12 resultados para Functions graph
em Brock University, Canada
Resumo:
One group of 12 non learning disabled students and two groups of 12 learning disabled students between the ges of 10 and 12 were measured on implicit and explicit knowledge cquisition. Students in each group implicitly cquired knowledge bout I of 2 vocabulary rules. The vocabulary rules governed the pronunciation of 2 types of pseudowords. After completing the implicit acquisition phase, all groups were administered a test of implicit knowledge. The non learning disabled group and I learning disabled group were then asked to verbalize the knowledge acquired during the initial phase. This was a test of explicit knowledge. All 3 groups were then given a postlest of implicit knowledge. This tcst was a measure of the effectiveness of the employment of the verbalization technique. Results indicate that implicit knowledge capabilities for both the learning disabled and non learning disabled groups were intact. However. there were significant differences between groups on explicit knowledge capabilities. This led to the conclusion that implicit functions show little individual differences, and that explicit functions are affected by ability difference. Furthermore, the employment of the verbalization technique significantly increased POStlest scores for learning disabled students. This suggested that the use of metacognitive techniques was a beneficial learning tool for learning disabled students.
Resumo:
Background: Ang II plays a major role in cardiovascular regulation. Recently, it has become apparent that vascular superoxide anion may play an important role in hypertension development. Treatment with antisense NAD(P)H oxidase or SOD decreased BP in Ang II-infused rats. Wang et al recently reported mice which lack one of the subunits of NAD(P)H oxidase developed hypertension at a much lower extent when compared to the wild type animals infused with Ang II, indicating that superoxide anion contributes to elevation in BP in the Ang II-infused hypertensive model. In the Ang II-infused hypertensive model, altered reactivity of blood vessels is often associated with the elevation of systolic blood pressure. We have observed abnormal tension development and impaired endothelium-dependent relaxation in the isolated aorta of Ang II-infused and DOCA-salt hypertensive rats. Recently, several other cellular signal molecules, including ERK1I2 and PI3K, have been determined to play important roles in the regulation of smooth muscle contraction and relaxation. ERKl/2 and PI3K pathways are also reported to contribute to Ang II induced cell growth, hypertrophy, remodeling and contraction. Moreover, these signaling pathways have shown ROS-sensitive properties. Therefore, the aim of the present study is to investigate the roles of ERKl12 and PI3K in vascular oxidative stress, spontaneous tone and impaired endothelium relaxation in Ang II-infused hypertensive model. Hypothesis: We hypothesize that the activation of ERKl12 and PI3K are elevated in response to an Ang II infusion for 6 days. The elevated activation of phospho-ERKl/2 and PI3K mediated the increased level of vascular superoxide anion, the abnormal vascular contraction and impaired endothelium-dependent vascular relaxation in Ang II-infused hypertensive rats. Methods: Vascular superoxide anion level is measured by lucigenin chemiluminescence. Spontaneous tone and ACh-induced endothelium-dependent relaxation was measured by isometric tension recording in organ chamber. The activity of ERK pathway will be measured by its Western blot of phosphorylation of ERK. PI3K activity was evaluated indirectly by Western blot of the phosphorylation of PDKl, a downstream protein of PI3K signaling pathway. The role of each pathway was also addressed via comparing the responses to the specific inhibitors. Results: Superoxide anion was markedly increased in the isolated thoracic aorta from Ang II-infused rats. There was spontaneous tone developed in rings from Ang II-induced hypertensive but not sham-operated normotensive rats. ACh-induced endothelium-dependent relaxation function is impaired in Ang II-infused hypertensive rats. Superoxide dismutase and NAD(P)H oxidase inhibitor, apocynin, inhibited the abnormal spontaneous tone and ameliorated impaired endothelium-dependent relaxation. The expression of phopho-ERKII2 was enhanced in Ang II-infused rats, indicating the activity of ERK1I2 could be increased. MEK1I2 inhibitors, PD98059 and U126, but not their inactive analogues, SB203580 and U124, significantly reduced the vascular superoxide anion in aortas from Ang II-infused rats. The MEK1I2 inhibitors reduced the spontaneous tone and improved the impaired endothelium-dependent relaxation in aorta of hypertension. These findings supported the role of ERKII2 signaling pathway in vascular oxidative stress, spontaneous tone and impaired endothelium-dependent relaxation in Ang II-infused hypertensive rats. The amount of phospho-PDK, a downstream protein of PI3K was increased in Ang II rats indicating the activity of PI3K activity was elevated. Strikingly, PI3K significantly inhibited the increase of superoxide anion level, abnormal spontaneous tone and restored endothelium-dependent relaxation in Ang II-infused hypertensive rats. These findings indicated the important role of PI3K in Ang II-infused hypertensive rats. Conclusion: ERKII2 and PI3K signaling pathways are sustained activated in Ang II-infused hypertensive rats. The activated ERKII2 and PI3K mediate the increase of vascular superoxide anion level, vascular abnormal spontaneous tone and impaired endothelium-dependent relaxation.
Resumo:
The Zubarev equation of motion method has been applied to an anharmonic crystal of O( ,,4). All possible decoupling schemes have been interpreted in order to determine finite temperature expressions for the one phonon Green's function (and self energy) to 0()\4) for a crystal in which every atom is on a site of inversion symmetry. In order to provide a check of these results, the Helmholtz free energy expressions derived from the self energy expressions, have been shown to agree in the high temperature limit with the results obtained from the diagrammatic method. Expressions for the correlation functions that are related to the mean square displacement have been derived to 0(1\4) in the high temperature limit.
Resumo:
Methods for both partial and full optimization of wavefunction parameters are explored, and these are applied to the LiH molecule. A partial optimization can be easily performed with little difficulty. But to perform a full optimization we must avoid a wrong minimum, and deal with linear-dependency, time step-dependency and ensemble-dependency problems. Five basis sets are examined. The optimized wavefunction with a 3-function set gives a variational energy of -7.998 + 0.005 a.u., which is comparable to that (-7.990 + 0.003) 1 of Reynold's unoptimized \fin ( a double-~ set of eight functions). The optimized wavefunction with a double~ plus 3dz2 set gives ari energy of -8.052 + 0.003 a.u., which is comparable with the fixed-node energy (-8.059 + 0.004)1 of the \fin. The optimized double-~ function itself gives an energy of -8.049 + 0.002 a.u. Each number above was obtained on a Bourrghs 7900 mainframe computer with 14 -15 hrs CPU time.
Resumo:
Multiple measures have been devised by clinicians and theorists from many different backgrounds for the purpose of assessing the influence of the frontal lobes on behaviour. Some utilize self-report measures to investigate behavioural characteristics such as risktaking, sensation seeking, impulsivity, and sensitivity to reward and punishment in an attempt to understand complex human decision making. Others rely more on neuroimaging and electrophysiological investigation involving experimental tasks thought to demonstrate executive functions in action, while other researchers prefer to study clinical populations with selective damage. Neuropsychological models of frontal lobe functioning have led to a greater appreciation of the dissociations among various aspects of prefrontal cortex function. This thesis involves (1) an examination of various psychometric and experimental indices of executive functions for coherence as one would predict on the basis of highly developed neurophysiological models of prefrontal function, particularly those aspects of executive function that involve predominantly cognitive abilities versus processes characterized by affect regulation; and (2) investigation of the relations between risk-taking, attentional abilties and their associated characteristics using a neurophysiological model of prefrontal functions addressed in (1). Late adolescence is a stage in which the prefrontal cortices undergo intensive structural and functional maturational changes; this period also involves increases in levels of risky and sensation driven behaviours, as well as a hypersensitivity to reward and a reduction in inhibition. Consequently, late adolescence spears to represent an ideal developmental period in which to examine these decision-making behaviours due to the maximum variability of behavioural characteristics of interest. Participants were 45 male undergraduate 18- to 19-year olds, who completed a battery of measures that included self-report, experimental and behavioural measures designed to assess particular aspects of prefrontal and executive functioning. As predicted, factor analysis supported the grouping of executive process by type (either primarily cognitive or affective), conforming to the orbitofrontal versus dorsolateral typology; risk-taking and associated characteristics were associated more with the orbitofrontal than the dorsolateral factor, whereas attentional and planning abilities tended to correlate more strongly with the dorsolateral factor. Results are discussed in light of future assessment, investigation and understanding of complex human decision-making and executive functions. Implications, applications and suggestions for future research are also proposed.
Resumo:
The hyper-star interconnection network was proposed in 2002 to overcome the drawbacks of the hypercube and its variations concerning the network cost, which is defined by the product of the degree and the diameter. Some properties of the graph such as connectivity, symmetry properties, embedding properties have been studied by other researchers, routing and broadcasting algorithms have also been designed. This thesis studies the hyper-star graph from both the topological and algorithmic point of view. For the topological properties, we try to establish relationships between hyper-star graphs with other known graphs. We also give a formal equation for the surface area of the graph. Another topological property we are interested in is the Hamiltonicity problem of this graph. For the algorithms, we design an all-port broadcasting algorithm and a single-port neighbourhood broadcasting algorithm for the regular form of the hyper-star graphs. These algorithms are both optimal time-wise. Furthermore, we prove that the folded hyper-star, a variation of the hyper-star, to be maixmally fault-tolerant.
Resumo:
Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.
Resumo:
A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.
Resumo:
Let f(x) be a complex rational function. In this work, we study conditions under which f(x) cannot be written as the composition of two rational functions which are not units under the operation of function composition. In this case, we say that f(x) is prime. We give sufficient conditions for complex rational functions to be prime in terms of their degrees and their critical values, and we derive some conditions for the case of complex polynomials. We consider also the divisibility of integral polynomials, and we present a generalization of a theorem of Nieto. We show that if f(x) and g(x) are integral polynomials such that the content of g divides the content of f and g(n) divides f(n) for an integer n whose absolute value is larger than a certain bound, then g(x) divides f(x) in Z[x]. In addition, given an integral polynomial f(x), we provide a method to determine if f is irreducible over Z, and if not, find one of its divisors in Z[x].
Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks
Resumo:
Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.
Resumo:
(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.