Développements et applications de méthodes computationnelles pour l'étude de l'agrégation des protéines amyloïdes

Les protéines sont au coeur de la vie. Ce sont d'incroyables nanomachines moléculaires spécialisées et améliorées par des millions d'années d'évolution pour des fonctions bien définies dans la cellule. La structure des protéines, c'est-à-dire l'arrangement tridimensionnel de leurs atomes, est intimement liée à leurs fonctions. L'absence apparente de structure pour certaines protéines est aussi de plus en plus reconnue comme étant tout aussi cruciale. Les protéines amyloïdes en sont un exemple marquant : elles adoptent un ensemble de structures variées difficilement observables expérimentalement qui sont associées à des maladies neurodégénératives. Cette thèse, dans un premier temps, porte sur l'étude structurelle des protéines amyloïdes bêta-amyloïde (Alzheimer) et huntingtine (Huntington) lors de leur processus de repliement et d'auto-assemblage. Les résultats obtenus permettent de décrire avec une résolution atomique les interactions des ensembles structurels de ces deux protéines. Concernant la protéine bêta-amyloïde (AB), nos résultats identifient des différences structurelles significatives entre trois de ses formes physiologiques durant ses premières étapes d'auto-assemblage en environnement aqueux. Nous avons ensuite comparé ces résultats avec ceux obtenus au cours des dernières années par d'autres groupes de recherche avec des protocoles expérimentaux et de simulations variés. Des tendances claires émergent de notre comparaison quant à l'influence de la forme physiologique de AB sur son ensemble structurel durant ses premières étapes d'auto-assemblage. L'identification des propriétés structurelles différentes rationalise l'origine de leurs propriétés d'agrégation distinctes. Par ailleurs, l'identification des propriétés structurelles communes offrent des cibles potentielles pour des agents thérapeutiques empêchant la formation des oligomères responsables de la neurotoxicité. Concernant la protéine huntingtine, nous avons élucidé l'ensemble structurel de sa région fonctionnelle située à son N-terminal en environnement aqueux et membranaire. En accord avec les données expérimentales disponibles, nos résultats sur son repliement en environnement aqueux révèlent les interactions dominantes ainsi que l'influence sur celles-ci des régions adjacentes à la région fonctionnelle. Nous avons aussi caractérisé la stabilité et la croissance de structures nanotubulaires qui sont des candidats potentiels aux chemins d'auto-assemblage de la région amyloïde de huntingtine. Par ailleurs, nous avons également élaboré, avec un groupe d'expérimentateurs, un modèle détaillé illustrant les principales interactions responsables du rôle d'ancre membranaire de la région N-terminal, qui sert à contrôler la localisation de huntingtine dans la cellule. Dans un deuxième temps, cette thèse porte sur le raffinement d'un modèle gros-grain (sOPEP) et sur le développement d'un nouveau modèle tout-atome (aaOPEP) qui sont tous deux basés sur le champ de force gros-grain OPEP, couramment utilisé pour l'étude du repliement des protéines et de l'agrégation des protéines amyloïdes. L'optimisation de ces modèles a été effectuée dans le but d'améliorer les prédictions de novo de la structure de peptides par la méthode PEP-FOLD. Par ailleurs, les modèles OPEP, sOPEP et aaOPEP ont été inclus dans un nouveau code de dynamique moléculaire très flexible afin de grandement simplifier leurs développements futurs.

Patient-specific anisotropic model of human trunk based on MR data

There are many ways to generate geometrical models for numerical simulation, and most of them start with a segmentation step to extract the boundaries of the regions of interest. This paper presents an algorithm to generate a patient-specific three-dimensional geometric model, based on a tetrahedral mesh, without an initial extraction of contours from the volumetric data. Using the information directly available in the data, such as gray levels, we built a metric to drive a mesh adaptation process. The metric is used to specify the size and orientation of the tetrahedral elements everywhere in the mesh. Our method, which produces anisotropic meshes, gives good results with synthetic and real MRI data. The resulting model quality has been evaluated qualitatively and quantitatively by comparing it with an analytical solution and with a segmentation made by an expert. Results show that our method gives, in 90% of the cases, as good or better meshes as a similar isotropic method, based on the accuracy of the volume reconstruction for a given mesh size. Moreover, a comparison of the Hausdorff distances between adapted meshes of both methods and ground-truth volumes shows that our method decreases reconstruction errors faster. Copyright © 2015 John Wiley & Sons, Ltd.

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements

CBIR Using Local and Global Properties of Image Sub-blocks

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation and finding the corner density in each partition. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). Euclidean distance measure is used for computing the distance between the features of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

A key based cache replacement policy for cooperative caching in mobile ad hoc networks

Cooperative caching in mobile ad hoc networks aims at improving the efficiency of information access by reducing access latency and bandwidth usage. Cache replacement policy plays a vital role in improving the performance of a cache in a mobile node since it has limited memory. In this paper we propose a new key based cache replacement policy called E-LRU for cooperative caching in ad hoc networks. The proposed scheme for replacement considers the time interval between the recent references, size and consistency as key factors for replacement. Simulation study shows that the proposed replacement policy can significantly improve the cache performance in terms of cache hit ratio and query delay

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

A virtual backbone based approach for cooperative caching in mobile ad hoc networks

Cache look up is an integral part of cooperative caching in ad hoc networks. In this paper, we discuss a cooperative caching architecture with a distributed cache look up protocol which relies on a virtual backbone for locating and accessing data within a cooperate cache. Our proposal consists of two phases: (i) formation of a virtual backbone and (ii) the cache look up phase. The nodes in a Connected Dominating Set (CDS) form the virtual backbone. The cache look up protocol makes use of the nodes in the virtual backbone for effective data dissemination and discovery. The idea in this scheme is to reduce the number of nodes involved in cache look up process, by constructing a CDS that contains a small number of nodes, still having full coverage of the network. We evaluated the effect of various parameter settings on the performance metrics such as message overhead, cache hit ratio and average query delay. Compared to the previous schemes the proposed scheme not only reduces message overhead, but also improves the cache hit ratio and reduces the average delay

Intelligent Agent-based Multilingual Information Retrieval System

The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

English-Malayalam Cross-Lingual Information Retrieval – an Experience

This paper describes about an English-Malayalam Cross-Lingual Information Retrieval system. The system retrieves Malayalam documents in response to query given in English or Malayalam. Thus monolingual information retrieval is also supported in this system. Malayalam is one of the most prominent regional languages of Indian subcontinent. It is spoken by more than 37 million people and is the native language of Kerala state in India. Since we neither had any full-fledged online bilingual dictionary nor any parallel corpora to build the statistical lexicon, we used a bilingual dictionary developed in house for translation. Other language specific resources like Malayalam stemmer, Malayalam morphological root analyzer etc developed in house were used in this work

Content Based Image Retrieval System for Malayalam Handwritten Characters

Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance

On structural, optical and dielectric properties of zinc aluminate nanoparticles

Zinc aluminate nanoparticles with average particle size of 40 nm were synthesized using a sol–gel combustion method. X-ray diffractometry result was analysed by Rietveld refinement method to establish the phase purity of the material. Different stages of phase formation of the material during the synthesis were investigated using differential scanning calorimetry and differential thermogravimetric analysis. Particle size was determined with transmission electron microscopy and the optical bandgap of the nanoparticles was determined by absorption spectroscopy in the ultraviolet-visible range. Dielectric permittivity and a.c. conductivity of the material were measured for frequencies from 100 kHz to 8 MHz in the temperature range of 30–120◦C. The presence of Maxwell– Wagner type interfacial polarization was found to exist in the material and hopping of electron by means of quantum mechanical tunneling is attributed as the reason for the observed a.c. conductivity

Developing a Theoretical Framework for a Study on the Impact of Advertising Credibility of Consumer Healthcare Products

The tough competition in the global and national markets and new trends in consumerism resulted in an increase in the volume of advertisements. Sometimes advertisers are successful in achieving their intended objectives with a particular advertisement and sometimes they are not .These factors contributed a lot towards the decision making problems of advertising agencies with regard to the selection of appropriate advertising strategies and tactics. The tough competition and large volume of advertising make the consumers confused and this even created doubts in the minds of consumers about the genuineness and reliability of manufacturers and products. These factors caused a query regarding the active role of credibility element in advertising. The proposed study examines the effects of advertising credibility in consumer health care non durable product advertising on communication effect, purchase behavior and ad skepticism. This paper examines the need for the study of advertising credibility and reviews the advertising- consumer behaviour- credibility – healthcare theories which form a basis for the study. It identifies the different components and dimensions of advertising credibility and the importance of communication effect, purchase behavior and ad skepticism. It also studies the relevance of credibility in the consumer healthcare products advertising and suggests a Theoretical Framework for the proposed study

Mn2þ-induced room-temperature ferromagnetism and spin-glass behavior in hydrothermally grown Mn-doped ZnO nanorods

The magnetic properties of Mn-doped ZnO (ZnO:Mn) nanorods grown by hydrothermal process at a temperature of 200 8C and a growth time of 3 h have been studied. The samples were characterized by using powder X-ray diffraction with Rietveld refinement, scanning electron microscopy, energy-dispersive X-ray analysis and SQUID magnetometry. Mn (3 wt%) and (5 wt%)-doped ZnO samples exhibit paramagnetic and ferromagnetic behavior, respectively, at room temperature. The spin-glass behavior is observed from the samples with respect to the decrease of temperature. At 10 K, both samples exhibit a hysteresis loop with relatively low coercivity. The room-temperature ferromagnetism in 5 wt% Mn-doped ZnO nanorods is attributed to the increase in the specific area of grain boundaries, interaction between dopant Mn2þ ions substituted at Zn2þ site and the interaction between Mn2þ ions and Zn2þ ions from the ZnO host lattice

Framework for middleware executed on mobile devices

Die ubiquitäre Datenverarbeitung ist ein attraktives Forschungsgebiet des vergangenen und aktuellen Jahrzehnts. Es handelt von unaufdringlicher Unterstützung von Menschen in ihren alltäglichen Aufgaben durch Rechner. Diese Unterstützung wird durch die Allgegenwärtigkeit von Rechnern ermöglicht die sich spontan zu verteilten Kommunikationsnetzwerken zusammen finden, um Informationen auszutauschen und zu verarbeiten. Umgebende Intelligenz ist eine Anwendung der ubiquitären Datenverarbeitung und eine strategische Forschungsrichtung der Information Society Technology der Europäischen Union. Das Ziel der umbebenden Intelligenz ist komfortableres und sichereres Leben. Verteilte Kommunikationsnetzwerke für die ubiquitäre Datenverarbeitung charakterisieren sich durch Heterogenität der verwendeten Rechner. Diese reichen von Kleinstrechnern, eingebettet in Gegenstände des täglichen Gebrauchs, bis hin zu leistungsfähigen Großrechnern. Die Rechner verbinden sich spontan über kabellose Netzwerktechnologien wie wireless local area networks (WLAN), Bluetooth, oder UMTS. Die Heterogenität verkompliziert die Entwicklung und den Aufbau von verteilten Kommunikationsnetzwerken. Middleware ist eine Software Technologie um Komplexität durch Abstraktion zu einer homogenen Schicht zu reduzieren. Middleware bietet eine einheitliche Sicht auf die durch sie abstrahierten Ressourcen, Funktionalitäten, und Rechner. Verteilte Kommunikationsnetzwerke für die ubiquitäre Datenverarbeitung sind durch die spontane Verbindung von Rechnern gekennzeichnet. Klassische Middleware geht davon aus, dass Rechner dauerhaft miteinander in Kommunikationsbeziehungen stehen. Das Konzept der dienstorienterten Architektur ermöglicht die Entwicklung von Middleware die auch spontane Verbindungen zwischen Rechnern erlaubt. Die Funktionalität von Middleware ist dabei durch Dienste realisiert, die unabhängige Software-Einheiten darstellen. Das Wireless World Research Forum beschreibt Dienste die zukünftige Middleware beinhalten sollte. Diese Dienste werden von einer Ausführungsumgebung beherbergt. Jedoch gibt es noch keine Definitionen wie sich eine solche Ausführungsumgebung ausprägen und welchen Funktionsumfang sie haben muss. Diese Arbeit trägt zu Aspekten der Middleware-Entwicklung für verteilte Kommunikationsnetzwerke in der ubiquitären Datenverarbeitung bei. Der Schwerpunkt liegt auf Middleware und Grundlagentechnologien. Die Beiträge liegen als Konzepte und Ideen für die Entwicklung von Middleware vor. Sie decken die Bereiche Dienstfindung, Dienstaktualisierung, sowie Verträge zwischen Diensten ab. Sie sind in einem Rahmenwerk bereit gestellt, welches auf die Entwicklung von Middleware optimiert ist. Dieses Rahmenwerk, Framework for Applications in Mobile Environments (FAME²) genannt, beinhaltet Richtlinien, eine Definition einer Ausführungsumgebung, sowie Unterstützung für verschiedene Zugriffskontrollmechanismen um Middleware vor unerlaubter Benutzung zu schützen. Das Leistungsspektrum der Ausführungsumgebung von FAME² umfasst: • minimale Ressourcenbenutzung, um auch auf Rechnern mit wenigen Ressourcen, wie z.B. Mobiltelefone und Kleinstrechnern, nutzbar zu sein • Unterstützung für die Anpassung von Middleware durch Änderung der enthaltenen Dienste während die Middleware ausgeführt wird • eine offene Schnittstelle um praktisch jede existierende Lösung für das Finden von Diensten zu verwenden • und eine Möglichkeit der Aktualisierung von Diensten zu deren Laufzeit um damit Fehlerbereinigende, optimierende, und anpassende Wartungsarbeiten an Diensten durchführen zu können Eine begleitende Arbeit ist das Extensible Constraint Framework (ECF), welches Design by Contract (DbC) im Rahmen von FAME² nutzbar macht. DbC ist eine Technologie um Verträge zwischen Diensten zu formulieren und damit die Qualität von Software zu erhöhen. ECF erlaubt das aushandeln sowie die Optimierung von solchen Verträgen.