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Institut
- Westfälisches Institut für Gesundheit (38)
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We report on investigations that illustrate the interaction between the specific immune system and a young avascular tumor growing due to a diffusive nutrient supply. We formulate a hybrid cellular automata-partial differential equation (CA-PDE) model which includes cell cycle dynamics and allows for tracking the spatial and temporal evolution of this elaborate biological system. We present results of two dimensional numerical simulations that, specifically in this work, include special cases of the spherical and papillary tumor growth, the infiltration of immune system cells into the tumor and the escape of tumor cells from the regime of the immune cells.
Stereotactic frame systems are widely used in neurosurgery. The accuracy of frame devices is considered as a gold standard to which the accuracy of new frameless stereotactic navigation systems is compared. The purpose of this study is to develop a general approach for the prediction of the application accuracy of stereotactic systems. The approach will be applied to the frame‐based biopsy performed with three frame devices: Leksell G, Cosman–Roberts–Wells (CRW), and Brown–Roberts–Wells (BRW). A work‐flow analysis will be carried out demonstrating that the accuracy relevant for a clinical application comprises several error sources including imaging, target and entry point selection, image to frame coordinates registration, and the setting of mechanical parameters of the frame. These error sources will be postulated to obey a Gaussian distribution probability density. The linear, i.e., Gaussian, error propagation, will be used to link all error contributions thus to calculate the cumulative accuracy of the frame used in the application. Although the Gaussian approach is an approximation, it allows for an analytical treatment of the accuracy. Both the accuracy at the target point and the accuracy of the probe needle guidance along the planned trajectory have been investigated. Of great significance is the relationship found between accuracy, pixel dimension, and image slice thickness, the latter being the dominant factor for slices of more than 1.5 mm thickness, yielding inaccuracies larger than 1.5 mm. For target points the predictions for the application accuracy have been compared to the results of measurements, showing good agreement with the experimental data.
A qualitative work‐flow analysis of a neurosurgical procedure indicates that the resolution of the image used to plan the intervention is the major source of inaccuracy. Quantitative experimental measurements confirm this observation. They fail, however, to explain the relationship between the accuracy of the frame components involved in a stereotactic procedure and the overall application accuracy. This investigation shows that the novel Gaussian approach is a flexible framework for the calculation of the application accuracy of frame systems. Therefore, the Gaussian approach provides a detailed understanding of the interplay between the various factors affecting accuracy. The basic ideas and limitations of the Gaussian approach are briefly explained. The effect of fiducial marker distribution and registration is investigated and shown to introduce a spatial dependence to the accuracy. The results of the Gaussian approach are compared with experimental data for three stereotactic frame devices: Leksell G, Cosman–Roberts–Wells, and Brown–Roberts–Wells. Although the Gaussian approach is an approximation, it reproduces the accuracy measured in the experiment within the statistical error of that experiment. Comp Aid Surg 4:77–86 (1999). © 1999 Wiley‐Liss, Inc.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.
With ongoing developments in the field of smart cities and digitalization in general, data is becoming a driving factor and value stream for new and existing economies alike. However, there exists an increasing centralization and monopolization of data holders and service providers, especially in the form of the big US-based technology companies in the western world and central technology providers with close ties to the government in the Asian regions. Self Sovereign Identity (SSI) provides the technical building blocks to create decentralized data-driven systems, which bring data autonomy back to the users. In this paper we propose a system in which the combination of SSI and token economy based incentivisation strategies makes it possible to unlock the potential value of data-pools without compromising the data autonomy of the users.
A Crypto-Token Based Charging Incentivization
Scheme for Sustainable Light Electric Vehicle
Sharing
(2021)
The ecological impact of shared light electric vehicles (LEV) such as kick scooters is still widely discussed. Especially the fact that the vehicles and batteries are collected using diesel vans in order to charge empty batteries with electricity of unclear origin is perceived as unsustainable. A better option could be to let the users charge the vehicles themselves whenever it is necessary. For this, a decentralized,flexible and easy to install network of off-grid solar charging stations could bring renewable electricity where it is needed without sacrificing the convenience of a free float sharing system. Since the charging stations are powered by solar energy the most efficient way to utilize them would be to charge the vehicles when the sun is shining. In order to make users charge the vehicle it is necessary to provide some form of benefit for
them doing so. This could be either a discount or free rides. A
particularly robust and well-established mechanism is controlling incentives via means of blockchain-based cryptotokens. This paper demonstrates a crypto-token based scheme for incentivizing users to charge sharing vehicles during times of considerable solar irradiation in order to contribute to more sustainable mobility services.
The technology of polymer electrolyte membrane (PEM) electrolysis provides an efficient way to produce hydrogen. In combination with renewable energy sources, it promises to be one of the key factors towards a carbon-free energy infrastructure in the future. Today, PEM electrolyzers with a power consumption higher than 1 MW and a gas output pressure of 30 bar (or even higher) are already commercially available. Nevertheless, fundamental research and development for an improved efficiency is far from being finally accomplished, and mostly takes place on a laboratory scale. Upscaling the laboratory prototypes to an industrial size usually cannot be achieved without facing further problems and/or losing efficiency. With our novel system design based on hydraulic cell compression, a lot of the commonly occurring problems like inhomogeneous temperature and current distribution can be avoided. In this study we present first results of an upscaling by a factor of 30 in active cell area.
To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.
In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.
Based on the fact that titanium and titanium alloys have poor fretting fatigue resistance and poor tribological properties, it is necessary to apply some surface engineering methods in order to increase the exploitation characteristics of these materials. One may either implement some surface treatment technologies or even deposit overlay coatings by thermal spraying.
The present study is focused on the achieved properties of the ceramic coatings (Al2O3 + 13 wt.% TiO2) deposited onto a titanium substrate using high velocity oxygen fuel (HVOF) and plasma spraying (APS) respectively.
The effect of the deposition method on the microstructure, phase constituents, and mechanical properties of the ceramic coatings was investigated by means of scanning electron microscopy (SEM), X-ray diffraction technique (XRD) and nanoindentation tests. The sliding wear performances of the Al2O3–TiO2 coatings were tested using a pin on disk wear tester.
The European General Data Protection Regulation (GDPR), which went into effect in May 2018, brought new rules for the processing of personal data that affect many business models, including online advertising. The regulation’s definition of personal data applies to every company that collects data from European Internet users. This includes tracking services that, until then, argued that they were collecting anonymous information and data protection requirements would not apply to their businesses.
Previous studies have analyzed the impact of the GDPR on the prevalence of online tracking, with mixed results. In this paper, we go beyond the analysis of the number of third parties and focus on the underlying information sharing networks between online advertising companies in terms of client-side cookie syncing. Using graph analysis, our measurement shows that the number of ID syncing connections decreased by around 40 % around the time the GDPR went into effect, but a long-term analysis shows a slight rebound since then. While we can show a decrease in information sharing between third parties, which is likely related to the legislation, the data also shows that the amount of tracking, as well as the general structure of cooperation, was not affected. Consolidation in the ecosystem led to a more centralized infrastructure that might actually have negative effects on user privacy, as fewer companies perform tracking on more sites.
Advanced Persistent Threats (APTs) are one of the main challenges in modern computer security. They are planned and performed by well-funded, highly-trained and often state-based actors. The first step of such an attack is the reconnaissance of the target. In this phase, the adversary tries to gather as much intelligence on the victim as possible to prepare further actions. An essential part of this initial data collection phase is the identification of possible gateways to intrude the target.
In this paper, we aim to analyze the data that threat actors can use to plan their attacks. To do so, we analyze in a first step 93 APT reports and find that most (80 %) of them begin by sending phishing emails to their victims. Based on this analysis, we measure the extent of data openly available of 30 entities to understand if and how much data they leak that can potentially be used by an adversary to craft sophisticated spear phishing emails. We then use this data to quantify how many employees are potential targets for such attacks. We show that 83 % of the analyzed entities leak several attributes of uses, which can all be used to craft sophisticated phishing emails.
In the modern Web, service providers often rely heavily on third parties to run their services. For example, they make use of ad networks to finance their services, externally hosted libraries to develop features quickly, and analytics providers to gain insights into visitor behavior.
For security and privacy, website owners need to be aware of the content they provide their users. However, in reality, they often do not know which third parties are embedded, for example, when these third parties request additional content as it is common in real-time ad auctions.
In this paper, we present a large-scale measurement study to analyze the magnitude of these new challenges. To better reflect the connectedness of third parties, we measured their relations in a model we call third party trees, which reflects an approximation of the loading dependencies of all third parties embedded into a given website. Using this concept, we show that including a single third party can lead to subsequent requests from up to eight additional services. Furthermore, our findings indicate that the third parties embedded on a page load are not always deterministic, as 50 % of the branches in the third party trees change between repeated visits. In addition, we found that 93 % of the analyzed websites embedded third parties that are located in regions that might not be in line with the current legal framework. Our study also replicates previous work that mostly focused on landing pages of websites. We show that this method is only able to measure a lower bound as subsites show a significant increase of privacy-invasive techniques. For example, our results show an increase of used cookies by about 36 % when crawling websites more deeply.
Hydrogen concentrations in ZnO single crystals exposing different surfaces have been determined to be in the range of (0.02–0.04) at.% with an error of ±0.01 at.% using nuclear reaction analysis. In the subsurface region, the hydrogen concentration has been determined to be higher by up to a factor of 10. In contrast to the hydrogen in the bulk, part of the subsurface hydrogen is less strongly bound, can be removed by heating to 550°C, and reaccommodated by loading with atomic hydrogen. By exposing the ZnO(10-10) surface to water above room temperature and to atomic hydrogen, respectively, hydroxylation with the same coverage of hydrogen is observed.
This paper makes a contribution to the discussion on microfoundations of dynamic capabilities – actions and interactions in organizations that enable continuous organizational renewal. More specifically, we propose the idea that dynamic capabilities of an organization
are a positive function of corresponding dynamic capabilities of individual and collective actors in the organization. Further, we develop the assumption that not only individual acts of managers but also of individuals and teams without managerial responsibility relate to dynamic capabilities of the organization. Following a holistic view, we also take into consideration empowering working conditions as enhancing factor of this function. To
examine these roots of dynamic capabilities, we use a multi level model of competence provided by Wilkens, Keller and Schmette (2006) that operationalizes the concept of dynamic
capabilities provided by Teece (2007) on a concisely behavioural base. We investigated our hypotheses with a standardized questionnaire in a case study of a German plant engineering company with 112 participants and found first support for our assumptions. Our results show an impact of individual dynamic capabilities on dynamic capabilities of the organization which is mediated by team dynamic capabilities. Psychological and social-structural empowerment moderated this relationship. A case-specific interpretation and implications for future research and practice are discussed.
Under ambient conditions, almost all metals are coated by an oxide. These coatings, the result of a chemical reaction, are not passive. Many of them bind, activate and modify adsorbed molecules, processes that are exploited, for example, in heterogeneous catalysis and photochemistry. Here we report an effect of general importance that governs the bonding, structure formation and dissociation of molecules on oxidic substrates. For a specific example, methanol adsorbed on the rutile TiO2(110) single crystal surface, we demonstrate by using a combination of experimental and theoretical techniques that strongly bonding adsorbates can lift surface relaxations beyond their adsorption site, which leads to a sig- nificant substrate-mediated interaction between adsorbates. The result is a complex super- structure consisting of pairs of methanol molecules and unoccupied adsorption sites. Infrared spectroscopy reveals that the paired methanol molecules remain intact and do not depro- tonate on the defect-free terraces of the rutile TiO2(110) surface.
Three dinuclear zinc carboxylate complexes [L1−3Zn(μ,η2-O2CPh)]2 (1, 2, 4) containing either the bidentate N,N′-chelating β-diketiminate ligand RNC(Me)C(H)C(Me)NR (R = 2,6-iPr2-C6H3, L1, complex 1), the tridentate O,N,N-chelating ligand OC(Me)C(H)C(Me)NCH2CH2NMe2 (L2, complex 2) or the bis-N,N′-chelating bis-β-diketiminate ligand RNC(Me)C(H)C(Me)NNC(Me)C(H)C(Me)NR (R = 2,6-iPr2-C6H3, L3, complex 4) were synthesized and characterized including single-crystal X-ray diffraction. Reaction of the neutral bis-β-diketimine (L3(H)2) with two equivalents of ZnMe2 leads to the expected heteroleptic dinuclear zinc complex L3(ZnMe)2 3 in 93 % yield. Further reaction with benzoic acid PhCO2H leads to complex 4. Complex 2 forms a rather strong carboxylate-bridged dimer, whereas the carboxylate groups in complexes 1 and 4 act as asymmetrical bridges between both Zn atoms, pointing to the formation of a weakly bonded dimer. The zinc atoms in 1 and 4 are tetrahedrally coordinated, whereas in 2 the coordination number is increased to five due to the coordination of the pendant donor arm. The ring opening polymerization (ROP) of rac-lactide was investigated with the zinc complexes 1–4 and diazabicycloundec-7-ene (DBU) as a co-catalyst. Complexes 2 and 3 are active polymerization catalysts, which in the presence of DBU converted 200 equiv. of rac-lactide into polylactide within 10 min at ambient temperature. The analysis of the crude polymer showed that the lactide polymerization with catalyst 2 occurs via a slightly modified activated-monomer mechanism.
Recent experimental results showing atypical nonlinear absorption and marked deviations from well known universality in the low temperature acoustic and dielectric losses in amorphous solids prove the need for improving the understanding of the nature of two-level systems (TLSs) in these materials. Here we suggest the study of TLSs focused on their properties which are nonuniversal. Our theoretical analysis shows that the standard tunneling model and the recently suggested two-TLS model provide markedly different predictions for the experimental outcome of these studies. Our results may be directly tested in disordered lattices, e.g KBr:CN, where there is ample theoretical support for the validity of the two-TLS model, as well as in amorphous solids. Verification of our results in the latter will significantly enhance understanding of the nature of TLSs in amorphous solids, and the ability to manipulate them and reduce their destructive effect in various cutting edge applications including superconducting qubits.
Description and Analysis of Glycosidic Residues in the Largest Open Natural Products Database
(2021)
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT (COlleCtion of Open Natural prodUcTs) database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day.
The German supply chain law ( Lieferkettensorgfaltspflichtengesetz, abbreviated: LkSG) which enters into force on 1 January 2023 is part of the developing legal framework for human rights in global supply chains. Like the French vigilance law, it represents a new generation of supply chain laws which impose mandatory human rights due diligence obligations. The LkSG requires enterprises to exercise a number of due diligence obligations – from conducting risk analysis to undertaking preventive measures or remedial actions. The law is based on public enforcement via a competent authority, the Federal Office for Economic Affairs and Export Control (BAFA). The BAFA monitors and enforces compliance with the due diligence obligations. Non-compliant enterprises can be fined with up to 800,000 Euros and, in some cases, up to 2% of the annual turnover. Whilst the LkSG is an important step towards achieving greater corporate sustainability, it also has limitations. It was a political compromise and, as such, it does not include a new civil liability for non-compliance. Moreover, by default, it only applies to the enterprise’s own business area and its direct suppliers, whereas indirect suppliers are only included where the enterprise has substantiated knowledge that an obligation has been violated.
In this study, a novel design concept for PEMFC (polymer electrolytemembrane fuel cell) stacks is presented with singlecells inserted in pockets surrounded by a hydraulic medium. Thehydraulic pressure introduces necessary compression forces to themembrane electrode assembly of each cell within a stack. Moreover, homogeneous cell cooling is achieved by this medium. First,prototypes presented in this work indicate that, upscaling of cells for the novelstack design is possible without significantperformancelosses. Due to its modularity and scalability, this stackdesign meets the requirements for large PEMFC units.
In this experimental work polymer electrolyte membrane fuel cell (PEMFC) electrodes are analysed, which are prepared by the use of two sorts of carbon nano fibres (CNF) serving as support material for platinum nano particles. Those CNFs, which are heat treated subsequently to their production, have a higher graphitisation degree than fibres as produced. The improved graphitisation degree leads to higher electrical conductivity, which is favourably for the use in PEMFC electrodes. Samples have been analysed, in order to determine graphitisation degree, electrical conductivity, as well as morphology and loading of the prepared electro catalyst. Membrane electrode assemblies manufactured from prepared electrodes are analysed in-situ in a PEM fuel cell test environment. It has been determined that power output for samples containing CNFs with higher graphitisation degree is increased by about 13.5%.
In the polymer electrolyte membrane fuel cells (PEMFC) state of the art, rare and expensive platinum group metals (PGM) or PGM alloys are used as catalyst material. Reduction of PGMs in PEMFC electrodes is strongly required to reach cost targets for this technology. An optimal catalyst utilization is achieved in case of nano-structured particles supported on carbon material with a large specific surface area. In this study, graphitic material, in form of carbon nanofibers (CNF), is decorated with Pt particles, serving as catalyst material for PEMFC electrodes with low Pt loading. As a novelty, the effect of oxygen plasma treatment of CNFs previously to platinum particle deposition has been studied. Electrodes are investigated in respect of the optimal morphology, microstructure as well as electrochemical properties. Therefore, samples are characterized by means of scanning electron microscopy combined with energy dispersive X-ray analysis, transmission electron microscopy, thermogravimetry, X-ray diffraction as well as X-ray fluorescence analysis. In order to determine the electrochemical active surface area of catalyst particles, cyclic voltammetry has been performed in 0.5 M sulphuric acid. Selected samples have been investigated in a PEMFC test bench according to their polarization behavior.