Refine
Year of publication
Document Type
- Article (9)
- Doctoral Thesis (2)
- Conference Proceeding (1)
- diplomthesis (1)
- Working Paper (1)
Has Fulltext
- yes (14)
Is part of the Bibliography
- no (14) (remove)
Keywords
- simulation (14) (remove)
Institute
- Medizin (4)
- Physik (3)
- Biochemie und Chemie (2)
- Informatik (2)
- Psychologie (1)
Previous studies in patients with single-sided deafness (SSD) have reported results of pitch comparisons between electric stimulation of their cochlear implant (CI) and acoustic stimulation presented to their near-normal hearing contralateral ear. These comparisons typically used sinusoids, although the percept elicited by electric stimulation may be closer to a wideband stimulus. Furthermore, it has been shown that pitch comparisons between sounds with different timbres is a difficult task and subjected to various types of range biases. The present study aims to introduce a method to minimize non-sensory biases, and to investigate the effect of different acoustic stimulus types on the frequency and variability of the electric-acoustic pitch matches. Pitch matches were collected from 13 CI users with SSD using the binary search procedure. Electric stimulation was presented at either an apical or a middle electrode position, at a rate of 800 pps. Acoustic stimulus types were sinusoids (SINE), 1/3-octave wide narrow bands of Gaussian noises (NBN), or 1/3-octave wide pulse spreading harmonic complexes (PSHC). On the one hand, NBN and PSHC are presumed to better mimic the spread of excitation produced by a single-electrode stimulation than SINE. On the other hand, SINE and PSHC contain less inherent fluctuations than NBN and may therefore provide a temporal pattern closer to that produced by a constant-amplitude electric pulse train. Analysis of mean pitch match variance showed no differences between stimulus types. However, mean pitch matches showed effects of electrode position and stimulus type, with the middle electrode always matched to a higher frequency than the apical one (p < 0.001), and significantly higher across-subject pitch matches for PSHC compared with SINE (p = 0.017). Mean pitch matches for all stimulus types were better predicted by place-dependent characteristic frequencies (CFs) based on an organ of Corti map compared with a spiral ganglion map. CF predictions were closest to pitch matches with SINE for the apical electrode position, and conversely with NBN or PSHC for the middle electrode position. These results provide evidence that the choice of acoustic stimulus type can have a significant effect on electric-acoustic pitch matching.
Specific functions of biological systems often require conformational transitions of macromolecules. Thus, being able to describe and predict conformational changes of biological macromolecules is not only important for understanding their impact on biological function, but will also have implications for the modelling of (macro)molecular complex formation and in structure-based drug design approaches. The “conformational selection model” provides the foundation for computational investigations of conformational fluctuations of the unbound protein state. These fluctuations may reveal conformational states adopted by the bound proteins. The aim of this work is to incorporate directional information in a geometry-based approach, in order to sample biologically relevant conformational space extensively. Interestingly, coarse-grained normal mode (CGNM) approaches, e.g., the elastic network model (ENM) and rigid cluster normal mode analysis (RCNMA), have emerged recently and provide directions of intrinsic motions in terms of harmonic modes (also called normal modes). In my previous work and in other studies it has been shown that conformational changes upon ligand binding occur along a few low-energy modes of unbound proteins and can be efficiently calculated by CGNM approaches. In order to explore the validity and the applicability of CGNM approaches, a large-scale comparison of essential dynamics (ED) modes from molecular dynamics (MD) simulations and normal modes from CGNM was performed over a dataset of 335 proteins. Despite high coarse-graining, low frequency normal modes from CGNM correlate very well with ED modes in terms of directions of motions (average maximal overlap is 0.65) and relative amplitudes of motions (average maximal overlap is 0.73). In order to exploit the potential of CGNM approaches, I have developed a three-step approach for efficient exploration of intrinsic motions of proteins. The first two steps are based on recent developments in rigidity and elastic network theory. Initially, static properties of the protein are determined by decomposing the protein into rigid clusters using the graph-theoretical approach FIRST at an all-atom representation of the protein. In a second step, dynamic properties of the molecule are revealed by the rotations-translations of blocks approach (RTB) using an elastic network model representation of the coarse-grained protein. In the final step, the recently introduced idea of constrained geometric simulations of diffusive motions in proteins is extended for efficient sampling of conformational space. Here, the low-energy (frequency) normal modes provided by the RCNMA approach are used to guide the backbone motions. The NMSim approach was validated on hen egg white lysozyme by comparing it to previously mentioned simulation methods in terms of residue fluctuations, conformational space explorations, essential dynamics, sampling of side-chain rotamers, and structural quality. Residue fluctuations in NMSim generated ensemble is found to be in good agreement with MD fluctuations with a correlation coefficient of around 0.79. A comparison of different geometry-based simulation approaches shows that FRODA is restricted in sampling the backbone conformational space. CONCOORD is restricted in sampling the side-chain conformational space. NMSim sufficiently samples both the backbone and the side-chain conformations taking experimental structures and conformations from the state of the art MD simulation as reference. The NMSim approach is also applied to a dataset of proteins where conformational changes have been observed experimentally, either in domain or functionally important loop regions. The NMSim simulations starting from the unbound structures are able to reach conformations similar to ligand bound conformations (RMSD < 2.4 Å) in 4 out of 5 cases of domain moving proteins. In these four cases, good correlation coefficients (R > 0.7) between the RMS fluctuations derived from NMSim generated structures and two experimental structures are observed. Furthermore, intrinsic fluctuations in NMSim simulation correlate with the region of loop conformational changes observed upon ligand binding in 2 out of 3 cases. The NMSim generated pathway of conformational change from the unbound structure to the ligand bound structure of adenylate kinase is validated by a comparison to experimental structures reflecting different states of the pathway as proposed by previous studies. Interestingly, the generated pathway confirms that the LID domain closure precedes the closing of the NMPbind domain, even if no target conformation is provided in NMSim. Hence, the results in this study show that, incorporating directional information in the geometry-based approach NMSim improves the sampling of biologically relevant conformational space and provides a computationally efficient alternative to state of the art MD simulations.
Due to the massive parallel operation modes at GSI accelerators, a lot of accelerator setup and re-adjustment has to be made by operators during a beam time. This is typically done manually using potentiometers and is very time-consuming. With the FAIR project the complexity of the accelerator facility increases further and for efficiency reasons it is recommended to establish a high level of automation for future operation. Modern Accelerator Control Systems allow a fast access to both, accelerator settings and beam diagnostics data. This provides the opportunity to implement algorithms for automated adjustment of e.g. magnet settings to maximize transmission and optimize required beam parameters. The fast-switching magnets in GSI-beamlines are an optimal basis for an automatic exploration of the parameter-space. The optimization of the parameters for the SIS18 multi-turn-injection using a genetic algorithm has already been simulated*. The first results of our automatized online parameter optimization at the CRYRING@ESR injector are presented here.
Configuration, simulation and visualization of simple biochemical reaction-diffusion systems in 3D
(2004)
Background In biological systems, molecules of different species diffuse within the reaction compartments and interact with each other, ultimately giving rise to such complex structures like living cells. In order to investigate the formation of subcellular structures and patterns (e.g. signal transduction) or spatial effects in metabolic processes, it would be helpful to use simulations of such reaction-diffusion systems. Pattern formation has been extensively studied in two dimensions. However, the extension to three-dimensional reaction-diffusion systems poses some challenges to the visualization of the processes being simulated. Scope of the Thesis The aim of this thesis is the specification and development of algorithms and methods for the three-dimensional configuration, simulation and visualization of biochemical reaction-diffusion systems consisting of a small number of molecules and reactions. After an initial review of existing literature about 2D/3D reaction-diffusion systems, a 3D simulation algorithm (PDE solver), based on an existing 2D-simulation algorithm for reaction-diffusion systems written by Prof. Herbert Sauro, has to be developed. In a succeeding step, this algorithm has to be optimized for high performance. A prototypic 3D configuration tool for the initial state of the system has to be developed. This basic tool should enable the user to define and store the location of molecules, membranes and channels within the reaction space of user-defined size. A suitable data structure has to be defined for the representation of the reaction space. The main focus of this thesis is the specification and prototypic implementation of a suitable reaction space visualization component for the display of the simulation results. In particular, the possibility of 3D visualization during course of the simulation has to be investigated. During the development phase, the quality and usability of the visualizations has to be evaluated in user tests. The simulation, configuration and visualization prototypes should be compliant with the Systems Biology Workbench to ensure compatibility with software from other authors. The thesis is carried out in close cooperation with Prof. Herbert Sauro at the Keck Graduate Institute, Claremont, CA, USA. Due to this international cooperation the thesis will be written in English.
Background: The objective of the STREAM Trial was to evaluate the effect of simulation training on process times in acute stroke care.
Methods: The multicenter prospective interventional STREAM Trial was conducted between 10/2017 and 04/2019 at seven tertiary care neurocenters in Germany with a pre- and post-interventional observation phase. We recorded patient characteristics, acute stroke care process times, stroke team composition and simulation experience for consecutive direct-to-center patients receiving intravenous thrombolysis (IVT) and/or endovascular therapy (EVT). The intervention consisted of a composite intervention centered around stroke-specific in situ simulation training. Primary outcome measure was the ‘door-to-needle’ time (DTN) for IVT. Secondary outcome measures included process times of EVT and measures taken to streamline the pre-existing treatment algorithm.
Results: The effect of the STREAM intervention on the process times of all acute stroke operations was neutral. However, secondary analyses showed a DTN reduction of 5 min from 38 min pre-intervention (interquartile range [IQR] 25–43 min) to 33 min (IQR 23–39 min, p = 0.03) post-intervention achieved by simulation-experienced stroke teams. Concerning EVT, we found significantly shorter door-to-groin times in patients who were treated by teams with simulation experience as compared to simulation-naive teams in the post-interventional phase (−21 min, simulation-naive: 95 min, IQR 69–111 vs. simulation-experienced: 74 min, IQR 51–92, p = 0.04).
Conclusion: An intervention combining workflow refinement and simulation-based stroke team training has the potential to improve process times in acute stroke care.
Programele computerizate au un rol indiscutabil în atingerea unor standarde ridicate în procesul educațional. Pe de altă parte acestea sunt instrumente eficiente în identificarea particularităților cazurilor clinice, evaluarea acestora în conformitate cu indicii clinico-biologici specifici. În timpul procesului didactic, simularea are un rol esenţial, ca o prefaţă la procedurile practice care formează abilităţile practice pe fiecare entitate clinică în medicina dentară.
Molecular dynamics (MD) simulation serves as an important and widely used computational tool to study molecular systems at an atomic resolution. No experimental technique is capable of generating a complete description of the dynamical structure of the biomolecules in their native solution environment. MD simulations allow us to study the dynamics and structure of the system and, moreover, helps in the interpretation of experimental observations. MD simulation was first introduced and applied by Alder and Wainwright in 1957 \cite{Alder57}. However, the first MD simulation of a macromolecule of biological interest was published 28 years ago \cite{McCammon77}. The simulation was concerned with the bovine pancreatic trypsin inhibitor (BPTI) protein, which has served as the hydrogen molecule'' of protein dynamics because of its small size, high stability, and relatively accurate X-ray structure available in 1977 \cite{Deisenhofer75}. This method is now widely used to tackle larger and more complex biological systems \cite{Groot01,Roux02} and has been facilitated by the development of fast and efficient methods for treating the long-range electrostatic interactions \cite{Essmann95}, the availability of faster parallel computers, and the continuous development of empirical molecular mechanical force fields \cite{Langley98,Cheatham99,Foloppe00}. It took several years until the first MD simulations of nucleic acid systems were performed \cite{Levitt83,Tidor83,Prabhakaran83,Nilsson86}. These investigations, which were also performed in vacuo, clearly demonstrated the importance of proper handling of electrostatics in a highly charged nucleic acid system, and different approaches, such as reduction of the phosphate charges and addition of hydrated counterions, have been applied to remedy this shortcoming and to maintain stable DNA structures. A few years later, the first MD simulation of a DNA molecule, including explicit water molecules and counterions was published \cite{Seibel85}. Various MD simulations on fully solvated RNA molecules with explicit inclusion of mobile ions indicated the importance of proper treatment of the environment of highly charged nucleic acids \cite{Lee95,Zichi95,Auffinger97,Auffinger99}. Given the central roles of RNA in the life of cells, it is important to understand the mechanism by which RNA forms three dimensional structures endowed with properties such as catalysis, ligand binding, and recognition of proteins. Furthermore, the increasing awareness of the essential role of RNA in controlling viral replication and in bacterial protein synthesis emphazises the potential of ribonucleicacids as targets for developing new antibacterial and new antiviral drugs. Driven by fruitful collaborations in the Sonderforschungsbereich RNA-Ligand interactions" the model RNA systems in this study include various RNA tetraloops and HIV-1 TAR RNA. For the latter system, the binding sites of heteroaromatic compounds have been studied employing automated docking calculations \cite{Goodsell90}. The results show that it is possible to use this tool to dock small rigid ligands to an RNA molecule, while large and flexible molecules are clearly problematic. The main part of this work is focused on MD simulations of RNA tetraloops.
The RFQ direct injection project (RFQ-DIP) for the neutrino physics experiment IsoDAR aims at an efficient injection of a high-current H²⁺ beam into the dedicated 60 MeV driver cyclotron. Therefore, it is intended to use a compact 32.8 MHz RFQ structure of the split-coaxial type as a pre-buncher. To determine the thermal elongation of the 1.4 m long electrode rods as well as the thermal frequency detuning of the RF structure at a maximum nominal power load of 3.6 kW, an extensive thermal and structural mechanical analysis using COMSOL Multiphysics was conducted. The water heating along the cooling channels as well as the properties of heat transfer from the copper structure to the cooling water were taken into account, which required CFD simulations of the cooling water flow in the turbulent regime. Here we present the methods and results of the sophisticated thermal and structural mechanical simulations using COMSOL and provide a comparison to more simplistic simulations conducted with CST Studio Suite.
Focused electron-beam-induced deposition (FEBID) is a highly versatile direct-write approach with particular strengths in the 3D nanofabrication of functional materials. Despite its apparent similarity to other 3D printing approaches, non-local effects related to precursor depletion, electron scattering and sample heating during the 3D growth process complicate the shape-true transfer from a target 3D model to the actual deposit. Here, we describe an efficient and fast numerical approach to simulate the growth process, which allows for a systematic study of the influence of the most important growth parameters on the resulting shape of the 3D structures. The precursor parameter set derived in this work for the precursor Me3PtCpMe enables a detailed replication of the experimentally fabricated nanostructure, taking beam-induced heating into account. The modular character of the simulation approach allows for additional future performance increases using parallelization or drawing on the use of graphics cards. Ultimately, beam-control pattern generation for 3D FEBID will profit from being routinely combined with this fast simulation approach for optimized shape transfer.
An optimized Bayesian hierarchical two-parameter logistic model for small-sample item calibration
(2019)
Accurate item calibration in models of item response theory (IRT) requires rather large samples. For instance, N > 500 respondents are typically recommended for the two-parameter logistic (2PL) model. Hence, this model is considered a large-scale application, and its use in small-sample contexts is limited. Hierarchical Bayesian approaches are frequently proposed to reduce the sample size requirements of the 2PL. This study compared the small-sample performance of an optimized Bayesian hierarchical 2PL (H2PL) model to its standard inverse Wishart specification, its nonhierarchical counterpart, and both unweighted and weighted least squares estimators (ULSMV and WLSMV) in terms of sampling efficiency and accuracy of estimation of the item parameters and their variance components. To alleviate shortcomings of hierarchical models, the optimized H2PL (a) was reparametrized to simplify the sampling process, (b) a strategy was used to separate item parameter covariances and their variance components, and (c) the variance components were given Cauchy and exponential hyperprior distributions. Results show that when combining these elements in the optimized H2PL, accurate item parameter estimates and trait scores are obtained even in sample sizes as small as N = 100. This indicates that the 2PL can also be applied to smaller sample sizes encountered in practice. The results of this study are discussed in the context of a recently proposed multiple imputation method to account for item calibration error in trait estimation.
This article is about creative writing in GFL-Lecture in Egypt. Writing as a skill is rarely considered in GFL- Lecture. Teachers pay attention to other skills such as reading, listening, or speaking, whereby writing is only considered receptively to promote speaking or grammar. This article is about trying to promote creative writing in GFL-Lecture and to offer new suggestions and tips. In a further step, this article deals with the presentation of some creative writing tasks that were carried out among the students of the third year at the language faculty (Al-Alsun) in Sohag. Finally, the conclusions are drawn, and results of creative writing shown.
Waldwachstumsmodelle sind ein ideales Werkzeug, um Auswirkungen veränderter Umweltbedingungen auf das Wachstum der Bäume aufzuzeigen. Ziel des Teilprojektes „Waldwachstumsreaktionen und Systemprozesse“ im Rahmen von ENFORCHANGE war, durch die Kombination von Wachstumsmodellen mit unterschiedlichen methodischen Ansätzen regionale Auswirkungen standörtlicher und klimatischer Veränderungen auf die Waldentwicklung zu analysieren und somit bessere Grundlagen für eine angepasste Forstbetriebsplanung zu schaffen. Anhand des physiologischen Wachstumsmodells BALANCE wurde der Einfluss der prognostizierten Klimaänderungen auf das Wachstum der Bäume abgeschätzt. Die für verschiedene Baumarten und regionaltypische Bestände gewonnenen Reaktionsmuster konnten anschließend in das managementorientierte Wachstumsmodell SILVA übertragen werden. Die Entwicklung repräsentativer Waldbestände wurde in SILVA für einen Zeitraum von 30 Jahren simuliert, wobei verschiedene Nutzungsszenarien untersucht wurden, um Handlungsspielräume und mögliche strategische Planungen für Forstbetriebe aufzuzeigen. Die gewonnenen Erkenntnisse für die praktische Betriebsplanung wurden am Beispiel des kommunalen Forstbetriebes Zittau dargestellt. Es wird deutlich, wie die Forstplanung von derartigen Szenarioanalysen profitieren kann. Die Simulationsrechnungen unter Annahme geänderter Klimaverhältnisse zeigen, dass die Bestände unter diesen Bedingungen ein verringertes Reaktionsvermögen auf waldbauliche Maßnahmen aufweisen, was insbesondere bei den Zuwächsen bemerkbar ist. Dabei haben Laubholzbestände, die bereits jetzt auf 27% der Betriebsfläche stocken, vermutlich eine Pufferwirkung und mildern die Auswirkungen der Klimaänderungen auf die Produktivität des Gesamtbetriebes ab.
Background: Transfusion of red blood cell concentrate can be life-saving, but requires accurate dose calculations in children. Aims: We tested the hypothesis that cognitive aids would improve identification of the correct recommended volumes and products, according to the German National Transfusion guidelines, in pediatric transfusion scenarios. Methods: Four online questionnaire-based scenarios, two with hemodynamically stable and two with hemodynamically unstable children, were sent to German and international pediatric anesthetists for completion. In the two stable scenarios, participants were given pre-filled tables that contained all required information. For the two emergency scenarios, existing algorithms were used and required calculation by the user. The results were classified into three categories of deviations from the recommended values (DRV): DRV120 (<80% or >120%), as the acceptable variation; DRV 300 (<33% or >300%), the deviation of concern for potential harm; and DRV 1000 (<10% or >1000%), the excessive deviation with a high probability of harm. Results: A total of 1.458 pediatric anesthetists accessed this simulation questionnaire, and 402 completed questionnaires were available for analysis. A pre-filled tabular aid, avoiding calculations, led to a reduction in deviation rates in the category of DRV120 by 60% for each and of DRV300 by 17% and 20%, respectively. The use of algorithms as aids for unstable emergencies led to a reduction in the deviation rate only for DRV120 (20% and 15% respectively). In contrast, the deviation rates for DRV300 and DRV1000 rose by 37% and 16%, respectively. Participants used higher transfusion thresholds for the emergency case of a 2-year-old compromised child than for the stable case with a patient of the same age (on average, 8.6 g/dL, 95% CI 8.5–8.8 versus 7.1 g/dL, 95% CI 7.0–7.2, p < 0.001) if not supported by our aids. Participants also used a higher transfusion threshold for unstable children aged 3 months than for stable children of the same age (on average, 8.9 g/dL, 95% CI 8.7–9.0 versus 7.9 g/dL, 95% CI 7.7–8.0, p < 0.001). Conclusions: The use of cognitive aids with precalculated transfusion volumes for determining transfusion doses in children may lead to improved adherence to published recommendations, and could potentially reduce dosing deviations outside those recommended by the German national transfusion guidelines.
The paper proposes a variation of simulation for checking and proving contextual equivalence in a non-deterministic call-by-need lambda-calculus with constructors, case, seq, and a letrec with cyclic dependencies. It also proposes a novel method to prove its correctness. The calculus' semantics is based on a small-step rewrite semantics and on may-convergence. The cyclic nature of letrec bindings, as well as non-determinism, makes known approaches to prove that simulation implies contextual equivalence, such as Howe's proof technique, inapplicable in this setting. The basic technique for the simulation as well as the correctness proof is called pre-evaluation, which computes a set of answers for every closed expression. If simulation succeeds in finite computation depth, then it is guaranteed to show contextual preorder of expressions.