arXiv subjects

Markus Scholz

Publications and source records attributed to Markus Scholz.

18 recordsLinked to original sources

arXiv2026

Femtosecond concerted rotation of molecules on a 2D material interface

Interfaces between molecules and 2D materials exhibit energy-driven functionalities, wherein charge transfer directs molecular motion. Unlike equilibrium systems, where molecular assemblies settle into static configurations, continuous energy input can drive transient, collective molecular rearrangements. Here, we reveal ultrafast spectroscopic fingerprints of a collective rotational response of molecules on a 2D material following photoexcitation. Our results suggest that photoinduced charge transfer reshapes the interfacial energy potential, giving rise to macroscopic, unidirectional molecular rotation and the formation of a homochiral molecular arrangement. Using a multiplexed ultrafast photoemission spectroscopy approach, we simultaneously track, electronic states, atomic positions, and orbital wavefunctions with femtosecond and sub-ångström resolution. Multimodal valence and core electron emission analysis disentangles the intertwined electronic-structural dynamics of the molecule and the 2D material, revealing the dynamic modulation of charge distribution and intermolecular forces that drive collective molecular motion. Our findings open a pathway for designing energy-driven molecular systems with tunable interfacial dynamics, with potential applications in chiral engineering and active matter systems.

cond-mat.mtrl-sci↗

arXiv2025

Developing hybrid mechanistic and data-driven personalized prediction models for platelet dynamics

Hematotoxicity, drug-induced damage to the blood-forming system, is a frequent side effect of cytotoxic chemotherapy and poses a significant challenge in clinical practice due to its high inter-patient variability and limited predictability. Current mechanistic models often struggle to accurately forecast outcomes for patients with irregular or atypical trajectories. In this study, we develop and compare hybrid mechanistic and data-driven approaches for individualized time series modeling of platelet counts during chemotherapy. We consider hybrid models that combine mechanistic models with neural networks, known as universal differential equations. As a purely data-driven alternative, we utilize a nonlinear autoregressive exogenous model using gated recurrent units as the underlying architecture. These models are evaluated across a range of real patient scenarios, varying in data availability and sparsity, to assess predictive performance. Our findings demonstrate that data-driven methods, when provided with sufficient data, significantly improve prediction accuracy, particularly for high-risk patients with irregular platelet dynamics. This highlights the potential of data-driven approaches in enhancing clinical decision-making. In contrast, hybrid and mechanistic models are superior in scenarios with limited or sparse data. The proposed modeling and comparison framework is generalizable and could be extended to predict other treatment-related toxicities, offering broad applicability in personalized medicine.

cs.LG↗

arXiv2024

Spin polarization of the two-dimensional electron gas at the EuO/SrTiO$_3$ interface

Spin-polarized two-dimensional electron gases (2DEGs) are of particular interest for functional oxide electronics applications. The redox-created 2DEG residing on the strontium titanate, SrTiO$_3$ (STO), side of a europium monoxide (EuO)/SrTiO$_3$ (001) interface is expected to be significantly spin-polarized due to the proximity to the strong ($7\,μ_B/f.u.$) Heisenberg ferromagnet EuO. We apply magnetic circular dichroism in the angular distribution (MCDAD) of photoemitted electrons to investigate whether and how the induced spin polarization of the 2DEG depends on the dimensionality of the overlaying EuO layer. The experimental data are complemented by density functional theory calculations with a Hubbard $U$ term (DFT+$U$). We show that the EuO/STO interfacial 2DEG is spin-polarized even for ultrathin EuO overlayers, starting at an EuO threshold thickness of only two monolayers. Additional EuO monolayers even increase the induced magnetic Ti moment and thus the spin polarization of the 2DEG. Our results and the potential to enhance the magnetic order of EuO by other proximity effects indicate that the EuO/STO (001) interface is an ideal template for creating (multi-)functional spin-polarized 2DEGs for application in oxide electronics.

cond-mat.mtrl-sci↗

arXiv2024

A compact approach to higher-resolution resonant inelastic X-ray scattering detection using photoelectrons

The detection of inelastically scattered soft X-rays with high energy resolution usually requires large grating spectrometers. Recently, photoelectron spectrometry for analysis of X-rays (PAX) has been rediscovered for modern spectroscopy experiments at synchrotron light sources. By converting scattered photons to electrons and using an electron energy analyser, the energy resolution for resonant inelastic X-ray scattering (RIXS) becomes decoupled from the X-ray spot size and instrument length. In this work, we develop PAX towards high energy resolution using a modern photoemission spectroscopy setup studying Ba2Cu3O4Cl2 at the Cu L3-edge. We measure a momentum transfer range of 24% of the first Brillouin zone simultaneously. Our results hint at the observation of a magnon excitation below 100 meV energy transfer and show intensity variations related to the dispersion of dd-excitations. With dedicated setups, PAX can become an alternative to the best and largest RIXS instruments, while at the same time opening new opportunities to acquire RIXS at a range of momentum transfers simultaneously and combine it with angle-resolved photoemission spectroscopy in a single instrument.

cond-mat.mtrl-sci↗

arXiv2023

Operationalizing Assurance Cases for Data Scientists: A Showcase of Concepts and Tooling in the Context of Test Data Quality for Machine Learning

Assurance Cases (ACs) are an established approach in safety engineering to argue quality claims in a structured way. In the context of quality assurance for Machine Learning (ML)-based software components, ACs are also being discussed and appear promising. Tools for operationalizing ACs do exist, yet mainly focus on supporting safety engineers on the system level. However, assuring the quality of an ML component within the system is commonly the responsibility of data scientists, who are usually less familiar with these tools. To address this gap, we propose a framework to support the operationalization of ACs for ML components based on technologies that data scientists use on a daily basis: Python and Jupyter Notebook. Our aim is to make the process of creating ML-related evidence in ACs more effective. Results from the application of the framework, documented through notebooks, can be integrated into existing AC tools. We illustrate the application of the framework on an example excerpt concerned with the quality of the test data.

cs.SE↗

arXiv2023

New insights into the laser-assisted photoelectric effect from solid-state surfaces

Photoemission from a solid surface provides a wealth of information about the electronic structure of the surface and its dynamic evolution. Ultrafast pump-probe experiments are particularly useful to study the dynamic interactions of photons with surfaces as well as the ensuing electron dynamics induced by these interactions. Time-resolved laser-assisted photoemission (tr-LAPE) from surfaces is a novel technique to gain deeper understanding of the fundamentals underlying the photoemission process. Here, we present the results of a femtosecond time-resolved soft X-ray photoelectron spectroscopy experiment on two different metal surfaces conducted at the X-ray Free-Electron Laser FLASH in Hamburg. We study photoemission from the W 4f and Pt 4f core levels using ultrashort soft X-ray pulses in combination with synchronized infrared (IR) laser pulses. When both pulses overlap in time and space, laser-assisted photoemission results in the formation of a series of sidebands that reflect the dynamics of the laser-surface interaction. We demonstrate a qualitatively new level of sideband generation up to the sixth order and a surprising material dependence of the number of sidebands that has so far not been predicted by theory. We provide a semi-quantitative explanation of this phenomenon based on the different dynamic dielectric responses of the two materials. Our results advance the understanding of the LAPE process and reveal new details of the IR field present in the surface region, which is determined by the dynamic interplay between the IR laser field and the dielectric response of the metal surfaces.

cond-mat.mtrl-sci↗

arXiv2023

Out-of-equilibrium charge redistribution in a copper-oxide based superconductor by time-resolved X-ray photoelectron spectroscopy

Charge-transfer excitations are of paramount importance for understanding the electronic structure of copper-oxide based high-temperature superconductors. In this study, we investigate the response of a Bi$_2$Sr$_2$CaCu$_2$O$_{\mathrm{8}+ δ}$ crystal to the charge redistribution induced by an infrared ultrashort pulse. Element-selective time-resolved core-level photoelectron spectroscopy with a high energy resolution allows disentangling the dynamics of oxygen ions with different coordination and bonds thanks to their different chemical shifts. Our experiment shows that the O\,$1s$ component arising from the Cu-O planes is significantly perturbed by the infrared light pulse. Conversely, the apical oxygen, also coordinated with Sr ions in the Sr-O planes, remains unaffected. This result highlights the peculiar behavior of the electronic structure of the Cu-O planes. It also unlocks the way to study the out-of-equilibrium electronic structure of copper-oxide-based high-temperature superconductors by identifying the O\,$1s$ core-level emission originating from the oxygen ions in the Cu-O planes. This ability could be critical to gain information about the strongly-correlated electron ultrafast dynamical mechanisms in the Cu-O plane in the normal and superconducting phases.

cond-mat.str-el↗

arXiv2022

Electron Dynamics at High-Energy Densities in Nickel from Non-linear Resonant X-ray Absorption Spectra

The pulse intensity from X-ray free-electron lasers (FELs) can create extreme excitation densities in solids, entering the regime of non-linear X-ray-matter interactions. We show L3-edge absorption spectra of metallic nickel thin films with fluences entering a regime where several X-ray photons are incident per absorption cross-section. Main features of the observed non-linear spectral changes are described with a predictive rate model for electron population dynamics during the pulse, utilizing a fixed density of states and tabulated ground-state properties.

cond-mat.mtrl-sci↗

arXiv2022

Resolving molecular diffusion and aggregation of antibody proteins with megahertz X-ray free-electron laser pulses

X-ray free-electron lasers (XFELs) with megahertz repetition rate can provide novel insights into structural dynamics of biological macromolecule solutions. However, very high dose rates can lead to beam-induced dynamics and structural changes due to radiation damage. Here, we probe the dynamics of dense antibody protein (Ig-PEG) solutions using megahertz X-ray photon correlation spectroscopy (MHz-XPCS) at the European XFEL. By varying the total dose and dose rate, we identify a regime for measuring the motion of proteins in their first coordination shell, quantify XFEL-induced effects such as driven motion, and map out the extent of agglomeration dynamics. The results indicate that for average dose rates below $1.06\,\mathrm{kGy}\mathrm{μs}^{-1}$ in a time window up to $10\,\mathrm{μs}$, it is possible to capture the protein dynamics before the onset of beam induced aggregation. We refer to this approach as correlation before aggregation and demonstrate that MHz-XPCS bridges an important spatio-temporal gap in measurement techniques for biological samples.

physics.bio-ph↗

arXiv2022

On the use of multilayer Laue lenses with X-ray Free Electron Lasers

Multilayer Laue lenses were used for the first time to focus x-rays from an X-ray Free Electron Laser (XFEL). In an experiment, which was performed at the European XFEL, we demonstrated focusing to a spot size of a few tens of nanometers. A series of runs in which the number of pulses per train was increased from 1 to 2, 3, 4, 5, 6, 7, 10, 20 and 30 pulses per train, all with a pulse separation of 3.55 us, was done using the same set of lenses. The increase in the number of pulses per train was accompanied with an increase of x-ray intensity (transmission) from 9% to 92% at 5 pulses per train, and then the transmission was reduced to 23.5 % when the pulses were increased further. The final working condition was 30 pulses per train and 23.5% transmission. Only at this condition we saw that the diffraction efficiency of the MLLs changed over the course of a pulse train, and this variation was reproducible from train to train. We present the procedure to align and characterize these lenses and discuss challenges working with the pulse trains from this unique x-ray source.

physics.acc-ph↗

arXiv2021

Genetic Regulation of Cytokine Response in Patients with Acute Community-acquired Pneumonia

Background: Community-acquired pneumonia (CAP) is an acute disease condition with a high risk of rapid deteriorations. We analysed the influence of genetics on cytokine regulation to obtain a better understanding of patient's heterogeneity. Methods: For up to N=389 genotyped participants of the PROGRESS study of hospitalised CAP patients, we performed a genome-wide association study of ten cytokines IL-1b, IL-6, IL-8, IL-10, IL-12, MCP-1 (MCAF), MIP-1a (CCL3), VEGF, VCAM-1, and ICAM-1. Consecutive secondary analyses were performed to identify independent hits and corresponding causal variants. Results: 102 SNPs from 14 loci showed genome-wide significant associations with five of the cytokines. The most interesting associations were found at 6p21.1 for VEGF (p=1.58x10E-20), at 17q21.32 (p=1.51x10E-9) and at 10p12.1 (p=2.76x10E-9) for IL-1b, at 10p13 for MIP-1a (CCL3) (p=2.28x10E-9), and at 9q34.12 for IL-10 (p=4.52x10E-8). Functionally plausible genes could be assigned to the majority of loci including genes involved in cytokine secretion, granulocyte function, and cilial kinetics. Conclusions: This is the first context-specific genetic association study of blood cytokine concentrations in CAP patients revealing numerous biologically plausible candidate genes. Two of the loci were also associated with atherosclerosis with probable common or consecutive pathomechanisms.

q-bio.QM↗

arXiv2021

On the parametrization of epidemiologic models -- lessons from modelling COVID-19 epidemic

A plethora of prediction models of SARS-CoV-2 pandemic were proposed in the past. Prediction performances not only depend on the structure and features of the model, but also on its parametrization. Official databases are often biased due to lag in reporting of cases, changing testing policy or incompleteness of data. Moreover, model parametrization is time-dependent e.g. due to changing age-structures, new emerging virus variants, non-pharmaceutical interventions and ongoing vaccination programs. To cover these aspects, we develop a principled approach to parametrize SIR-type epidemiologic models of different complexities by embedding the model structure as a hidden layer into a general Input-Output Non-Linear Dynamical System (IO-NLDS). Non-explicitly modelled impacts on the system are imposed as inputs of the system. Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. We estimate model parameters including their time-dependence by a Bayesian knowledge synthesis process considering parameter ranges derived from external studies as prior information. We applied this approach on a SIR-type model and data of Germany and Saxony demonstrating good prediction performances. By our approach, we can estimate and compare for example the relative effectiveness of non-pharmaceutical interventions and can provide scenarios of the future course of the epidemic under specified conditions. Our method of parameter estimation can be translated to other data sets, i.e. other countries and other SIR-type models even for other disease contexts.

q-bio.PE↗

arXiv2021

Factorization and discrete-time representation of multivariate CARMA processes

In this paper we show that stationary and non-stationary multivariate continuous-time ARMA (MCARMA) processes have the representation as a sum of multivariate complex-valued Ornstein-Uhlenbeck processes under some mild assumptions. The proof benefits from properties of rational matrix polynomials. A conclusion is an alternative description of the autocovariance function of a stationary MCARMA process. Moreover, that representation is used to show that the discrete-time sampled MCARMA(p,q) process is a weak VARMA(p,p-1) process if second moments exist. That result complements the weak VARMA(p,p-1) representation derived in Chambers and Thornton (2012). In particular, it relates the right solvents of the autoregressive polynomial of the MCARMA process to the right solvents of the autoregressive polynomial of the VARMA process; in the one-dimensional case the right solvents are the zeros of the autoregressive polynomial. Finally, a factorization of the sample autocovariance function of the noise sequence is presented which is useful for statistical inference.

math.ST↗

arXiv2020

Genome-wide association and transcriptome analysis reveals serum ghrelin to be linked with GFRAL

Objective: Ghrelin is an orexigenic peptide hormone involved in the regulation of energy homeostasis, food intake and glucose metabolism. Serum levels increase anticipating a meal and fall afterwards. Underlying genetic mechanisms of the ghrelin secretion are unknown. Methods: Total serum ghrelin was measured in 1501 subjects selected from the population-based LIFE-ADULT-sample after an overnight fast. A genome-wide association study (GWAS) was performed. Gene-based expression association analyses (transcriptome-wide association study (TWAS)) were done using MetaXcan. Results: In the GWAS, three loci reached genome-wide significance: the WW-domain containing the oxidoreductase-gene (WWOX; p=1.80E-10) on chromosome 16q23.3-24.1 (SNP: rs76823993); the Contactin-Associated Protein-Like 2 gene (CNTNAP2; p=9.0E-9) on chromosome 7q35-q36 (SNP: rs192092592) and the Ghrelin And Obestatin Prepropeptide gene (GHRL; p=2.72E-8) on chromosome 3p25.3 (SNP: rs143729751). In the TWAS, serum ghrelin was negatively associated with RNA expression of the GDNF Family Receptor Alpha Like (GFRAL), receptor of the anorexigenic Growth Differentiation Factor-15 (GDF15), (z-score=-4.288, p=1.81E-05). Furthermore, ghrelin was positively associated with Ribosomal Protein L36 (RPL36; z-score=4.848, p=1.25E-06). Conclusions: Our findings provide evidence of a functional link between two major players of weight regulation, the ghrelin system and the GDF15/GFRAL-pathway.

q-bio.GN↗

arXiv2019

Quasi-maximum likelihood estimation for cointegrated continuous-time state space models observed at low frequencies

In this paper, we investigate quasi-maximum likelihood (QML) estimation for the parameters of a cointegrated solution of a continuous-time linear state space model observed at discrete time points. The class of cointegrated solutions of continuous-time linear state space models is equivalent to the class of cointegrated continuous-time ARMA (MCARMA) processes. As a start, some pseudo-innovations are constructed to be able to define a QML-function. Moreover, the parameter vector is divided appropriately in long-run and short-run parameters using a representation for cointegrated solutions of continuous-time linear state space models as a sum of a Lévy process plus a stationary solution of a linear state space model. Then, we establish the consistency of our estimator in three steps. First, we show the consistency for the QML estimator of the long-run parameters. In the next step, we calculate its consistency rate. Finally, we use these results to prove the consistency for the QML estimator of the short-run parameters. After all, we derive the limiting distributions of the estimators. The long-run parameters are asymptotically mixed normally distributed, whereas the short-run parameters are asymptotically normally distributed. The performance of the QML estimator is demonstrated by a simulation study.

math.ST↗

arXiv2017

Cointegrated Continuous-time Linear State Space and MCARMA Models

In this paper we define and characterize cointegrated continuous-time linear state-space models. A main result is that a cointegrated continuous-time linear state-space model can be represented as a sum of a Lévy process and a stationary linear state-space model. Moreover, we prove that the class of cointegrated multivariate Lévy-driven autoregressive moving-average (MCARMA) processes, the continuous-time analogues of the classical vector ARMA processes, is equivalent to the class of cointegrated continuous-time linear state space models. Necessary and sufficient conditions for MCARMA processes to be cointegrated are given as well extending the results of Comte for MCAR processes. The conditions depend on the autoregressive polynomial. Finally, we investigate cointegrated continuous-time linear state-space models observed on a discrete time-grid and derive an error correction form for this model. The error correction form is based on an infinite linear filter in contrast to the finite linear filter for VAR models.

math.PR↗

arXiv2013

Comparing measures of association in 2x2 probability tables

Measures of association play a role in selecting 2x2 tables exhibiting strong dependence in high-dimensional binary data. Several measures are in use differing on specific tables and in their dependence on the margins. We study a 2-dimensional group of margin transformations on the 3-dimensional manifold T of all 2x2 probability tables. The margin transformations allow introducing natural coordinates that identify T with the real 3-space such that the x-axis corresponds to log(sqrt(odds-ratio)) and margins vary on planes x=const. We use these coordinates to visualise and compare measures of association with respect to their dependence on the margins given the odds-ratio, their limit behaviour when cells approach zero and their weighting properties. We propose a novel measure of association in which tables with single small entries are up-weighted but those with skewed margins are down-weighted according to the relative entropy among the tables of the same odds-ratio.

math.ST↗

arXiv2009

A Canonical Measure of Allelic Association

The measurement of biallelic pair-wise association called linkage disequilibrium (LD) is an important issue in order to understand the genomic architecture. A large variety of such measures of association have been proposed in the literature. We propose and justify six biometrical postulates which should be fulfilled by a canonical measure of LD. In short, LD measures are defined as a mapping of probability tables to the set of real numbers. They should be zero in case of independence and extremal if one of the entries approaches zero while the marginals are positively bounded. They should reflect the symmetry group of the tables and be invariant under certain transformations of the marginals (selection invariance). There scale should have maximum entropy relative to a calibrating symmetric distribution. None of the established measures fulfil all of these properties in general. We prove that there is a unique canonical measure of LD for each choice of a calibrating distribution. We compa- re the canonical LD measures with other candidates from the literature. We recommend the canonical measure derived from Jeffreys' non-informative prior distribution when assessing linkage disequilibrium of SNP array data. In a second part, we consider various estimators for the theoretical LD measures discussed and compare them in a simulation study.

stat.AP↗