Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain’s neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

An evaluation of the accuracy of models for the determination of the weighted mean temperature of the atmosphere

The estimates of the zenith wet delay resulting from the analysis of data from space techniques, such as GPS and VLBI, have a strong potential in climate modeling and weather forecast applications. In order to be useful to meteorology, these estimates have to be converted to precipitable water vapor, a process that requires the knowledge of the weighted mean temperature of the atmosphere, which varies both in space and time. In recent years, several models have been proposed to predict this quantity. Using a database of mean temperature values obtained by ray-tracing radiosonde profiles of more than 100 stations covering the globe, and about 2.5 year’s worth of data, we have analyzed several of these models. Based on data from the European region, we have concluded that the models provide identical levels of precision, but different levels of accuracy. Our results indicate that regionally-optimized models do not provide superior performance compared to the global models.

Characterization of pro- and anti-angiogenic factors in models of diabetic retinopathy

Dissertação de mestrado, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2015

Business Models for Cloud Computing: Experiences from Developing Modeling & Simulation as a Service Applications in Industry

The potential of cloud computing is gaining significant interest in Modeling & Simulation (M&S). The underlying concept of using computing power as a utility is very attractive to users that can access state-of-the-art hardware and software without capital investment. Moreover, the cloud computing characteristics of rapid elasticity and the ability to scale up or down according to workload make it very attractive to numerous applications including M&S. Research and development work typically focuses on the implementation of cloud-based systems supporting M&S as a Service (MSaaS). Such systems are typically composed of a supply chain of technology services. How is the payment collected from the end-user and distributed to the stakeholders in the supply chain? We discuss the business aspects of developing a cloud platform for various M&S applications. Business models from the perspectives of the stakeholders involved in providing and using MSaaS and cloud computing are investigated and presented.

Application of genetic algorithms in the design of an electrical potential of fractional order

Fractional calculus (FC) is currently being applied in many areas of science and technology. In fact, this mathematical concept helps the researches to have a deeper insight about several phenomena that integer order models overlook. Genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. This methodology applies the concepts that describe biological evolution to obtain optimal solution in many different applications. In this line of thought, in this work we use the FC and the GA concepts to implement the electrical fractional order potential. The performance of the GA scheme, and the convergence of the resulting approximation, are analyzed. The results are analyzed for different number of charges and several fractional orders.

Implementation of fractional-order electromagnetic potential through a genetic algorithm

Several phenomena present in electrical systems motivated the development of comprehensive models based on the theory of fractional calculus (FC). Bearing these ideas in mind, in this work are applied the FC concepts to define, and to evaluate, the electrical potential of fractional order, based in a genetic algorithm optimization scheme. The feasibility and the convergence of the proposed method are evaluated.

Models and tools for value systems analysis in collaborative environments

Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative Networks

Development of human central nervous system 3D in vitro models for preclinical research

Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.

Species distribution models reveal apparent competitive and facilitative effects of a dominant species on the distribution of tundra plants

Abiotic factors are considered strong drivers of species distribution and assemblages. Yet these spatial patterns are also influenced by biotic interactions. Accounting for competitors or facilitators may improve both the fit and the predictive power of species distribution models (SDMs). We investigated the influence of a dominant species, Empetrum nigrum ssp. hermaphroditum, on the distribution of 34 subordinate species in the tundra of northern Norway. We related SDM parameters of those subordinate species to their functional traits and their co-occurrence patterns with E. hermaphroditum across three spatial scales. By combining both approaches, we sought to understand whether these species may be limited by competitive interactions and/or benefit from habitat conditions created by the dominant species. The model fit and predictive power increased for most species when the frequency of occurrence of E. hermaphroditum was included in the SDMs as a predictor. The largest increase was found for species that 1) co-occur most of the time with E. hermaphroditum, both at large (i.e. 750 m) and small spatial scale (i.e. 2 m) or co-occur with E. hermaphroditum at large scale but not at small scale and 2) have particularly low or high leaf dry matter content (LDMC). Species that do not co-occur with E. hermaphroditum at the smallest scale are generally palatable herbaceous species with low LDMC, thus showing a weak ability to tolerate resource depletion that is directly or indirectly induced by E. hermaphroditum. Species with high LDMC, showing a better aptitude to face resource depletion and grazing, are often found in the proximity of E. hermaphroditum. Our results are consistent with previous findings that both competition and facilitation structure plant distribution and assemblages in the Arctic tundra. The functional and co-occurrence approaches used were complementary and provided a deeper understanding of the observed patterns by refinement of the pool of potential direct and indirect ecological effects of E. hermaphroditum on the distribution of subordinate species. Our correlative study would benefit being complemented by experimental approaches.

CD4+CD25+Foxp3+ regulatory T cells: from basic research to potential therapeutic use.

Regulatory T cells control immune responses to self- and foreign-antigens and play a major role in maintaining the balance between immunity and tolerance. This article reviews recent key developments in the field of CD4+CD25+Foxp3+ regulatory T (TREG) cells. It presents their characteristics and describes their range of activity and mechanisms of action. Some models of diseases triggered by the imbalance between TREG cells and effector pathogenic T cells are described and their potential therapeutic applications in humans are outlined.

The paracaspase MALT1: biological function and potential for therapeutic inhibition.

The paracaspase MALT1 has a central role in the activation of lymphocytes and other immune cells including myeloid cells, mast cells and NK cells. MALT1 activity is required not only for the immune response, but also for the development of natural Treg cells that keep the immune response in check. Exaggerated MALT1 activity has been associated with the development of lymphoid malignancies, and recently developed MALT1 inhibitors show promising anti-tumor effects in xenograft models of diffuse large B cell lymphoma. In this review, we provide an overview of the present understanding of MALT1's function, and discuss possibilities for its therapeutic targeting based on recently developed inhibitors and animal models.

QUANTIFICATION AND EXTRACTION OF SURFACE FEATURES FROM DIGITAL TERRAIN MODELS

Digital Terrain Models (DTMs) are important in geology and geomorphology, since elevation data contains a lot of information pertaining to geomorphological processes that influence the topography. The first derivative of topography is attitude; the second is curvature. GIS tools were developed for derivation of strike, dip, curvature and curvature orientation from Digital Elevation Models (DEMs). A method for displaying both strike and dip simultaneously as colour-coded visualization (AVA) was implemented. A plug-in for calculating strike and dip via Least Squares Regression was created first using VB.NET. Further research produced a more computationally efficient solution, convolution filtering, which was implemented as Python scripts. These scripts were also used for calculation of curvature and curvature orientation. The application of these tools was demonstrated by performing morphometric studies on datasets from Earth and Mars. The tools show promise, however more work is needed to explore their full potential and possible uses.

Investigating the role of potential genetic markers that can predict risk for steroid refractory inflammatory bowel disease

Contexte - La variation interindividuelle de la réponse aux corticostéroïdes (CS) est un problème important chez les patients atteints de maladies inflammatoires d’intestin. Ce problème est bien plus accentué chez les enfants avec la prévalence de la corticodépendance extrêmement (~40 %) élevée. La maladie réfractaire au CS a des répercussions sur le développement et le bien-être physique et psychologique des patients et impose des coûts médicaux élevés, particulièrement avec la maladie active comparativement à la maladie en rémission, le coût étant 2-3 fois plus élevé en ambulatoire et 20 fois plus élevé en hôpital. Il est ainsi primordial de déterminer les marqueurs prédictifs de la réponse aux CS. Les efforts précédents de découvrir les marqueurs cliniques et démographiques ont été équivoques, ce qui souligne davantage le besoin de marqueurs moléculaires. L'action des CS se base sur des processus complexes déterminés génétiquement. Deux gènes, le ABCB1, appartenant à la famille des transporteurs transmembraneaux, et le NR3C1, encodant le récepteur glucocorticoïde, sont des éléments importants des voies métaboliques. Nous avons postulé que les variations dans ces gènes ont un rôle dans la variabilité observée de la réponse aux CS et pourraient servir en tant que les marqueurs prédictifs. Objectifs - Nous avons visé à: (1) examiner le fardeau de la maladie réfractaire aux CS chez les enfants avec la maladie de Crohn (MC) et le rôle des caractéristiques cliniques et démographiques potentiellement liés à la réponse; (2) étudier l'association entre les variantes d'ADN de gène ABCB1 et la réponse aux CS; (3) étudier les associations entre les variantes d'ADN de gène NR3C1 et la réponse aux CS. Méthodes - Afin d’atteindre ces objectifs, nous avons mené une étude de cohorte des patients recrutés dans deux cliniques pédiatriques tertiaires de gastroentérologie à l’Ottawa (CHEO) et à Montréal (HSJ). Les patients avec la MC ont été diagnostiqués avant l'âge de 18 ans selon les critères standard radiologiques, endoscopiques et histopathologiques. La corticorésistance et la corticodépendance ont été définies en adaptant les critères reconnus. L’ADN, acquise soit du sang ou de la salive, était génotypée pour des variations à travers de gènes ABCB1 et NR3C1 sélectionnées à l’aide de la méthodologie de tag-SNP. La fréquence de la corticorésistance et la corticodépendance a été estimée assumant une distribution binomiale. Les associations entre les variables cliniques/démographiques et la réponse aux CS ont été examinées en utilisant la régression logistique en ajustant pour des variables potentielles de confusion. Les associations entre variantes génétiques de ABCB1 et NR3C1 et la réponse aux CS ont été examinées en utilisant la régression logistique assumant différents modèles de la transmission. Les associations multimarqueurs ont été examinées en utilisant l'analyse de haplotypes. Les variantes nongénotypées ont été imputées en utilisant les données de HAPMAP et les associations avec SNPs imputés ont été examinées en utilisant des méthodes standard. Résultats - Parmi 645 patients avec la MC, 364 (56.2%) ont reçu CS. La majorité de patients étaient des hommes (54.9 %); présentaient la maladie de l’iléocôlon (51.7%) ou la maladie inflammatoire (84.6%) au diagnostic et étaient les Caucasiens (95.6 %). Huit pourcents de patients étaient corticorésistants et 40.9% - corticodépendants. Le plus bas âge au diagnostic (OR=1.34, 95% CI: 1.03-3.01, p=0.040), la maladie cœxistante de la région digestive supérieure (OR=1.35, 95% CI: 95% CI: 1.06-3.07, p=0.031) et l’usage simultané des immunomodulateurs (OR=0.35, 95% CI: 0.16-0.75, p=0.007) ont été associés avec la corticodépendance. Un total de 27 marqueurs génotypés à travers de ABCB1 (n=14) et NR3C1 (n=13) ont été en l'Équilibre de Hardy-Weinberg, à l’exception d’un dans le gène NR3C1 (rs258751, exclu). Dans ABCB1, l'allèle rare de rs2032583 (OR=0.56, 95% CI: 0.34-0.95, p=0.029) et génotype hétérozygote (OR=0.52, 95% CI: 0.28-0.95 p=0.035) ont été négativement associes avec la dépendance de CS. Un haplotype à 3 marqueurs, comprenant le SNP fonctionnel rs1045642 a été associé avec la dépendance de CS (p empirique=0.004). 24 SNPs imputés introniques et six haplotypes ont été significativement associés avec la dépendance de CS. Aucune de ces associations n'a cependant maintenu la signification après des corrections pour des comparaisons multiples. Dans NR3C1, trois SNPs: rs10482682 (OR=1.43, 95% CI: 0.99-2.08, p=0.047), rs6196 (OR=0.55, 95% CI: 0.31-0.95, p=0.024), et rs2963155 (OR=0.64, 95% CI: 0.42-0.98, p=0.039), ont été associés sous un modèle additif, tandis que rs4912911 (OR=0.37, 95% CI: 0.13-1.00, p=0.03) et rs2963156 (OR=0.32, 95% CI: 0.07-1.12, p=0.047) - sous un modèle récessif. Deux haplotypes incluant ces 5 SNPs (AAACA et GGGCG) ont été significativement (p=0.006 et 0.01 empiriques) associés avec la corticodépendance. 19 SNPs imputés ont été associés avec la dépendance de CS. Deux haplotypes multimarqueurs (p=0.001), incluant les SNPs génotypés et imputés, ont été associés avec la dépendance de CS. Conclusion - Nos études suggèrent que le fardeau de la corticodépendance est élevé parmi les enfants avec le CD. Les enfants plus jeunes au diagnostic et ceux avec la maladie coexistante de la région supérieure ainsi que ceux avec des variations dans les gènes ABCB1 et NR3C1 étaient plus susceptibles de devenir corticodépendants.

A class of bivariate Erlang distributions and ruin probabilities in multivariate risk models

Nous y introduisons une nouvelle classe de distributions bivariées de type Marshall-Olkin, la distribution Erlang bivariée. La transformée de Laplace, les moments et les densités conditionnelles y sont obtenus. Les applications potentielles en assurance-vie et en finance sont prises en considération. Les estimateurs du maximum de vraisemblance des paramètres sont calculés par l'algorithme Espérance-Maximisation. Ensuite, notre projet de recherche est consacré à l'étude des processus de risque multivariés, qui peuvent être utiles dans l'étude des problèmes de la ruine des compagnies d'assurance avec des classes dépendantes. Nous appliquons les résultats de la théorie des processus de Markov déterministes par morceaux afin d'obtenir les martingales exponentielles, nécessaires pour établir des bornes supérieures calculables pour la probabilité de ruine, dont les expressions sont intraitables.

The potential utility of age, triage score, and disposition data contained in emergency department electronic records for influenza-like illness surveillance in Montreal

La surveillance de l’influenza s’appuie sur un large spectre de données, dont les données de surveillance syndromique provenant des salles d’urgences. De plus en plus de variables sont enregistrées dans les dossiers électroniques des urgences et mises à la disposition des équipes de surveillance. L’objectif principal de ce mémoire est d’évaluer l’utilité potentielle de l’âge, de la catégorie de triage et de l’orientation au départ de l’urgence pour améliorer la surveillance de la morbidité liée aux cas sévères d’influenza. Les données d’un sous-ensemble des hôpitaux de Montréal ont été utilisées, d’avril 2006 à janvier 2011. Les hospitalisations avec diagnostic de pneumonie ou influenza ont été utilisées comme mesure de la morbidité liée aux cas sévères d’influenza, et ont été modélisées par régression binomiale négative, en tenant compte des tendances séculaires et saisonnières. En comparaison avec les visites avec syndrome d’allure grippale (SAG) totales, les visites avec SAG stratifiées par âge, par catégorie de triage et par orientation de départ ont amélioré le modèle prédictif des hospitalisations avec pneumonie ou influenza. Avant d’intégrer ces variables dans le système de surveillance de Montréal, des étapes additionnelles sont suggérées, incluant l’optimisation de la définition du syndrome d’allure grippale à utiliser, la confirmation de la valeur de ces prédicteurs avec de nouvelles données et l’évaluation de leur utilité pratique.