arXiv subjects

Christian Wagner

Publications and source records attributed to Christian Wagner.

At least 55 records · Page 3Linked to original sources

arXiv2021

Control of Scanning Quantum Dot Microscopy

Scanning quantum dot microscopy is a recently developed high-resolution microscopy technique that is based on atomic force microscopy and is capable of imaging the electrostatic potential of nanostructures like molecules or single atoms. Recently, it could be shown that it not only yields qualitatively but also quantitatively cutting edge images even on an atomic level. In this paper we present how control is a key enabling element to this. The developed control approach consists of a two-degree-of-freedom control framework that comprises a feedforward and a feedback part. For the latter we design two tailored feedback controllers. The feedforward part generates a reference for the current scanned line based on the previously scanned one. We discuss in detail various aspects of the presented control approach and its implications for scanning quantum dot microscopy. We evaluate the influence of the feedforward part and compare the two proposed feedback controllers. The proposed control algorithms speed up scanning quantum dot microscopy by more than a magnitude and enable to scan large sample areas.

eess.SY↗

arXiv2021

Vortical flow structures induced by red blood cells in capillaries

Knowledge about the flow field of the plasma around the red blood cells in capillary flow is important for a physical understanding of blood flow and the transport of micro- and nanoparticles and molecules in the flowing plasma. We conduct an experimental study on the flow field around red blood cells in capillary flow that are complemented by simulations of vortical flow between red blood cells. Red blood cells were injected in a 10x12 micrometer rectangular microchannel at a low hematocrit and the flow field around a single or two cells have been characterized thanks to a highspeed camera and by tracking 250 nm nanoparticles in flow behaving as tracers. While the flow field around a steady croissant shape is found to be relatively similar to that of a rigid sphere, the flow field around a slipper shape exhibits a small vortex at the rear of the red blood cell. Even more pronounced are vortex-like structures observed in the central region between two neighboring croissants. Conclusions: The rotation frequency of the vortices is to a good approximation, inversely proportional to the distance between the cells. Our experimental data are confirmed and complemented by numerical simulations.

physics.bio-ph↗

arXiv2020

Autonomous robotic nanofabrication with reinforcement learning

The ability to handle single molecules as effectively as macroscopic building-blocks would enable the construction of complex supramolecular structures inaccessible to self-assembly. The fundamental challenges obstructing this goal are the uncontrolled variability and poor observability of atomic-scale conformations. Here, we present a strategy to work around both obstacles, and demonstrate autonomous robotic nanofabrication by manipulating single molecules. Our approach employs reinforcement learning (RL), which finds solution strategies even in the face of large uncertainty and sparse feedback. We demonstrate the potential of our RL approach by removing molecules autonomously with a scanning probe microscope from a supramolecular structure -- an exemplary task of subtractive manufacturing at the nanoscale. Our RL agent reaches an excellent performance, enabling us to automate a task which previously had to be performed by a human. We anticipate that our work opens the way towards autonomous agents for the robotic construction of functional supramolecular structures with speed, precision and perseverance beyond our current capabilities.

cond-mat.mes-hall↗

arXiv2020

Disaster Resilience and Asset Prices

This paper investigates whether security markets price the effect of social distancing on firms' operations. We document that firms that are more resilient to social distancing significantly outperformed those with lower resilience during the COVID-19 outbreak, even after controlling for the standard risk factors. Similar cross-sectional return differentials already emerged before the COVID-19 crisis: the 2014-19 cumulative return differential between more and less resilient firms is of similar size as during the outbreak, suggesting growing awareness of pandemic risk well in advance of its materialization. Finally, we use stock option prices to infer the market's return expectations after the onset of the pandemic: even at a two-year horizon, stocks of more pandemic-resilient firms are expected to yield significantly lower returns than less resilient ones, reflecting their lower exposure to disaster risk. Hence, going forward, markets appear to price exposure to a new risk factor, namely, pandemic risk.

q-fin.GN↗

arXiv2020

A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation

Deep learning based image segmentation has achieved the state-of-the-art performance in many medical applications such as lesion quantification, organ detection, etc. However, most of the methods rely on supervised learning, which require a large set of high-quality labeled data. Data annotation is generally an extremely time-consuming process. To address this problem, we propose a generic semi-supervised learning framework for image segmentation based on a deep convolutional neural network (DCNN). An encoder-decoder based DCNN is initially trained using a few annotated training samples. This initially trained model is then copied into sub-models and improved iteratively using random subsets of unlabeled data with pseudo labels generated from models trained in the previous iteration. The number of sub-models is gradually decreased to one in the final iteration. We evaluate the proposed method on a public grand-challenge dataset for skin lesion segmentation. Our method is able to significantly improve beyond fully supervised model learning by incorporating unlabeled data.

cs.CV↗

arXiv2020

Fusing Online Gaussian Process-Based Learning and Control for Scanning Quantum Dot Microscopy

Elucidating electrostatic surface potentials contributes to a deeper understanding of the nature of matter and its physicochemical properties, which is the basis for a wide field of applications. Scanning quantum dot microscopy, a recently developed technique allows to measure such potentials with atomic resolution. For an efficient deployment in scientific practice, however, it is essential to speed up the scanning process. To this end we employ a two-degree-of-freedom control paradigm, in which a Gaussian process is used as the feedforward part. We present a tailored online learning scheme of the Gaussian process, adapted to scanning quantum dot microscopy, that includes hyperparameter optimization during operation to enable fast and precise scanning of arbitrary surface structures. For the potential application in practice, the accompanying computational cost is reduced evaluating different sparse approximation approaches. The fully independent training conditional approximation, used on a reduced set of active training data, is found to be the most promising approach.

eess.SY↗

arXiv2019

Swimming of bacterium \textit{Bacillus subtilis} with multiple bundles of flagella

We characterize the bundle properties for three different strains of \textit{B. subtilis} bacteria with various numbers of flagella. Our study reveals that, surprisingly, the number of bundles is independent of the number of flagella, and the formation of three bundles is always the most frequent case. We assume that this relates to the fact that different mutants have the same body length. There is no significant difference between the bundle width and length for distinct strains, but the projected angle between the bundles increases with the flagellar number. Furthermore, we find that the swimming speed is anti-correlated with the projected angle between the bundles, and the wobbling angle between the swimming direction and cell body increases with the number of flagella. Our findings highlight the impact of geometrical properties of bacteria such as body length and bundle configuration on their motility.

physics.bio-ph↗

arXiv2019

Cross-sectional focusing of red blood cells in a constricted microfluidic channel

Constrictions in blood vessels and microfluidic devices can dramatically change the spatial distribution of passing cells or particles and are commonly used in biomedical cell sorting applications. However, the three-dimensional nature of cell focusing in the channel cross-section remains poorly investigated. Here, we explore the cross-sectional distribution of living and rigid red blood cells passing a constricted microfluidic channel by tracking individual cells in multiple layers across the channel depth and across the channel width. While cells are homogeneously distributed in the channel cross-section pre-contraction, we observe a strong geometry-induced focusing towards the four channel faces post-contraction. The magnitude of this cross-sectional focusing effect increases with increasing Reynolds number for both living and rigid red blood cells. We discuss how this non-uniform cell distribution downstream of the contraction results in an apparent double-peaked velocity profile in particle image velocimetry analysis and show that trapping of red blood cells in the recirculation zones of the abrupt construction depends on cell deformability.

physics.flu-dyn↗

arXiv2019

Inelastic electron tunneling spectroscopy for probing strongly correlated many-body systems by scanning tunneling microscopy

We present an extension of the tunneling theory for scanning tunneling microcopy (STM) to include different types of vibrational-electronic couplings responsible for inelastic contributions to the tunnel current in the strong-coupling limit. It allows for a better understanding of more complex scanning tunneling spectra of molecules on a metallic substrate in separating elastic and inelastic contributions. The starting point is the exact solution of the spectral functions for the electronic active local orbitals in the absence of the STM tip. This includes electron-phonon coupling in the coupled system comprising the molecule and the substrate to arbitrary order including the anti-adiabatic strong coupling regime as well as the Kondo effect on a free electron spin of the molecule. The tunneling current is derived in second order of the tunneling matrix element which is expanded in powers of the relevant vibrational displacements. We use the results of an ab-initio calculation for the single-particle electronic properties as an adapted material-specific input for a numerical renormalization group approach for accurately determining the electronic properties of a NTCDA molecule on Ag(111) as a challenging sample system for our theory. Our analysis shows that the mismatch between the ab-initio many-body calculation of the tunnel current in the absence of any electron-phonon coupling to the experiment scanning tunneling spectra can be resolved by including two mechanisms: (i) a strong unconventional Holstein term on the local substrate orbital leads to reduction of the Kondo temperature and (ii) a different electron-vibrational coupling to the tunneling matrix element is responsible for inelastic steps in the $dI/dV$ curve at finite frequencies.

cond-mat.mes-hall↗

arXiv2019

Exploring how Component Factors and their Uncertainty Affect Judgements of Risk in Cyber-Security

Subjective judgements from experts provide essential information when assessing and modelling threats in respect to cyber-physical systems. For example, the vulnerability of individual system components can be described using multiple factors, such as complexity, technological maturity, and the availability of tools to aid an attack. Such information is useful for determining attack risk, but much of it is challenging to acquire automatically and instead must be collected through expert assessments. However, most experts inherently carry some degree of uncertainty in their assessments. For example, it is impossible to be certain precisely how many tools are available to aid an attack. Traditional methods of capturing subjective judgements through choices such as \emph{high}, \emph{medium} or \emph{low} do not enable experts to quantify their uncertainty. However, it is important to measure the range of uncertainty surrounding responses in order to appropriately inform system vulnerability analysis. We use a recently introduced interval-valued response-format to capture uncertainty in experts' judgements and employ inferential statistical approaches to analyse the data. We identify key attributes that contribute to hop vulnerability in cyber-systems and demonstrate the value of capturing the uncertainty around these attributes. We find that this uncertainty is not only predictive of uncertainty in the overall vulnerability of a given system component, but also significantly informs ratings of overall component vulnerability itself. We propose that these methods and associated insights can be employed in real world situations, including vulnerability assessments of cyber-physical systems, which are becoming increasingly complex and integrated into society, making them particularly susceptible to uncertainty in assessment.

cs.CR↗

arXiv2019

Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets

Recently, there has been much research into modelling of uncertainty in human perception through Fuzzy Sets (FSs). Most of this research has focused on allowing respondents to express their (intra) uncertainty using intervals. Here, depending on the technique used and types of uncertainties being modelled different types of FSs can be obtained (e.g., Type-1, Interval Type-2, General Type-2). Arguably, one of the most flexible techniques is the Interval Agreement Approach (IAA) as it allows to model the perception of all respondents without making assumptions such as outlier removal or predefined membership function types (e.g. Gaussian). A key aspect in the analysis of interval-valued data and indeed, IAA based agreement models of said data, is to determine the position and strengths of agreement across all the sources/participants. While previously, the Agreement Ratio was proposed to measure the strength of agreement in fuzzy set based models of interval data, said measure has only been applicable to type-1 fuzzy sets. In this paper, we extend the Agreement Ratio to capture the degree of inter-group agreement modelled by a General Type-2 Fuzzy Set when using the IAA. This measure relies on using a similarity measure to quantitatively express the relation between the different levels of agreement in a given FS. Synthetic examples are provided in order to demonstrate both behaviour and calculation of the measure. Finally, an application to real-world data is provided in order to show the potential of this measure to assess the divergence of opinions for ambiguous concepts when heterogeneous groups of participants are involved.

cs.AI↗

arXiv2019

The Theory of Scanning Quantum Dot Microscopy

Electrostatic forces are among the most common interactions in nature and omnipresent at the nanoscale. Scanning probe methods represent a formidable approach to study these interactions locally. The lateral resolution of such images is, however, often limited as they are based on measuring the force (gradient) due to the entire tip interacting with the entire surface. Recently, we developed scanning quantum dot microscopy (SQDM), a new technique for the imaging and quantification of surface potentials which is based on the gating of a nanometer-size tip-attached quantum dot by the local surface potential and the detection of charge state changes via non-contact atomic force microscopy. Here, we present a rigorous formalism in the framework of which SQDM can be understood and interpreted quantitatively. In particular, we present a general theory of SQDM based on the classical boundary value problem of electrostatics, which is applicable to the full range of sample properties (conductive vs insulating, nanostructured vs homogeneously covered). We elaborate the general theory into a formalism suited for the quantitative analysis of images of nanostructured but predominantly flat and conductive samples.

cond-mat.mes-hall↗

arXiv2019

Agent-Based Simulation Modelling for Reflecting on Consequences of Digital Mental Health

The premise of this working paper is based around agent-based simulation models and how to go about creating them from given incomplete information. Agent-based simulations are stochastic simulations that revolve around groups of agents that each have their own characteristics and can make decisions. Such simulations can be used to emulate real life situations and to create hypothetical situations without the need for real-world testing prior. Here we describe the development of an agent-based simulation model for studying future digital mental health scenarios. An incomplete conceptual model has been used as the basis for this development. To define differences in responses to stimuli we employed fuzzy decision making logic. The model has been implemented but not been used for structured experimentation yet. This is planned as our next step.

cs.MA↗

arXiv2019

Strain and screening: Optical properties of a small-diameter carbon nanotube from first principles

Carbon nanotubes (CNTs) are a one-dimensional material system with intriguing physical properties that lead to emerging applications. While CNTs are unusually strain resistant compared to bulk materials, their optical-absorption spectrum is highly strain dependent. It is an open question, as to what extent this is attributed to strain-dependent (i) electronic single-particle transitions, (ii) dielectric screening, or (iii) atomic geometries including CNT radii. We use cutting-edge theoretical spectroscopy to explain strain-dependent electronic structure and optical properties of an (8,0) CNT. Quasiparticle effects are taken into account using Hedin's GW approximation and excitonic effects are described by solving a Bethe-Salpeter-equation for the optical polarization function. This accurate first-principles approach allows us to identify an inuence of strain on screening of the Coulomb electron-electron interaction and to quantify the impact on electronic structure and optical absorption of one-dimensional systems. We interpret our thoroughly converged results using an existing scaling relation and extend the use of this relation to strained CNTs: We show that it captures optical absorption with satisfactory accuracy, as long as screening, quasiparticle gap, and effective electron and hole masses of the strained CNT are known.

physics.comp-ph↗

arXiv2019

Flagellar number governs bacterial spreading and transport efficiency

Peritrichous bacteria synchronize and bundle their flagella to actively swim while disruption of the bundle leads to tumbling. It is still not known whether the number of flagella represents an evolutionary adaptation towards optimizing bacterial navigation. Here, we study the swimming dynamics of differentially flagellated Bacillus subtilis strains in a quasi-two-dimensional system. We find that decreasing the number of flagella N reduces the average turning angle between two successive run phases and enhances the duration and directional persistence of the run phase. As a result, having less flagella is beneficial for long-distance transport and fast spreading, while having a lot of flagella is advantageous for the processes which require localization and slow dynamics, such as biofilm formation. We develop a two-state random walk model that incorporates spontaneous switchings between the states and yields exact analytical expressions for transport properties, in remarkable agreement with experiments. The results of numerical simulations based on our two-state model suggest that the efficiency of searching and exploring the environment is optimized at intermediate values of N. The optimal choice of N, for which the search time is minimized, decreases with increasing the size of the environment in which the bacteria swim.

physics.bio-ph↗

arXiv2018

Influence of defect-induced deformations on electron transport in carbon nanotubes

We theoretically investigate the influence of defect-induced long-range deformations in carbon nanotubes on their electronic transport properties. To this end we perform numerical ab-initio calculations using a density-functional-based tight-binding (DFTB) model for various tubes with vacancies. The geometry optimization leads to a change of the atomic positions. There is a strong reconstruction of the atoms near the defect (called "distortion") and there is an additional long-range deformation. The impact of both structural features on the conductance is systematically investigated. We compare short and long CNTs of different kinds with and without long-range deformation. We find for the very thin (9,0)-CNT that the long-range deformation additionally affects the transmission spectrum and the conductance compared to the short-range lattice distortion. The conductance of the larger (11,0)- or the (14,0)-CNT is overall less affected implying that the influence of the long-range deformation decreases with increasing tube diameter. Furthermore, the effect can be either positive or negative depending on the CNT type and the defect type. Our results indicate that the long-range deformation must be included in order to reliably describe the electronic structure of defective, small-diameter zigzag tubes.

cond-mat.mes-hall↗

arXiv2018

Vesicle dynamics in confined steady and harmonically modulated Poiseuille flows

We present a numerical study of the time-dependent motion of a two-dimensional vesicle in a channel under an imposed flow. In a Poiseuille flow the shape of the vesicle depends on the flow strength, the mechanical properties of the membrane, and the width of the channel as reported in the past. This study is focused on the centered snaking (CSn) shape, where the vesicle shows an oscillatory motion like a swimmer flagella even though the flow is stationary. We quantify this behavior by the amplitude and frequency of the oscillations of the vesicle's center of mass. We observe regions in parameter space, where the CSn coexists with the parachute or the unconfined slipper. The influence of an amplitude modulation of the imposed flow on the dynamics and shape of the snaking vesicle is also investigated. For large modulation amplitudes transitions to static shapes are observed. A smaller modulation amplitude induces a modulation in amplitude and frequency of the center of mass of the snaking vesicle. In a certain parameter range we find that the center of mass oscillates with a constant envelope indicating the presence of at least two stable states.

physics.bio-ph↗

arXiv2018

Classification of red blood cell shapes in flow using outlier tolerant machine learning

The manual evaluation, classification and counting of biological objects demands for an enormous expenditure of time and subjective human input may be a source of error. Investigating the shape of red blood cells (RBCs) in microcapillary Poiseuille flow, we overcome this drawback by introducing a convolutional neural regression network for an automatic, outlier tolerant shape classification. From our experiments we expect two stable geometries: the so-called `slipper' and `croissant' shapes depending on the prevailing flow conditions and the cell-intrinsic parameters. Whereas croissants mostly occur at low shear rates, slippers evolve at higher flow velocities. With our method, we are able to find the transition point between both `phases' of stable shapes which is of high interest to ensuing theoretical studies and numerical simulations. Using statistically based thresholds, from our data, we obtain so-called phase diagrams which are compared to manual evaluations. Prospectively, our concept allows us to perform objective analyses of measurements for a variety of flow conditions and to receive comparable results. Moreover, the proposed procedure enables unbiased studies on the influence of drugs on flow properties of single RBCs and the resulting macroscopic change of the flow behavior of whole blood.

physics.bio-ph↗