Digital kids, analogue students : a mixed methods study of students' engagement with a school-based Web 2.0 learning innovation

The inquiry documented in this thesis is located at the nexus of technological innovation and traditional schooling. As we enter the second decade of a new century, few would argue against the increasingly urgent need to integrate digital literacies with traditional academic knowledge. Yet, despite substantial investments from governments and businesses, the adoption and diffusion of contemporary digital tools in formal schooling remain sluggish. To date, research on technology adoption in schools tends to take a deficit perspective of schools and teachers, with the lack of resources and teacher ‘technophobia’ most commonly cited as barriers to digital uptake. Corresponding interventions that focus on increasing funding and upskilling teachers, however, have made little difference to adoption trends in the last decade. Empirical evidence that explicates the cultural and pedagogical complexities of innovation diffusion within long-established conventions of mainstream schooling, particularly from the standpoint of students, is wanting. To address this knowledge gap, this thesis inquires into how students evaluate and account for the constraints and affordances of contemporary digital tools when they engage with them as part of their conventional schooling. It documents the attempted integration of a student-led Web 2.0 learning initiative, known as the Student Media Centre (SMC), into the schooling practices of a long-established, high-performing independent senior boys’ school in urban Australia. The study employed an ‘explanatory’ two-phase research design (Creswell, 2003) that combined complementary quantitative and qualitative methods to achieve both breadth of measurement and richness of characterisation. In the initial quantitative phase, a self-reported questionnaire was administered to the senior school student population to determine adoption trends and predictors of SMC usage (N=481). Measurement constructs included individual learning dispositions (learning and performance goals, cognitive playfulness and personal innovativeness), as well as social and technological variables (peer support, perceived usefulness and ease of use). Incremental predictive models of SMC usage were conducted using Classification and Regression Tree (CART) modelling: (i) individual-level predictors, (ii) individual and social predictors, and (iii) individual, social and technological predictors. Peer support emerged as the best predictor of SMC usage. Other salient predictors include perceived ease of use and usefulness, cognitive playfulness and learning goals. On the whole, an overwhelming proportion of students reported low usage levels, low perceived usefulness and a lack of peer support for engaging with the digital learning initiative. The small minority of frequent users reported having high levels of peer support and robust learning goal orientations, rather than being predominantly driven by performance goals. These findings indicate that tensions around social validation, digital learning and academic performance pressures influence students’ engagement with the Web 2.0 learning initiative. The qualitative phase that followed provided insights into these tensions by shifting the analytics from individual attitudes and behaviours to shared social and cultural reasoning practices that explain students’ engagement with the innovation. Six indepth focus groups, comprising 60 students with different levels of SMC usage, were conducted, audio-recorded and transcribed. Textual data were analysed using Membership Categorisation Analysis. Students’ accounts converged around a key proposition. The Web 2.0 learning initiative was useful-in-principle but useless-in-practice. While students endorsed the usefulness of the SMC for enhancing multimodal engagement, extending peer-topeer networks and acquiring real-world skills, they also called attention to a number of constraints that obfuscated the realisation of these design affordances in practice. These constraints were cast in terms of three binary formulations of social and cultural imperatives at play within the school: (i) ‘cool/uncool’, (ii) ‘dominant staff/compliant student’, and (iii) ‘digital learning/academic performance’. The first formulation foregrounds the social stigma of the SMC among peers and its resultant lack of positive network benefits. The second relates to students’ perception of the school culture as authoritarian and punitive with adverse effects on the very student agency required to drive the innovation. The third points to academic performance pressures in a crowded curriculum with tight timelines. Taken together, findings from both phases of the study provide the following key insights. First, students endorsed the learning affordances of contemporary digital tools such as the SMC for enhancing their current schooling practices. For the majority of students, however, these learning affordances were overshadowed by the performative demands of schooling, both social and academic. The student participants saw engagement with the SMC in-school as distinct from, even oppositional to, the conventional social and academic performance indicators of schooling, namely (i) being ‘cool’ (or at least ‘not uncool’), (ii) sufficiently ‘compliant’, and (iii) achieving good academic grades. Their reasoned response therefore, was simply to resist engagement with the digital learning innovation. Second, a small minority of students seemed dispositionally inclined to negotiate the learning affordances and performance constraints of digital learning and traditional schooling more effectively than others. These students were able to engage more frequently and meaningfully with the SMC in school. Their ability to adapt and traverse seemingly incommensurate social and institutional identities and norms is theorised as cultural agility – a dispositional construct that comprises personal innovativeness, cognitive playfulness and learning goals orientation. The logic then is ‘both and’ rather than ‘either or’ for these individuals with a capacity to accommodate both learning and performance in school, whether in terms of digital engagement and academic excellence, or successful brokerage across multiple social identities and institutional affiliations within the school. In sum, this study takes us beyond the familiar terrain of deficit discourses that tend to blame institutional conservatism, lack of resourcing and teacher resistance for low uptake of digital technologies in schools. It does so by providing an empirical base for the development of a ‘third way’ of theorising technological and pedagogical innovation in schools, one which is more informed by students as critical stakeholders and thus more relevant to the lived culture within the school, and its complex relationship to students’ lives outside of school. It is in this relationship that we find an explanation for how these individuals can, at the one time, be digital kids and analogue students.

An analysis of assessment outcomes from eight years' operation of the Australian border weed risk assessment system

The majority of Australian weeds are exotic plant species that were intentionally introduced for a variety of horticultural and agricultural purposes. A border weed risk assessment system (WRA) was implemented in 1997 in order to reduce the high economic costs and massive environmental damage associated with introducing serious weeds. We review the behaviour of this system with regard to eight years of data collected from the assessment of species proposed for importation or held within genetic resource centres in Australia. From a taxonomic perspective, species from the Chenopodiaceae and Poaceae were most likely to be rejected and those from the Arecaceae and Flacourtiaceae were most likely to be accepted. Dendrogram analysis and classification and regression tree (TREE) models were also used to analyse the data. The latter revealed that a small subset of the 35 variables assessed was highly associated with the outcome of the original assessment. The TREE model examining all of the data contained just five variables: unintentional human dispersal, congeneric weed, weed elsewhere, tolerates or benefits from mutilation, cultivation or fire, and reproduction by vegetative propagation. It gave the same outcome as the full WRA model for 71% of species. Weed elsewhere was not the first splitting variable in this model, indicating that the WRA has a capacity for capturing species that have no history of weediness. A reduced TREE model (in which human-mediated variables had been removed) contained four variables: broad climate suitability, reproduction in less or than equal to 1 year, self-fertilisation, and tolerates and benefits from mutilation, cultivation or fire. It yielded the same outcome as the full WRA model for 65% of species. Data inconsistencies and the relative importance of questions are discussed, with some recommendations made for improving the use of the system.

Development of appropriateness explicit criteria for cataract extraction by phacoemulsification

Background: Consensus development techniques were used in the late 1980s to create explicit criteria for the appropriateness of cataract extraction. We developed a new appropriateness of indications tool for cataract following the RAND method. We tested the validity of our panel results. Methods: Criteria were developed using a modified Delphi panel judgment process. A panel of 12 ophthalmologists was assembled. Ratings were analyzed regarding the level of agreement among panelists. We studied the influence of all variables on the final panel score using linear and logistic regression models. The explicit criteria developed were summarized by classification and regression tree analysis. Results: Of the 765 indications evaluated by the main panel in the second round, 32.9% were found appropriate, 30.1% uncertain, and 37% inappropriate. Agreement was found in 53% of the indications and disagreement in 0.9%. Seven variables were considered to create the indications and divided into three groups: simple cataract, with diabetic retinopathy, or with other ocular pathologies. The preoperative visual acuity in the cataractous eye and visual function were the variables that best explained the panel scoring. The panel results were synthesized and presented in three decision trees. Misclassification error in the decision trees, as compared with the panel original criteria, was 5.3%. Conclusion: The parameters tested showed acceptable validity for an evaluation tool. These results support the use of this indication algorithm as a screening tool for assessing the appropriateness of cataract extraction in field studies and for the development of practice guidelines.

Snail heterogeneity in clear cell renal cell carcinoma

Background: Intratumor heterogeneity may be responsible of the unpredictable aggressive clinical behavior that some clear cell renal cell carcinomas display. This clinical uncertainty may be caused by insufficient sampling, leaving out of histological analysis foci of high grade tumor areas. Although molecular approaches are providing important information on renal intratumor heterogeneity, a focus on this topic from the practicing pathologist' perspective is still pending. Methods: Four distant tumor areas of 40 organ-confined clear cell renal cell carcinomas were selected for histopathological and immunohistochemical evaluation. Tumor size, cell type (clear/granular), Fuhrman's grade, Staging, as well as immunostaining with Snail, ZEB1, Twist, Vimentin, E-cadherin, beta-catenin, PTEN, p-Akt, p110 alpha, and SETD2, were analyzed for intratumor heterogeneity using a classification and regression tree algorithm. Results: Cell type and Fuhrman's grade were heterogeneous in 12.5 and 60 % of the tumors, respectively. If cell type was homogeneous (clear cell) then the tumors were low-grade in 88.57 % of cases. Immunostaining heterogeneity was significant in the series and oscillated between 15 % for p110a and 80 % for Snail. When Snail immunostaining was homogeneous the tumor was histologically homogeneous in 100 % of cases. If Snail was heterogeneous, the tumor was heterogeneous in 75 % of the cases. Average tumor diameter was 4.3 cm. Tumors larger than 3.7 cm were heterogeneous for Vimentin immunostaining in 72.5 % of cases. Tumors displaying negative immunostaining for both ZEB1 and Twist were low grade in 100 % of the cases. Conclusions: Intratumor heterogeneity is a common event in clear cell renal cell carcinoma, which can be monitored by immunohistochemistry in routine practice. Snail seems to be particularly useful in the identification of intratumor heterogeneity. The suitability of current sampling protocols in renal cancer is discussed.

基于广义模型和分类回归树的中国常见树种地理分布模拟研究

研究植被、物种分布与环境的关系一直是生态学中的重点。长期以来，在全球变化与陆地生态系统的研究中，主要研究重点是对大尺度植被分布的模拟和预测，并建立了大量的气候－植被分布关系模型。而对于物种潜在分布的模拟和预测，国内外相关的研究较少。近年来，随着统计技术和地理信息系统的发展，用于预测物种分布的统计模型技术得到了迅速的发展。统计模型技术已被广泛应用于生物地理分布、植物群落、生物多样性、气候变化影响评估等方面。 本论文基于当前在物种分布研究中应用广泛的广义线性模型、广义加法模型及分类回归树3种统计模型技术，对我国常见树种的地理分布进行模拟分析，并比较不同模型模拟精度的优劣，将模拟精度较高的模型应用于预测未来气候情景下我国几种主要树种的未来潜在地理分布。 基于建立的广义线性模型（GLM）、二次项逐步回归广义线性模型（SGLM）、广义加法模型（GAM）和分类回归树（CART）4个模型对我国20种常见树种地理分布进行模拟，结果表明，4个模型均有较高的模拟精度。GAM的模拟精度最高;添加二次项并进行逐步回归有效的提高了GLM的模拟精度;CART是一种基于规则的模型技术，模拟结果比GLM稍好，比GAM略差。 对不同树种的模拟分析表明，4个模型对于主要分布在暖温带落叶阔叶林区域的油松、辽东栎分布的模拟结果较差;GLM对分布在温带针阔混交林中红松、蒙古栎、胡桃楸和糠椴的模拟结果不太理想;4个模型对分布在中国亚热带常绿阔叶林区域的树种均表现出较高的模拟精度;对广布种也表现出很高的模拟精度。 结合地理信息系统，以地图形式将青冈、油松的模拟结果表示出来。结果表明：地理信息系统直观的反映出了模型模拟结果差异。4个模型均能很好模拟青冈的分布，且模拟结果接近;而对油松分布模拟结果4个模型均不甚理想，以GLM最差。这些结果与模型模拟评估结果相吻合。 在未来气候变化情景下，基于4个模型模拟结果优劣，以我国三种主要造林树种马尾松、油松、红松和两种常见树种青冈、蒙古栎为研究对象，分析其未来变化趋势。结果表明，未来气候变化情景下，对于马尾松而言，4个模型均预测马尾松在基本保持原有分布的基础上，其未来潜在分布区域均有所扩大，且有向西和向北扩展的趋势;对于油松而言，基于GLM、SGLM和GAM3个模型，油松的未来潜在分布除有北移的趋势外，其分布区还将向东北和西南两个方向扩展;对于红松而言，基于SGLM、GAM和CART3个模型的预测结果较为接近，即红松的未来潜在分布区域将有所减少;对蒙古栎而言，4个模型预测蒙古栎未来分布均将向西扩展;对青冈而言，4个模型预测青冈能基本保持其原有分布区，并向西和向北扩展，其中CART预测结果还表明，青冈在广东南部及广西南部的分布区域将消失。

Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

Facteurs de risque de chutes chez les aînés vivant dans la communauté et ayant recours aux services de soutien à domicile : covariables dépendantes du temps et événements récurrents

Les chutes chez les personnes âgées représentent un problème majeur. Il n’est donc pas étonnant que l’identification des facteurs qui en accroissent le risque ait mobilisé autant d’attention. Les aînés plus fragiles ayant besoin de soutien pour vivre dans la communauté sont néanmoins demeurés le parent pauvre de la recherche, bien que, plus récemment, les autorités québécoises en aient fait une cible d’intervention prioritaire. Les études d’observation prospectives sont particulièrement indiquées pour étudier les facteurs de risque de chutes chez les personnes âgées. Leur identification optimale est cependant compliquée par le fait que l’exposition aux facteurs de risque peut varier au cours du suivi et qu’un même individu peut subir plus d’un événement. Il y a 20 ans, des chercheurs ont tenté de sensibiliser leurs homologues à cet égard, mais leurs efforts sont demeurés vains. On continue aujourd’hui à faire peu de cas de ces considérations, se concentrant sur la proportion des personnes ayant fait une chute ou sur le temps écoulé jusqu’à la première chute. On écarte du coup une quantité importante d’information pertinente. Dans cette thèse, nous examinons les méthodes en usage et nous proposons une extension du modèle de risques de Cox. Nous illustrons cette méthode par une étude des facteurs de risque susceptibles d’être associés à des chutes parmi un groupe de 959 personnes âgées ayant eu recours aux services publics de soutien à domicile. Nous comparons les résultats obtenus avec la méthode de Wei, Lin et Weissfeld à ceux obtenus avec d’autres méthodes, dont la régression logistique conventionnelle, la régression logistique groupée, la régression binomiale négative et la régression d’Andersen et Gill. L’investigation est caractérisée par des prises de mesures répétées des facteurs de risque au domicile des participants et par des relances téléphoniques mensuelles visant à documenter la survenue des chutes. Les facteurs d’exposition étudiés, qu’ils soient fixes ou variables dans le temps, comprennent les caractéristiques sociodémographiques, l’indice de masse corporelle, le risque nutritionnel, la consommation d’alcool, les dangers de l’environnement domiciliaire, la démarche et l’équilibre, et la consommation de médicaments. La quasi-totalité (99,6 %) des usagers présentaient au moins un facteur à haut risque. L’exposition à des risques multiples était répandue, avec une moyenne de 2,7 facteurs à haut risque distincts par participant. Les facteurs statistiquement associés au risque de chutes incluent le sexe masculin, les tranches d’âge inférieures, l’histoire de chutes antérieures, un bas score à l’échelle d’équilibre de Berg, un faible indice de masse corporelle, la consommation de médicaments de type benzodiazépine, le nombre de dangers présents au domicile et le fait de vivre dans une résidence privée pour personnes âgées. Nos résultats révèlent cependant que les méthodes courantes d’analyse des facteurs de risque de chutes – et, dans certains cas, de chutes nécessitant un recours médical – créent des biais appréciables. Les biais pour les mesures d’association considérées proviennent de la manière dont l’exposition et le résultat sont mesurés et définis de même que de la manière dont les méthodes statistiques d’analyse en tiennent compte. Une dernière partie, tout aussi innovante que distincte de par la nature des outils statistiques utilisés, complète l’ouvrage. Nous y identifions des profils d’aînés à risque de devenir des chuteurs récurrents, soit ceux chez qui au moins deux chutes sont survenues dans les six mois suivant leur évaluation initiale. Une analyse par arbre de régression et de classification couplée à une analyse de survie a révélé l’existence de cinq profils distinctifs, dont le risque relatif varie de 0,7 à 5,1. Vivre dans une résidence pour aînés, avoir des antécédents de chutes multiples ou des troubles de l’équilibre et consommer de l’alcool sont les principaux facteurs associés à une probabilité accrue de chuter précocement et de devenir un chuteur récurrent. Qu’il s’agisse d’activité de dépistage des facteurs de risque de chutes ou de la population ciblée, cette thèse s’inscrit dans une perspective de gain de connaissances sur un thème hautement d’actualité en santé publique. Nous encourageons les chercheurs intéressés par l’identification des facteurs de risque de chutes chez les personnes âgées à recourir à la méthode statistique de Wei, Lin et Weissfeld car elle tient compte des expositions variables dans le temps et des événements récurrents. Davantage de recherches seront par ailleurs nécessaires pour déterminer le choix du meilleur test de dépistage pour un facteur de risque donné chez cette clientèle.

L'évaluation du risque de récidive chez les agresseurs sexuels adultes

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Validierung von HPLC-Methoden zur Bestimmung von Polyphenolen und Carotinoiden in Möhren, Weizen und Mais unterschiedlicher Herkunft

In den vorliegenden Untersuchungen wurde der Gehalt von Carotinoiden in Weizen, Mais und Möhren sowie der Polyphenolgehalt in Möhren mit analytischen Methoden zum Nachweis dieser Substanzen gemessen. Der Gehalt der Carotinoide in Mais und der Gehalt der phenolischen Bestandteile in Möhren wurde mit Messungen mittels HPLC-Analytik gemessen. Die Methoden wurden aus literaturbekannten Verfahren abgeleitet und an die Anforderungen der untersuchten Probenmatrices angepasst und validiert. Dem Verfahren lag die Frage zugrunde, ob es möglich ist, Kulturpflanzen aus verschiedenen Anbausystemen auf der Basis des Gehaltes bestimmter sekundärer Pflanzeninhaltsstoffe zu differenzieren und aufgrund von Unterschieden im Gehalt der sekundären Pflanzeninhaltsstoffe zu klassifizieren. Die Gesamtverfahren wurden dabei gemäß der ISO 17025 validiert. Für die Messungen standen Proben aus definierten Langzeitversuchen und Erzeugerproben ausgesuchter ökologisch bzw. konventionell arbeitender Anbaubetriebe zur Verfügung. Als Grundlage für eine valide Methodeneinschätzung wurden die Messungen an codierten Proben vorgenommen. Eine Decodierung der Proben erfolgte erst nach der Vorlage der Messergebnisse in den genannten Projekten. Die Messung und Auswertung des Carotinoidgehaltes in Weizen, Mais und Möhren vor dem Hintergrund der Differenzierung und Klassifizierung erfolgte in Proben eines Erntejahres. Die Messung des Gehaltes phenolischer Substanzen in Möhren erfolgte in Möhren aus 3 Erntejahren. Die verwendeten HPLC-Verfahren konnten in Bezug auf den analytischen Teil der Messungen in den einzelnen Verfahrensschritten Linearität, Spezifität, Präzision und Robustheit erfolgreich überprüft werden. Darüber hinaus wurden wichtige Einflussgrößen auf die Messungen bestimmt. Für die Verfahren zur photometrischen Bestimmung der Gesamtcarotinoide konnte eine Grundkalibrierung der Parameter Präzision und Linearität des Verfahrens erfolgreich durchgeführt werden. Während der Anwendung der HPLC-Methoden an codierten Proben konnten in allen untersuchten Probenmatrices quantitativ bedeutende Inhaltsstoffe nachgewiesen und identifiziert werden. Eine vollständige Identifizierung aller dargestellten Peaks konnte in den Untersuchungen der Polyphenole in Möhren und der Carotinoide in Mais nicht erfolgen. Im Hinblick auf die Frage nach der Differenzierung und Klassifizierung ergab sich in den verschiedenen Proben ein unterschiedliches Bild. Sowohl durch den Carotinoid- als auch den Polyphenolgehalt konnten einzelne Proben statistisch signifikant differenziert werden. Die Trennleistung hing dabei sowohl von den jeweiligen Komponenten als auch von der untersuchten Probenmatrix ab. Ein durchgängig höherer Gehalt sekundärer Pflanzeninhaltsstoffe in Proben aus ökologischem Anbau konnte nicht bestätigt werden. Für die Klassifizierung der Proben verschiedener Anbauvarianten und konnten multivariate statistische Methoden, wie lineare Diskriminantenanalyse (LDA) und Classification and Regression Tree (CART), erfolgreich angewandt werden. Eine Klassifizierung mit unterschiedlichen statistischen Verfahren erbrachte dabei unterschiedliche Ergebnisse. In der Klassifizierung der decodierten Proben mittels LDA wirkten sich die Faktoren Sorte und Standort stärker auf das Klassifizierungsergebnis aus als der Faktor Anbausystem. Eine Klassifizierung der decodierten Proben nach dem Anbausystem wurde mit dem CART-Verfahren durchgeführt. Auf dieser Basis wurden für die Polyphenole in Möhren 97 % der Proben richtig klassifiziert. Durch die Messwerte des Carotinoidgehaltes und des Luteingehaltes in Weizen konnte der größere Teil der Proben (90 %) korrekt klassifiziert werden. Auf der Basis des Carotinoidgehaltes in Mais wurde der Großteil der Proben (95 %) korrekt nach dem Anbausystem klassifiziert. Auf der Basis des mittels HPLC gemessenen Carotinoidgehaltes in Möhren konnten die Proben 97 % korrekt klassifiziert werden (97 %). Insgesamt erscheint der Grundgedanke der Klassifizierung durch den Gehalt sekundärer Pflanzeninhaltsstoffe vielversprechend. Durch die vielfältigen Einflussgrößen auf den Sekundärstoffwechsel von Pflanzen müssten Veränderungen, die durch Sorte und Standort auftreten, über mehrere Jahre erhoben und systematisiert werden.

Enfermedad tiroidea autoinmune en pacientes colombianos con lupus eritematoso sistémico

Objetivos: Determinar la prevalencia y los factores asociados con el desarrollo de hipotiroidismo autoinmune (HA) en una cohorte de pacientes con lupus eritematoso sistémico (LES), y analizar la información actual en cuanto a la prevalencia e impacto de la enfermedad tiroidea autoinmune y la autoinmunidad tiroidea en pacientes con LES. Métodos: Este fue un estudio realizado en dos pasos. Primero, un total de 376 pacientes con LES fueron evaluados sistemáticamente por la presencia de: 1) HA confirmado, 2) positividad para anticuerpos tiroperoxidasa/tiroglobulina (TPOAb/TgAb) sin hipotiroidismo, 3) hipotiroidismo no autoinmune, y 4) pacientes con LES sin hipotiroidismo ni positividad para TPOAb/TgAb. Se construyeron modelos multivariados y árboles de regresión y clasificación para analizar los datos. Segundo, la información actual fue evaluada a través de una revisión sistemática de la literatura (RLS). Se siguieron las guías PRISMA para la búsqueda en las bases de datos PubMed, Scopus, SciELO y Librería Virtual en Salud. Resultados: En nuestra cohorte, la prevalencia de HA confirmado fue de 12% (Grupo 1). Sin embargo, la frecuencia de positividad para TPOAb y TgAb fue de 21% y 10%, respectivamente (Grupo 2). Los pacientes con LES sin HA, hipotiroidismo no autoinmune ni positividad para TPOAb/TgAb constituyeron el 40% de la corhorte. Los pacientes con HA confirmada fueron estadísticamente significativo de mayor edad y tuvieron un inicio tardío de la enfermedad. El tabaquismo (ORA 6.93, IC 95% 1.98-28.54, p= 0.004), la presencia de Síndrome de Sjögren (SS) (ORA 23.2, IC 95% 1.89-359.53, p= 0.015) y la positividad para anticuerpos anti-péptido cíclico citrulinado (anti-CCP) (ORA 10.35, IC 95% 1.04-121.26, p= 0.047) se asociaron con la coexistencia de LES-HA, ajustado por género y duración de la enfermedad. El tabaquismo y el SS fueron confirmados como factores predictivos para LES-HA (AUC del modelo CART = 0.72). En la RSL, la prevalencia de ETA en LES varío entre 1% al 60%. Los factores asociados con esta poliautoinmunidad fueron el género femenino, edad avanzada, tabaquismo, positividad para algunos anticuerpos, SS y el compromiso articular y cutáneo. Conclusiones: La ETA es frecuente en pacientes con LES, y no afecta la severidad del LES. Los factores de riesgo identificados ayudarán a los clínicos en la búsqueda de ETA. Nuestros resultados deben estimular políticas para la suspensión del tabaquismo en pacientes con LES.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Developing a provisional definition of flare in patients with established gout

Objective Various nonvalidated criteria for disease flare have been used in studies of gout. Our objective was to develop empirical definitions for a gout flare from patient-reported features. Methods Possible elements for flare criteria were previously reported. Data were collected from 210 gout patients at 8 international sites to evaluate potential gout flare criteria against the gold standard of an expert rheumatologist definition. Flare definitions based on the presence of the number of criteria independently associated with the flare and classification and regression tree approaches were developed. Results The mean +/- SD age of the study participants was 56.2 +/- 15 years, 207 of them (98%) were men, and 54 of them (26%) had flares of gout. The presence of any patient-reported warm joint, any patient-reported swollen joint, patient-reported pain at rest score of >3 (010 scale), and patient-reported flare were independently associated with the study gold standard. The greatest discriminating power was noted for the presence of 3 or more of the above 4 criteria (sensitivity 91% and specificity 82%). Requiring all 4 criteria provided the highest specificity (96%) and positive predictive value (85%). A classification tree identified pain at rest with a score of >3, followed by patient self-reported flare, as the rule associated with the gold standard (sensitivity 83% and specificity 90%). Conclusion We propose definitions for a disease flare based on self-reported items in patients previously diagnosed as having gout. Patient-reported flare, joint pain at rest, warm joints, and swollen joints were most strongly associated with presence of a gout flare. These provisional definitions will next be validated in clinical trials.

Augmented reality in sport scenarios using cameras mounted on a tripod

[ES] In this paper we address the problem of inserting virtual content in a video sequence. The method we propose uses just image information. We perform primitive tracking, camera calibration, real and virtual camera synchronisation and finally rendering to insert the virtual content in the real video sequence. To simplify the calibration step we assume that cameras are mounted on a tripod (which is a common situation in practise). The primitive tracking procedure, which uses lines and circles as primitives, is performed by means of a CART (Classification and Regression Tree). Finally, the virtual and real camera synchronisation and rendering is performed using functions of OpenGL (Open Graphic Library). We have applied the method proposed to sport event scenarios, specifically, soccer matches. In order to illustrate its performance, it has been applied to real HD (High Definition) video sequences. The quality of the proposed method is validated by inserting virtual elements in such HD video sequence.

CART application to image primitives tracking

[EN] [EN] In this paper we present a new method for image primitives tracking based on a CART (Classification and Regression Tree). Primitives tracking procedure uses lines and circles as primitives. We have applied the proposed method to sport event scenarios, specifically, soccer matches. We estimate CART parameters using a learning procedure based on RGB image channels. In order to illustrate its performance, it has been applied to real HD (High Definition) video sequences and some numerical experiments are shown. The quality of the primitives tracking with the decision tree is validated by the percentage error rates obtained and the comparison with other techniques as a morphological method. We also present applications of the proposed method to camera calibration and graphic object insertion in real video sequences.

A computational model of prosody for Yorùbá text-to-speech synthesis

This work examines prosody modelling for the Standard Yorùbá (SY) language in the context of computer text-to-speech synthesis applications. The thesis of this research is that it is possible to develop a practical prosody model by using appropriate computational tools and techniques which combines acoustic data with an encoding of the phonological and phonetic knowledge provided by experts. Our prosody model is conceptualised around a modular holistic framework. The framework is implemented using the Relational Tree (R-Tree) techniques (Ehrich and Foith, 1976). R-Tree is a sophisticated data structure that provides a multi-dimensional description of a waveform. A Skeletal Tree (S-Tree) is first generated using algorithms based on the tone phonological rules of SY. Subsequent steps update the S-Tree by computing the numerical values of the prosody dimensions. To implement the intonation dimension, fuzzy control rules where developed based on data from native speakers of Yorùbá. The Classification And Regression Tree (CART) and the Fuzzy Decision Tree (FDT) techniques were tested in modelling the duration dimension. The FDT was selected based on its better performance. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration and intonation, using different techniques and their subsequent integration. Our approach provides us with a flexible and extendible model that can also be used to implement, study and explain the theory behind aspects of the phenomena observed in speech prosody.