NMR studies on supramolecular aggregates in solution and the solid state

The aim of this work presented here is the characterization of structure and dynamics of different types of supramolecular systems by advanced NMR spectroscopy. One of the characteristic features of NMR spectroscopy is based on its high selectivity. Thus, it is desirable to exploit this technique for studying structure and dynamics of large supramolecular systems without isotopic enrichment. The observed resonance frequencies are not only isotope specific but also influenced by local fields, in particular by the distribution of electron density around the investigated nucleus. Barbituric acid are well known for forming strongly hydrogen-bonded complexes with variety of adenine derivatives. The prototropic tautomerism of this material facilitates an adjustment to complementary bases containing a DDA(A = hydrogen bond acceptor site, D = hydrogen bond donor site) or ADA sequences, thereby yielding strongly hydrogen-bonded complexes. In this contribution solid-state structures of the enolizable chromophor "1-n-butyl-5-(4-nitrophenyl)-barbituric acid" that features adjustable hydrogen-bonding properties and the molecular assemblies with three different strength of bases (Proton sponge, adenine mimetic 2,6-diaminopyridine (DAP) and 2,6-diacetamidopyridine (DAC)) are studied. Diffusion NMR spectroscopy gives information over such interactions and has become the method of choice for measuring the diffusion coefficient, thereby reflecting the effective size and shape of a molecular species. In this work the investigation of supramolecular aggregates in solution state by means of DOSY NMR techniques are performed. The underlying principles of DOSY NMR experiment are discussed briefly and more importantly two applications demonstrating the potential of this method are focused on. Calix[n]arenes have gained a rather prominent position, both as host materials and as platforms to design specific receptors. In this respect, several different capsular contents of tetra urea calix[4]arenes (benzene, benzene-d6, 1-fluorobenzene, 1-fluorobenzene-d5, 1,4-difluorobenzene, and cobaltocenium) are studied by solid state NMR spectroscopy. In the solid state, the study of the interaction between tetra urea calix[4]arenes and guest is simplified by the fact that the guests molecule remains complexed and positioned within the cavity, thus allowing a more direct investigation of the host-guest interactions.

An architecture for scaling ontology networks

Constructing ontology networks typically occurs at design time at the hands of knowledge engineers who assemble their components statically. There are, however, use cases where ontology networks need to be assembled upon request and processed at runtime, without altering the stored ontologies and without tampering with one another. These are what we call "virtual [ontology] networks", and keeping track of how an ontology changes in each virtual network is called "multiplexing". Issues may arise from the connectivity of ontology networks. In many cases, simple flat import schemes will not work, because many ontology managers can cause property assertions to be erroneously interpreted as annotations and ignored by reasoners. Also, multiple virtual networks should optimize their cumulative memory footprint, and where they cannot, this should occur for very limited periods of time. We claim that these problems should be handled by the software that serves these ontology networks, rather than by ontology engineering methodologies. We propose a method that spreads multiple virtual networks across a 3-tier structure, and can reduce the amount of erroneously interpreted axioms, under certain raw statement distributions across the ontologies. We assumed OWL as the core language handled by semantic applications in the framework at hand, due to the greater availability of reasoners and rule engines. We also verified that, in common OWL ontology management software, OWL axiom interpretation occurs in the worst case scenario of pre-order visit. To measure the effectiveness and space-efficiency of our solution, a Java and RESTful implementation was produced within an Apache project. We verified that a 3-tier structure can accommodate reasonably complex ontology networks better, in terms of the expressivity OWL axiom interpretation, than flat-tree import schemes can. We measured both the memory overhead of the additional components we put on top of traditional ontology networks, and the framework's caching capabilities.

A clustering method for robust and reliable large scale functional and structural protein sequence annotation

Bioinformatics, in the last few decades, has played a fundamental role to give sense to the huge amount of data produced. Obtained the complete sequence of a genome, the major problem of knowing as much as possible of its coding regions, is crucial. Protein sequence annotation is challenging and, due to the size of the problem, only computational approaches can provide a feasible solution. As it has been recently pointed out by the Critical Assessment of Function Annotations (CAFA), most accurate methods are those based on the transfer-by-homology approach and the most incisive contribution is given by cross-genome comparisons. In the present thesis it is described a non-hierarchical sequence clustering method for protein automatic large-scale annotation, called “The Bologna Annotation Resource Plus” (BAR+). The method is based on an all-against-all alignment of more than 13 millions protein sequences characterized by a very stringent metric. BAR+ can safely transfer functional features (Gene Ontology and Pfam terms) inside clusters by means of a statistical validation, even in the case of multi-domain proteins. Within BAR+ clusters it is also possible to transfer the three dimensional structure (when a template is available). This is possible by the way of cluster-specific HMM profiles that can be used to calculate reliable template-to-target alignments even in the case of distantly related proteins (sequence identity < 30%). Other BAR+ based applications have been developed during my doctorate including the prediction of Magnesium binding sites in human proteins, the ABC transporters superfamily classification and the functional prediction (GO terms) of the CAFA targets. Remarkably, in the CAFA assessment, BAR+ placed among the ten most accurate methods. At present, as a web server for the functional and structural protein sequence annotation, BAR+ is freely available at http://bar.biocomp.unibo.it/bar2.0.

Generalized Differential Quadrature Finite Element Method applied to Advanced Structural Mechanics

Over the years the Differential Quadrature (DQ) method has distinguished because of its high accuracy, straightforward implementation and general ap- plication to a variety of problems. There has been an increase in this topic by several researchers who experienced significant development in the last years. DQ is essentially a generalization of the popular Gaussian Quadrature (GQ) used for numerical integration functions. GQ approximates a finite in- tegral as a weighted sum of integrand values at selected points in a problem domain whereas DQ approximate the derivatives of a smooth function at a point as a weighted sum of function values at selected nodes. A direct appli- cation of this elegant methodology is to solve ordinary and partial differential equations. Furthermore in recent years the DQ formulation has been gener- alized in the weighting coefficients computations to let the approach to be more flexible and accurate. As a result it has been indicated as Generalized Differential Quadrature (GDQ) method. However the applicability of GDQ in its original form is still limited. It has been proven to fail for problems with strong material discontinuities as well as problems involving singularities and irregularities. On the other hand the very well-known Finite Element (FE) method could overcome these issues because it subdivides the computational domain into a certain number of elements in which the solution is calculated. Recently, some researchers have been studying a numerical technique which could use the advantages of the GDQ method and the advantages of FE method. This methodology has got different names among each research group, it will be indicated here as Generalized Differential Quadrature Finite Element Method (GDQFEM).

Efficient certification of feasibility and objective value of linear programs and its applications

The use of linear programming in various areas has increased with the significant improvement of specialized solvers. Linear programs are used as such to model practical problems, or as subroutines in algorithms such as formal proofs or branch-and-cut frameworks. In many situations a certified answer is needed, for example the guarantee that the linear program is feasible or infeasible, or a provably safe bound on its objective value. Most of the available solvers work with floating-point arithmetic and are thus subject to its shortcomings such as rounding errors or underflow, therefore they can deliver incorrect answers. While adequate for some applications, this is unacceptable for critical applications like flight controlling or nuclear plant management due to the potential catastrophic consequences. We propose a method that gives a certified answer whether a linear program is feasible or infeasible, or returns unknown'. The advantage of our method is that it is reasonably fast and rarely answers unknown'. It works by computing a safe solution that is in some way the best possible in the relative interior of the feasible set. To certify the relative interior, we employ exact arithmetic, whose use is nevertheless limited in general to critical places, allowing us to rnremain computationally efficient. Moreover, when certain conditions are fulfilled, our method is able to deliver a provable bound on the objective value of the linear program. We test our algorithm on typical benchmark sets and obtain higher rates of success compared to previous approaches for this problem, while keeping the running times acceptably small. The computed objective value bounds are in most of the cases very close to the known exact objective values. We prove the usability of the method we developed by additionally employing a variant of it in a different scenario, namely to improve the results of a Satisfiability Modulo Theories solver. Our method is used as a black box in the nodes of a branch-and-bound tree to implement conflict learning based on the certificate of infeasibility for linear programs consisting of subsets of linear constraints. The generated conflict clauses are in general small and give good rnprospects for reducing the search space. Compared to other methods we obtain significant improvements in the running time, especially on the large instances.

Problem-specific design of metaheuristics for constrained spanning tree problems

When designing metaheuristic optimization methods, there is a trade-off between application range and effectiveness. For large real-world instances of combinatorial optimization problems out-of-the-box metaheuristics often fail, and optimization methods need to be adapted to the problem at hand. Knowledge about the structure of high-quality solutions can be exploited by introducing a so called bias into one of the components of the metaheuristic used. These problem-specific adaptations allow to increase search performance. This thesis analyzes the characteristics of high-quality solutions for three constrained spanning tree problems: the optimal communication spanning tree problem, the quadratic minimum spanning tree problem and the bounded diameter minimum spanning tree problem. Several relevant tree properties, that should be explored when analyzing a constrained spanning tree problem, are identified. Based on the gained insights on the structure of high-quality solutions, efficient and robust solution approaches are designed for each of the three problems. Experimental studies analyze the performance of the developed approaches compared to the current state-of-the-art.

A mesoscopic simulation method for electrolyte solutions

This thesis deals with the development of a novel simulation technique for macromolecules in electrolyte solutions, with the aim of a performance improvement over current molecular-dynamics based simulation methods. In solutions containing charged macromolecules and salt ions, it is the complex interplay of electrostatic interactions and hydrodynamics that determines the equilibrium and non-equilibrium behavior. However, the treatment of the solvent and dissolved ions makes up the major part of the computational effort. Thus an efficient modeling of both components is essential for the performance of a method. With the novel method we approach the solvent in a coarse-grained fashion and replace the explicit-ion description by a dynamic mean-field treatment. Hence we combine particle- and field-based descriptions in a hybrid method and thereby effectively solve the electrokinetic equations. The developed algorithm is tested extensively in terms of accuracy and performance, and suitable parameter sets are determined. As a first application we study charged polymer solutions (polyelectrolytes) in shear flow with focus on their viscoelastic properties. Here we also include semidilute solutions, which are computationally demanding. Secondly we study the electro-osmotic flow on superhydrophobic surfaces, where we perform a detailed comparison to theoretical predictions.

Bottom-up solution synthesis of structurally defined graphene nanoribbons

Graphene nanoribbons (GNRs), which are defined as nanometer-wide strips of graphene, are attracting an increasing attention as one on the most promising materials for future nanoelectronics. Unlike zero-bandgap graphene that cannot be switched off in transistors, GNRs possess open bandgaps that critically depend on their width and edge structures. GNRs were predominantly prepared through “top-down” methods such as “cutting” of graphene and “unzipping” of carbon nanotubes, but these methods cannot precisely control the structure of the resulting GNRs. In contrast, “bottom-up” chemical synthetic approach enables fabrication of structurally defined and uniform GNRs from tailor-made polyphenylene precursors. Nevertheless, width and length of the GNRs obtainable by this method were considerably limited. In this study, lateral as well as longitudinal extensions of the GNRs were achieved while preserving the high structural definition, based on the bottom-up solution synthesis. Initially, wider (~2 nm) GNRs were synthesized by using laterally expanded monomers through AA-type Yamamoto polymerization, which proved more efficient than the conventional A2B2-type Suzuki polymerization. The wider GNRs showed broad absorption profile extending to the near-infrared region with a low optical bandgap of 1.12 eV, which indicated a potential of such GNRs for the application in photovoltaic cells. Next, high longitudinal extension of narrow (~1 nm) GNRs over 600 nm was accomplished based on AB-type Diels–Alder polymerization, which provided corresponding polyphenylene precursors with the weight-average molecular weight of larger than 600,000 g/mol. Bulky alkyl chains densely installed on the peripheral positions of these GNRs enhanced their liquid-phase processability, which allowed their formation of highly ordered self-assembled monolayers. Furthermore, non-contact time-resolved terahertz spectroscopy measurements demonstrated high charge-carrier mobility within individual GNRs. Remarkably, lateral extension of the AB-type monomer enabled the fabrication of wider (~2 nm) and long (>100 nm) GNRs through the Diels–Alder polymerization. Such longitudinally extended and structurally well-defined GNRs are expected to allow the fabrication of single-ribbon transistors for the fundamental studies on the electronic properties of the GNRs as well as contribute to the development of future electronic devices.

Control over microstructure evolution and device performance in solution processable organic field-effect transistors

Die Arbeit beschäftigt sich mit der Kontrolle von Selbstorganisation und Mikrostruktur von organischen Halbleitern und deren Einsatz in OFETs. In Kapiteln 3, 4 und 5 eine neue Lösungsmittel-basierte Verabeitungsmethode, genannt als Lösungsmitteldampfdiffusion, ist konzipiert, um die Selbstorganisation von Halbleitermolekülen auf der Oberfläche zu steuern. Diese Methode als wirkungsvolles Werkzeug erlaubt eine genaue Kontrolle über die Mikrostruktur, wie in Kapitel 3 am Beispiel einer D-A Dyad bestehend aus Hexa-peri-hexabenzocoronene (HBC) als Donor und Perylene Diimide (PDI) als Akzeptor beweisen. Die Kombination aus Oberflächenmodifikation und Lösungsmitteldampf kann die Entnetzungseffekte ausgleichen, so dass die gewüschte Mikrostruktur und molekulare Organisation auf der Oberfläche erreicht werden kann. In Kapiteln 4 und 5 wurde diese Methode eingesetzt, um die Selbstorganisation von Dithieno[2, 3-d;2’, 3’-d’] benzo[1,2-b;4,5-b’]dithiophene (DTBDT) und Cyclopentadithiophene -benzothiadiazole copolymer (CDT-BTZ) Copolymer zu steuern. Die Ergebnisse könnten weitere Studien stimulieren und werfen Licht aus andere leistungsfaähige konjugierte Polymere. rnIn Kapiteln 6 und 7 Monolagen und deren anschlieβende Mikrostruktur von zwei konjugierten Polymeren, Poly (2,5-bis(3-alkylthiophen-2-yl)thieno[3,2-b]thiophene) PBTTT und Poly{[N,N ′-bis(2-octyldodecyl)-naphthalene-1,4,5,8-bis (dicarboximide)-2,6-diyl]-alt-5,5′- (2,2′-bithiophene)}, P(NDI2OD-T2)) wurden auf steife Oberflächen mittels Tauchbeschichtung aufgebracht. Da sist das erste Mal, dass es gelungen ist, Polymer Monolagen aus der Lösung aufzubringen. Dieser Ansatz kann weiter auf eine breite Reihe von anderen konjugierten Polymeren ausgeweitet werden.rnIn Kapitel 8 wurden PDI-CN2 Filme erfolgreich von Monolagen zu Bi- und Tri-Schichten auf Oberflächen aufgebracht, die unterschiedliche Rauigkeiten besitzen. Für das erste Mal, wurde der Einfluss der Rauigkeit auf Lösungsmittel-verarbeitete dünne Schichten klar beschrieben.rn

Regularization methods for the solution of a nonlinear least-squares problem in tomography

In this work we study a polyenergetic and multimaterial model for the breast image reconstruction in Digital Tomosynthesis, taking into consideration the variety of the materials forming the object and the polyenergetic nature of the X-rays beam. The modelling of the problem leads to the resolution of a high-dimensional nonlinear least-squares problem that, due to its nature of inverse ill-posed problem, needs some kind of regularization. We test two main classes of methods: the Levenberg-Marquardt method (together with the Conjugate Gradient method for the computation of the descent direction) and two limited-memory BFGS-like methods (L-BFGS). We perform some experiments for different values of the regularization parameter (constant or varying at each iteration), tolerances and stop conditions. Finally, we analyse the performance of the several methods comparing relative errors, iterations number, times and the qualities of the reconstructed images.

Development of an LC-MS/MS method for the quantitation of 55 compounds prescribed in combined cardiovascular therapy

This paper reports an LC-MS/MS method with positive electrospray ionization for the screening of commonly prescribed cardiovascular drugs in human plasma, including compounds with antihypertensive (57), antidiabetic (12), hypolipemiant (5), anticoagulant (2) and platelet anti-aggregation (2) effects. Sample treatment consisted of a simple protein precipitation with MeOH/0.1 M ZnSO₄ (4:1, v/v) solution after the addition of internal standard, followed by evaporation and reconstitution. Analytes separation was performed on a Polar-RP column (150 m x 2 mm, 4 μm) using a gradient elution of 15 min. The MS system was operated in MRM mode, monitoring one quantitation and one confirmation transition for each analyte. The recovery of the protein precipitation step ranged from 50 to 70% for most of the compounds, while some were considerably affected by matrix effects. Since several analytes fulfilled the linearity, accuracy and precision values required by the ICH guidelines, the method proved to be suitable for their quantitative analysis. The limits of quantitation varied from 0.38 to 9.1 μg/L and the limits of detection from 0.12 to 5.34 μg/L. The method showed to be suitable for the detection of plasma samples of patients under cardiovascular treatment with the studied drugs, and for 55 compounds reliable quantitative results could be obtained.

Development and validation of a liquid chromatography-tandem mass spectrometry method for the simultaneous determination of nine corticosteroid residues in bovine liver samples

A liquid chromatography tandem mass spectrometry (LC-MS/MS) confirmatory method for the simultaneous determination of nine corticosteroids in liver, including the four MRL compounds listed in Council Regulation 37/2010, was developed. After an enzymatic deconjugation and a solvent extraction of the liver tissue, the resulting solution was cleaned up through an SPE Oasis HLB cartridge. The analytes were then detected by liquid chromatography-negative-ion electrospray tandem mass spectrometry, using deuterium-labelled internal standards. The procedure was validated as a quantitative confirmatory method according to the Commission Decision 2002/657/EC criteria. The results showed that the method was suitable for statutory residue testing regarding the following performance characteristics: instrumental linearity, specificity, precision (repeatability and intra-laboratory reproducibility), recovery, decision limit (CCα), detection capability (CCβ) and ruggedness. All the corticosteroids can be detected at a concentration around 1 μg kg(-1); the recoveries were above 62% for all the analytes. Repeatability and reproducibility (within-laboratory reproducibility) for all the analytes were below 7.65% and 15.5%, respectively.

Using scenario tree modelling for targeted herd sampling to substantiate freedom from disease

BACKGROUND: In order to optimise the cost-effectiveness of active surveillance to substantiate freedom from disease, a new approach using targeted sampling of farms was developed and applied on the example of infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) in Switzerland. Relevant risk factors (RF) for the introduction of IBR and EBL into Swiss cattle farms were identified and their relative risks defined based on literature review and expert opinions. A quantitative model based on the scenario tree method was subsequently used to calculate the required sample size of a targeted sampling approach (TS) for a given sensitivity. We compared the sample size with that of a stratified random sample (sRS) with regard to efficiency. RESULTS: The required sample sizes to substantiate disease freedom were 1,241 farms for IBR and 1,750 farms for EBL to detect 0.2% herd prevalence with 99% sensitivity. Using conventional sRS, the required sample sizes were 2,259 farms for IBR and 2,243 for EBL. Considering the additional administrative expenses required for the planning of TS, the risk-based approach was still more cost-effective than a sRS (40% reduction on the full survey costs for IBR and 8% for EBL) due to the considerable reduction in sample size. CONCLUSIONS: As the model depends on RF selected through literature review and was parameterised with values estimated by experts, it is subject to some degree of uncertainty. Nevertheless, this approach provides the veterinary authorities with a promising tool for future cost-effective sampling designs.

Parallel algorithm for solving integer linear programs

Linear programs, or LPs, are often used in optimization problems, such as improving manufacturing efficiency of maximizing the yield from limited resources. The most common method for solving LPs is the Simplex Method, which will yield a solution, if one exists, but over the real numbers. From a purely numerical standpoint, it will be an optimal solution, but quite often we desire an optimal integer solution. A linear program in which the variables are also constrained to be integers is called an integer linear program or ILP. It is the focus of this report to present a parallel algorithm for solving ILPs. We discuss a serial algorithm using a breadth-first branch-and-bound search to check the feasible solution space, and then extend it into a parallel algorithm using a client-server model. In the parallel mode, the search may not be truly breadth-first, depending on the solution time for each node in the solution tree. Our search takes advantage of pruning, often resulting in super-linear improvements in solution time. Finally, we present results from sample ILPs, describe a few modifications to enhance the algorithm and improve solution time, and offer suggestions for future work.

Numerical solutions of elliptic inverse problems via the equation error method

To estimate a parameter in an elliptic boundary value problem, the method of equation error chooses the value that minimizes the error in the PDE and boundary condition (the solution of the BVP having been replaced by a measurement). The estimated parameter converges to the exact value as the measured data converge to the exact value, provided Tikhonov regularization is used to control the instability inherent in the problem. The error in the estimated solution can be bounded in an appropriate quotient norm; estimates can be derived for both the underlying (infinite-dimensional) problem and a finite-element discretization that can be implemented in a practical algorithm. Numerical experiments demonstrate the efficacy and limitations of the method.