Plasma polymerization of cyclopropylamine in a low-pressure cylindrical magnetron reactor: A PIC-MC study of the roles of ions and radicals

A study of plasma polymerization of cyclopropylamine in a low-pressure cylindrical magnetron reactor is presented. Both experimental and numerical approaches are used to investigate thin film growth mechanisms and polymer film properties depending on the magnetic field strength. Combining both approaches enables the consistency of the numerical model to be checked while acquiring data for understanding the observed phenomena. Samples are first analyzed by x-ray photoelectron spectroscopy, time of flight secondary ion mass spectrometry, and ion beam analysis to illustrate the differences in degrees of chemical functionalization and cross-linking between the regions of high and low magnetic fields. 3D particle-in-cell Monte Carlo collision simulations are then performed to shed light on experimental results, after implementing a set of electron-cyclopropylamine collision cross sections computed using the R-matrix method. The simulations enable the main radicals produced in the discharge to be tracked by determining their production rates, how they diffuse in the plasma, and how they absorb on the reactor walls. Additionally, the cyclopropylamine ion (C₃H₇N⁺) behavior is followed to bring insights into the respective roles of ions and radicals during the plasma polymerization process

Crystallisation Phenomena of In2O3:H Films

The crystallisation of sputter-deposited, amorphous In2O3:H films was investigated. The influence of deposition and crystallisation parameters onto crystallinity and electron hall mobility was explored. Significant precipitation of metallic indium was discovered in the crystallised films by electron energy loss spectroscopy. Melting of metallic indium at ~160 °C was suggested to promote primary crystallisation of the amorphous In2O3:H films. The presence of hydroxyl was ascribed to be responsible for the recrystallization and grain growth accompanying the inter-grain In-O-In bounding. Metallic indium was suggested to provide an excess of free electrons in as-deposited In2O3 and In2O3:H films. According to the ultraviolet photoelectron spectroscopy, the work function of In2O3:H increased during crystallisation from 4 eV to 4.4 eV, which corresponds to the oxidation process. Furthermore, transparency simultaneously increased in the infraredspectral region. Water was queried to oxidise metallic indium in UHV at higher temperature as compared to oxygen in ambient air. Secondary ion mass-spectroscopy results revealed that the former process takes place mostly within the top ~50 nm. The optical band gap of In2O3:H increased by about 0.2 eV during annealing, indicating a doping effect. This was considered as a likely intra-grain phenomenon caused by both (In0)O•• and (OH−)O• point defects. The inconsistencies in understanding of In2O3:H crystallisation, which existed in the literature so far, were considered and explained by the multiplicity and disequilibrium of the processes running simultaneously.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Correlation of structural and optical properties using virtual materials analysis

Thin film growth of TiO2 by physical vapor deposition processes is simulated in the Virtual Coater framework resulting in virtual thin films. The simulations are carried out for artificial, simplified deposition conditions as well as for conditions representing a real coating process. The study focuses on porous films which exhibit a significant anisotropy regarding the atomistic structure and consequently, to the index of refraction. A method how to determine the effective anisotropic index of refraction of virtual thin films by the effective medium theory is developed. The simulation applies both, classical molecular dynamics as well as kinetic Monte Carlo calculations, and finally the properties of the virtual films are compared to experimentally grown films especially analyzing the birefringence in the evaluation

Response to Therapeutic Sleep Deprivation: A Naturalistic Study of Clinical and Genetic Factors and Post-treatment Depressive Symptom Trajectory

Research has shown that therapeutic sleep deprivation (SD) has rapid antidepressant effects in the majority of depressed patients. Investigation of factors preceding and accompanying these effects may facilitate the identification of the underlying biological mechanisms. This exploratory study aimed to examine clinical and genetic factors predicting response to SD and determine the impact of SD on illness course. Mood during SD was also assessed via visual analogue scale. Depressed inpatients (n = 78) and healthy controls (n = 15) underwent ~36 h of SD. Response to SD was defined as a score of ≤ 2 on the Clinical Global Impression Scale for Global Improvement. Depressive symptom trajectories were evaluated for up to a month using self/expert ratings. Impact of genetic burden was calculated using polygenic risk scores for major depressive disorder. In total, 72% of patients responded to SD. Responders and non-responders did not differ in baseline self/expert depression symptom ratings, but mood differed. Response was associated with lower age (p = 0.007) and later age at life-time disease onset (p = 0.003). Higher genetic burden of depression was observed in non-responders than healthy controls. Up to a month post SD, depressive symptoms decreased in both patients groups, but more in responders, in whom effects were sustained. The present findings suggest that re-examining SD with a greater focus on biological mechanisms will lead to better understanding of mechanisms of depression

Analyzing multitarget activity landscapes using protein-ligand interaction fingerprints: interaction cliffs.

This is the original submitted version, before peer review. The final peer-reviewed version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/ci500721x.Activity landscape modeling is mostly a descriptive technique that allows rationalizing continuous and discontinuous SARs. Nevertheless, the interpretation of some landscape features, especially of activity cliffs, is not straightforward. As the nature of activity cliffs depends on the ligand and the target, information regarding both should be included in the analysis. A specific way to include this information is using protein-ligand interaction fingerprints (IFPs). In this paper we report the activity landscape modeling of 507 ligand-kinase complexes (from the KLIFS database) including IFP, which facilitates the analysis and interpretation of activity cliffs. Here we introduce the structure-activity-interaction similarity (SAIS) maps that incorporate information on ligand-target contact similarity. We also introduce the concept of interaction cliffs defined as ligand-target complexes with high structural and interaction similarity but have a large potency difference of the ligands. Moreover, the information retrieved regarding the specific interaction allowed the identification of activity cliff hot spots, which help to rationalize activity cliffs from the target point of view. In general, the information provided by IFPs provides a structure-based understanding of some activity landscape features. This paper shows examples of analyses that can be carried out when IFPs are added to the activity landscape model.M-L is very grateful to CONACyT (No. 217442/312933) and the Cambridge Overseas Trust for funding. AB thanks Unilever for funding and the European Research Council for a Starting Grant (ERC-2013- StG-336159 MIXTURE). J.L.M-F. is grateful to the School of Chemistry, Department of Pharmacy of the National Autonomous University of Mexico (UNAM) for support. This work was supported by a scholarship from the Secretariat of Public Education and the Mexican government

Automatic identification of variables in epidemiological datasets using logic regression

textabstractBackground: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies

Zwischen konzeptionellem Empowerment und gelebter Fremdbestimmung : zur Situation von Menschen mit psychischer Erkrankung in Sozialtherapeutischen Wohnstätten.

Die Bachelorarbeit befasst sich mit den Möglichkeiten der Umsetzung einer selbstbestimmten Lebensführung in Sozialtherapeutischen Wohnstätten für Menschen mit psychischer Erkrankung. Dabei werden sowohl das bestehende sozialpsychiatrische Hilfesystem, als auch eine Auswahl an theoretischen Konstrukten zum Themenkomplex Selbstbestimmung bearbeitet. Diese fachtheoretischen Erkenntnisse werden durch die Ergebnisse einer standardisierten Befragung an 83 Bewohnern Sozialtherapeutischer Wohnstätten ergänzt, um in der Gesamtheit einen multiperspektivischen Blick auf das Themengebiet zu gewähren. Die Verknüpfung theoretischer Aspekte mit eigenen praktischen Erfahrungen und Sichtweisen der Adressaten, soll dabei eine Handreichung sein, um vorhandene Strukturen in Sozialtherapeutischen Wohnstätten weiter zu verbessern

Dissertatio Inauguralis Medica De Glandulis Corporis Humani

Quam ... Publice Defendet Andreas Gotthardus Fridericus Pflug Wetzlariensis ... Die XXVI Martii MDCCLXXXVIIAutopsie nach Ex. der ULB DüsseldorfVorlageform der Veröffentlichungsangabe: Duisburgi ad Rhenum, Stanno Viduae Benthonianae Acad. Typogr.Universität Duisburg, Dissertation, 26. März 178

Asymptotically Optimal Allocation of Simulation Experiments in Discrete Stochastic Optimization

Approximate solutions for discrete stochastic optimization problems are often obtained via simulation. It is reasonable to complement these solutions by confidence regions for the argmin-set. We address the question, how a certain total number of random draws should be distributed among the set of alternatives. We propose a one-step allocation rule which turns out to be asymptotically optimal in the case of normal errors for two goals: To minimize the costs caused by using only an approximate solution and to minimize the expected size of the confidence sets