Klassische und ab initio Molekulardynamik-Untersuchungen zu Germaniumdioxidschmelzen

Germaniumdioxid (GeO2) ist ein Glasbildner, der wie das homologe SiO2 ein ungeordnetes tetraedrisches Netzwerk ausbildet. In dieser Arbeit werden mit Hilfe von Molekulardynamik-Computersimulationen die Struktur und Dynamik von GeO2 in Abhängigkeit von der Temperatur untersucht. Dazu werden sowohl Simulationen mit einem klassischen Paarpotentialmodell von Oeffner und Elliott als auch ab initio-Simulationen gemäß der Car-Parrinello-Molekulardynamik (CPMD), bei der elektronische Freiheitsgrade mittels Dichtefunktionaltheorie beschrieben werden, durchgeführt. In der klassischen Simulation werden dazu ein Temperaturen zwischen 6100 K und 2530 K betrachtet. Darüberhinaus ermöglichen Abkühlläufe auf T=300 K das Studium der Struktur des Glases. Zum Vergleich werden CPMD-Simulationen für kleinere Systeme mit 60 bzw. 120 Teilchen bei den Temperaturen 3760 K und 3000 K durchgeführt. In den klassischen Simulationen kann die im Experiment bis 1700 K nachgewiesene, im Vergleich zu SiO2 starke, Temperaturabhängigkeit der Dichte auch bei höheren Temperaturen beobachtet werden. Gute Übereinstimmungen der Simulationen mit experimentellen Daten zeigen sich bei der Untersuchung verschiedener struktureller Größen, wie z.B. Paarkorrelationsfunktionen, Winkelverteilungen, Koordinationszahlen und Strukturfaktoren. Es können leichte strukturelle Abweichungen der CPMD-Simulationen von den klassischen Simulationen aufgezeigt werden: 1. Die Paarabstände in CPMD sind durchweg etwas kleiner. 2. Es zeigt sich, daß die Bindungen in den ab initio-Simulationen weicher sind, was sich auch in einer etwas stärkeren Temperaturabhängigkeit der strukturellen Größen im Vergleich zu den klassischen Simulationen niederschlägt. 3. Für CPMD kann ein vermehrtes Auftreten von Dreierringstrukturen gezeigt werden. 4. In der CPMD werden temperaturabhängige Defektstrukturen in Form von Sauerstoffpaaren beobachtet, die vor allem bei 3760 K, kaum jedoch bei 3000 K auftreten. Alle strukturellen Unterschiede zwischen klassischer und CPMD-Simulation sind eindeutig nicht auf Finite-Size-Effekte aufgrund der kleinen Systemgrößen in den CPMD-Simulationen zurückzuführen, d.h. sie sind tatsächlich methodisch bedingt. Bei der Dynamik von GeO2 wird in den klassischen Simulationen ebenfalls eine gute Übereinstimmung mit experimentellen Daten beobachtet, was ein Vergleich der Diffusionskonstanten mit Viskositätsmessungen bei hohen Temperaturen belegt. Die Diffusionskonstanten zeigen teilweise ein verschiedenes Verhalten zum homologen SiO2. Sie folgen in GeO2 bei Temperaturen unter 3000 K einem Arrheniusgesetz mit einer deutlich niedrigeren Aktivierungsenergie. Darüberhinaus werden die Möglichkeiten der Parametrisierung eines neuen klassischen Paarpotentials mittels der Kräfte entlang der CPMD-Trajektorien untersucht. Es zeigt sich, daß derartige Parametrisierungen sehr stark von den gewählten Startparametern abhängen. Ferner führen sämtliche an die Schmelze parametrisierten Potentiale zu zu hohen Dichten im Vergleich zum Experiment. Zum einen liegt dies sehr wahrscheinlich daran,daß für das System GeO2 Kraftdaten allein nicht ausreichen, um grundlegende strukturelle Größen, wie z.B. Paarkorrelationen und Winkelverteilungen, der CPMD-Simulationen gut reproduzieren zu können. Zum anderen ist wohl die Beschreibung mittels Paarpotentialen nicht ausreichend und es ist erforderlich, Merkörperwechselwirkungen in Betracht zu ziehen.

Longitudinal evolution of cognitive functions in patients with multiple system atrophy: a prospective study

Introduction and Background: Multiple system atrophy (MSA) is a sporadic, adult-onset, progressive neurodegenerative disease characterized clinically by parkinsonism, cerebellar ataxia, and autonomic failure. We investigated cognitive functions longitudinally in a group of probable MSA patients, matching data with sleep parameters. Patients and Methods: 10 patients (7m/3f) underwent a detailed interview, a general and neurological examination, laboratory exams, MRI scans, a cardiovascular reflexes study, a battery of neuropsychological tests, and video-polysomnographic recording (VPSG). Patients were revaluated (T1) a mean of 16±5 (range: 12-28) months after the initial evaluation (T0). At T1, the neuropsychological assessment and VPSG were repeated. Results: The mean patient age was 57.8±6.4 years (range: 47-64) with a mean age at disease onset of 53.2±7.1 years (range: 43-61) and symptoms duration at T0 of 60±48 months (range: 12-144). At T0, 7 patients showed no cognitive deficits while 3 patients showed isolated cognitive deficits. At T1, 1 patient worsened developing multiple cognitive deficits from a normal condition. At T0 and T1, sleep efficiency was reduced, REM latency increased, NREM sleep stages 1-2 slightly increased. Comparisons between T1 and T0 showed a significant worsening in two tests of attention and no significant differences of VPSG parameters. No correlation was found between neuropsychological results and VPSG findings or RBD duration. Discussion and Conclusions: The majority of our patients do not show any cognitive deficits at T0 and T1, while isolated cognitive deficits are present in the remaining patients. Attention is the cognitive function which significantly worsened. Our data confirm the previous findings concerning the prevalence, type and the evolution of cognitive deficits in MSA. Regarding the developing of a condition of dementia, our data did not show a clear-cut diagnosis of dementia. We confirm a mild alteration of sleep structure. RBD duration does not correlate with neuropsychological findings.

Mode-coupling theory: generalizations, high dimensions and microscopic dynamics

This work contains several applications of the mode-coupling theory (MCT) and is separated into three parts. In the first part we investigate the liquid-glass transition of hard spheres for dimensions d→∞ analytically and numerically up to d=800 in the framework of MCT. We find that the critical packing fraction ϕc(d) scales as d²2^(-d), which is larger than the Kauzmann packing fraction ϕK(d) found by a small-cage expansion by Parisi and Zamponi [J. Stat. Mech.: Theory Exp. 2006, P03017 (2006)]. The scaling of the critical packing fraction is different from the relation ϕc(d)∼d2^(-d) found earlier by Kirkpatrick and Wolynes [Phys. Rev. A 35, 3072 (1987)]. This is due to the fact that the k dependence of the critical collective and self nonergodicity parameters fc(k;d) and fcs(k;d) was assumed to be Gaussian in the previous theories. We show that in MCT this is not the case. Instead fc(k;d) and fcs(k;d), which become identical in the limit d→∞, converge to a non-Gaussian master function on the scale k∼d^(3/2). We find that the numerically determined value for the exponent parameter λ and therefore also the critical exponents a and b depend on the dimension d, even at the largest evaluated dimension d=800. In the second part we compare the results of a molecular-dynamics simulation of liquid Lennard-Jones argon far away from the glass transition [D. Levesque, L. Verlet, and J. Kurkijärvi, Phys. Rev. A 7, 1690 (1973)] with MCT. We show that the agreement between theory and computer simulation can be improved by taking binary collisions into account [L. Sjögren, Phys. Rev. A 22, 2866 (1980)]. We find that an empiric prefactor of the memory function of the original MCT equations leads to similar results. In the third part we derive the equations for a mode-coupling theory for the spherical components of the stress tensor. Unfortunately it turns out that they are too complex to be solved numerically.

Computer simulations of two-dimensional colloidal crystals under confinement and shear

In this thesis we are presenting a broadly based computer simulation study of two-dimensional colloidal crystals under different external conditions. In order to fully understand the phenomena which occur when the system is being compressed or when the walls are being sheared, it proved necessary to study also the basic motion of the particles and the diffusion processes which occur in the case without these external forces. In the first part of this thesis we investigate the structural transition in the number of rows which occurs when the crystal is being compressed by placing the structured walls closer together. Previous attempts to locate this transition were impeded by huge hysteresis effects. We were able to determine the transition point with higher precision by applying both the Schmid-Schilling thermodynamic integration method and the phase switch Monte Carlo method in order to determine the free energies. These simulations showed not only that the phase switch method can successfully be applied to systems with a few thousand particles and a soft crystalline structure with a superimposed pattern of defects, but also that this method is way more efficient than a thermodynamic integration when free energy differences are to be calculated. Additionally, the phase switch method enabled us to distinguish between several energetically very similar structures and to determine which one of them was actually stable. Another aspect considered in the first result chapter of this thesis is the ensemble inequivalence which can be observed when the structural transition is studied in the NpT and in the NVT ensemble. The second part of this work deals with the basic motion occurring in colloidal crystals confined by structured walls. Several cases are compared where the walls are placed in different positions, thereby introducing an incommensurability into the crystalline structure. Also the movement of the solitons, which are created in the course of the structural transition, is investigated. Furthermore, we will present results showing that not only the well-known mechanism of vacancies and interstitial particles leads to diffusion in our model system, but that also cooperative ring rotation phenomena occur. In this part and the following we applied Langevin dynamics simulations. In the last chapter of this work we will present results on the effect of shear on the colloidal crystal. The shear was implemented by moving the walls with constant velocity. We have observed shear banding and, depending on the shear velocity, that the inner part of the crystal breaks into several domains with different orientations. At very high shear velocities holes are created in the structure, which originate close to the walls, but also diffuse into the inner part of the crystal.

Numerical analysis of the relation between interactions and structure in a molecular fluid

Coarse graining is a popular technique used in physics to speed up the computer simulation of molecular fluids. An essential part of this technique is a method that solves the inverse problem of determining the interaction potential or its parameters from the given structural data. Due to discrepancies between model and reality, the potential is not unique, such that stability of such method and its convergence to a meaningful solution are issues.rnrnIn this work, we investigate empirically whether coarse graining can be improved by applying the theory of inverse problems from applied mathematics. In particular, we use the singular value analysis to reveal the weak interaction parameters, that have a negligible influence on the structure of the fluid and which cause non-uniqueness of the solution. Further, we apply a regularizing Levenberg-Marquardt method, which is stable against the mentioned discrepancies. Then, we compare it to the existing physical methods - the Iterative Boltzmann Inversion and the Inverse Monte Carlo method, which are fast and well adapted to the problem, but sometimes have convergence problems.rnrnFrom analysis of the Iterative Boltzmann Inversion, we elaborate a meaningful approximation of the structure and use it to derive a modification of the Levenberg-Marquardt method. We engage the latter for reconstruction of the interaction parameters from experimental data for liquid argon and nitrogen. We show that the modified method is stable, convergent and fast. Further, the singular value analysis of the structure and its approximation allows to determine the crucial interaction parameters, that is, to simplify the modeling of interactions. Therefore, our results build a rigorous bridge between the inverse problem from physics and the powerful solution tools from mathematics. rn

Subjective cognitive complaints one year after ceasing adjuvant endocrine treatment for early-stage breast cancer

Background:In the BIG 1-98 trial objective cognitive function improved in postmenopausal women 1 year after cessation of adjuvant endocrine therapy for breast cancer. This report evaluates changes in subjective cognitive function (SCF).Methods:One hundred postmenopausal women, randomised to receive 5 years of adjuvant tamoxifen, letrozole, or a sequence of the two, completed self-reported measures on SCF, psychological distress, fatigue, and quality of life during the fifth year of trial treatment (year 5) and 1 year after treatment completion (year 6). Changes between years 5 and 6 were evaluated using the Wilcoxon signed-rank test. Subjective cognitive function and its correlates were explored.Results:Subjective cognitive function and the other patient-reported outcomes did not change significantly after cessation of endocrine therapy with the exception of improvement for hot flushes (P=0.0005). No difference in changes was found between women taking tamoxifen or letrozole. Subjective cognitive function was the only psychosocial outcome with a substantial correlation between year 5 and 6 (Spearman's R=0.80). Correlations between SCF and the other patient-reported outcomes were generally low.Conclusion:Improved objective cognitive function but not SCF occur following cessation of adjuvant endocrine therapy in the BIG 1-98 trial. The substantial correlation of SCF scores over time may represent a stable attribute.British Journal of Cancer advance online publication, 24 April 2012; doi:10.1038/bjc.2012.156 www.bjcancer.com.

A Framework for the Automation of Discrete-Event Simulation Experiments

Simulation is an important resource for researchers in diverse fields. However, many researchers have found flaws in the methodology of published simulation studies and have described the state of the simulation community as being in a crisis of credibility. This work describes the project of the Simulation Automation Framework for Experiments (SAFE), which addresses the issues that undermine credibility by automating the workflow in the execution of simulation studies. Automation reduces the number of opportunities for users to introduce error in the scientific process thereby improvingthe credibility of the final results. Automation also eases the job of simulation users and allows them to focus on the design of models and the analysis of results rather than on the complexities of the workflow.

Simulation of titration experiments

Nowadays computer simulation is used in various fields, particularly in laboratories where it is used for the exploration data which are sometimes experimentally inaccessible. In less developed countries where there is a need for up to date laboratories for the realization of practical lessons in chemistry, especially in secondary schools and some higher institutions of learning, it may permit learners to carryout experiments such as titrations without the use of laboratory materials and equipments. Computer simulations may also permit teachers to better explain the realities of practical lessons, given that computers have now become very accessible and less expensive compared to the acquisition of laboratory materials and equipments. This work is aimed at coming out with a virtual laboratory that shall permit the simulation of an acid-base titration and an oxidation-reduction titration with the use of synthetic images. To this effect, an appropriate numerical method was used to obtain appropriate organigram, which were further transcribed into source codes with the help of a programming language so as to come out with the software.

ITP in dynamically double-coated fused-silica capillaries

Bidirectional ITP in fused-silica capillaries double-coated with Polybrene and poly-(vinylsulfonate) is a robust approach for analysis of low-molecular-mass compounds. EOF towards the cathode is strong (mobility >4.0 x 10(-8) m(2)/Vs) within the entire pH range investigated (2.40-8.08), dependent on ionic strength and buffer used and, at constant ionic strength, higher at alkaline pH. Electrokinetic separations and transport in such coated capillaries can be described with a dynamic computer model which permits the combined simulation of electrophoresis and electroosmosis in which the EOF is predicted either with a constant (i.e. pH- and ionic strength-independent) or a pH- and ionic strength-dependent electroosmotic mobility. Detector profiles predicted by computer simulation agree qualitatively well with bidirectional isotachopherograms that are monitored with a setup comprising two axial contactless conductivity detectors and a UV absorbance detector. The varying EOF predicted with a pH- and ionic strength-dependent electroosmotic mobility can be regarded as being realistic.

High-resolution computer simulations of stacking of weak bases using a transient pH boundary in capillary electrophoresis. 1. Concept and impact of sample ionic strength

The dynamics of focusing weak bases using a transient pH boundary was examined via high-resolution computer simulation software. Emphasis was placed on the mechanism and impact that the presence of salt, namely, NaCl, has on the ability to focus weak bases. A series of weak bases with mobilities ranging from 5 x 10(-9) to 30 x 10(-9) m2/V x s and pKa values between 3.0 and 7.5 were examined using a combination of 65.6 mM formic acid, pH 2.85, for the separation electrolyte, and 65.6 mM formic acid, pH 8.60, for the sample matrix. Simulation data show that it is possible to focus weak bases with a pKa value similar to that of the separation electrolyte, but it is restricted to weak bases having an electrophoretic mobility of 20 x 10(-9) m2/V x s or quicker. This mobility range can be extended by the addition of NaCl, with 50 mM NaCl allowing stacking of weak bases down to a mobility of 15 x 10(-9) m2/V x s and 100 mM extending the range to 10 x 10(-9) m2/V x s. The addition of NaCl does not adversely influence focusing of more mobile bases, but does prolong the existence of the transient pH boundary. This allows analytes to migrate extensively through the capillary as a single focused band around the transient pH boundary until the boundary is dissipated. This reduces the length of capillary that is available for separation and, in extreme cases, causes multiple analytes to be detected as a single highly efficient peak.

Taking an Object-Centric View on Dynamic Information with Object Flow Analysis

A large body of research analyzes the runtime execution of a system to extract abstract behavioral views. Those approaches primarily analyze control flow by tracing method execution events or they analyze object graphs of heap snapshots. However, they do not capture how objects are passed through the system at runtime. We refer to the exchange of objects as the object flow, and we claim that object flow is necessary to analyze if we are to understand the runtime of an object-oriented application. We propose and detail Object Flow Analysis, a novel dynamic analysis technique that takes this new information into account. To evaluate its usefulness, we present a visual approach that allows a developer to study classes and components in terms of how they exchange objects at runtime. We illustrate our approach on three case studies.

Transfer Functions in Artificial Neural Networks - A Simulation-Based Tutorial

Artificial neural networks are based on computational units that resemble basic information processing properties of biological neurons in an abstract and simplified manner. Generally, these formal neurons model an input-output behaviour as it is also often used to characterize biological neurons. The neuron is treated as a black box; spatial extension and temporal dynamics present in biological neurons are most often neglected. Even though artificial neurons are simplified, they can show a variety of input-output relations, depending on the transfer functions they apply. This unit on transfer functions provides an overview of different transfer functions and offers a simulation that visualizes the input-output behaviour of an artificial neuron depending on the specific combination of transfer functions.

Realistic Single Cell Modeling – from Experiment to Simulation

This tutorial gives a step by step explanation of how one uses experimental data to construct a biologically realistic multicompartmental model. Special emphasis is given on the many ways that this process can be imprecise. The tutorial is intended for both experimentalists who want to get into computer modeling and for computer scientists who use abstract neural network models but are curious about biological realistic modeling. The tutorial is not dependent on the use of a specific simulation engine, but rather covers the kind of data needed for constructing a model, how they are used, and potential pitfalls in the process.

Modeling Calcium Concentration and Biochemical Reactions

Almost all regions of the brain receive one or more neuromodulatory inputs, and disrupting these inputs produces deficits in neuronal function. Neuromodulators act through intracellular second messenger pathways to influence the electrical properties of neurons, integration of synaptic inputs, spatio-temporal firing dynamics of neuronal networks, and, ultimately, systems behavior. Second messengers pathways consist of series of bimolecular reactions, enzymatic reactions, and diffusion. Calcium is the second messenger molecule with the most effectors, and thus is highly regulated by buffers, pumps and intracellular stores. Computational modeling provides an innovative, yet practical method to evaluate the spatial extent, time course and interaction among second messenger pathways, and the interaction of second messengers with neuron electrical properties. These processes occur both in compartments where the number of molecules are large enough to describe reactions deterministically (e.g. cell body), and in compartments where the number of molecules is small enough that reactions occur stochastically (e.g. spines). – In this tutorial, I explain how to develop models of second messenger pathways and calcium dynamics. The first part of the tutorial explains the equations used to model bimolecular reactions, enzyme reactions, calcium release channels, calcium pumps and diffusion. The second part explains some of the GENESIS, Kinetikit and Chemesis objects that implement the appropriate equations. In depth explanation of calcium and second messenger models is provided by reviewing code, both in XPP, Chemesis and Kinetikit, that implements simple models of calcium dynamics and second messenger cascades.

The art to keep in touch: The ''good use'' of Lagrange multipliers

Physically-based modeling for computer animation allows to produce more realistic motions in less time without requiring the expertise of skilled animators. But, a computer animation is not only a numerical simulation based on classical mechanics since it follows a precise story-line. One common way to define aims in an animation is to add geometric constraints. There are several methods to manage these constraints within a physically-based framework. In this paper, we present an algorithm for constraints handling based on Lagrange multipliers. After few remarks on the equations of motion that we use, we present a first algorithm proposed by Platt. We show with a simple example that this method is not reliable. Our contribution consists in improving this algorithm to provide an efficient and robust method to handle simultaneous active constraints.