Intra- and inter-hemispheric interactions in somatosensory processing of pain : dynamical causal modeling analysis of fMRI data

La douleur est une expérience perceptive comportant de nombreuses dimensions. Ces dimensions de douleur sont inter-reliées et recrutent des réseaux neuronaux qui traitent les informations correspondantes. L’élucidation de l'architecture fonctionnelle qui supporte les différents aspects perceptifs de l'expérience est donc une étape fondamentale pour notre compréhension du rôle fonctionnel des différentes régions de la matrice cérébrale de la douleur dans les circuits corticaux qui sous tendent l'expérience subjective de la douleur. Parmi les diverses régions du cerveau impliquées dans le traitement de l'information nociceptive, le cortex somatosensoriel primaire et secondaire (S1 et S2) sont les principales régions généralement associées au traitement de l'aspect sensori-discriminatif de la douleur. Toutefois, l'organisation fonctionnelle dans ces régions somato-sensorielles n’est pas complètement claire et relativement peu d'études ont examiné directement l'intégration de l'information entre les régions somatiques sensorielles. Ainsi, plusieurs questions demeurent concernant la relation hiérarchique entre S1 et S2, ainsi que le rôle fonctionnel des connexions inter-hémisphériques des régions somatiques sensorielles homologues. De même, le traitement en série ou en parallèle au sein du système somatosensoriel constitue un autre élément de questionnement qui nécessite un examen plus approfondi. Le but de la présente étude était de tester un certain nombre d'hypothèses sur la causalité dans les interactions fonctionnelle entre S1 et S2, alors que les sujets recevaient des chocs électriques douloureux. Nous avons mis en place une méthode de modélisation de la connectivité, qui utilise une description de causalité de la dynamique du système, afin d'étudier les interactions entre les sites d'activation définie par un ensemble de données provenant d'une étude d'imagerie fonctionnelle. Notre paradigme est constitué de 3 session expérimentales en utilisant des chocs électriques à trois différents niveaux d’intensité, soit modérément douloureux (niveau 3), soit légèrement douloureux (niveau 2), soit complètement non douloureux (niveau 1). Par conséquent, notre paradigme nous a permis d'étudier comment l'intensité du stimulus est codé dans notre réseau d'intérêt, et comment la connectivité des différentes régions est modulée dans les conditions de stimulation différentes. Nos résultats sont en faveur du mode sériel de traitement de l’information somatosensorielle nociceptive avec un apport prédominant de la voie thalamocorticale vers S1 controlatérale au site de stimulation. Nos résultats impliquent que l'information se propage de S1 controlatéral à travers notre réseau d'intérêt composé des cortex S1 bilatéraux et S2. Notre analyse indique que la connexion S1→S2 est renforcée par la douleur, ce qui suggère que S2 est plus élevé dans la hiérarchie du traitement de la douleur que S1, conformément aux conclusions précédentes neurophysiologiques et de magnétoencéphalographie. Enfin, notre analyse fournit des preuves de l'entrée de l'information somatosensorielle dans l'hémisphère controlatéral au côté de stimulation, avec des connexions inter-hémisphériques responsable du transfert de l'information à l'hémisphère ipsilatéral.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.

The Degree of Word-Expansion of Lexicalized RRWW-Automata

Restarting automata can be seen as analytical variants of classical automata as well as of regulated rewriting systems. We study a measure for the degree of nondeterminism of (context-free) languages in terms of deterministic restarting automata that are (strongly) lexicalized. This measure is based on the number of auxiliary symbols (categories) used for recognizing a language as the projection of its characteristic language onto its input alphabet. This type of recognition is typical for analysis by reduction, a method used in linguistics for the creation and verification of formal descriptions of natural languages. Our main results establish a hierarchy of classes of context-free languages and two hierarchies of classes of non-context-free languages that are based on the expansion factor of a language.

Understanding Recreational Services of Urban Riverfront Space for Planning Purposes

In the process of urbanization, natural and semi-natural landscapes are increasingly cherished as open space and recreational resource. Urban rivers are part of this kind of resource and thus play an important role in managing urban resilience and health. Employing the example of Tianjin, this doctoral dissertation research aims at learning to understand how to plan and design for the interface zones between urban water courses and for the land areas adjacent to such water courses. This research also aims at learning how to link waterfront space with other urban space in order to make a recreational space system for the benefit of people. Five questions of this dissertation are: 1) what is the role of rivers in spatial and open space planning? 2) What are the human needs regarding outdoor open space? 3) How do river and water front spatial structures affect people's recreational activities? 4) How to define the recreational service of urban river and waterfront open space? 5) How might answering these question change planning and design of urban open space? Quantitative and qualitative empirical approaches were combined in this study for which literature review and theoretical explorations provide the basis. Empirical investigations were conducted in the city of Tianjin. The quantitative approach includes conducting 267 quantitative interviews, and the qualitative approach includes carrying out field observations and mappings. GIS served to support analysis and visualization of empirical information that was generated through this study. By responding to the five research questions, findings and lessons include the following: 1) In the course of time rivers have gained importance in all levels and scales of spatial planning and decision making. Regarding the development of ecological networks, mainly at national scale, rivers are considered significant linear elements. Regarding regional and comprehensive development, river basins and watersheds are often considered as the structural link for strategic ecological, economic, social and recreational planning. For purposes of urban planning, particularly regarding recreational services in cities, the distribution of urban open spaces often follows the structure of river systems. 2) For the purpose of classifying human recreational needs that relate to outdoor open space Maslow's hierarchy of human needs serves as theoretical basis. The classes include geographical, safety, physiological, social and aesthetic need. These classes serve as references while analyzing river and waterfront open space and other kinds of open space. 3) Regarding the question how river and waterfront spatial structures might affect people's recreational activities, eight different landscape units were identified and compared in the case study area. Considering the thermal conditions of Tianjin, one of these landscape units was identified as affording the optimal spatial arrangement which mostly meets recreational needs. The size and the shape of open space, and the plants present in an open space have been observed as being most relevant regarding recreational activities. 4) Regarding the recreational service of urban river and waterfront open space the results of this research suggest that the recreational service is felt less intensively as the distances between water 183 front and open space user’s places of residence are increasing. As a method for estimating this ‘Service Distance Effect’ the following formula may be used: Y = a*ebx. In this equation Y means the ‘Service Distance’ between homes and open space, and X means the percentage of the people who live within this service distance. Coefficient "a" represents the distance of the residential area nearest to the water front. The coefficient "b" is a comprehensive capability index that refers to the size of the available and suitable recreational area. 5) Answers found to the questions above have implications for the planning and design of urban open space. The results from the quantitative study of recreational services of waterfront open space were applied to the assessment of river-based open space systems. It is recommended that such assessments might be done employing the network analysis function available with any GIS. In addition, several practical planning and designing suggestions are made that would help remedy any insufficient base for satisfying recreational needs. The understanding of recreational need is considered helpful for the proposing planning and designing ideas and for the changing of urban landscapes. In the course of time Tianjin's urban water system has shrunk considerably. At the same time rivers and water courses have shaped Tianjin's urban structure in noticeable ways. In the process of urbanization water has become increasingly important to the citizens and their everyday recreations. Much needs to be changed in order to improve recreational opportunities and to better provide for a livable city, most importantly when considering the increasing number of old people. Suggestions made that are based on results of this study, might be implemented in Tianjin. They are 1) to promote the quality of the waterfront open space and to make all linear waterfront area accessible recreational spaces. Then, 2), it is advisable to advocate the concept of green streets and to combine green streets with river open space in order to form an everyday recreational network. And 3) any sound urban everyday recreational service made cannot rely on only urban rivers; the whole urban structure needs to be improved, including adding small open space and optimize the form of urban communities, finally producing a multi-functional urban recreational network.

Improving Multi-class Text Classification with Naive Bayes

There are numerous text documents available in electronic form. More and more are becoming available every day. Such documents represent a massive amount of information that is easily accessible. Seeking value in this huge collection requires organization; much of the work of organizing documents can be automated through text classification. The accuracy and our understanding of such systems greatly influences their usefulness. In this paper, we seek 1) to advance the understanding of commonly used text classification techniques, and 2) through that understanding, improve the tools that are available for text classification. We begin by clarifying the assumptions made in the derivation of Naive Bayes, noting basic properties and proposing ways for its extension and improvement. Next, we investigate the quality of Naive Bayes parameter estimates and their impact on classification. Our analysis leads to a theorem which gives an explanation for the improvements that can be found in multiclass classification with Naive Bayes using Error-Correcting Output Codes. We use experimental evidence on two commonly-used data sets to exhibit an application of the theorem. Finally, we show fundamental flaws in a commonly-used feature selection algorithm and develop a statistics-based framework for text feature selection. Greater understanding of Naive Bayes and the properties of text allows us to make better use of it in text classification.

Multiclass Classification of SRBCTs

A novel approach to multiclass tumor classification using Artificial Neural Networks (ANNs) was introduced in a recent paper cite{Khan2001}. The method successfully classified and diagnosed small, round blue cell tumors (SRBCTs) of childhood into four distinct categories, neuroblastoma (NB), rhabdomyosarcoma (RMS), non-Hodgkin lymphoma (NHL) and the Ewing family of tumors (EWS), using cDNA gene expression profiles of samples that included both tumor biopsy material and cell lines. We report that using an approach similar to the one reported by Yeang et al cite{Yeang2001}, i.e. multiclass classification by combining outputs of binary classifiers, we achieved equal accuracy with much fewer features. We report the performances of 3 binary classifiers (k-nearest neighbors (kNN), weighted-voting (WV), and support vector machines (SVM)) with 3 feature selection techniques (Golub's Signal to Noise (SN) ratios cite{Golub99}, Fisher scores (FSc) and Mukherjee's SVM feature selection (SVMFS))cite{Sayan98}.

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

Análisis de la diplomacia cultural de Brasil como una estrategia para consolidarse como potencia emergente en el sistema internacional, a partir del segundo período presidencial de Luis Inácio Lula Da Silva

Este trabajo de grado es una aproximación a la Diplomacia Cultural como un instrumento político retomado por Luis Inácio Lula Da Silva, del cual Brasil se sirve para ganar un espacio en el Sistema Internacional, ascender en la jerarquización de los Estados y posicionarse como una Potencia Emergente. Del conjunto de elementos que componen la Diplomacia Cultural y otros factores típicos como la economía, este país Latinoamericano se convierte en un jugador global.

A matter of fundamentals : sound and silence in the radio drama of Samuel Beckett

Samuel Beckett was arguably one of the most influential writers of the 20th century. Known for his stage plays, including the renowned En attendant Godot (1948), Beckett’s contribution to the field of radio drama is often overlooked. His corpus of radio dramas included some of the most innovativeradio works of the post-World War II period. For Beckett, radio drama was not exclusively verbocentric, for he always maintained that his work was “a matter of fundamental sounds (no joke intended) made as fully as possible” (Frost 362). His (radio) drama aesthetics defined a strict hierarchy of sound whereby the dramatist balances sound effects, music and the characters’ dialogue – and the use of silence. In this essay, I examine the juxtaposition of sound and silence in Samuel Beckett’s most influential radio dramas: All That Fall, Embers, Words and Music and Cascando. In the end, this essay will show that the sounds and silence employed in Beckett’s radio dramatic works were inextricably linked, which added to the overall meaning of his dramas.

Vigencia de La novela ecuatoriana, de Ángel F. Rojas (Dossier: Cuatro narradores del 30, relecturas en su centenario)

Luego de ubicar a Ángel F. Rojas entre los ensayistas de temas literarios de su generación, la autora sustenta la vigencia del crítico lojano. Más allá de que no exista, en el siglo XX, ningún otro estudio de similar alcance sobre la novela ecuatoriana, plantea que los méritos de esta obra radican en los criterios de periodización empleados, en que los juicios emitidos se sustentan en criterios estéticos, y en que jerarquiza las obras de acuerdo a su valor literario, no se trata de crítica impresionista o biografista, ni sesgada negativamente por consideraciones ideológicas. Rojas incluye, entonces, tres rasgos propios de la moderna crítica literaria: el deslinde, el establecimiento de jerarquías y la emisión de juicios sustentados en la literaturidad de las obras. Un buen número de las conclusiones del autor mantiene actualidad, igual ocurre con la significación de muchas de ellas en el canon del país. El texto de Rojas inicia la moderna crítica literaria ecuatoriana, y mantiene su lugar referencial entre los estudios de la novela en este país.

Learning a procedural task: effectiveness of multimedia presentations

Three experiments investigated the effectiveness of presenting procedural information through different media and their combinations. Experiment 1 examined the effectiveness of text, line drawings, text and line drawings, video. and video stills for learning a first aid task. The results showed an advantage of text and line drawings and of the video presentation over the other three conditions for both bandaging performance and answering questions about the task. Experiment 2 showed that the beneficial effect of the combination of text and pictures could not be accounted for simply in terms of a dual coding explanation. Rather, the effectiveness of the media and their combinations was influenced by the extent to which they conveyed action information. Finally, Experiment 3 showed no evidence of a contiguity effect: text and pictures were as effective when presented together on the same screen as when they were presented separately. Copyright © 2000 John Wiley & Sons, Ltd.

Phylogeny and the hierarchical organization of plant diversity

R. H. Whittaker's idea that plant diversity can be divided into a hierarchy of spatial components from alpha at the within-habitat scale through beta for the turnover of species between habitats to gamma along regional gradients implies the underlying existence of alpha, beta, and gamma niches. We explore the hypothesis that the evolution of a, (3, and gamma niches is also hierarchical, with traits that define the a niche being labile, while those defining a and 7 niches are conservative. At the a level we find support for the hypothesis in the lack of close significant phylogenetic relationship between meadow species that have similar a niches. In a second test, a niche overlap based on a variety of traits is compared between congeners and noncongeners in several communities; here, too, there is no evidence of a correlation between a niche and phylogeny. To test whether beta and gamma niches evolve conservatively, we reconstructed the evolution of relevant traits on evolutionary trees for 14 different clades. Tests against null models revealed a number of instances, including some in island radiations, in which habitat (beta niche) and elevational maximum (an aspect of the gamma niche) showed evolutionary conservatism.

Responsiveness to change by standard-form contract drafters: A case study of the FIDIC White Book

Purpose – The purpose of this paper is to focus on the Fédération Internationale des Ingénieurs-Conseils (FIDIC) White Book standard form of building contract. It tracks the changes to this contract over its four editions, and seeks to identify their underlying causes. Design/methodology/approach – The changes made to the White Book are quantified using a specific type of quantitative content analysis. The amended clauses are then examined to understand the nature of the changes made. Findings – The length of the contract increased by 34 per cent between 1990 and 2006. A large proportion of the overall increase can be attributed to the clauses dealing with “conflict of interest/corruption” and “dispute resolution”. In both instances, the FIDIC drafting committees have responded to international developments to discourage corruption, and to encourage the use of alternative dispute resolution. Between 1998 and 2006, the average length of the sentences increased slightly, raising the question of whether long sentences are easily understood by users of contracts. Research limitations/implications – Quantification of text appears to be particularly useful for the analysis of documents which are regularly updated because changes can be clearly identified and the length of sentences can be determined, leading to conclusions about the readability of the text. However, caution is needed because changes of great relevance can be made to contract clauses without actually affecting their length. Practical implications – The paper will be instructive for contract drafters and informative for users of FIDIC's White Book. Originality/value – Quantifying text has been rarely used regarding standard-form contracts in the field of construction.