Fuzzy tolerance/equivalence relations from intersection, union and complement operators and their application to a clustering method

This master thesis work introduces the fuzzy tolerance/equivalence relation and its application in cluster analysis. The work presents about the construction of fuzzy equivalence relations using increasing generators. Here, we investigate and research on the role of increasing generators for the creation of intersection, union and complement operators. The objective is to develop different varieties of fuzzy tolerance/equivalence relations using different varieties of increasing generators. At last, we perform a comparative study with these developed varieties of fuzzy tolerance/equivalence relations in their application to a clustering method.

Protection of plasmid DNA by a Ginkgo biloba extract from the effects of stannous chloride and the action on the labeling of blood elements with technetium-99m

Ginkgo biloba extract (EGb) is a phytotherapeutic agent used for the treatment of ischemic and neurological disorders. Because the action of this important extract is not fully known, assays using different biological systems need to be performed. Red blood cells (RBC) are labeled with technetium-99m (Tc-99m) and used in nuclear medicine. The labeling depends on a reducing agent, usually stannous chloride (SnCl2). We assessed the effect of different concentrations of EGb on the labeling of blood constituents with Tc-99m, as sodium pertechnetate (3.7 MBq), and on the mobility of a plasmid DNA treated with SnCl2 (1.2 µg/ml) at room temperature. Blood was incubated with EGb before the addition of SnCl2 and Tc-99m. Plasma (P) and RBC were separated and precipitated with trichloroacetic acid, and soluble (SF-P and SF-RBC) and insoluble (IF-P and IF-RBC) fractions were isolated. The plasmid was incubated with Egb, SnCl2 or EGb plus SnCl2 and agarose gel electrophoresis was performed. The gel was stained with ethidium bromide and the DNA bands were visualized by fluorescence in an ultraviolet transilluminator system. EGb decreased the labeling of RBC, IF-P and IF-RBC. The supercoiled form of the plasmid was modified by treatment with SnCl2 and protected by 40 mg/ml EGb. The effect of EGb on the tested systems may be due to its chelating action with the stannous ions and/or pertechnetate or to the capability to generate reactive oxygen species that could oxidize the stannous ion.

Category fluency test: effects of age, gender and education on total scores, clustering and switching in Brazilian Portuguese-speaking subjects

Verbal fluency tests are used as a measure of executive functions and language, and can also be used to evaluate semantic memory. We analyzed the influence of education, gender and age on scores in a verbal fluency test using the animal category, and on number of categories, clustering and switching. We examined 257 healthy participants (152 females and 105 males) with a mean age of 49.42 years (SD = 15.75) and having a mean educational level of 5.58 (SD = 4.25) years. We asked them to name as many animals as they could. Analysis of variance was performed to determine the effect of demographic variables. No significant effect of gender was observed for any of the measures. However, age seemed to influence the number of category changes, as expected for a sensitive frontal measure, after being controlled for the effect of education. Educational level had a statistically significant effect on all measures, except for clustering. Subject performance (mean number of animals named) according to schooling was: illiterates, 12.1; 1 to 4 years, 12.3; 5 to 8 years, 14.0; 9 to 11 years, 16.7, and more than 11 years, 17.8. We observed a decrease in performance in these five educational groups over time (more items recalled during the first 15 s, followed by a progressive reduction until the fourth interval). We conclude that education had the greatest effect on the category fluency test in this Brazilian sample. Therefore, we must take care in evaluating performance in lower educational subjects.

Measurement of annexin V uptake and lactadherin labeling for the quantification of apoptosis in adherent Tca8113 and ACC-2 cells

Phosphatidylserine (PS) exposure occurs during the cell death program and fluorescein-labeled lactadherin permits the detection of PS exposure earlier than annexin V in suspended cell lines. Adherent cell lines were studied for this apoptosis-associated phenomenon to determine if PS probing methods are reliable because specific membrane damage may occur during harvesting. Apoptosis was induced in the human tongue squamous carcinoma cell line (Tca8113) and the adenoid cystic carcinoma cell line (ACC-2) by arsenic trioxide. Cells were harvested with a modified procedure and labeled with lactadherin and/or annexin V. PS exposure was localized by confocal microscopy and apoptosis was quantified by flow cytometry. The detachment procedure without trypsinization did not induce cell damage. In competition binding experiments, phospholipid vesicles competed for more than 95 and 90% of lactadherin but only about 75 and 70% of annexin V binding to Tca8113 and ACC-2 cells. These data indicate that PS exposure occurs in three stages during the cell death program and that fluorescein-labeled lactadherin permitted the detection of early PS exposure. A similar pattern of PS exposure has been observed in two malignant cell lines with different adherence, suggesting that this pattern of PS exposure is common in adherent cells. Both lactadherin and annexin V could be used in adherent Tca8113 and ACC-2 cell lines when an appropriate harvesting procedure was used. Lactadherin is more sensitive than annexin V for the detection of PS exposure as the physical structure of PS in these blebs and condensed apoptotic cell surface may be more conducive to binding lactadherin than annexin V.

Clustering of psychiatric and somatic illnesses in the general population: multimorbidity and socioeconomic correlates

The distribution of psychiatric disorders and of chronic medical illnesses was studied in a population-based sample to determine whether these conditions co-occur in the same individual. A representative sample (N = 1464) of adults living in households was assessed by the Composite International Diagnostic Interview, version 1.1, as part of the São Paulo Epidemiological Catchment Area Study. The association of sociodemographic variables and psychological symptoms regarding medical illness multimorbidity (8 lifetime somatic conditions) and psychiatric multimorbidity (15 lifetime psychiatric disorders) was determined by negative binomial regression. A total of 1785 chronic medical conditions and 1163 psychiatric conditions were detected in the population concentrated in 34.1 and 20% of respondents, respectively. Subjects reporting more psychiatric disorders had more medical illnesses. Characteristics such as age range (35-59 years, risk ratio (RR) = 1.3, and more than 60 years, RR = 1.7), being separated (RR = 1.2), being a student (protective effect, RR = 0.7), being of low educational level (RR = 1.2) and being psychologically distressed (RR = 1.1) were determinants of medical conditions. Age (35-59 years, RR = 1.2, and more than 60 years, RR = 0.5), being retired (RR = 2.5), and being psychologically distressed (females, RR = 1.5, and males, RR = 1.4) were determinants of psychiatric disorders. In conclusion, psychological distress and some sociodemographic features such as age, marital status, occupational status, educational level, and gender are associated with psychiatric and medical multimorbidity. The distribution of both types of morbidity suggests the need of integrating mental health into general clinical settings.

Encapsulated specialty oils commercialized in São Paulo state, Brazil: evaluation of identity (fatty acid profile) and compliance of fatty acids and Vitamin E contents with nutrition labeling

Encapsulated specialty oils commercialized in São Paulo state, Brazil, were evaluated for their identity (fatty acids profile) and compliance with nutrition labeling (fatty acids and Vitamin E (alpha tocopherol) contents). Twenty one samples [flaxseed oil (6), evening primrose (5), safflower (8), borage (1), and black currant (1)] purchased from local markets or collected by the health surveillance agency were analyzed. The fatty acids and vitamin E contents were analyzed by gas chromatography with flame ionization detector and liquid chromatography with UV detector, respectively. Nine samples were adulterated (5 samples of safflower oil, 3 of flaxseed oil, and one of evening primrose). Among them, 3 flaxseed and 2 safflower oil samples were probably adulterated by the addition of soybean oil. Conjugated linoleic acid (CLA) was found in two safflower oils samples although the sale of oils with conjugated linoleic acid (CLA) is not permitted by the National Health Surveillance Agency in Brazil (ANVISA). Only two samples presented all values in compliance with nutrition labeling (one safflower oil sample and one borage oil sample). The results show that a continuous monitoring of encapsulated specialty oils commercialized in Brazil is necessary including a greater number of samples and sanitary surveillance.

Intelligence acquisition methods in cyber domain : examining the circumstantial applicability of cyber intelligence acquisition methods using a hierarchical model

Phenomena in cyber domain, especially threats to security and privacy, have proven an increasingly heated topic addressed by different writers and scholars at an increasing pace – both nationally and internationally. However little public research has been done on the subject of cyber intelligence. The main research question of the thesis was: To what extent is the applicability of cyber intelligence acquisition methods circumstantial? The study was conducted in sequential a manner, starting with defining the concept of intelligence in cyber domain and identifying its key attributes, followed by identifying the range of intelligence methods in cyber domain, criteria influencing their applicability, and types of operatives utilizing cyber intelligence. The methods and criteria were refined into a hierarchical model. The existing conceptions of cyber intelligence were mapped through an extensive literature study on a wide variety of sources. The established understanding was further developed through 15 semi-structured interviews with experts of different backgrounds, whose wide range of points of view proved to substantially enhance the perspective on the subject. Four of the interviewed experts participated in a relatively extensive survey based on the constructed hierarchical model on cyber intelligence that was formulated in to an AHP hierarchy and executed in the Expert Choice Comparion online application. It was concluded that Intelligence in cyber domain is an endorsing, cross-cutting intelligence discipline that adds value to all aspects of conventional intelligence and furthermore that it bears a substantial amount of characteristic traits – both advantageous and disadvantageous – and furthermore that the applicability of cyber intelligence methods is partly circumstantially limited.

Cognitive Behavior Therapy for Obsessive-Compulsive Behavior in Children with Autism Spectrum Disorder: A Comparison of Hierarchical Linear Modelling and Visual Analysis

Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.

The Impact of Labeling in Childhood on the Sense of Self of Young Adults

Research studies on labeling of children have either focused on the effects of formal labels on the lives of children with exceptionalities and mental health issues, or the effect of informal labeling by parents, peers and teachers on teenagers. The effects of informal labeling in childhood and its implications in later life or for one’s career choice have not yet been examined. This study adds to the growing research on informal labeling. The purpose of this qualitative study was to determine what negative effects informal labeling of children as deviant had on their lives. Data were gathered through semi-structured interviews conducted with seventeen young adults, between the ages of sixteen and thirty years, from a post-secondary institution and an organization for homeless youth. The results showed an initial negative impact on the lives of the young adults during their childhood and early teenage years but as they progressed into their late teens and early adulthood, most were able to overcome their negative labels suggesting resilience. There were no significant gender differences in the impact of the labels. The implications of the study for policy makers and parents are discussed as well as some recommendations for parents and practitioners are offered.

Assessing the Reproducibility of Clustering of Molecular Dynamics Conformations on Self-Organizing Maps

The goal of most clustering algorithms is to find the optimal number of clusters (i.e. fewest number of clusters). However, analysis of molecular conformations of biological macromolecules obtained from computer simulations may benefit from a larger array of clusters. The Self-Organizing Map (SOM) clustering method has the advantage of generating large numbers of clusters, but often gives ambiguous results. In this work, SOMs have been shown to be reproducible when the same conformational dataset is independently clustered multiple times (~100), with the help of the Cramérs V-index (C_v). The ability of C_v to determine which SOMs are reproduced is generalizable across different SOM source codes. The conformational ensembles produced from MD (molecular dynamics) and REMD (replica exchange molecular dynamics) simulations of the penta peptide Met-enkephalin (MET) and the 34 amino acid protein human Parathyroid Hormone (hPTH) were used to evaluate SOM reproducibility. The training length for the SOM has a huge impact on the reproducibility. Analysis of MET conformational data definitively determined that toroidal SOMs cluster data better than bordered maps due to the fact that toroidal maps do not have an edge effect. For the source code from MATLAB, it was determined that the learning rate function should be LINEAR with an initial learning rate factor of 0.05 and the SOM should be trained by a sequential algorithm. The trained SOMs can be used as a supervised classification for another dataset. The toroidal 10×10 hexagonal SOMs produced from the MATLAB program for hPTH conformational data produced three sets of reproducible clusters (27%, 15%, and 13% of 100 independent runs) which find similar partitionings to those of smaller 6×6 SOMs. The χ^2 values produced as part of the C_v calculation were used to locate clusters with identical conformational memberships on independently trained SOMs, even those with different dimensions. The χ^2 values could relate the different SOM partitionings to each other.

(A) Photoregulation of DNA Functions by Cyclic Azobenzene-tethered Oligonucleotides (B) Site-specific Fluorescent Labeling of DNA using Inverse Electron Demand Diels-Alder Reaction between trans-Cyclooctene Derivatives and BODIPY-Tetrazine Adducts

(A) Most azobenzene-based photoswitches require UV light for photoisomerization, which limit their applications in biological systems due to possible photodamage. Cyclic azobenzene derivatives, on the other hand, can undergo cis-trans isomerization when exposed to visible light. A shortened synthetic scheme was developed for the preparation of a building block containing cyclic azobenzene and D-threoninol (cAB-Thr). trans-Cyclic azobenzene was found to thermally isomerize back to the cis-form in a temperature-dependent manner. cAB-Thr was transformed into the corresponding phosphoramidite and subsequently incorporated into oligonucleotides by solid phase synthesis. Melting temperature measurement suggested that incorporation of cis-cAB into oligonucleotides destabilizes DNA duplexes, these findings corroborate with circular dichroism measurement. Finally, Fluorescent Energy Resonance Transfer experiments indicated that trans-cAB can be accommodated in DNA duplexes. (B) Inverse Electron Demand Diels-Alder reactions (IEDDA) between trans-olefins and tetrazines provide a powerful alternative to existing ligation chemistries due to its fast reaction rate, bioorthogonality and mutual orthogonality with other click reactions. In this project, an attempt was pursued to synthesize trans-cyclooctene building blocks for oligonucleotide labeling by reacting with BODIPY-tetrazine. Rel-(1R-4E-pR)-cyclooct-4-enol and rel-(1R,8S,9S,4E)-Bicyclo[6.1.0]non-4-ene-9-ylmethanol were synthesized and then transformed into the corresponding propargyl ether. Subsequent Sonogashira reactions between these propargylated compounds with DMT-protected 5-iododeoxyuridine failed to give the desired products. Finally a methodology was pursued for the synthesis of BODIPY-tetrazine conjugates that will be used in future IEDDA reactions with trans-cyclooctene modified oligonucleotides.

Annotation syntaxico-sémantique des actants en corpus spécialisé

L’annotation en rôles sémantiques est une tâche qui permet d’attribuer des étiquettes de rôles telles que Agent, Patient, Instrument, Lieu, Destination etc. aux différents participants actants ou circonstants (arguments ou adjoints) d’une lexie prédicative. Cette tâche nécessite des ressources lexicales riches ou des corpus importants contenant des phrases annotées manuellement par des linguistes sur lesquels peuvent s’appuyer certaines approches d’automatisation (statistiques ou apprentissage machine). Les travaux antérieurs dans ce domaine ont porté essentiellement sur la langue anglaise qui dispose de ressources riches, telles que PropBank, VerbNet et FrameNet, qui ont servi à alimenter les systèmes d’annotation automatisés. L’annotation dans d’autres langues, pour lesquelles on ne dispose pas d’un corpus annoté manuellement, repose souvent sur le FrameNet anglais. Une ressource telle que FrameNet de l’anglais est plus que nécessaire pour les systèmes d’annotation automatisé et l’annotation manuelle de milliers de phrases par des linguistes est une tâche fastidieuse et exigeante en temps. Nous avons proposé dans cette thèse un système automatique pour aider les linguistes dans cette tâche qui pourraient alors se limiter à la validation des annotations proposées par le système. Dans notre travail, nous ne considérons que les verbes qui sont plus susceptibles que les noms d’être accompagnés par des actants réalisés dans les phrases. Ces verbes concernent les termes de spécialité d’informatique et d’Internet (ex. accéder, configurer, naviguer, télécharger) dont la structure actancielle est enrichie manuellement par des rôles sémantiques. La structure actancielle des lexies verbales est décrite selon les principes de la Lexicologie Explicative et Combinatoire, LEC de Mel’čuk et fait appel partiellement (en ce qui concerne les rôles sémantiques) à la notion de Frame Element tel que décrit dans la théorie Frame Semantics (FS) de Fillmore. Ces deux théories ont ceci de commun qu’elles mènent toutes les deux à la construction de dictionnaires différents de ceux issus des approches traditionnelles. Les lexies verbales d’informatique et d’Internet qui ont été annotées manuellement dans plusieurs contextes constituent notre corpus spécialisé. Notre système qui attribue automatiquement des rôles sémantiques aux actants est basé sur des règles ou classificateurs entraînés sur plus de 2300 contextes. Nous sommes limités à une liste de rôles restreinte car certains rôles dans notre corpus n’ont pas assez d’exemples annotés manuellement. Dans notre système, nous n’avons traité que les rôles Patient, Agent et Destination dont le nombre d’exemple est supérieur à 300. Nous avons crée une classe que nous avons nommé Autre où nous avons rassemblé les autres rôles dont le nombre d’exemples annotés est inférieur à 100. Nous avons subdivisé la tâche d’annotation en sous-tâches : identifier les participants actants et circonstants et attribuer des rôles sémantiques uniquement aux actants qui contribuent au sens de la lexie verbale. Nous avons soumis les phrases de notre corpus à l’analyseur syntaxique Syntex afin d’extraire les informations syntaxiques qui décrivent les différents participants d’une lexie verbale dans une phrase. Ces informations ont servi de traits (features) dans notre modèle d’apprentissage. Nous avons proposé deux techniques pour l’identification des participants : une technique à base de règles où nous avons extrait une trentaine de règles et une autre technique basée sur l’apprentissage machine. Ces mêmes techniques ont été utilisées pour la tâche de distinguer les actants des circonstants. Nous avons proposé pour la tâche d’attribuer des rôles sémantiques aux actants, une méthode de partitionnement (clustering) semi supervisé des instances que nous avons comparée à la méthode de classification de rôles sémantiques. Nous avons utilisé CHAMÉLÉON, un algorithme hiérarchique ascendant.

Clustering algorithms and shape factor methods to discriminate among small GTPase phenotypes using DIC image analysis.

Naïvement perçu, le processus d’évolution est une succession d’événements de duplication et de mutations graduelles dans le génome qui mènent à des changements dans les fonctions et les interactions du protéome. La famille des hydrolases de guanosine triphosphate (GTPases) similaire à Ras constitue un bon modèle de travail afin de comprendre ce phénomène fondamental, car cette famille de protéines contient un nombre limité d’éléments qui diffèrent en fonctionnalité et en interactions. Globalement, nous désirons comprendre comment les mutations singulières au niveau des GTPases affectent la morphologie des cellules ainsi que leur degré d’impact sur les populations asynchrones. Mon travail de maîtrise vise à classifier de manière significative différents phénotypes de la levure Saccaromyces cerevisiae via l’analyse de plusieurs critères morphologiques de souches exprimant des GTPases mutées et natives. Notre approche à base de microscopie et d’analyses bioinformatique des images DIC (microscopie d’interférence différentielle de contraste) permet de distinguer les phénotypes propres aux cellules natives et aux mutants. L’emploi de cette méthode a permis une détection automatisée et une caractérisation des phénotypes mutants associés à la sur-expression de GTPases constitutivement actives. Les mutants de GTPases constitutivement actifs Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V ont été analysés avec succès. En effet, l’implémentation de différents algorithmes de partitionnement, permet d’analyser des données qui combinent les mesures morphologiques de population native et mutantes. Nos résultats démontrent que l’algorithme Fuzzy C-Means performe un partitionnement efficace des cellules natives ou mutantes, où les différents types de cellules sont classifiés en fonction de plusieurs facteurs de formes cellulaires obtenus à partir des images DIC. Cette analyse démontre que les mutations Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V induisent respectivement des phénotypes amorphe, allongé, rond et large qui sont représentés par des vecteurs de facteurs de forme distincts. Ces distinctions sont observées avec différentes proportions (morphologie mutante / morphologie native) dans les populations de mutants. Le développement de nouvelles méthodes automatisées d’analyse morphologique des cellules natives et mutantes s’avère extrêmement utile pour l’étude de la famille des GTPases ainsi que des résidus spécifiques qui dictent leurs fonctions et réseau d’interaction. Nous pouvons maintenant envisager de produire des mutants de GTPases qui inversent leur fonction en ciblant des résidus divergents. La substitution fonctionnelle est ensuite détectée au niveau morphologique grâce à notre nouvelle stratégie quantitative. Ce type d’analyse peut également être transposé à d’autres familles de protéines et contribuer de manière significative au domaine de la biologie évolutive.

Distributed conditional computation

L'objectif de cette thèse est de présenter différentes applications du programme de recherche de calcul conditionnel distribué. On espère que ces applications, ainsi que la théorie présentée ici, mènera à une solution générale du problème d'intelligence artificielle, en particulier en ce qui a trait à la nécessité d'efficience. La vision du calcul conditionnel distribué consiste à accélérer l'évaluation et l'entraînement de modèles profonds, ce qui est très différent de l'objectif usuel d'améliorer sa capacité de généralisation et d'optimisation. Le travail présenté ici a des liens étroits avec les modèles de type mélange d'experts. Dans le chapitre 2, nous présentons un nouvel algorithme d'apprentissage profond qui utilise une forme simple d'apprentissage par renforcement sur un modèle d'arbre de décisions à base de réseau de neurones. Nous démontrons la nécessité d'une contrainte d'équilibre pour maintenir la distribution d'exemples aux experts uniforme et empêcher les monopoles. Pour rendre le calcul efficient, l'entrainement et l'évaluation sont contraints à être éparse en utilisant un routeur échantillonnant des experts d'une distribution multinomiale étant donné un exemple. Dans le chapitre 3, nous présentons un nouveau modèle profond constitué d'une représentation éparse divisée en segments d'experts. Un modèle de langue à base de réseau de neurones est construit à partir des transformations éparses entre ces segments. L'opération éparse par bloc est implémentée pour utilisation sur des cartes graphiques. Sa vitesse est comparée à deux opérations denses du même calibre pour démontrer le gain réel de calcul qui peut être obtenu. Un modèle profond utilisant des opérations éparses contrôlées par un routeur distinct des experts est entraîné sur un ensemble de données d'un milliard de mots. Un nouvel algorithme de partitionnement de données est appliqué sur un ensemble de mots pour hiérarchiser la couche de sortie d'un modèle de langage, la rendant ainsi beaucoup plus efficiente. Le travail présenté dans cette thèse est au centre de la vision de calcul conditionnel distribué émis par Yoshua Bengio. Elle tente d'appliquer la recherche dans le domaine des mélanges d'experts aux modèles profonds pour améliorer leur vitesse ainsi que leur capacité d'optimisation. Nous croyons que la théorie et les expériences de cette thèse sont une étape importante sur la voie du calcul conditionnel distribué car elle cadre bien le problème, surtout en ce qui concerne la compétitivité des systèmes d'experts.

SPATIAL CLUSTERING ALGORITHMS-AN OVERVIEW.

An Overview of known spatial clustering algorithms The space of interest can be the two-dimensional abstraction of the surface of the earth or a man-made space like the layout of a VLSI design, a volume containing a model of the human brain, or another 3d-space representing the arrangement of chains of protein molecules. The data consists of geometric information and can be either discrete or continuous. The explicit location and extension of spatial objects define implicit relations of spatial neighborhood (such as topological, distance and direction relations) which are used by spatial data mining algorithms. Therefore, spatial data mining algorithms are required for spatial characterization and spatial trend analysis. Spatial data mining or knowledge discovery in spatial databases differs from regular data mining in analogous with the differences between non-spatial data and spatial data. The attributes of a spatial object stored in a database may be affected by the attributes of the spatial neighbors of that object. In addition, spatial location, and implicit information about the location of an object, may be exactly the information that can be extracted through spatial data mining