The purpose of the work is to employ molecular simulation to further extend the understanding of Self-Assembled Monolayers (SAMs), especially as it relates to three particular applications: organic-inorganic composite membranes, surface treatments in Micro-Electro-Mechanical Systems (MEMS) and organic-surface-modified Ordered Mesoporous Materials (OMMs). The first focus area for the work is the use of SAMS in organic-inorganic composite membranes for gas separations. These composite membranes, recently proposed in the literature, are based on the chemical derivatization of porous inorganic surfaces with organic oligomers. Our simulations achieve good qualitative agreement with experiment in several respects, including the improvement in the overall selectivity of the membrane and decrease in the permeance when increasing the chain length. The best improvement in the overall solubility selectivity is reached when the chains span throughout the pore. The second application focus is on the use of SAMs as coatings in MEMS devices. The work focuses on the modeling of adhesion issues for SAM coatings at the molecular level. It is shown that as the chain length is increased from 4 to 18 carbon atoms, the adhesion forces between two monolayers at the same separations decreases. The third application focus is on the use of SAMs for tailoring surface and structural properties of OMMs, in particular, porous silicas. A molecular study of structural and surface properties of a silica material with a 5 nm pore size, modified via chemical bonding of organosilanes with a range of sizes (C4, C8 and C18) is presented. Grand canonical MC simulations are employed to obtain nitrogen adsorption isotherms for unmodified and modified MCM-41 material models. Furthermore, the density profiles of alkyl chains and nitrogen molecules are analyzed to clarify the differences in the adsorption mechanisms in unmodified and modified materials. The position of the capillary condensation steps gradually shifted to lower pressure values with the increase in size of the bonded ligands, and this shift was accompanied by a gradual disappearance of the hysteresis loop. As the length of the bonded ligands is increased, a systematic decrease in the pore diameter is observed and the multi-layer adsorption mechanism in modified model materials diminishes.

Modern data collection methods are now frequently returning observations that should be viewed as the result of digitized recording or sampling from stochastic processes rather than vectors of finite length. In spite of great demands, only a few classification methodologies for such data have been suggested and supporting theory is quite limited. The focus of this dissertation is on discrimination and classification in this infinite dimensional setting. The methodology and theory we develop are based on the abstract canonical correlation concept of Eubank and Hsing (2005), and motivated by the fact that Fisher's discriminant analysis method is intimately tied to canonical correlation analysis. Specifically, we have developed a theoretical framework for discrimination and classification of sample paths from stochastic processes through use of the Loeve-Parzen isomorphism that connects a second order process to the reproducing kernel Hilbert space generated by its covariance kernel. This approach provides a seamless transition between the finite and infinite dimensional settings and lends itself well to computation via smoothing and regularization. In addition, we have developed a new computational procedure and illustrated it with simulated data and Canadian weather data.

Metal--organic frameworks (MOFs) are porous crystalline materials that are synthesized from rigid organic ligands and metal-containing clusters. They are highly tunable as a number of different structures can be made by simply changing the organic ligand and/or metal ion. MOFs are a promising class of materials for many energy-related applications, including H2 storage and CO2 capture and sequestration. Computational studies can provide insights into MOFs and the mechanism of gas sorption and separation. Theoretical studies on existing MOFs are performed to determine what structural characteristics leads to favorable gas sorption mechanisms. The results from these studies can provide insights into designing new MOFs that are tailored for specific applications. In this work, grand canonical Monte Carlo (GCMC) simulations were performed in various MOFs to understand the gas sorption mechanisms and identify the favorable sorption sites in the respective materials. Experimental observables such as sorption isotherms and associated isosteric heat of adsorption, Qst, values can be generated using this method. Outstanding agreement with experimental measurements engenders confidence in a variety of molecular level predictions. Explicit many-body polarization effects were shown to be important for the modeling of gas sorption in highly charged/polar MOFs that contain open-metal sites. Indeed, this was demonstrated through a series of simulation studies in various MOFs with rht topology that contain such sites. Specifically, the inclusion of many-body polarization interactions was essential to reproduce the experimentally observed sorption isotherms and Qst values and capture the binding of sorbate molecules onto the open-metal sites in these MOFs. This work also presents computational studies on a family of pillared square grid that are water-stable and display high CO2 sorption and selectivity. These MOFs are deemed promising for industrial applications and CO2 separations. Simulations in these materials revealed favorable interactions between the CO2 molecules and the SiF62- pillars. Further, the compound with the smallest pore size exhibits the highest selectivity for CO2 as demonstrated through both experimental and theoretical studies. Many other MOFs with intriguing sorption properties are investigated in this work and their sorption mechanisms have been discerned through molecular simulation.

Pharmaceutical biotechnology has been emerging as a defined, increasingly important area of science dedicated to the discovery and delivery of drugs and therapies for the treatment of various human diseases. In contrast to the advancement in pharmaceutical biotechnology, current drug discovery efforts are facing unprecedented challenges. Difficulties in identifying novel drug targets and developing effective and safe drugs are closely related to the complexity of the network of interacting human proteins. Protein-protein interactions mediate virtually all cellular processes. Therefore both identification and understanding of protein-protein interactions are essential to the process of deciphering disease mechanisms and developing treatments. Unfortunately, our current knowledge and understanding of the human interactome is largely incomplete. Most of the unknown protein-protein interactions are expected to be weak and/or transient, hence are not easily identified. These unknown or uncharacterized interactions could affect the efficacy and toxicity of drug candidates, contributing to the high rate of failure. In an attempt to facilitate the ongoing efforts in drug discovery, we describe herein a series of novel methods and their applications addressing the broad topic of protein-protein interactions. We have developed a highly efficient site-specific protein cross-linking technology mediated by the genetically incorporated non-canonical amino acid L-DOPA to facilitate the identification and characterization of weak protein-protein interactions. We also established a protocol to incorporate L-DOPA into proteins in mammalian cells to enable in vivo site-specific protein cross-kinking. We then applied the DOPA-mediated cross-linking methodology to design a protein probe which can potentially serve as a diagnostic tool or a modulator of protein-protein interactions in vivo. To deliver such engineered proteins or other bioanalytical reagents into single live cells, we established a laser-assisted cellular nano-surgery protocol which would enable detailed observations of cell-to-cell variability and communication. Finally we investigated a possible experimental scheme to genetically evolve a fluorescent peptide, which has tremendous potential as a tool in cellular imaging and dynamic observation of protein-protein interactions in vivo. We aim to contribute to the discovery and development of new drugs and eventually to the overall health of our society by adding the technology above to the array of currently available bioanalytical tools. / text

Šiame darbe nagrinėjama objektinių ir reliacinių schemų integruojamumo ir suderinamumo problema. Programinei įrangai kurti šiuo metu populiariausios objektinės programavimo kalbos, tačiau duomenys, kuriais manipuliuojama, dažniausiai saugojami reliacinėse duomenų bazėse, todėl aktualu programuojant naudojamas struktūras susieti su reliacinės duomenų bazės struktūromis. Organizacijų informacijų sistemose duomenys dažnai yra saugojami keliose duomenų saugyklose, yra poreikis integruoti įvairiose saugyklose esančius duomenis. Tam tikslui naudojamos federacinės duomenų bazės, besiremiančios kanoniniu duomenų modeliu. Šiame darbe aprašomas objektinių ir reliacinių schemų integracijos modelis. Pasiūlytas skurdus kanoninis duomenų modelis, kurį sudaro atributai ir apribojimai: funkcinės, jungimo/projekcijos ir poaibio priklausomybės. Aprašytos transformacijos iš reliacinių ir objektinių schemų į kanoninę schemą, algoritmas kanoninėms schemoms integruoti, kanoninės schemos transformacija į struktūrinius tipus, naudojant modifikuotą sintezės algoritmą, ir OWL. Aprašyti algoritmai leidžia pasiekti vienareikšmiškumą ir iš dalies automatizuotumą. Modifikuotas sintezės algoritmas duoda geresnius rezultatus nei standartinis, nes įvertina jungimo/projekcijos priklausomybes. Pasiūlyti algoritmai gali būti naudojami integracijai, norint atkurti konceptualiąją schemą ar objektines struktūras iš reliacinės schemos. / In this work the problem of integration and compatibility of relational and object schemas is investigated. Nowadays object-oriented programming languages are the most popular, but data that has to be manipulated is usually stored in relational databases. It is relevant to map structures that are used in programming languages to relational structures. Data is usually stored in several repositories in enterprise information systems, so there is the need to integrate them. Federated databases are used for this purpose, and they have canonical data model. Semantically poor canonical data model, which consists of attributes and constraints (functional, join and subset dependencies), is proposed. Algorithms are given for transforming relational and object schemas to canonical schema, integrating canonical schemas, transforming canonical schema to structural types (using modified synthesis algorithm) and OWL. Proposed algorithms give unambiguous result and can be partially automated. Modified synthesis algorithm gives better results than standard algorithm as it takes join dependencies into account. The algorithms can be used to restore conceptual schema and object structures from relational schema as well as to integrate schemas.

No description available.

Some branches of quantum gravity demand the existence of higher dimensions and the addition of higher curvature terms to the gravitational Lagrangian in the form of the Lovelock polynomials. In this thesis we investigate some of the classical properties of Lovelock gravity. We first derive the Hamiltonian for Lovelock gravity and find that it takes the same form as in general relativity when written in terms of the Misner-Sharp mass function. We then minimally couple the action to matter fields to find Hamilton’s equations of motion. These are gauge fixed to be in the Painleve-Gullstrand co–ordinates and are well suited to numerical studies of black hole formation. We then use these equations of motion for the massless scalar field to study the formation of general relativistic black holes in four to eight dimensions and Einstein-Gauss-Bonnet black holes in five and six dimensions. We study Choptuik scaling, a phenomenon which relates the initial conditions of a matter distribution to the final observables of small black holes. In both higher dimensional general relativity and Einstein-Gauss-Bonnet gravity we confirm the existence of cusps in the mass scaling relation which had previously only been observed in four dimensional general relativity. In the general relativistic case we then calculate the critical exponents for four to eight dimensions and find agreement with previous calculations by Bland et al but not Sorkin et al who both worked in null co–ordinates. For the Einstein-Gauss-Bonnet case we find that the self-similar behaviour seen in the general relativistic case is destroyed. We find that it is replaced by some other form of scaling structure. In five dimensions we find that the period of the critical solution at the origin is proportional to roughly the cube root of the Gauss-Bonnet parameter and that there is evidence for a minimum black hole radius. In six dimensions we see evidence for a new type of scaling. We also show, from the equations of motion, that there is reason to expect qualitative differences between five and higher dimensions.

Carbonaceous engine deposits tend to accumulate on most of the inner surfaces of the car engine. The presence of these deposits leads to a deteriorated efficiency of the engine and a number of adverse effects, such as higher propensity of the engine to knock. It has been proposed that selective adsorption of some of the fuel components in the porous deposits (and changing composition of the pre-combustion fuel) could be a contributing mechanism of the diminished efficiency of the engine. This, as well as other mechanisms of the deposits action, crucially depend on the porous structure of the material. Therefore, the aim of this investigation is to develop a method, which is able to accurately characterize the internal porous structure of the engine deposits and predict their adsorption properties at different conditions. This should allow us to assess whether the selective adsorption of fuel components is indeed a plausible contributing mechanism to the diminished performance of the engine. Accurate characterization of the engine deposits faces several difficulties due to their complex porous structure and chemical composition. A widely adopted approach in the characterization of activated carbons, which combines molecular simulation, specifically grand canonical Monte Carlo (GCMC) in slit pores, and experimental adsorption isotherms, is the starting point for the method suggested in this work. In this thesis, we will demonstrate that, by systematic modification of the solid-fluid interaction in the molecular simulation, we are able to correctly account for the chemical structural heterogeneity of the samples used. The new parameters of solid-fluid interaction allow us to extract representative pore size distributions and investigate the adsorption properties under different conditions of temperature and pressure, based on the obtained pore size distribution. Specifically, using the experimental data from a single ethane isotherm at 278K we accurately predict ethane adsorption at other temperatures and in different samples. Additionally, the proposed method is able to predict the adsorption of more complex hydrocarbons, i.e. n-butane and isobutane. The performance of the method is assessed by comparing the simulations results with the experimental adsorption measurements data on the engine deposits samples. Another important capability of the method is that it enables us to generate adsorption predictions of two key components commonly used to represent the combustion properties of the fuel, n-heptane and isooctane. We explore the equilibrium adsorption properties of these components based on the determined pore size distributions of the deposit samples. The results presented in the thesis highlight the importance of the adsorption in the internal porous structure of the engine deposits. The present study reinforces the value of molecular simulation combined with a limited number of experimental measurements, to accurately characterize heterogeneous carbonaceous materials and to make predictions at different conditions with sufficient precision.

Some branches of quantum gravity demand the existence of higher dimensions and the addition of higher curvature terms to the gravitational Lagrangian in the form of the Lovelock polynomials. In this thesis we investigate some of the classical properties of Lovelock gravity. We first derive the Hamiltonian for Lovelock gravity and find that it takes the same form as in general relativity when written in terms of the Misner-Sharp mass function. We then minimally couple the action to matter fields to find Hamilton’s equations of motion. These are gauge fixed to be in the Painleve-Gullstrand co–ordinates and are well suited to numerical studies of black hole formation. We then use these equations of motion for the massless scalar field to study the formation of general relativistic black holes in four to eight dimensions and Einstein-Gauss-Bonnet black holes in five and six dimensions. We study Choptuik scaling, a phenomenon which relates the initial conditions of a matter distribution to the final observables of small black holes. In both higher dimensional general relativity and Einstein-Gauss-Bonnet gravity we confirm the existence of cusps in the mass scaling relation which had previously only been observed in four dimensional general relativity. In the general relativistic case we then calculate the critical exponents for four to eight dimensions and find agreement with previous calculations by Bland et al but not Sorkin et al who both worked in null co–ordinates. For the Einstein-Gauss-Bonnet case we find that the self-similar behaviour seen in the general relativistic case is destroyed. We find that it is replaced by some other form of scaling structure. In five dimensions we find that the period of the critical solution at the origin is proportional to roughly the cube root of the Gauss-Bonnet parameter and that there is evidence for a minimum black hole radius. In six dimensions we see evidence for a new type of scaling. We also show, from the equations of motion, that there is reason to expect qualitative differences between five and higher dimensions.

Gegenstand dieser Arbeit sind sog. nicht-kanonische bzw. unintegrierte Nebensätze. Diese Nebensätze zeichnen sich dadurch aus, dass sie sich mittels gängiger Kriterien (Satzgliedstatus, Verbletztstellung) nicht klar als koordiniert oder subordiniert beschreiben lassen. Das Phänomen nicht-kanonischer Nebensätze ist ein Thema, welches in der Sprachwissenschaft generell seit den späten Siebzigern (Davison 1979) diskutiert wird und spätestens mit Fabricius-Hansen (1992) auch innerhalb der germanistischen Linguistik angekommen ist. Ein viel beachteter Komplex ist hierbei – neben der reinen Identifizierung nicht-kanonischer Satzgefüge – meist auch die Erstellung einer Klassifikation zur Erfassung zumindest einiger nicht-kanonischer Gefüge, wie dies etwa bei Fabricius-Hansen (1992) und Reis (1997) zu sehen ist. Das Ziel dieser Studie ist es, eine exhaustive Klassifikation der angesprochenen Nebensatztypen vorzunehmen. Dazu werden zunächst – unter Zuhilfenahme von Korpusdaten – alle potentiellen Subordinationsmerkmale genauer untersucht, da die meisten bisherigen Studien zu diesem Thema die stets gleichen Merkmale als gegeben voraussetzen. Dabei wird sich herausstellen, dass nur eine kleine Anzahl von Merkmalen sich wirklich zweifelsfrei dazu eignet, Aufschluss über die Satzverknüpfungsqualität zu geben. Die anschließend aufgestellte Taxonomie deutscher Nebensätze wird schließlich einzig mit der Postulierung einer nicht-kanonischen Nebensatzklasse auskommen. Sie ist darüber hinaus auch in der Lage, die zahlreich vorkommenden Ausnahmefälle zu erfassen. Dies heißt konkret, dass auch etwaige Nebensätze, die sich aufgrund bestimmter Eigenschaften teilweise idiosynkratisch verhalten, einfach in die vorgeschlagene Klassifikation übernommen werden können. In diesem Zuge werde ich weiterhin zeigen, wie eine Nebensatzklassifikation auch sog. sekundären Subordinationsmerkmalen gerecht werden kann, obwohl diese sich hinsichtlich der einzelnen Nebensatzklassen nicht einheitlich verhalten. Schließlich werde ich eine theoretische Modellierung der zuvor postulierten Taxonomie vornehmen, die auf Basis der HPSG mittels Merkmalsvererbung alle möglichen Nebensatztypen zu erfassen imstande ist. / This study focuses on so-called non-canonical or unintegrated clauses in German. These clauses cannot easily be categorized as either subordinate or coordinate by using classical criteria like the syntactic function or the position of the finite verb. In linguistics in general, this phenomenon has been discussed since the seventies (Davison 1979) and Fabricius-Hansen (1992) brought this topic to German linguistics. Apart from the mere identification of non-canonical clause types, previous studies mostly deal with classification approaches in order to be able to subsume at least some non-canonical clause types under the same category, see Fabricius-Hansen (1992) or Reis (1997). This study aims at providing an exhaustive classification of non-canonical clause types. In order to do so, I will first look at all potential diagnostics that could be used to distinguish between different clause linkage patterns. This needs to be addressed because most previous studies simply assume a certain set of diagnostics to be relevant and valid. Eventually, it will turn out that only a very limited number of criteria can serve as clear diagnostics with regard to a certain clause linkage status. After that, I will present a taxonomy of German clauses that is able to cover all non-canonical clauses only with postulating one additional subcategory. Furthermore, this classification is also able to cover the numerous cases of non-canonical clauses that show idiosyncratic behavior. Besides, I will further show how such a classification can address so-called secondary diagnostics. Finally, the previously established taxonomy will be embedded in a generative framework. By using HPSG and its default inheritance principle, it is possible to capture all non-canonical clause types within one simple classification.