Corporate Governance and Dividend Policy in European Banking

This dissertation investigates corporate governance and dividend policy in banking. This topic has recently attracted the attention of numerous scholars all over the world and currently remains one of the most discussed topics in Banking. The core of the dissertation is constituted by three papers. The first paper generalizes the main achievements in the field of relevant study using the approach of meta-analysis. The second paper provides an empirical analysis of the effect of banking corporate governance on dividend payout. Finally, the third paper investigates empirically the effect of government bailout during 2007-2010 on corporate governance and dividend policy of banks. The dissertation uses a new hand-collected data set with information on corporate governance, ownership structure and compensation structure for a sample of listed banks from 15 European countries for the period 2005-2010. The empirical papers employ such econometric approaches as Within-Group model, difference-in-difference technique, and propensity score matching method based on the Nearest Neighbor Matching estimator. The main empirical results may be summarized as follows. First, we provide evidence that CEO power and connection to government are associated with lower dividend payout ratios. This result supports the view that banking regulators are prevalently concerned about the safety of the bank, and powerful bank CEOs can afford to distribute low payout ratios, at the expense of minority shareholders. Next, we find that government bailout during 2007-2010 changes the banks’ ownership structure and helps to keep lending by bailed bank at the pre-crisis level. Finally, we provide robust evidence for increased control over the banks that receive government money. These findings show the important role of government when overcoming the consequences of the banking crisis, and high quality of governance of public bailouts in European countries.

Essays on the Empirical Analysis of Economic and Political Development in Sub-Saharan Africa

In Sub-Saharan Africa, non-democratic events, like civil wars and coup d'etat, destroy economic development. This study investigates both domestic and spatial effects on the likelihood of civil wars and coup d'etat. To civil wars, an increase of income growth is one of common research conclusions to stop wars. This study adds a concern on ethnic fractionalization. IV-2SLS is applied to overcome causality problem. The findings document that income growth is significant to reduce number and degree of violence in high ethnic fractionalized countries, otherwise they are trade-off. Income growth reduces amount of wars, but increases its violent level, in the countries with few large ethnic groups. Promoting growth should consider ethnic composition. This study also investigates the clustering and contagion of civil wars using spatial panel data models. Onset, incidence and end of civil conflicts spread across the network of neighboring countries while peace, the end of conflicts, diffuse only with the nearest neighbor. There is an evidence of indirect links from neighboring income growth, without too much inequality, to reduce the likelihood of civil wars. To coup d'etat, this study revisits its diffusion for both all types of coups and only successful ones. The results find an existence of both domestic and spatial determinants in different periods. Domestic income growth plays major role to reduce the likelihood of coup before cold war ends, while spatial effects do negative afterward. Results on probability to succeed coup are similar. After cold war ends, international organisations seriously promote democracy with pressure against coup d'etat, and it seems to be effective. In sum, this study indicates the role of domestic ethnic fractionalization and the spread of neighboring effects to the likelihood of non-democratic events in a country. Policy implementation should concern these factors.

Un algoritmo di rotazione di immagini per la decorazione digitale ceramica

L'attività di tesi è stata svolta presso la divisione System Ceramics della società System Group S.p.A. di Fiorano Modenese (MO) che si occupa dello sviluppo di soluzioni per l'industria ceramica, tra cui la decorazione delle piastrelle. Tipicamente nelle industrie ceramiche la movimentazione dei pezzi è effettuata tramite nastro trasportatore e durante il trasporto i pezzi possono subire leggeri movimenti. Se il pezzo non viene allineato alla stampante prima della fase di decorazione la stampa risulta disallineata e vi possono essere alcune zone non stampate lungo i bordi del pezzo. Perciò prima di procedere con la decorazione è fondamentale correggere il disallineamento. La soluzione più comune è installare delle guide all'ingresso del sistema di decorazione. Oltre a non consentire un’alta precisione, questa soluzione si dimostra inadatta nel caso la decorazione venga applicata in fasi successive da stampanti diverse. Il reparto di ricerca e sviluppo di System Ceramics ha quindi ideato una soluzione diversa e innovativa seguendo l'approccio inverso: allineare la grafica via software a ogni pezzo in base alla sua disposizione, invece che intervenire fisicamente modificandone la posizione. Il nuovo processo di stampa basato sull'allineamento software della grafica consiste nel ricavare inizialmente la disposizione di ogni piastrella utilizzando un sistema di visione artificiale posizionato sul nastro prima della stampante. Successivamente la grafica viene elaborata in base alla disposizione del pezzo ed applicata una volta che il pezzo arriva presso la zona di stampa. L'attività di tesi si è focalizzata sulla fase di rotazione della grafica ed è consistita nello studio e nell’ottimizzazione del prototipo di applicazione esistente al fine di ridurne i tempi di esecuzione. Il prototipo infatti, sebbene funzionante, ha un tempo di esecuzione così elevato da risultare incompatibile con la velocità di produzione adottata dalle industrie ceramiche.

Position-dependent effects on stability in tricyclo-DNA modified oligonucleotide duplexes

A series of oligodeoxyribonucleotides and oligoribonucleotides containing single and multiple tricyclo(tc)-nucleosides in various arrangements were prepared and the thermal and thermodynamic transition profiles of duplexes with complementary DNA and RNA evaluated. Tc-residues aligned in a non-continuous fashion in an RNA strand significantly decrease affinity to complementary RNA and DNA, mostly as a consequence of a loss of pairing enthalpy DeltaH. Arranging the tc-residues in a continuous fashion rescues T(m) and leads to higher DNA and RNA affinity. Substitution of oligodeoxyribonucleotides in the same way causes much less differences in T(m) when paired to complementary DNA and leads to substantial increases in T(m) when paired to complementary RNA. CD-spectroscopic investigations in combination with molecular dynamics simulations of duplexes with single modifications show that tc-residues in the RNA backbone distinctly influence the conformation of the neighboring nucleotides forcing them into higher energy conformations, while tc-residues in the DNA backbone seem to have negligible influence on the nearest neighbor conformations. These results rationalize the observed affinity differences and are of relevance for the design of tc-DNA containing oligonucleotides for applications in antisense or RNAi therapy.

Analysis and Prediction of Transient Opacity Spikes Using Dimensional Modeling

Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

Eruptive history of Maderas volcano using new 40Ar/39Ar ages and geochemical analyses

Maderas volcano is a small, andesitic stratovolcano located on the island of Ometepe, in Lake Nicaragua, Nicaragua with no record of historic activity. Twenty-one samples were collected from lava flows from Maderas in 2010. Selected samples were analyzed for whole-rock geochemical data using ICP-AES and/or were dated using the 40Ar/39Ar method. The results of these analyses were combined with previously collected data from Maderas as well as field observations to determine the eruptive history of the volcano and create a geologic map. The results of the geochemical analyses indicate that Maderas is a typical Central American andesitic volcano similar to other volcanoes in Nicaragua and Costa Rica and to its nearest neighbor, Concepción volcano. It is different from Concepción in one important way – higher incompatible elements. Determined age dates range from 176.8 ± 6.1 ka to 70.5 ± 6.1 ka. Based on these ages and the geomorphology of the volcano which is characterized by a bisecting graben, it is proposed that Maderas experienced two clear generations of development with three separate phases of volcanism: initial build-up of the older cone, pre-graben lava flows, and post-graben lava flows. The ages also indicate that Maderas is markedly older than Concepción which is historically active. Results were also analyzed regarding geologic hazards. The 40Ar/39Ar ages indicate that Maderas has likely been inactive for tens of thousands of years and the risk of future volcanic eruptions is low. However, earthquake, lahar and landslide hazards exist for the communities around the volcano. The steep slopes of the eroded older cone are the most likely source of landslide and lahar hazards.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

Guaranteed greedy routing in overlay networks

Greedy routing can be used in mobile ad-hoc networks as geographic routing protocol. This paper proposes to use greedy routing also in overlay networks by positioning overlay nodes into a multi-dimensional Euclidean space. Greedy routing can only be applied when a routing decision makes progress towards the final destination. Our proposed overlay network is built such that there will be always progress at each forwarding node. This is achieved by constructing at each node a so-called nearest neighbor convex set (NNCS). NNCSs can be used for various applications such as multicast routing, service discovery and Quality-of-Service routing. NNCS has been compared with Pastry, another topology-aware overlay network. NNCS has superior relative path stretches indicating the optimality of a path.

PDB-Explorer: a web-based interactive map of the protein data bank in shape space

Background The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. Methods A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. Results The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. Conclusion A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.​cheminfo.​org/​pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.

Similarity Mapplet: Interactive Visualization of the Directory of Useful Decoys and ChEMBL in High Dimensional Chemical Spaces

An Internet portal accessible at www.gdb.unibe.ch has been set up to automatically generate color-coded similarity maps of the ChEMBL database in relation to up to two sets of active compounds taken from the enhanced Directory of Useful Decoys (eDUD), a random set of molecules, or up to two sets of user-defined reference molecules. These maps visualize the relationships between the selected compounds and ChEMBL in six different high dimensional chemical spaces, namely MQN (42-D molecular quantum numbers), SMIfp (34-D SMILES fingerprint), APfp (20-D shape fingerprint), Xfp (55-D pharmacophore fingerprint), Sfp (1024-bit substructure fingerprint), and ECfp4 (1024-bit extended connectivity fingerprint). The maps are supplied in form of Java based desktop applications called “similarity mapplets” allowing interactive content browsing and linked to a “Multifingerprint Browser for ChEMBL” (also accessible directly at www.gdb.unibe.ch) to perform nearest neighbor searches. One can obtain six similarity mapplets of ChEMBL relative to random reference compounds, 606 similarity mapplets relative to single eDUD active sets, 30 300 similarity mapplets relative to pairs of eDUD active sets, and any number of similarity mapplets relative to user-defined reference sets to help visualize the structural diversity of compound series in drug optimization projects and their relationship to other known bioactive compounds.

The Chemical Space Project

One of the simplest questions that can be asked about molecular diversity is how many organic molecules are possible in total? To answer this question, my research group has computationally enumerated all possible organic molecules up to a certain size to gain an unbiased insight into the entire chemical space. Our latest database, GDB-17, contains 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens, by far the largest small molecule database reported to date. Molecules allowed by valency rules but unstable or nonsynthesizable due to strained topologies or reactive functional groups were not considered, which reduced the enumeration by at least 10 orders of magnitude and was essential to arrive at a manageable database size. Despite these restrictions, GDB-17 is highly relevant with respect to known molecules. Beyond enumeration, understanding and exploiting GDBs (generated databases) led us to develop methods for virtual screening and visualization of very large databases in the form of a “periodic system of molecules” comprising six different fingerprint spaces, with web-browsers for nearest neighbor searches, and the MQN- and SMIfp-Mapplet application for exploring color-coded principal component maps of GDB and other large databases. Proof-of-concept applications of GDB for drug discovery were realized by combining virtual screening with chemical synthesis and activity testing for neurotransmitter receptor and transporter ligands. One surprising lesson from using GDB for drug analog searches is the incredible depth of chemical space, that is, the fact that millions of very close analogs of any molecule can be readily identified by nearest-neighbor searches in the MQN-space of the various GDBs. The chemical space project has opened an unprecedented door on chemical diversity. Ongoing and yet unmet challenges concern enumerating molecules beyond 17 atoms and synthesizing GDB molecules with innovative scaffolds and pharmacophores.

An improved single-plaquette gauge action

We describe and test a nonperturbatively improved single-plaquette lattice action for 4-d SU(2) and SU(3) pure gauge theory, which suppresses large fluctuations of the plaquette, without requiring the naive continuum limit for smooth fields. We tune the action parameters based on torelon masses in moderate cubic physical volumes, and investigate the size of cut-off effects in other physical quantities, including torelon masses in asymmetric spatial volumes, the static quark potential, and gradient flow observables. In 2-d O(N) models similarly constructed nearest-neighbor actions have led to a drastic reduction of cut-off effects, down to the permille level, in a wide variety of physical quantities. In the gauge theories, we find significant reduction of lattice artifacts, and for some observables, the coarsest lattice result is very close to the continuum value. We estimate an improvement factor of 40 compared to using the Wilson gauge action to achieve the same statistical accuracy and suppression of cut-off effects.

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

A comparative study on unconstrained hand biometrics

Biometrics applied to mobile devices are of great interest for security applications. Daily scenarios can benefit of a combination of both the most secure systems and most simple and extended devices. This document presents a hand biometric system oriented to mobile devices, proposing a non-intrusive, contact-less acquisition process where final users should take a picture of their hand in free-space with a mobile device without removals of rings, bracelets or watches. The main contribution of this paper is threefold: firstly, a feature extraction method is proposed, providing invariant hand measurements to previous changes; second contribution consists of providing a template creation based on hand geometric distances, requiring information from only one individual, without considering data from the rest of individuals within the database; finally, a proposal for template matching is proposed, minimizing the intra-class similarity and maximizing the inter-class likeliness. The proposed method is evaluated using three publicly available contact-less, platform-free databases. In addition, the results obtained with these databases will be compared to the results provided by two competitive pattern recognition techniques, namely Support Vector Machines (SVM) and k-Nearest Neighbour, often employed within the literature. Therefore, this approach provides an appropriate solution to adapt hand biometrics to mobile devices, with an accurate results and a non-intrusive acquisition procedure which increases the overall acceptance from the final user.