schlaganfall zu erhalten. Wir zeigen, dass die Verwendung einfacher kinematischer Modelle für alle Gelenke ein praktikabler Ansatz zur Berechnung von Gelenkwinkeln und zur Extraktion relevanter Merkmale ist. Mit regelbasierten und lernbasierten Klassifizierungsmodellen sind wir in der Lage, zwischen mehreren Fehlertypen in der STS-Bewegung zu unterscheiden, mit einer durchschnittlichen Klassifizierungsgenauigkeit von 89,78 % bzw. 94,03 %. Im Gegensatz zu vielen modernsten Methoden, die nur eine binäre Klassifizierung von korrekter und fehlerhafter Ausführung bieten, ermöglicht unser Ansatz die Unterscheidung zwischen verschiedenen Fehlertypen. Darüber hinaus überwindet er die Einschränkungen komplexer, ortsabhängiger Kamerasysteme und die Anfälligkeit für magnetische Störungen. Dies unterstreicht die Machbarkeit dieses Ansatzes für die Bewertung der STS-Bewegung mit potenziellen Anwendungen für die Bereitstellung automatisierter Rückmeldungen für die Rehabilitation nach einem Schlaganfall und die Unterstützung der Wiederherstellung von Aktivitäten des täglichen Lebens
Structure and function of the geldanamycin amide synthase from Streptomyces hygroscopicus
Full text linkAmide synthases catalyze the formation of macrolactam rings from aniline-containing polyketide-derived seco-acids as found in the important class of ansamycin antibiotics. One of these amide synthases is the geldanamycin amide synthase GdmF, which we recombinantly expressed, purified and studied in detail both functionally as well as structurally. Here we show that purified GdmF catalyzes the amide formation using synthetically derived substrates. The atomic structures of the ligand-free enzyme and in complex with simplified substrates reveal distinct structural features of the substrate binding site and a putative role of the flexible interdomain region for the catalysis reaction
Probing RNA-protein complex dynamics and structure by solid-state NMR and DNP spectroscopy
Full text linkRNA plays a crucial role in various biological processes, including catalysis, protein synthesis and gene regulation. Very often, RNA acts not alone but in complex with proteins (ribonucleoprotein, RNP). Unlike static representations often seen in biological illustrations, RNA is highly dynamic, undergoing a wide range of molecular motions. Understanding RNA structure and dynamics within RNPs is critical for elucidating their cellular function. Several structural biology techniques, including X-ray crystallography, solution-state NMR, and cryo-EM, have been used to study RNPs. However, these methods often face challenges due to RNA’s dynamics (for X-ray and cryo-EM) or its large molecular weight (for solution-state NMR).
Solid-state NMR (ssNMR) is a powerful tool for probing biomolecular structure and dynamics at the atomic level, with Dynamic Nuclear Polarization (DNP) further boosting sensitivity. While widely used for membrane proteins and amyloids, its application to RNA has been limited until recent advancements. While studies by the Drobny and Görlach groups have highlighted ssNMR’s potential for characterizing RNA structure and dynamics, our group recently solved the first-ever structure of an RNA and protein-RNA complex using ssNMR, opening the door to broader applications and advanced techniques.
In my thesis I have developed advanced ssNMR methods that allowed to characterize dynamics of RNA in protein-RNA complex and gain insight into protein-RNA interaction interface by application of sensitivity-boosting DNP technique.
In first part of my thesis, I have measured 15N longitudinal relaxation time constants (T1) of 26mer box C/D RNA to assess sequence-specific RNA motions at various MAS (Magic Angle Spinning) rates. This data provided crucial information about site-specific structural flexibility of RNA. Briefly, non-base-paired regions (loops and bulges), exhibited faster T1 relaxation rates, indicative of increased flexibility. Conversely, base-paired regions showed slower relaxation rates, reflecting more rigid and stable nucleotides. Furthermore, I have comprehensively characterized impact of the spin diffusion on T1 relaxation data, provided a framework for future dynamics studies of RNA by ssNMR.
In second part of my thesis, I have applied DNP spectroscopy and Specific Cross-Relaxation Enhancement by Active Motions under DNP (SCREAM-DNP) to selectively zoom-in on protein-RNA interaction interface and rapidly identify crucial interacting residues. I have identified strong interaction between the I93δ methyl group of the L7Ae protein and adenosine A19 of the 26mer RNA, with weaker interactions between other methyl groups (such as V95) and RNA nucleotides. This highlights the importance of the I93δ methyl group in the structural interaction between L7Ae and box C/D RNA.
In summary, in my thesis I have combined ssNMR and SCREAM-DNP to capture the sequence-specific dynamics of box C/D RNA and explore the key interactions between RNA and protein methyl groups. These findings provide a deeper understanding of the structural flexibility and arrangements within the L7Ae-box C/D RNA complex. Furthermore, this work emphasizes the utility of DNP and ssNMR as powerful tools for studying complex biomolecular systems. It advances our understanding of RNA dynamics and interactions in biological contexts, with significant implications for the future of RNA-based therapeutic development
Functional analysis of LCP-LytR_C-domain proteins in c-di-AMP signalling and cell differentiation in Streptomyces
Full text linkThe cell envelope of gram-positive bacteria comprises of peptidoglycan covalently attached to glycopolymers, and is critical for cellular integrity, shape and vitality. The soil-dwelling Streptomyces represents an important paradigm in biotechnology and pharmaceutical due to their ability to produce an array of secondary metabolites and displays a complex life-cycle transitioning from multicellular filamentous vegetative mycelia to unicellular spores. For growth, Streptomyces elongate via apical tip extension and hyphal branching, that requires localization and assembly of cell wall machinery at the growing tips, we have limited knowledge about their cell wall biogenesis, composition and functions.
In their natural environment, Streptomyces often encounter osmotic stress caused by rainfall or drought. To endure such challenges, they employ the nucleotide second messenger c-di-AMP, which is a well-established regulator of ion and osmolyte homeostasis in bacteria and is produced by the diadenylate cyclase DisA in Streptomyces. An elevation in c-di-AMP upon inactivation of the phosphodiesterase ataC interferes with the growth and differentiation of the bacteria. The molecular mechanisms behind these physiological effects are not understood. Hence, the aims of this study were to identify the genetic pathways directly or indirectly regulated by c-di-AMP in Streptomyces.
In this study, I identified and characterized the LCP-LytR_C domain protein CglA (Vnz_13690) as a key cell wall glycopolymer ligase in S. venezuelae. Out of four LCP-LytR_C domain encoding proteins, only deletion of cglA leads to development and sporulation defects. CglA specifically localizes in cell wall biosynthesis zones, and its mutation leads to a significant decrease of glycopolymers, enlarged vegetative hyphae with defective FtsZ-ring positioning and formation. This results in the formation of mispositioned division septum, abnormal cell compartments and spores with reduced vitality. Furthermore, this study revealed a unique physiological link between c-di-AMP signalling and cell wall glycopolymer deposition, as inactivation of cglA restores growth of the S. venezuelae disA mutant at high salinity. Besides, global RNA-seq analyses of the c-di-AMP metabolizing mutants, presented some potential elements that might be involved in the developmental defect of the ataC mutant.
In summary, this study revealed CglA as a novel component of cell wall biogenesis in Streptomyces, essential for cell shape maintenance and cellular vitality in filamentous, multicellular bacteria.Die Zellhülle Gram-positiver Bakterien besteht aus Peptidoglykan, das kovalent an Glykopolymere gebunden ist, und ist entscheidend für die Integrität, Form und Vitalität der Zelle. Das im Boden lebende Bakterium Streptomyces stellt ein wichtiges Paradigma in der Biotechnologie und Pharmazie dar, da es in der Lage ist, eine Reihe von Sekundärmetaboliten zu produzieren, und einen komplexen Lebenszyklus aufweist, der von mehrzelligen, fadenförmigen, vegetativen Myzelien zu einzelligen Sporen übergeht. Für ihr Wachstum strecken sich Streptomyces durch apikale Spitzenverlängerung und hyphale Verzweigung, was die Lokalisierung und den Aufbau von Zellwandmaschinen an den wachsenden Spitzen erfordert. Wir haben nur begrenzte Kenntnisse über ihre Zellwandbiogenese, Zusammensetzung und Funktionen. In ihrer natürlichen Umgebung sind Streptomyceten häufig osmotischem Stress ausgesetzt, der durch Regenfälle oder Trockenheit verursacht wird. Um solchen Herausforderungen standzuhalten, nutzen sie den Nukleotid-Sekundär-Botenstoff c-di-AMP, der ein bekannter Regulator der Ionen- und Osmolyt-Homöostase in Bakterien ist und von der Diadenylatcyclase DisA in Streptomyces produziert wird. Ein Anstieg von c-di-AMP bei Inaktivierung der Phosphodiesterase ataC beeinträchtigt das Wachstum und die Differenzierung der Bakterien. Die molekularen Mechanismen hinter diesen physiologischen Effekten sind nicht bekannt. Ziel dieser Studie war es daher, die genetischen Signalwege zu identifizieren, die direkt oder indirekt durch c-di-AMP in Streptomyces reguliert werden. In dieser Studie identifizierte und charakterisierte ich das LCP-LytR_C-Domänenprotein CglA (Vnz_13690) als eine wichtige Zellhülle Glykopolymerligase in S. venezuelae. Von den vier für die LCP-LytR_C-Domäne kodierenden Proteinen führt nur die Deletion von CglA zu Entwicklungs- und Sporulationsdefekten. CglA ist spezifisch in den Biosynthesezonen der Zellwand lokalisiert, und seine Mutation führt zu einer erheblichen Verringerung der Glykopolymere, vergrößerten vegetativen Hyphen mit fehlerhafter Positionierung und Bildung von FtsZ-Ringen. Dies führt zur Bildung eines falsch positionierten Teilungsseptums, abnormalen Zellkompartimenten und Sporen mit verminderter Vitalität. Darüber hinaus zeigte diese Studie eine einzigartige physiologische Verbindung zwischen c-di-AMP-Signalen und der Ablagerung von Zellwandglykopolymeren, da die Inaktivierung von cglA das Wachstum der S. venezuelae disA-Mutante bei hohem Salzgehalt wiederherstellt. Außerdem ergaben globale RNA-Sequenz-Analysen der c-di-AMP-metabolisierenden Mutanten einige potenzielle Elemente, die an dem Entwicklungsdefekt der ataC-Mutante beteiligt sein könnten. Zusammenfassend lässt sich sagen, dass diese Studie CglA als neuartige Komponente der Zellwandbiogenese in Streptomyces enthüllt hat, die für die Aufrechterhaltung der Zellform und der zellulären Vitalität in fadenförmigen, mehrzelligen Bakterien wesentlich ist
Solutions of 3×3 Systems of Linear Equations Presented on a Golden Plate
Full text linkThis paper presents a direct solution method for 3×3 systems of linear equations. The derivation is based on a sketch of the Reverse-2X Method introduced in [LAM25], as well as the Reverse Gauss-Jordan Algorithm. Owing to the requirement of only a single mathematical operation to determine the third variable, the proposed solution outperforms all state-of-the-art methods, including the 4X Method described in [LAM25]
Identität und Sprachwelt von deutsch-spanischen Herkunftssprecher:innen : Eine empirische Untersuchung zu Identitätsaspekten und Sprachnutzung
Full text link[No abstract available
Novel adaptive time integration and consistent coupling of structural components in an aeroelastic simulation framework
Full text linkAeronautical structures play a pivotal role in the context of climate protection. While the expansion of wind energy is making an increasingly significant contribution to the transition towards renewable energy sources, aviation remains in the spotlight due to its substantial share in global greenhouse gas emissions. In order to enhance the efficiency of aeronautical systems, there is an increasing tendency to develop slender, thus highly flexible structures made from composite materials. However, this leads to increased susceptibility to vibrations and amplifies the complexity of fluid–structure interaction, thereby posing considerable challenges for the accurate prediction of the behaviour. The reliable design of such structures requires the use of novel computational methods capable of accurately capturing both geometric nonlinearities and the intrinsically nonlinear coupling between airflow and structural response. This gives rise to a fundamental trade-off: while high-fidelity numerical methods offer superior accuracy, their computational costs often render them impractical, particularly during the early stages of the design process. As a result, attention is increasingly directed towards mid-fidelity approaches, which seek to achieve a well-balanced compromise between modelling accuracy and computational expense.
This thesis aims to advance the development of an aeroelastic simulation environment that combines the Unsteady Vortex Lattice Method with geometrically exact beam theory, employing a strongly coupled interaction between aerodynamic and structural models. The central objective is to improve the trade-off between accuracy and efficiency through targeted methodological enhancements.
To this end, a consistent geometrically exact node-to-node coupling element is introduced, enabling the connection of structural components. Its formulation ensures objectivity and path independence, conserves mechanical invariants such as linear and angular momentum as well as total energy, and also permits the inclusion of mass distributions and damping effects. The performance of this coupling element is demonstrated through modal, static and dynamic analyses.
In order to reduce computational costs, a heuristic adaptive time-stepping approach is developed, based on the temporal evolution of physical system variables. This allows for the detection of near-quasi-steady-state conditions without additional computational costs, enabling an increase in time-step size and thus a reduction in total simulation time.
In addition, a second adaptive strategy is introduced to improve numerical robustness, based on local error estimation. This method employs Richardson's extrapolation along with a more accurate approximation of unsteady aerodynamic forces, allowing the time-step size to be dynamically adjusted according to the estimated local error. Numerical experiments demonstrate that this approach not only enhances robustness in the presence of instability or strong nonlinearities, but can also lead to reductions in computational costs.
A comparison of both adaptive time-stepping strategies confirms the intended development goals. The heuristic method, while requiring case-specific parameter tuning, is particularly well suited for accelerating large numbers of similar simulations. The error-based approach, in contrast, selects time steps more efficiently with respect to the deviation from a reference solution but entails higher computational demands. The comparison further shows that the developed coupling element can be effectively integrated with both time integration schemes.
In summary, the thesis demonstrates that the targeted enhancement of existing mid-fidelity approaches can improve the trade-off between modelling fidelity and computational efficiency. In doing so, it contributes to the less computational expensive and more robust development of future lightweight and flexible aeronautical structures
Geospatial representation learning: from road networks to trajectories
Full text linkIn today’s increasingly connected urban environments, effectively processing and analyzing spatio-temporal data has become crucial for intelligent transportation systems, urban planning, and location-based services. However, the complexity of gathered spatio-temporal data poses significant challenges, such as high dimensionality, noisy and irregular sampling, complex spatial-temporal dependencies, and heterogeneous data. Geospatial representation learning addresses these challenges by automatically learning low-dimensional vector representations that capture the essential characteristics and relationships within complex spatio-temporal data structures, enabling efficient processing and analysis.
This thesis advances geospatial representation learning through novel methodological contributions in two fundamental and interconnected domains: road network representation learning and trajectory representation learning. Road networks serve as the underlying infrastructure that defines and constrains mobility in urban environments, consisting of roads connected by intersections. Trajectories capture the movement patterns of vehicles and individuals traversing these networks over time, thus containing rich information about how road users interact with the road network, including traffic patterns, road preferences, and temporal dynamics. For road network representation learning, we propose TrajRNE, a novel approach that advances beyond static network topology by deeply incorporating trajectory information into the model architecture, enabling the capture of actual traffic flows, user preferences, and complex spatio-temporal dependencies between roads. Further, we employ road network representation techniques in a novel transfer learning framework, to predict traffic in urban regions without historical traffic data, leveraging knowledge transfer from data-rich cities. Thus, enabling traffic prediction in regions with no traffic sensors or where traffic data is inaccessible. For trajectory representation learning, we present TIGR, a novel framework that effectively integrates grid-based and road network-based modalities with spatio-temporal dynamics to capture more intricate and complementary aspects of the underlying trajectory. Moreover, we demonstrate the practical value of trajectory representations in data misuse scenarios to re-identify leaked and possibly modified trajectories. This capability addresses critical privacy concerns, as trajectory data contains sensitive personal information that requires protection from unauthorized distribution to ensure secure data sharing. These methodological advances in geospatial representation learning enable more effective analysis of urban mobility patterns while establishing crucial building blocks for geospatial foundation models capable of understanding and reasoning about urban environments at scale
Frequency metrology with optimal ramsey interferometry for optical atomic clocks
Full text linkDie Frequenzmetrologie bildet einen Grundstein moderner Präzisionsmessungen und optische Atomuhren gehören derzeit zu den genauesten Messinstrumente. Korrelierte Quantenzustände und Messstrategien versprechen eine weitere Steigerung der Stabilität, indem das Quantenprojektionsrauschen unter das Standard-Quanten-Limit unkorrelierter Atome gesenkt wird. Die Entwicklung robuster Strategien unter rea-listischen Bedingungen ist jedoch weiterhin eine zentrale Herausforderung. Diese Dissertation widmet sich dieser Fragestellung, indem der Kompromiss zwischen verschränkungsbasierter Sensitivitätssteigerung und Robustheit gegenüber Dekohärenz-prozessen und Rauschen untersucht wird. Dabei werden Uhren mit einzelnen Ensemblen betrachtet, bei denen die atomare Referenz in jedem Uhrenzyklus periodisch mittels identischer Ramsey-Protokolle abgefragt wird. In diesem Kontext stellt diese Arbeit einen theoretischen Ratgeber für die Entwicklung optischer Atomuhren der nächsten Generation dar. Aufbauend auf einer umfassenden theoretischen Beschreibung von Atomuhren werden optimale Ramsey-Strategien identifiziert, mit dem Fokus auf Regimen, die durch spontane Emission und Laserrauschen limitiert sind.
Im ersten Teil wird gezeigt, dass maximal verschränkte GHZ-ähnliche Zustände in Kombination mit korrelierten Messungen und nichtlinearen Schätzstrategien unter spontaner Emission einen Gewinn von bis zu 2.25 dB ermöglichen -- vergleichbar mit fundamentalen Schranken für Ensemble mit mehreren Dutzend Atomen. Dieses Ergebnis ist insbesondere bemerkenswert, da GHZ-Zustände unter Dephasierung infolge von weißem Frequenzrauschen keine Vorteile gegenüber dem Standard-Quanten-Limit bieten. Der beobachtete Gewinn beruht auf einem Veto-Signal, das Fehler durch spontane Emission erkennt und reduziert. Die Robustheit dieser GHZ-ähnlichen Protokolle wird durch umfassende Monte-Carlo-Simulationen demonstiert.
Der zweite Teil präsentiert einen Fortschrittsbericht zur Frequenzmetrologie in optischen Atomuhren, die primär durch Laserrauschen limitiert sind. Durch Konsolidierung und Erweiterung früherer Erkenntnisse zu laserrauschlimitierten Uhren und variationellen Abfrageprotkollen werden optimale Ramsey-Protokolle für eine Vielzahl realistischer Szenarien identifiziert -- darunter verschiedene experimentelle Plattformen, Ensemblegrößen, sowie unterschiedliche Abfragedauern und Totzeiten. Die optimalen Protokolle hängen stark von den experimentellen Bedingungen ab, da die Uhrenstabilität im Allgemeinen einen Kompromiss zwischen Quantenprojektions-rauschen, Kohärenzzeitlimit, Frequenzsprüngen und Totzeiteffekten darstellt. Aufgrund dieser experimentellen Einschränkungen bieten variationelle Abfrageprotokolle lediglich für Tweezer-Arrays mit mehreren Dutzend Atomen signifikante Vorteile, sofern Quantenprojektionsrauschen die dominante Limitierung darstellt. Während-dessen repräsentieren Standardprotokolle -- unter Verwendung kohärenter Zustände, gequetschter Zustände und GHZ Zustände -- in vielen Experimenten robuste Strategien und erreichen Stabilitäten nahe der fundamentalen Stabilitätsgrenzen.Frequency metrology represents a cornerstone of modern precision measurements and optical atomic clocks, in particular, have emerged as one of the most precise measurement devices. Correlated quantum states and measurements promise further improvements in the accuracy of frequency metrology and the stability of atomic clocks by reducing quantum projection noise below the standard quantum limit imposed by uncorrelated atoms. However, developing strategies robust under realistic conditions remains challenging. This thesis addresses this research question by investigating the trade-off between achieving entanglement-enhanced sensitivity and maintaining robustness against decoherence processes and noise sources. Specifically, we consider frequency metrology tailored to single-ensemble clocks, in which the atomic reference is periodically interrogated utilizing identical Ramsey protocols in each clock cycle. In this framework, this thesis aims to provide theoretical guidance for the development of next-generation optical atomic clocks. After establishing a comprehensive theoretical foundation for atomic clock operation, we identify optimal Ramsey interrogation schemes primarily focusing on regimes limited by spontaneous decay and laser noise.
In the first part, we show that maximally entangled GHZ-like states -- in conjunction with a correlated measurement and nonlinear estimation strategy -- achieve gains of up to 2.25 dB in the presence of spontaneous decay, comparable to fundamental bounds for up to several tens of atoms. This result is particularly surprising since GHZ states do not provide any enhancement under dephasing due to white frequency noise compared to the standard quantum limit. The gain arises from a veto signal, which allows for the detection and mitigation of errors caused by spontaneous decay events. We demonstrate the robustness of these GHZ-like protocol through comprehensive Monte-Carlo simulations of atomic clocks.
In the second part, we present progress on frequency metrology tailored to optical atomic clocks primarily limited by laser noise. By consolidating and extending previous findings on laser noise limited atomic clocks and variational quantum circuits, we identify optimal Ramsey interrogation schemes across a variety of scenarios, including different experimental platforms, ensemble sizes and a broad range of interrogation durations and dead times. The optimal Ramsey protocols strongly depend on the specific experimental parameters, as clock stability generally reflects a trade-off between quantum projection noise, the coherence time limit, fringe hops and dead time effects. Although variational quantum circuits with low complexity promise substantial enhancements in idealized settings, practical constraints in realistic scenarios limit these advantages. As a result, only tweezer arrays with several tens of atoms -- operating in the regime dominated by quantum projection noise -- benefit significantly from these protocols, while standard protocols -- utilizing coherent spin states, spin-squeezed states and GHZ states -- represent robust interrogation schemes in a variety of experimental setups, closely approaching the ultimate lower limit