892 resultados para research higher degree


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Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.

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Reproductive isolation between lineages is expected to accumulate with divergence time, but the time taken to speciate may strongly vary between different groups of organisms. In anuran amphibians, laboratory crosses can still produce viable hybrid offspring >20 My after separation, but the speed of speciation in closely related anuran lineages under natural conditions is poorly studied. Palearctic green toads (Bufo viridis subgroup) offer an excellent system to address this question, comprising several lineages that arose at different times and form secondary contact zones. Using mitochondrial and nuclear markers, we previously demonstrated that in Sicily, B. siculus and B. balearicus developed advanced reproductive isolation after Plio-Pleistocene divergence (2.6 My, 3.3-1.9), with limited historic mtDNA introgression, scarce nuclear admixture, but low, if any, current gene flow. Here, we study genetic interactions between younger lineages of early Pleistocene divergence (1.9 My, 2.5-1.3) in northeastern Italy (B. balearicus, B. viridis). We find significantly more, asymmetric nuclear and wider, differential mtDNA introgression. The population structure seems to be molded by geographic distance and barriers (rivers), much more than by intrinsic genomic incompatibilities. These differences of hybridization between zones may be partly explained by differences in the duration of previous isolation. Scattered research on other anurans suggests that wide hybrid zones with strong introgression may develop when secondary contacts occur <2 My after divergence, whereas narrower zones with restricted gene flow form when divergence exceeds 3 My. Our study strengthens support for this rule of thumb by comparing lineages with different divergence times within the same radiation.

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Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

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The aim of this paper is to analyse the impact of university knowledge and technology transfer activities on academic research output. Specifically, we study whether researchers with collaborative links with the private sector publish less than their peers without such links, once controlling for other sources of heterogeneity. We report findings from a longitudinal dataset on researchers from two engineering departments in the UK between 1985 until 2006. Our results indicate that researchers with industrial links publish significantly more than their peers. Academic productivity, though, is higher for low levels of industry involvement as compared to high levels.

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The diagnosis of idiopathic Parkinson's disease (IPD) is entirely clinical. The fact that neuronal damage begins 5-10 years before occurrence of sub-clinical signs, underlines the importance of preclinical diagnosis. A new approach for in-vivo pathophysiological assessment of IPD-related neurodegeneration was implemented based on recently developed neuroimaging methods. It is based on non- invasive magnetic resonance data sensitive to brain tissue property changes that precede macroscopic atrophy in the early stages of IPD. This research aims to determine the brain tissue property changes induced by neurodegeneration that can be linked to clinical phenotypes which will allow us to create a predictive model for early diagnosis in IPD. We hypothesized that the degree of disease progression in IPD patients will have a differential and specific impact on brain tissue properties used to create a predictive model of motor and non-motor impairment in IPD. We studied the potential of in-vivo quantitative imaging sensitive to neurodegeneration- related brain tissue characteristics to detect changes in patients with IPD. We carried out methodological work within the well established SPM8 framework to estimate the sensitivity of tissue probability maps for automated tissue classification for detection of early IPD. We performed whole-brain multi parameter mapping at high resolution followed by voxel-based morphometric (VBM) analysis and voxel-based quantification (VBQ) comparing healthy subjects to IPD patients. We found a trend demonstrating non-significant tissue property changes in the olfactory bulb area using the MT and R1 parameter with p<0.001. Comparing to the IPD patients, the healthy group presented a bilateral higher MT and R1 intensity in this specific functional region. These results did not correlate with age, severity or duration of disease. We failed to demonstrate any changes with the R2* parameter. We interpreted our findings as demyelination of the olfactory tract, which is clinically represented as anosmia. However, the lack of correlation with duration or severity complicates its implications in the creation of a predictive model of impairment in IPD.

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Objective To analyze the characteristics of faculty work in nursing higher education. Method An exploratory qualitative study with a theoretical-methodological framework of dialectical and historical materialism. The faculty work process was adopted as the analytical category, grounded on conceptions of work and professionalism. Semi-structured interviews were conducted with 24 faculty members from three higher education institutions in the city of São Paulo, classified according to the typology of institutional contexts. Results The faculty members at these higher education institutions are a heterogeneous group, under different working conditions. Intensification and precarious conditions of the faculty work is common to all three contexts, although there are important distinctions in the practices related to teaching, research and extension. Conclusion Faculty professionalization can be the starting point for analyzing and coping with such a distinct reality of faculty work and practice.


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Abstract OBJECTIVE Developing and validating an instrument to evaluate the playfulness of games in health education contexts. METHODOLOGY A methodological, exploratory and descriptive research, developed in two stages: 1. Application of an open questionnaire to 50 graduate students, with content analysis of the answers and calculation of Kappa coefficient for defining items; 2. Procedures for construction of scales, with content validation by judges and analysis of the consensus estimate byContent Validity Index(CVI). RESULTS 53 items regarding the restless character of the games in the dimensions of playfulness, the formative components of learning and the profiles of the players. CONCLUSION Ludicity can be assessed by validated items related to the degree of involvement, immersion and reinvention of the subjects in the game along with the dynamics and playability of the game.

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D'Aspremont and Jacquemin's (1988) model is extended to studyalternative configurations of research agreements in a two--country integratedworld economy. Under unambiguous conditions on spillovers we show that:1) Allowing national firms to cooperate in R\&D confers them an advantageover foreign rivals, an effect similar to R\&D subsidies. 2) In a policygame, each government would allow national cooperative agreements. 3) Contraryto other trade policies which lead to a ``prisoners' dilemma'' result,welfare in both countries increases when they both allow R\&D cooperation.4) Welfare is even higher if a generalized (international) coalition isformed.

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BACKGROUND: Hypertension, hypercholesterolemia, obesity and smoking are highly prevalent among patients with familial premature coronary artery disease (FP-CAD). Whether these risk factors equally affect other family members remains unknown. METHODS: We examined 222 FP-CAD patients, 158 unaffected sibs, 197 offspring and 94 spouses in 108 FP-CAD families (> or = 2 sibs having survived CAD diagnosed before age 51 (M)/56 (F)), and compared them to population controls. RESULTS: Unaffected sibs had a higher prevalence of hypertension (49% versus 24%, p<0.001), hypercholesterolemia (47% versus 34%, p=0.002), abdominal obesity (35% versus 24%, p=0.006) and smoking (39% versus 24%, p=0.001) than population controls. Offspring had a higher prevalence of hypertension (females), hypercholesterolemia and abdominal obesity than population controls. No difference was observed between spouses and controls. Compared to unaffected sibs, FP-CAD affected sibs had a similar risk factor profile, except for smoking, which was more prevalent (76% versus 39%, p=0.008). CONCLUSIONS: Hypertension, obesity and hypercholesterolemia are highly prevalent among first-degree relatives, but not spouses, of patients with FP-CAD. These persons deserve special medical attention due to their familial/genetic susceptibility to atherogenic metabolic abnormalities. In these families, smoking may be the trigger for FP-CAD.

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This paper analyzes the formation of Research Corporations as an alternative governance structure for performing R&D compared to pursuing in-house R&D projects. Research Corporations are privatefor-profit research centers that bring together several firms with similar research goals. In a Research Corporation formal authority over the choice of projects is jointly exercised by the top management of the member firms. A private for-profit organization cannot commit not to interfere with the project choice of the researchers. However, increasing the number of member firms of the Research Corporation reduces the incentive of member firms to meddle with the research projects of researchers because exercising formal authority over the choice of research projects is a public good. The Research Corporation thus offers researchers greater autonomy than a single firm pursuing an identical research program in its in-house R&D department. This attracts higher ability researchers to the Research Corporation compared to the internal R&D department. The paper uses the theoretical model to analyze the organization of the Microelectronics and Computer Technology Corporation (MCC). The facts of this case confirm the existence of a tension between control over the choice of research projects and the ability of researchers that the organization is able to attract or hold onto.

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BACKGROUND: Strict definition of invasive aspergillosis (IA) cases is required to allow precise conclusions about the efficacy of antifungal therapy. The Global Comparative Aspergillus Study (GCAS) compared voriconazole to amphotericin B (AmB) deoxycholate for the primary therapy of IA. Because predefined definitions used for this trial were substantially different from the consensus definitions proposed by the European Organization for Research and Treatment of Cancer/Mycoses Study Group in 2008, we recategorized the 379 episodes of the GCAS according to the later definitions. METHODS: The objectives were to assess the impact of the current definitions on the classification of the episodes and to provide comparative efficacy for probable/proven and possible IA in patients treated with either voriconazole or AmB. In addition to original data, we integrated the results of baseline galactomannan serum levels obtained from 249 (65.7%) frozen samples. The original response assessment was accepted unchanged. RESULTS: Recategorization allowed 59 proven, 178 probable, and 106 possible IA cases to be identified. A higher favorable 12-week response rate was obtained with voriconazole (54.7%) than with AmB (29.9%) (P < .0001). Survival was higher for voriconazole for mycologically documented (probable/proven) IA (70.2%) than with AmB (54.9%) (P = .010). Higher response rates were obtained in possible IA treated with voriconazole vs AmB with the same magnitude of difference (26.2%; 95% confidence interval [CI], 7.2%-45.3%) as in mycologically documented episodes (24.3%; 95% CI, 11.9%-36.7%), suggesting that possible cases are true IA. CONCLUSIONS: Recategorization resulted in a better identification of the episodes and confirmed the higher efficacy of voriconazole over AmB deoxycholate in mycologically documented IA.

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BACKGROUND: Non-response is a major concern among substance use epidemiologists. When differences exist between respondents and non-respondents, survey estimates may be biased. Therefore, researchers have developed time-consuming strategies to convert non-respondents to respondents. The present study examines whether late respondents (converted former non-participants) differ from early respondents, non-consenters or silent refusers (consent givers but non-participants) in a cohort study, and whether non-response bias can be reduced by converting former non-respondents. METHODS: 6099 French- and 5720 German-speaking Swiss 20-year-old males (more than 94% of the source population) completed a short questionnaire on substance use outcomes and socio-demographics, independent of any further participation in a cohort study. Early respondents were those participating in the cohort study after standard recruitment procedures. Late respondents were non-respondents that were converted through individual encouraging telephone contact. Early respondents, non-consenters and silent refusers were compared to late respondents using logistic regressions. Relative non-response biases for early respondents only, for respondents only (early and late) and for consenters (respondents and silent refusers) were also computed. RESULTS: Late respondents showed generally higher patterns of substance use than did early respondents, but lower patterns than did non-consenters and silent refusers. Converting initial non-respondents to respondents reduced the non-response bias, which might be further reduced if silent refusers were converted to respondents. CONCLUSION: Efforts to convert refusers are effective in reducing non-response bias. However, converted late respondents cannot be seen as proxies of non-respondents, and are at best only indicative of existing response bias due to persistent non-respondents.

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We study the impact of university-industry research collaborations on academicoutput, in terms of productivity and direction of research. We report findings froma longitudinal dataset on all the researchers from the engineering departments inthe UK in the last 20 years. We control for the endogeneity caused by the dynamicnature of research and the existence of reverse causality. Our results indicate thatresearchers with industrial links publish significantly more. Productivity, though,is higher for low levels of industry involvement. Moreover, growing ties with theindustry skew research towards a more applied approach.

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Selostus: Sian kasvuominaisuuksien perinnölliset tunnusluvut arvioituna kolmannen asteen polynomifunktion avulla