Investigating the effects of caffeine on executive functions using traditional Stroop and a new ecologically-valid virtual reality task, the Jansari assessment of Executive Functions (JEF©)

Objective: Caffeine has been shown to have effects on certain areas of cognition, but in executive functioning the research is limited and also inconsistent. One reason could be the need for a more sensitive measure to detect the effects of caffeine on executive function. This study used a new non-immersive virtual reality assessment of executive functions known as JEF© (the Jansari Assessment of Executive Function) alongside the ‘classic’ Stroop Colour- Word task to assess the effects of a normal dose of caffeinated coffee on executive function. Method: Using a double-blind, counterbalanced within participants procedure 43 participants were administered either a caffeinated or decaffeinated coffee and completed the ‘JEF©’ and Stroop tasks, as well as a subjective mood scale and blood pressure pre- and post condition on two separate occasions a week apart. JEF© yields measures for eight separate aspects of executive functions, in addition to a total average score. Results: Findings indicate that performance was significantly improved on the planning, creative thinking, event-, time- and action-based prospective memory, as well as total JEF© score following caffeinated coffee relative to the decaffeinated coffee. The caffeinated beverage significantly decreased reaction times on the Stroop task, but there was no effect on Stroop interference. Conclusion: The results provide further support for the effects of a caffeinated beverage on cognitive functioning. In particular, it has demonstrated the ability of JEF© to detect the effects of caffeine across a number of executive functioning constructs, which weren’t shown in the Stroop task, suggesting executive functioning improvements as a result of a ‘typical’ dose of caffeine may only be detected by the use of more real-world, ecologically valid tasks.

Random extremal solutions of differential inclusions

Given a Lipschitz continuous multifunction $F$ on ${\mathbb{R}}^{n}$, we construct a probability measure on the set of all solutions to the Cauchy problem $\dot x\in F(x)$ with $x(0)=0$. With probability one, the derivatives of these random solutions take values within the set $ext F(x)$ of extreme points for a.e.~time $t$. This provides an alternative approach in the analysis of solutions to differential inclusions with non-convex right hand side.

Conception mécaniste-empirique des chaussées non revêtues

Dans le contexte où les routes non revêtues sont susceptibles de subir des charges importantes, une méthode rigoureuse pour la conception de ces chaussées basée sur des principes mécanistes-empiriques et sur le comportement mécanique des sols support est souhaitable. La conception mécaniste combinée à des lois d’endommagement permet l’optimisation des structures de chaussées non revêtues ainsi que la réduction des coûts de construction et d’entretien. Le but de ce projet est donc la mise au point d’une méthode de conception mécaniste-empirique adaptée aux chaussées non revêtues. Il a été question tout d’abord de mettre au point un code de calcul pour la détermination des contraintes et des déformations dans la chaussée. Ensuite, des lois d’endommagement empiriques pour les chaussées non revêtues ont été développées. Enfin, les méthodes de calcul ont permis la création d’abaques de conception. Le développement du code de calcul a consisté en une modélisation de la chaussée par un système élastique multi-couches. La modélisation a été faite en utilisant la transformation d’Odemark et les équations de Boussinesq pour le calcul des déformations sous la charge. L’élaboration des fonctions de transfert empiriques adaptées aux chaussées non revêtues a également été effectuée. Le développement des fonctions de transfert s’est fait en deux étapes. Tout d’abord, l’établissement de valeurs seuil d’orniérage considérant des niveaux jugés raisonnables de conditions fonctionnelle et structurale de la chaussée. Ensuite, le développement de critères de déformation admissible en associant les déformations théoriques calculées à l’aide du code de calcul à l’endommagement observé sur plusieurs routes en service. Les essais ont eu lieu sur des chaussées typiques reconstituées en laboratoire et soumises à un chargement répété par simulateur de charge. Les chaussées ont été instrumentées pour mesurer la déformation au sommet du sol d’infrastructure et les taux d’endommagements ont été mesurés au cours des essais.

Investigation of the role of long non-coding RNAs in oncogene induced cellular senescence

Cellular senescence is a stable arrest of cell proliferation induced by several factors such as activated oncogenes, oxidative stress and shortening of telomeres. Senescence acts as a tumour suppression mechanism to halt the progression of cancer. However, senescence may also impact negatively upon tissue regeneration, thus contributing to the effects of ageing. The eukaryotic genome is controlled by various modes of transcriptional and translational regulation. Focus has therefore centred on the role of long non- coding RNAs (lncRNAs) in regulating the genome. Accordingly, understanding how lncRNAs function to regulate the senescent genome is integral to improving our knowledge and understanding of tumour suppression and ageing. Within this study, I set out to investigate the expression of lncRNAs’ expression within models of senescence. Through a custom expression array, I have shown that expression of multiple different lncRNAs is up-regulated and down regulated in IMR90 replicative senescent fibroblasts and oncogene-induced senescent melanocytes. LncRNA expression was determined to be specific to stable senescence-associated cell arrest and predominantly within the nucleus of senescent cells. In order to examine the function of lncRNA expression in senescence, I selected lncRNA transcript ENST0000430998 (lncRNA_98) to focus my investigations upon. LncRNA_98 was robustly upregulated within multiple models of senescence and efficiently depleted using anti-sense oligonucleotide technology. Characterisation and unbiased RNA-sequencing of lncRNA_98 deficient senescent cells highlighted a list of genes that are regulated by lncRNA_98 expression in senescent cells and may regulate aspects of the senescence program. Specifically, the formation of SAHF was impeded upon depletion of lncRNA_98 expression and levels of total pRB protein expression severely decreased. Validation and recapitulation of consequences of pRB depletion was confirmed through lncRNA_98 knock-out cells generated using CRISPR technology. Surprisingly, inhibition of ATM kinase functions permitted the restoration of pRB protein levels within lncRNA_98 deficient cells. I propose that lncRNA_98 antagonizes the ability of ATM kinase to downregulate pRB expression at a post-transcriptional level, thereby potentiating senescence. Furthermore, lncRNA expression was detected within fibroblasts of old individuals and visualised within senescent melanocytes in human benign nevi, a barrier to melanoma progression. Conversely, mining of 337 TCGA primary melanoma data sets highlighted that the lncRNA_98 gene and its expression was lost from a significant proportion of melanoma samples, consistent with lncRNA_98 having a tumour suppressor functions. The data presented in this study illustrates that lncRNA_98 expression has a regulatory role over pRB expression in senescence and may regulate aspects of tumourigenesis and ageing.

Floating s- and p-type Gaussian Orbitals

The advantages of including a small number of p-type gaussian functions in a floating spherical gaussian orbital calculation are pointed out and illustrated by calculations on molecules which previously have proved to be troublesome. These include molecules such as F2 with multiple lone pairs and C2H2 with multiple bonds. A feature of the results is the excellent correlation between the orbital energies and those of a double zeta calculation reported by Snyder and Basch.

Spectral Frame Analysis and Learning through Graph Structure

This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.

Investigation of multisensory processing and structural brain differences in Autism Spectrum Disorder

This thesis is an investigation of structural brain abnormalities, as well as multisensory and unisensory processing deficits in autistic traits and Autism Spectrum Disorder (ASD). To achieve this, structural and functional magnetic resonance imaging (fMRI) and psychophysical techniques were employed. ASD is a neurodevelopmental condition which is characterised by the social communication and interaction deficits, as well as repetitive patterns of behaviour, interests and activities. These traits are thought to be present in a typical population. The Autism Spectrum Quotient questionnaire (AQ) was developed to assess the prevalence of autistic traits in the general population. Von dem Hagen et al. (2011) revealed a link between AQ with white matter (WM) and grey matter (GM) volume (using voxel-based-morphometry). However, their findings revealed no difference in GM in areas associated with social cognition. Cortical thickness (CT) measurements are known to be a more direct measure of cortical morphology than GM volume. Therefore, Chapter 2 investigated the relationship between AQ scores and CT in the same sample of participants. This study showed that AQ scores correlated with CT in the left temporo-occipital junction, left posterior cingulate, right precentral gyrus and bilateral precentral sulcus, in a typical population. These areas were previously associated with structural and functional differences in ASD. Thus the findings suggest, to some extent, autistic traits are reflected in brain structure - in the general population. The ability to integrate auditory and visual information is crucial to everyday life, and results are mixed regarding how ASD influences audiovisual integration. To investigate this question, Chapter 3 examined the Temporal Integration Window (TIW), which indicates how precisely sight and sound need to be temporally aligned so that a unitary audiovisual event can be perceived. 26 adult males with ASD and 26 age and IQ-matched typically developed males were presented with flash-beep (BF), point-light drummer, and face-voice (FV) displays with varying degrees of asynchrony and asked to make Synchrony Judgements (SJ) and Temporal Order Judgements (TOJ). Analysis of the data included fitting Gaussian functions as well as using an Independent Channels Model (ICM) to fit the data (Garcia-Perez & Alcala-Quintana, 2012). Gaussian curve fitting for SJs showed that the ASD group had a wider TIW, but for TOJ no group effect was found. The ICM supported these results and model parameters indicated that the wider TIW for SJs in the ASD group was not due to sensory processing at the unisensory level, but rather due to decreased temporal resolution at a decisional level of combining sensory information. Furthermore, when performing TOJ, the ICM revealed a smaller Point of Subjective Simultaneity (PSS; closer to physical synchrony) in the ASD group than in the TD group. Finding that audiovisual temporal processing is different in ASD encouraged us to investigate the neural correlates of multisensory as well as unisensory processing using functional magnetic resonance imaging fMRI. Therefore, Chapter 4 investigated audiovisual, auditory and visual processing in ASD of simple BF displays and complex, social FV displays. During a block design experiment, we measured the BOLD signal when 13 adults with ASD and 13 typically developed (TD) age-sex- and IQ- matched adults were presented with audiovisual, audio and visual information of BF and FV displays. Our analyses revealed that processing of audiovisual as well as unisensory auditory and visual stimulus conditions in both the BF and FV displays was associated with reduced activation in ASD. Audiovisual, auditory and visual conditions of FV stimuli revealed reduced activation in ASD in regions of the frontal cortex, while BF stimuli revealed reduced activation the lingual gyri. The inferior parietal gyrus revealed an interaction between stimulus sensory condition of BF stimuli and group. Conjunction analyses revealed smaller regions of the superior temporal cortex (STC) in ASD to be audiovisual sensitive. Against our predictions, the STC did not reveal any activation differences, per se, between the two groups. However, a superior frontal area was shown to be sensitive to audiovisual face-voice stimuli in the TD group, but not in the ASD group. Overall this study indicated differences in brain activity for audiovisual, auditory and visual processing of social and non-social stimuli in individuals with ASD compared to TD individuals. These results contrast previous behavioural findings, suggesting different audiovisual integration, yet intact auditory and visual processing in ASD. Our behavioural findings revealed audiovisual temporal processing deficits in ASD during SJ tasks, therefore we investigated the neural correlates of SJ in ASD and TD controls. Similar to Chapter 4, we used fMRI in Chapter 5 to investigate audiovisual temporal processing in ASD in the same participants as recruited in Chapter 4. BOLD signals were measured while the ASD and TD participants were asked to make SJ on audiovisual displays of different levels of asynchrony: the participants’ PSS, audio leading visual information (audio first), visual leading audio information (visual first). Whereas no effect of group was found with BF displays, increased putamen activation was observed in ASD participants compared to TD participants when making SJs on FV displays. Investigating SJ on audiovisual displays in the bilateral superior temporal gyrus (STG), an area involved in audiovisual integration (see Chapter 4), we found no group differences or interaction between group and levels of audiovisual asynchrony. The investigation of different levels of asynchrony revealed a complex pattern of results indicating a network of areas more involved in processing PSS than audio first and visual first, as well as areas responding differently to audio first compared to video first. These activation differences between audio first and video first in different brain areas are constant with the view that audio leading and visual leading stimuli are processed differently.

High temperature and vapor pressure deficit aggravate architectural effects but ameliorate non-architectural effects of salinity on dry mass production of tomato

Tomato (Solanum lycopersicum L.) is an important vegetable crop and often cultivated in regions exposed to salinity and high temperatures (HT) which change plant architecture, decrease canopy light interception and disturb physiological functions. However, the long-term effects of salinity and HT combination (S+HT) on plant growth are still unclear. A dynamic functional-structural plant model (FSPM) of tomato was parameterized and evaluated for different levels of S+HT combinations. The evaluated model was used to quantify the contributions of morphological changes (architectural effects) and physiological disturbances (non-architectural effects) on the reduction of shoot dry mass under S+HT. The model predicted architectural variables with high accuracy (>85%), which ensured the reliability of the model analyses. HT enhanced architectural effects but reduced non-architectural effects of salinity on dry mass production. The stronger architectural effects of salinity under HT could not be counterbalanced by the smaller non-architectural effects. Therefore, long-term influences of HT on shoot dry mass under salinity were negative at the whole plant level. Our model analysis highlights the importance of plant architecture at canopy level in studying the plant responses to the environments and shows the merits of dynamic FSPMs as heuristic tools.

Genome-scale analysis of the non-cultivable Treponema pallidum reveals extensive within-patient genetic variation

Insights into the genomic adaptive traits of Treponema pallidum, the causative bacterium of syphilis, have long been hampered due to the absence of in vitro culture models and the constraints associated with its propagation in rabbits. Here, we have bypassed the culture bottleneck by means of a targeted strategy never applied to uncultivable bacterial human pathogens to directly capture whole-genome T. pallidum data in the context of human infection. This strategy has unveiled a scenario of discreet T. pallidum interstrain single-nucleotide-polymorphism-based microevolution, contrasting with a rampant within-patient genetic heterogeneity mainly targeting multiple phase-variable loci and a major antigen-coding gene (tprK). TprK demonstrated remarkable variability and redundancy, intra- and interpatient, suggesting ongoing parallel adaptive diversification during human infection. Some bacterial functions (for example, flagella- and chemotaxis-associated) were systematically targeted by both inter- and intrastrain single nucleotide polymorphisms, as well as by ongoing within-patient phase variation events. Finally, patient-derived genomes possess mutations targeting a penicillin-binding protein coding gene (mrcA) that had never been reported, unveiling it as a candidate target to investigate the impact on the susceptibility to penicillin. Our findings decode the major genetic mechanisms by which T. pallidum promotes immune evasion and survival, and demonstrate the exceptional power of characterizing evolving pathogen subpopulations during human infection.

Homogenization of the p-Laplacian with nonlinear boundary condition on critical size particles: Identifying the strange term for the some non smooth and multivalued operators

We extend previous papers in the literature concerning the homogenization of Robin type boundary conditions for quasilinear equations, in the case of microscopic obstacles of critical size: here we consider nonlinear boundary conditions involving some maximal monotone graphs which may correspond to discontinuous or non-Lipschitz functions arising in some catalysis problems.

SVR-GARCH com misturas de kernels gaussianos

Dissertação (mestrado)—Universidade de Brasília, Departamento de Administração, Programa de Pós-graduação em Administração, 2016.

Le rôle des parents croyants non pratiquants dans l'initiation à la vie chrétienne des enfants de 8 à 12 ans : en complémentarité avec celui des intervenants en paroisse.

Cette-recherche-action émerge d’une problématique élaborée à partir de l’observation des pratiques catéchétiques à la paroisse Saint-Joachim dans le diocèse de Montréal. L’essentiel du projet se situe en théologie pratique, menée dans le cadre de la praxéologie pastorale. Un premier chapitre situe l’historique de la catéchèse en paroisse. Le deuxième déploie l’observation de la pratique à partir des pôles structurels et des fonctions d’élaboration, mais aussi par la mise à contribution des parents qui ont accepté de répondre à un questionnaire. Le troisième pose la problématique de la mise à l’écart des parents dans l’éducation à la foi et est suivi d’une interprétation sur un changement de posture et un appel à la coéducation dans la foi tout en prenant compte des évolutions des familles à l’égard du religieux. Cela est fait à partir de référents théologiques principalement, enrichis de référents dans les domaines de l’éducation et des sciences sociales. Des pistes à envisager avec les parents et avec les catéchètes sont ensuite formulées, avec un accent mis sur la pratique du dialogue pastoral et la notion d’accompagnement, et également en faisant le lien avec les différentes dimensions de la vie chrétienne. Le dernier chapitre veut offrir une prospective dans la transmission de la foi en révélant le rôle missionnaire de la catéchèse qui s’accorde avec la nouvelle évangélisation et la pastorale des familles.

Statistical properties of radiation of multiwavelength random DFB fiber laser

In the presented paper, the temporal and statistical properties of a Lyot filter based multiwavelength random DFB fiber laser with a wide flat spectrum, consisting of individual lines, were investigated. It was shown that separate spectral lines forming the laser spectrum have mostly Gaussian statistics and so represent stochastic radiation, but at the same time the entire radiation is not fully stochastic. A simple model, taking into account phenomenological correlations of the lines' initial phases was established. Radiation structure in the experiment and simulation proved to be different, demanding interactions between different lines to be described via a NLSE-based model.

Simple approximate MAP inference for Dirichlet processes mixtures

The Dirichlet process mixture model (DPMM) is a ubiquitous, flexible Bayesian nonparametric statistical model. However, full probabilistic inference in this model is analytically intractable, so that computationally intensive techniques such as Gibbs sampling are required. As a result, DPMM-based methods, which have considerable potential, are restricted to applications in which computational resources and time for inference is plentiful. For example, they would not be practical for digital signal processing on embedded hardware, where computational resources are at a serious premium. Here, we develop a simplified yet statistically rigorous approximate maximum a-posteriori (MAP) inference algorithm for DPMMs. This algorithm is as simple as DP-means clustering, solves the MAP problem as well as Gibbs sampling, while requiring only a fraction of the computational effort. (For freely available code that implements the MAP-DP algorithm for Gaussian mixtures see http://www.maxlittle.net/.) Unlike related small variance asymptotics (SVA), our method is non-degenerate and so inherits the “rich get richer” property of the Dirichlet process. It also retains a non-degenerate closed-form likelihood which enables out-of-sample calculations and the use of standard tools such as cross-validation. We illustrate the benefits of our algorithm on a range of examples and contrast it to variational, SVA and sampling approaches from both a computational complexity perspective as well as in terms of clustering performance. We demonstrate the wide applicabiity of our approach by presenting an approximate MAP inference method for the infinite hidden Markov model whose performance contrasts favorably with a recently proposed hybrid SVA approach. Similarly, we show how our algorithm can applied to a semiparametric mixed-effects regression model where the random effects distribution is modelled using an infinite mixture model, as used in longitudinal progression modelling in population health science. Finally, we propose directions for future research on approximate MAP inference in Bayesian nonparametrics.