21 resultados para Graph spectrum

em Brock University, Canada


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Autism is a developmental disorder that is characterized by abnonnal social interactions and communications as well as repetitive and restricted activities and interests. There is evidence of a genetic component, as 5% of younger siblings are diagnosed if their older sibling has been diagnosed. Autism is generally not diagnosed until age 3 at the earliest, yet it has been shown that early intervention for children with autism can greatly increase their functioning. Because of this, it is important that symptoms of autism are identified as early as possible so that diagnosis can occur as soon as possible to allow these children the earliest intervention. This thesis was divided into two parts. The first looked at the psychometrics of two proposed measures, the Parent Observation Checklist (POC), administered monthly, and the Infant Behavior Summary Evaluation (mSE), administered bimonthly, to see if they can be used with the infant population to identify autistic symptoms in infants who are at high risk for autism or related problems because they have an older sibling with autism. Study 1 reported acceptable psychometric properties of both the POC and IBSE in terms of test-retest reliability, internal consistency, construct validity and predictive validity. These results provide preliminary evidence that parent report measures can help to detect early symptoms of ASD in infants. The POC was shown to differentiate infants who were diagnosed from a matched group that was not diagnosed by 3 years of age. The second part of this thesis involved a telephone interview of parents who reported developmental and/or behavior problems in their high-risk infants that may be early signs of Autism Spectrum Disorder (ASD). During the interview, a service questionnaire was administered to see what interventions (including strategies recommended by the researchers) their at risk infants and affected older siblings were receiving, how satisfied the parents were with them and how effective they felt the interventions were. 3 Study 2 also yielded promising results. Parents utilized a variety of services for at risk infants and children with ASD. The interventions included empirically validated early intervention (e.g., ABA) to non-empirically validated treatments (e.g., diet therapy). The large number of nonempirically validated treatments parents used was surprising, yet parents reported being involved and satisfied, and thought that the services were effective. Parents' perceptions of their stress levels went down slightly and feelings of competence rose when they accessed services for their infants. Overall, the results of this thesis provide new evidence that parent-report methods hold promise as early detection instruments for ASD in at-risk infants. More research is needed to further validate these instruments as well as to understand the variables related to the parents' choice of early intervention for their at risk and affected children.

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The near ultraviolet absorption of phosgene has been assigned to a * 1 1 ~.--n, A;-- Al electronic transition from vapour phase spectra recorded under conditions of high resolution and low_t~mperature. Progressions in Vi, v2' V3' V4 and V4 ha\1e been identified in the spectrum and have been analyzed in terms of vibronic transitions between a planar ground and a nonplanar excited state. A ba~rier height of 3170 cm~l:and a nona planar equilibrium angle of 32.5 were calculated for the upper state from a fit of the energy levels of a Lorentzian-guadratic potential func- ~ion to the observed levels of V 4 . ' ~he false ori- 3in, 41 0 , of the spectrum has been assigned to the band at 33,631 cm -1 . An oscillator strength of -3 1 . 1 f = 1. a x 10 has been obtained for the A - A 2 1 transition.

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Cognitive and social levels of play engaged in by four-to-eight-year-old children with autism spectrum disorders were examined in naturalistic classroom settings. In addition, play at home was compared with play at school via parent and educator interviews. Seventeen school-age children, their educators and caregivers participated in the study. The most frequently observed play behaviours included parallel-functional play, adult interactions and solitary-functional play. The play of the children in the current study was consistent with that of typically-developing preschoolers. Mothers and educators did not differ significantly in their perspectives of the participants' play behaviours. In general, educators' and caregivers' reports were positively related to researcher observations of participants' play behaviours. Methodological considerations and practical implications for the findings are discussed.

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The purpose of this multiple case study was 1) to explore the effectiveness of an emotions recognition program for preschoolers with Autism Spectrum Disorders (ASD), and 2) to investigate one parent's perception of the emotions program. To address these objectives, the emotion unit scores of 7 preschoolers with ASD aged 3 to 5 years old (1 female, 6 males) were graphed and analyzed using visual inspection. In addition, the mother of 1 participant was interviewed to explore her perceptions of the emotions program and emotional learning. Overall, results revealed that participants' emotion recognition scores increased over the course of the emotions unit. The parent reported improvements in her son's expression and understanding of emotion, but noted that he continued to have difficulty with regulation of emotion. Implications for theory, education, and future research are discussed.

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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.

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This study sought to compare the results of the Motivation Assessment Scale (MAS; Durand & Crimmins, 1988), Questions About Behavior Function Scale (QABF; Matson & Vollmer, 1996) and Functional Analysis Screening Tool (FAST; Iwata & Deleon, 1996), when completed by parent informants in a sample of children and youth with autism spectrum disorders (ASD) who display challenging behaviour. Results indicated that there was low agreement between the functional hypotheses derived from each of three measures. In addition, correlations between functionally analogous scales were substantially lower than expected, while correlations between non-analogous subscales were stronger than anticipated. As indicated by this study, clinicians choosing to use FBA questionnaires to assess behavioural function, may not obtain accurate functional hypotheses, potentially resulting in ineffective intervention plans. The current study underscores the caution that must be taken when asking parents to complete these questionnaires to determine the function(s) of challenging behaviour for children/youth with ASD.

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This study examined the commonalities and the differences between creativity and the schizophrenia spectrum. The variables measured as potential commonalities and differences were creativity, schizotypy, cognitive inhibition, spatial ability, balancing skills, positive and negative presence, absorption, mystical experiences, childhood abuse, and neuroticism. Three community groups were recruited, consisting of 31 artists, 10 people with schizophrenia, and 31 comparisons matched for gender and age with the artists. A larger student group consisting of 102 students was also recruited in order to examine the correlations among the same variables within a larger, more normative, group. The largest commonality between the artist and the schizophrenic groups, who represented the extreme end of the schizophrenia spectrum, was the propensity to mystical experiences. The greatest differences between the artist and the schizophrenic groups were that the artists were higher in creativity, performed better on spatial abilities, had better balance, had more positive states of presence, and were lower in neuroticism than the schizophrenic group. In the student group, creativity was correlated with spatial ability, positive presence, absorption, and mystical experiences. In addition, creativity was significantly related to two facets of schizotypy, unusual experiences and impulsive nonconformity. In other words, students high in certain facets of schizotypy, who may share certain characteristics with those who have schizophrenia, are higher in creativity, but people who are on the extreme end of the schizophrenia spectrum, who have been diagnosed with schizophrenia, are not. The differences between the artist and schizophrenic groups on spatial ability, balance, sense of presence, and neuroticism may help to determine whether mystical experiences help to integrate creative work or destabilize and disorganize the sense of self. It may be that mystical experiences can be used more positively by the creative individuals than people with schizophrenia, in that artists and people high in creativity were higher in positive traits such as positive presence and lower on negative variables such as neuroticism, and introvertive anhedonia.

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Research indicates that Obsessive-Compulsive Disorder (OCD; DSM-IV-TR, American Psychiatric Association, 2000) is the second most frequent disorder to coincide with Autism Spectrum Disorder (ASD; Leyfer et aI., 2006). Excessive collecting and hoarding are also frequently reported in children with ASD (Berjerot, 2007). Although functional analysis (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) has successfully identified maintaining variables for repetitive behaviours such as of bizarre vocalizations (e.g., Wilder, Masuda, O'Connor, & Baham, 2001), tics (e.g., Scotti, Schulman, & Hojnacki, 1994), and habit disorders (e.g., Woods & Miltenberger, 1996), extant literature ofOCD and functional analysis methodology is scarce (May et aI., 2008). The current studies utilized functional analysis methodology to identify the types of operant functions associated with the OCD-related hoarding behaviour of a child with ASD and examined the efficacy of function-based intervention. Results supported hypotheses of automatic and socially mediated positive reinforcement. A corresponding function-based treatment plan incorporated antecedent strategies and differential reinforcement (Deitz, 1977; Lindberg, Iwata, Kahng, and DeLeon, 1999; Reynolds, 1961). Reductions in problem behaviour were evidenced through use of a multiple baseline across behaviours design and maintained during two-month follow-up. Decreases in symptom severity were also discerned through subjective measures of treatment effectiveness.

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Longitudinal studies of the development of autism spectrum disorders (ASD) provide an understanding of which variables may be important predictors of an ASD. The objective of the current study is to apply the reliable change index (RCI) statistic to examine whether the Parent Observation of Early Markers Scale (POEMS) is sensitive to developmental change, and whether these changes can be quantified along a child’s developmental trajectory. Ninety-six children with older siblings with autism were followed from 1-36 months of age. Group-based RCI analysis confirms that the POEMS is capable of detecting significant changes within pre-defined diagnostic groups. Within-subject analysis suggests that ongoing monitoring of a child at-risk for an ASD requires interpretation of both significant intervals identified by the RCI statistic, as well as the presence of repeated high (i.e., >70) scores. This study provides preliminary evidence for a reasonably sensitive and specific means by which individual change can be clinically monitored via parent report.

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By identifying early signs of Autism Spectrum Disorder, early intervention or parent training could be implemented and assist in increasing the developmental trajectory for these infants. This cross sectional study used the Parent Observation of Early Markers Scale (POEMS) to identify early signs of ASD in 69 high-risk (older sibling diagnosed with ASD) and 69 matched low-risk infants' families (no family history of ASD) between 6 and 36 months of age. The preliminary results showed the high-risk children had significantly more elevated POEMS items than the low-risk children at 12, 18,24,30 and 36 months of age. The results suggest that at-risk infants may show signs of ASD as early as 12 months of age, and that the POEMS could be used to guide early intervention or parent training for children 12 months or older.

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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.

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

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Abstract The therapeutic alliance (TA) is the most studied process of adult psychotherapeutic change (Zack et al., 2007) and has been found to have a moderate but robust relationship with therapeutic outcome regardless of treatment modality (Horvath, 2001). The TA is loosely described as the extent to which the therapist and the participant connect emotionally and work together towards goals. Conceptualizations of the TA with children have relied on adult models, even though it is widely acknowledged that the pediatric population will rarely willingly commit to therapy, nor readily admit to any challenges that they may be experiencing (Keeley, Geffken, McNamara & Storch, 2011). For children with Autism Spectrum Disorder (ASD) the therapeutic alliance may require an even greater retheorizing considering the communicative and social difficulties of this particular population. Despite this need, research on children with ASD and the therapeutic TA is almost non-existent. In this qualitative study, transcripts from semi-structured interviews with mothers of children with ASD were analyzed using Interpretative Phenomenological Analysis (IPA). IPA closely examines how individual people make sense of their life experiences using a theme-by-theme approach. The three interviewees were mothers whose children were participants in a nine-week Cognitive Behaviour Therapy (CBT) group for obsessive-compulsive behaviours (OCB). A total of four superordinate themes were identified: (i) Centralization and disremembering the TA, (ii) Qualities of the therapist, (iii) TA and the importance of time, and (iv) Signs of a healthy TA. The mothers’ perspectives on the TA suggest that, for them and their children, a strong TA was a required component of the therapy. Implications for clinicians and researchers are discussed.

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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.

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Each person with Autism Spectrum Disorder (ASD) comes with unique characteristics (idiosyncratic) that give clues to the world they know (Connolly, 2008). It is through their body that they (a) know the world they are experiencing, (b) make meaning, and (c) express certain behaviours. I used Laban’s Movement Analysis (LMA) to practice an attuned and appreciative approach to describing and understanding the body movement in one severe manifestation of autism in an adolescent male. LMA observes human movement across many disciplines and can be applied in many contexts providing a body honoring discourse for description (Connolly, 2008). The framework examines movement in body, space, quality, and relation. Each theme provides a detailed description of the individual’s movement, thus, giving us a richer understanding of patterns and possible triggers to self-injurious behaviours (SIB). During the summer of August 2013, I participated in Brock University’s annual Autism Camp and worked with a 15 year old male named “Aaron” who manifests with low functioning autism. The purpose of my research project was to code and analyze a series of photos taken to help gain insight into movement patterns associated with stressed embodiment and self-injury in “Aaron”. As I understood more about these embodied expressions, I uncovered valuable information on how to read patterns and discover what triggers these events, thus providing strategies on how to help people do more refined observations and make meaning of the behaviour. Laban’s movement analysis provided a sensitized discourse appropriate to the embodied expressions depicted in the photos.