Novel techniques of computational intelligence for analysis of astronomical structures

Gravitational forces cause the formation and evolution of a variety of cosmological structures. The detailed investigation and study of these structures is a crucial step towards our understanding of the universe. This thesis provides several solutions for the detection and classification of such structures. In the first part of the thesis, we focus on astronomical simulations, and we propose two algorithms to extract stellar structures. Although they follow different strategies (while the first one is a downsampling method, the second one keeps all samples), both techniques help to build more effective probabilistic models. In the second part, we consider observational data, and the goal is to overcome some of the common challenges in observational data such as noisy features and imbalanced classes. For instance, when not enough examples are present in the training set, two different strategies are used: a) nearest neighbor technique and b) outlier detection technique. In summary, both parts of the thesis show the effectiveness of automated algorithms in extracting valuable information from astronomical databases

Drawing, Handwriting Processing Analysis: New Advances and Challenges

International audienceDrawing and handwriting are communicational skills that are fundamental in geopolitical, ideological and technological evolutions of all time. drawingand handwriting are still useful in defining innovative applications in numerous fields. In this regard, researchers have to solve new problems like those related to the manner in which drawing and handwriting become an efficient way to command various connected objects; or to validate graphomotor skills as evident and objective sources of data useful in the study of human beings, their capabilities and their limits from birth to decline

Variational determination of the two-particle density matrix : the case of doubly-occupied space

The world at the level of the atom is described by the branch of science called quantum mechanics. The crown jewel of quantum mechanics is given by the Schrödinger equation which describes a system of indistinguishable particles, that interact with each other. However, an equation alone is not enough: the solution is what interests us. Unfortunately, the exponential scaling of the Hilbert space makes it unfeasible to calculate the exact wave function. This dissertation concerns itself with one of the many ab initio methods that were developed to solve this problem: the variational determination of the second-order density matrix. This method already has a long history. It is not considered to be on par with best ab initio methods. This work tries an alternative approach. We assume that the wave function has a Slater determinant expansion where all orbitals are doubly occupied or empty. This assumption drastically reduces the scaling of the N-representability conditions. The downside is that the energy explicitly depends on the used orbitals and thus an orbital optimizer is needed. The hope is that by using this approximation, we can capture the lion's share of the static correlation and that any missing dynamic correlation can be added through perturbation theory. We developed an algorithm based on Jacobi rotations. The scaling is much more favorable compared to the general case. The method is then tested on a array of benchmark systems

Towards Unified Object Analytics

Ph.DDOCTOR OF PHILOSOPH

Development of novel ligands influencing neurotransmission in the central nervous system

The development of novel drugs targeting GPCRs is of particular interest since modulation of subfamilies of this receptor class highly influences neurotransmission in the central nervous system. This study has focused on the development of ligands for the dopamine D3 receptor. The receptor belongs to the dopamine D2-like family among the biogenic amine binding GPCRs. The dopamine D3 receptor is involved in neurological and neuropsychiatric disorders such as Parkinson’s disease, schizophrenia and drug addiction. Due to its close structural similarity to the dopamine D2 receptor subtype, it is still a challenge to identify and further optimize new leads. Therefore an in vitro screening assay, which also allows elucidating comprehensive structure-affinity relationships, is required. In this investigation the implementation and evaluation of radioligand binding assays for human dopamine D2S and dopamine D3 receptors and for the related aminergic human histamine H1 receptor stably expressed in Chinese hamster ovary (CHO) cells has been performed. Saturation binding experiments with [³H]spiperone at dopamine D2S and D3 receptors and with [³H]mepyramine at histamine H1 receptors were carried out. The determined equilibrium dissociation constant of radioligands (Kd) and the total number of specific binding sites (Bmax) of the receptor membrane preparations were in good agreement with reference data. Inhibition constants (Ki) of reference ligands obtained in radioligand competition binding experiments at dopamine hD2S, hD3 and histamine H1 receptors validated the reliability and reproducibility of the assay. In order to discriminate agonists from antagonists, a GTP shift assay has been investigated for dopamine D2S and D3 receptors. In competition binding studies at dopamine D2S receptors the high- and low affinity state in the absence of the GTP analogue Gpp(NH)p has been recognized for the agonists pramipexole and the seleno analogue 54. In the presence of Gpp(NH)p a decrease in affinity, referred to as “GTP shift”, has been revealed for agonists at dopamine D2S and D3 receptors. An effect of Gpp(NH)p on dopamine D2S receptor binding has not been observed for the antagonists ST 198 and BP 897, while a reverse “GTP shift” has been noticed at the dopamine D3 receptor. For the development of novel ligands with high affinity and selectivity for dopamine D3 receptors, investigation in refined structure-affinity relationships (SAR) of analogues of the lead BP 897 has been performed. Replacement of the naphthalen-2-carboxamide of BP 897 by aryl amide residues (1 - 4) had a clear influence on affinity binding and selectivity for dopamine D3 receptors. Introduction of the benzo[b]thiophen-2-carboxamide (1) has markedly improved binding with subnanomolar affinity and enhanced selectivity for dopamine D3 receptors. Exchanging the aryl substituted basic alkanamine residue of 1 by a 1,2,3,4-tetrahydroisoquinoline moiety (6) emphasized the benefit of the 4-(2-methoxyphenyl) piperazine residue of BP 897 regarding dopamine D2 and D3 receptor affinities. The change of particular elements of BP 897 and the rearrangement of the amide functionality resulted in inverse amide compounds with new chemical properties. Moderate affinity binding data, as obtained for the isoindol-1-carbonyl compound 11, suggest that inverse amides provide a worthwhile new lead structure with a novel structural scaffold. A hybrid approach combining privileged scaffolds of histamine H1 receptor antagonists and fragments of dopamine D3 receptor-preferring ligands, related to BP 897and analogues has been investigated. Various benzhydrylpiperazine derivatives and related structures have shown moderate to high affinities for dopamine D3 receptors with the impressive enhancement of the cinnamide substituted bamipine-related hybrid 39, exhibiting the highest affinity and selectivity for dopamine D3 receptors. Improved affinity profiles of structural modified histamine H1 receptor antagonists for dopamine D2 and D3 receptors and a refined SAR has been achieved. A SAR of derivatives of the dopamine agonist pramipexole and the related etrabamine has been studied. The propargyl substituted etrabamine derivative 61 demonstrated highest affinity and selectivity. The ligand attracts attention since neuroprotective properties have been reported for the propargyl functionality. Further development resulted in the most promising compound 64, a cinnamide derivative with 4-fluoro substitution on the phenyl ring. Subnanomolar affinity and remarkable selectivity for dopamine D3 receptors has aroused particular interest in this ligand due to its development potential as a radioligand for PET studies. Radioligand binding studies in combination with virtual screening and different classification techniques of chemoinformatic methods resulted in further elucidation of SAR. New leads with novel chemical scaffolds have been found in the bicycle[2.2.1]heptane derivative 95 and the benzhydrylidene substituted pyrrolidindione 112 and can be further optimized by chemical modifications. The outcome of the studies provides the development of various novel high affine and dopamine D3 receptor selective ligands. Modifications of lead structures or application of chemoinformatic tools in combination with radioligand competition binding assays have resulted in new leads with different chemical scaffolds. Furthermore, a comprehensive insight into structure-affinity relationships of ligands at dopamine D3 receptors has been revealed. This refined SAR is valuable to develop more affine and selective drug candidates with a designed pharmacological receptor profile.Das Ziel der Arbeit war die Entwicklung von neuen Liganden zur Beeinflussung der Neurotransmission im zentralen Nervensystem. Der Fokus lag auf dem Dopamin-D3-Rezeptor, der eine wichtige Rolle bei Morbus Parkinson, Schizophrenie und Drogenmissbrauch spielt. Aufgrund seiner Strukturähnlichkeit zum Dopamin-D2-Rezeptor ist es eine Herausforderung, neue, selektive Leitstrukturen für den Dopamin-D3-Rezeptor zu identifizieren bzw. zu optimieren. Ein in vitro Testsystem ist hierfür erforderlich und ermöglicht das Aufstellen von Struktur-Wirkungsbeziehungen (SAR) und ein rationales Wirkstoffdesign. Die Arbeit umfasste die Etablierung von Radioliganden Bindungsassays an Dopamin-D2S- und -D3-Rezeptoren, sowie am verwandten aminergen Histamin-H1-Rezeptor, die stabil in Zelllinien von Ovarien des Chinesischen Hamsters exprimiert wurden. Sättigungsstudien wurden mit [³H]Spiperon am Dopamin-D2S- und D3-Rezeptor und mit [³H]Mepyramin am Histamin-H1-Rezeptor durchgeführt. Die ermittelten Dissoziationskonstanten (Kd) und maximale Zahl der Bindungsstellen (Bmax) stimmten mit den Literaturwerten überein. Die in Verdrängungsstudien bestimmten Inhibitionskonstanten (Ki) von Referenzsubstanzen am Dopamin-D2S- und -D3-Rezeptor sowie am Histamin-H1-Rezeptor bestätigten die Zuverlässigkeit und Reproduzierbarkeit der Bindungsassays. Zur Unterscheidung der Agonisten von Antagonisten wurden „GTP-Shift“ Assays am Dopamin-D2S- und -D3-Rezeptor angewandt. Für Pramipexol und das Selenanaloga 54 wurden zwei Bindungszustände mit unterschiedlichen Affinitäten (ein so genannter „high- und low affinity state“) am Dopamin-D2S-Rezeptor in Abwesenheit von Gpp(NH)p beobachtet. Eine Affinitätsabnahme („GTP-Shift“) in Anwesenheit von Gpp(NH)p zeigte sich für die Agonisten am Dopamin-D2S- und -D3-Rezeptor. Dieser Einfluss des Gpp(NH)p konnte nicht für den Antagonisten ST 198 und den partiellen Agonisten BP 897 gezeigt werden. Für diese Verbindung wurde ein inverser „GTP-Shift“, also eine Affinitätsverbesserung am Dopamin-D3-Rezeptor beobachtet. Um neue Liganden mit hoher Affinität und Selektivität für den Dopamin-D3-Rezeptor zu entwickeln, wurden ausführliche SAR verschiedener Derivate der Leitstruktur BP 897 und ST 198 erstellt. Der Austausch des Naphthalen-2-carboxamid-Rests von BP 897 durch verschiedene Arylamid-Strukturen (1 – 4) zeigte deren deutlichen Einfluss auf die Dopamin-D3-Rezeptorbindungsaffinität und -selektivität. Die Einführung eines Benzo[b]thiophen-2-carboxamid-Rests führte in Verbindung 1 zu herausragender subnanomolarer Affinität am Dopamin-D3-Rezeptor sowie zu deutlich erhöhter Selektivität im Vergleich zu BP 897. Die Variation des lipophilen basischen Amin-Restes von 1 ergab das 1,2,3,4-Tetrahydroisochinolin-Derivat 6. Verdrängungsstudien konnten den Vorteil des 4-(2-Methoxyphenyl)piperazine-Substituenten von BP 897 bezüglich der Affinitäten am Dopamin-D2S- und -D3-Rezeptor deutlich zeigen. Modifikationen einzelner Elemente von BP 897 und ST 198 und die veränderte Integration der Amid-Funktion in dem lipophilen Aryl-Rest führten zur Substanzklasse der inversen Amide mit neuen chemischen Eigenschaften. Moderate Bindungsaffinitäten, wie für das Isoindol-1-carbonyl-Derivat 11 gezeigt, legen nahe, dass inverse Amide eine lohnenswerte neue Leitstruktur mit andersartigem strukturellem Gerüst darstellen. In einer Hybrid-Strategie wurden Strukturelemente von Histamin-H1-Rezeptorantagonisten mit Substrukturen von Liganden mit ausgeprägter Dopamin-D3-Rezeptorpräferenz kombiniert. Daraus resultierten Benzhydrylpiperazin-Derivative und verwandte Substanzen mit moderater bis hoher Affinität am Dopamin-D3-Rezeptor. Besonders hervorzuheben ist das Zimtsäureamid substituierte und zum Bamipin verwandte Hybrid 39, welches die besten Ergebnisse in dieser Serie hinsichtlich Affinität und Selektivität am Dopamin-D3-Rezeptor erbrachte. Verbesserte pharmakologische Profile der strukturell modifizierten Histamine-H1-Rezeptorantagonisten am Dopamin-D2S- und -D3-Rezeptor und eine differenzierte SAR wurden erreicht. Für Derivate des Dopaminrezeptoragonisten Pramipexol und des strukturähnlichen Etrabamin wurden SAR ausgearbeitet. Das Propargyl substituierte Etrabamin-Derivat 61 zeigte herausragende Dopamin-D3-Rezeptoraffinität und -selektivität. Der Ligand ist von Interesse, da für den Propargyl-Rest neuroprotektive Eigenschaften berichtet wurden. Die Weiterentwicklung führte zur Verbindung 64, einem Zimtsäureamid-Derivat mit 4-Fluor-Substitution am Phenylring. Subnanomolare Affinität und hohe Selektivität am Dopamin-D3-Rezeptor prädestinieren 64 zur Anwendung als potentiellen PET-Radioliganden. Radioliganden Bindungsstudien wurden auf die Ergebnisse von virtuellen Screeningstudien angewandt. Sie führten zur Identifizierung neuer Leitstrukturen und zum weiteren Verständnis der SAR. Als neue Leitstrukturen mit verschiedenartigen chemischen Gerüsten wurden unter anderem das Bicyclo[2.2.1]heptan-Derivat 95 und der Benzhydryliden substituierte Pyrrolidindion Ligand 112 gefunden. Diese können nun zur weiteren Optimierung chemisch modifiziert werden. Die in dieser Arbeit durchgeführten Radioliganden Bindungsstudien führten zur Identifizierung, Entwicklung und Optimierung von hoch affinen und selektiven Dopamin-D3-Rezeptor Liganden. Des Weiteren ermöglichten die Ergebnisse eine ausführliche Vertiefung der SAR. Die kombinierte Strategie von chemoinformatischen Methoden und Radioliganden Bindungsstudien hat das Finden neuer Leitstrukturen als potentielle Arzneistoffe erlaubt. Die Resultate ermöglichen in der Zukunft ein gezieltes Liganden-Design mit einem gerichteten pharmakologischen Rezeptorprofil

Pattern Recognition

Pattern recognition is a very wide research field. It involves factors as diverse as sensors, feature extraction, pattern classification, decision fusion, applications and others. The signals processed are commonly one, two or three dimensional, the processing is done in real- time or takes hours and days, some systems look for one narrow object class, others search huge databases for entries with at least a small amount of similarity. No single person can claim expertise across the whole field, which develops rapidly, updates its paradigms and comprehends several philosophical approaches. This book reflects this diversity by presenting a selection of recent developments within the area of pattern recognition and related fields. It covers theoretical advances in classification and feature extraction as well as application-oriented works. Authors of these 25 works present and advocate recent achievements of their research related to the field of pattern recognition

Challenging swampland conjectures in exotic corners of the landscape

Effektive Feld-Theorie erlaubt uns die Physik unserer Welt auf unterschiedlichen Energie-Niveaus zu beschreiben. Umgekehrt muss eine effektive Theorie, mit der wir unsere Welt auf alltäglichen Skalen darstellen, bei hohen Energien mit der Quantengravitation vereinigt werden. Dies ist nicht uneingeschränkt möglich. Deshalb möchte das Swampland-Programm die Voraussetzungen unter welchen eine effektive Theorie mit der Gravitation gekoppelt werden kann eruieren. Diese Bedingungen werden “Swampland Conjectures” genannt. Sie geben klare Vorhersagen und begrenzen die effektiven Theorien, welche über das Standardmodell hinaus in Betracht gezogen werden sollten. Zum Beispiel soll ein langlebiges de-Sitter (dS) Universum schlicht unmöglich sein. In Anti-de-Sitter (AdS) ist die kosmologische Konstante an die Massen eines Turms von Teilchen gekoppelt, sodass der Energiebereich in welchem die effektive Theorie valide ist im Grenzfall des flachen Raumes verschwindet. Allerdings sind Swampland Conjectures generell nicht mathematisch beweisbar. Nur wenige konnten bislang rigoros bewiesen werden, und auch diese nur in speziellen Bereichen der String Theorie. Die meisten Swampland Conjectures beziehen Inspiration und Evidenz von der String Theorie und Schwarzen Löchern. String Theorie, eine natürliche Theorie der Quantengravitation, hat eine große Zahl an Vakua mit vielen gut verstandenen effektiven Theorien. Dies stellt eine riesige Datenmenge dar, mit welcher Swampland Conjectures überprüft werden können. Unglücklicherweise sind die am besten verstandenen Vakua nicht unbedingt eine repräsentative Menge. Mit ähnlichen Konfigurationen von BPS D-Branen und p-Form Flüssen sowie perturbativen Beiträgen besteht die reelle Gefahr, dass manche Swampland Conjectures nur ein Produkt der selektiven Datenauswahl sind. Die Arbeit, welche in dieser Dissertation präsentiert wird, testet die dS und AdS Swampland Conjectures in bislang weniger gut untersuchten Bereichen der String Theorie. Mit non-BPS Branen und Exotischen String Theorien versuchen wir Hindernisse, welche dS Vakua verhindern, zu umgehen. Immer wenn wir einen Schritt näher an dS kommen, tauchen stattdessen neue Probleme auf. Demzufolge wird die dS Swampland Conjecture auch in diesen exotischen Bereichen des String Landscape bestätigt. Schließlich untersuchen wir nicht-perturbative Beiträge und erkennen, dass die AdS Swampland Conjectures um log-terme ergänzt werden müssen. Zusammengefasst bestätigen wir die Swampland Conjectures bis auf log Korrekturen auch in exotischen Bereichen der String Theorie.Effective field theories are the way physics describes the world at different energies. Conversely, this means that any effective theory of our universe should couple to quantum gravity at high energies. Realizing that this is not always possible, the swampland program tries to delineate the conditions under which a low energy theory can be consistently completed with gravity in the UV. These conditions are called swampland conjectures. They give real predictions and bounds on the effective theories we should consider in beyond the standard model physics. For instance, it is conjectured that a long-lived de Sitter (dS) vacuum is simply impossible. In Anti-de Sitter (AdS), the magnitude of the cosmological constant is related to the mass of a tower of states, so that the energy cutoff of the effective theory goes to zero as we approach flat space. However, as the name “conjecture” already implies, these statements are not in general mathematically proven. Only a very few conjectures have been rigorously proven, and even then only in special subsectors of string theory. The bulk of the swampland conjectures takes inspiration and evidence from string theory and black hole physics. String theory as a natural theory of quantum gravity has a huge number of vacua, with many well characterized effective theories. This provides an enormous data set that swampland conjectures can be tested on. Unfortunately, the best understood vacua of string theory are not necessarily a representative set. With similar setups, only using standard D-branes, p-form fluxes and perturbative contributions, there is a danger that the swampland conjectures are a product of the lamppost effect. This is the motivation for the work presented in this thesis. We investigate the dS and AdS swampland conjectures in less explored regimes of string theory, in order to escape the lamppost. We introduce non-BPS branes and consider exotic string theories to try and get around various obstructions to finding dS vacua. Always we observe that while we do manage to circumvent obstructions, new problems appear. This confirms the no-dS conjecture also in exotic corners of the string landscape. Finally we consider non-perturbative contributions and find that here the AdS swampland conjectures have to be corrected by log-terms. In summary, we find that even in strange and new corners of string theory, and up to quantum log-corrections, the swampland conjectures still hold

Tensor Representations for Object Classification and Detection

A key problem in object recognition is finding a suitable object representation. For historical and computational reasons, vector descriptions that encode particular statistical properties of the data have been broadly applied. However, employing tensor representation can describe the interactions of multiple factors inherent to image formation. One of the most convenient uses for tensors is to represent complex objects in order to build a discriminative description. Thus thesis has several main contributions, focusing on visual data detection (e.g. of heads or pedestrians) and classification (e.g. of head or human body orientation) in still images and on machine learning techniques to analyse tensor data. These applications are among the most studied in computer vision and are typically formulated as binary or multi-class classification problems. The applicative context of this thesis is the video surveillance, where classification and detection tasks can be very hard, due to the scarce resolution and the noise characterising sensor data. Therefore, the main goal in that context is to design algorithms that can characterise different objects of interest, especially when immersed in a cluttered background and captured at low resolution. In the different amount of machine learning approaches, the ensemble-of-classifiers demonstrated to reach excellent classification accuracy, good generalisation ability, and robustness of noisy data. For these reasons, some approaches in that class have been adopted as basic machine classification frameworks to build robust classifiers and detectors. Moreover, also kernel machines has been exploited for classification purposes, since they represent a natural learning framework for tensors

Active Materials

What is an active material? This book aims to redefine perceptions of the materials that respond to their environment. Through the theory of the structure and functionality of materials found in nature a scientific approach to active materials is first identified. Further interviews with experts from the natural sciences and humanities then seeks to question and redefine this view of materials to create a new definition of active materials

Active Materials

What is an active material? This book aims to redefine perceptions of the materials that respond to their environment. Through the theory of the structure and functionality of materials found in nature a scientific approach to active materials is first identified. Further interviews with experts from the natural sciences and humanities then seeks to question and redefine this view of materials to create a new definition of active materials