873 resultados para Democratization of Knowledge


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An open prospective study was conducted among the patients visiting an urban medical policlinic for the first time without an appointment to assess whether the immigrants (who represent more than half of our patients) are aware of the health effects of smoking, whether the level of acculturation influences knowledge, and whether doctors give similar advice to Swiss and foreign smokers. 226 smokers, 105 Swiss (46.5%), and 121 foreign-born (53.5%), participated in the study. 32.2% (95% CI [24.4%; 41.1%]) of migrants and 9.6% [5.3%; 16.8%] of Swiss patients were not aware of negative effects of smoking. After adjustment for age, the multivariate model showed that the estimated odds of "ignorance of health effects of smoking" was higher for people lacking mastery of the local language compared with those mastering it (odds ratio (OR) = 7.5 [3.6; 15.8], p < 0.001), and higher for men (OR = 4.3 [1.9; 10.0], p < 0.001). Advice to stop smoking was given with similar frequency to immigrants (31.9% [24.2%; 40.8%] and Swiss patients (29.0% [21.0%; 38.5%]). Nonintegrated patients did not appear to receive less counselling than integrated patients (OR = 1.1 [0.6; 2.1], p = 0.812). We conclude that the level of knowledge among male immigrants not integrated or unable to speak the local language is lower than among integrated foreign-born and Swiss patients. Smoking cessation counselling by a doctor was only given to a minority of patients, but such counselling seemed irrespective of nationality.

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The work by Koglin et al. (Koglin, N., Kostopoulos, D., Reichmann, T., 2009. Geochemistry, petrogenesis and tectonic setting of the Samothraki mafic Suite, NE Greece: Trace-element, isotopic and zircon age constraints. Tectonophysics 473, 53-68. doi: 10.1016/j.tecto.2008.10.028), where the authors have proposed to nullify the scenario presented by Bonev and Stampfli (Bonev, N., Stampfli, G., 2008. Petrology, geochemistry and geodynamic implications of Jurassic island arc magmatism as revealed by mafic volcanic rocks in the Mesozoic low-grade sequence, eastern Rhodope, Bulgaria. Lithos 100, 210-233) is here Put under discussion. The arguments for this proposal are reviewed in the light of available stratigraphic and radiometric age constraints, geochemical signature and tectonics of highly relevant Jurassic ophiolitic suites occurring immediately north of the Samothraki mafic suite. Our conclusion is that the weak arguments and the lack of knowledge on the relevant constraints from the regional geologic information make inconsistent the Proposal and the model of these authors. (C) 2009 Elsevier B.V. All rights reserved.

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BackgroundDespite the intrinsic value of scientific disciplines, such as Economics, it is appropriate to gauge the impact of its applications on social welfare, or at least Health Economics (HE) case- its influence on health policy and management.MethodsThe three relevant features of knowledge (production, diffusion and application) are analyzed, more from an emic perspective the one used in Anthropology relying on the experience of the members of a culture- than from an etic approach seated on material descriptions and dubious statistics.ResultsThe soundness of the principles and results of HE depends on its disciplinary foundations,whereas its relevance than does not imply translation into practice- is more linked with the problems studied. Important contributions from Economics to the health sphere are recorded.HE in Spain ranks seventh in the world despite the relatively minor HE contents of its clinical and health services research journals.HE has in Spain more presence than influence, having failed to impregnate sufficiently thedaily events.ConclusionsHE knowledge required by a politician, a health manager or a clinician is rather limited; the main impact of HE could be to develop their intuition and awareness.

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Objectives: This study aims to explore subjectives theories (Flick, 1991) concerning sexualityamong gynaecologists. Methods: We conducted 27 deepened semi-structured interviews withmen and women gynaecologists, in the French part of Switzerland. A thematic contentanalysis was applied to the entire corpus. Results: We observe that discourse on sexualityissues can be source of discomfort during consultation with patients. Our analysis highlightsdisparities among levels of knowledge, attitudes and practices in gynaecologists. We observedthat their knowledges on sexuality seem to be constructed mainly on a profane knowledgebased on the common sense and/or their personal experiences. Furthermore, our findingsshow sex differences among physicians, especially on theoretical perspectives underlying theirdiscourse, and the time they allow themselves to spend with a patient. Conclusion: Nowadays,gynaecologists come across sexuality issues that go beyond anatomical and physiologicalconsiderations and for which they are not necessarily qualified. Our research suggests toanalyse both the role and the limits of gynaecologists as well as the motivations guiding theircurrent practice.

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In this chapter we portray the effects of female education and professional achievementon fertility decline in Spain over the period 1920-1980 (birth cohorts of 1900-1950).A longitudinal econometric approach is used to test the hypothesis that the effectsof women s education in the revaluing of their time had a very significant influence onfertility decline. Although in the historical context presented here improvements inschooling were on a modest scale, they were continuous (with the interruption of theCivil War) and had a significant impact in shaping a model of low fertility in Spain. Wealso stress the relevance of this result in a context such as the Spanish for which liberalvalues were absent, fertility control practices were forbidden, and labour forceparticipation of women was politically and socially constrained.

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Study of the mayfly order Ephemeroptera (Insecta) in Brazil: a scienciometric review. Despite an increase in the number of studies in recent years of the aquatic insect order Ephemeroptera (the mayflies) much still remains to be learnt. In order to identify the current state of knowledge of this group in Brazil, we performed a scienciometric analysis with the purpose of identifying the strong and weak points of Brazilian research into the group. Our research used the "Institute for Scientific Information - ISI" database and was based on the abstracts, titles and keywords of manuscripts published between 1992 and 2011. We selected the papers with the combination of the words "Ephemeroptera" and "Brazil*" based on a search in February 2012. We analyzed 92 articles, and noted a lack of studies in some Brazilian states, no specific studies about some families, and an absence of phylogenetic studies. To improve ecological studies, it is necessary to fine-tune taxonomic resolution. Moreover, there is a lack of studies investigating the environmental variables which influence the distribution of mayflies. Despite these gaps, if the rate of publication with mayflies proceeds at the same pace, we anticipate that many of these knowledge gaps will be closed.

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BACKGROUND: Interventions have been developed to reduce overestimations of substance use among others, especially for alcohol and among students. Nevertheless, there is a lack of knowledge on misperceptions of use for substances other than alcohol. We studied the prevalence of misperceptions of use for tobacco, cannabis, and alcohol and whether the perception of tobacco, cannabis, and alcohol use by others is associated with one's own use. METHODS: Participants (n=5216) in a cohort study from a census of 20-year-old men (N=11,819) estimated the prevalence of tobacco and cannabis use among peers of the same age and sex and the percentage of their peers drinking more alcohol than they did. Using the census data, we determined whether participants overestimated, accurately estimated, or underestimated substance use by others. Regression models were used to compare substance use by those who overestimated or underestimated peer substance with those who accurately estimated peer use. Other variables included in the analyses were the presence of close friends with alcohol or other drug problems and family history of substance use. RESULTS: Tobacco use by others was overestimated by 46.1% and accurately estimated by 37.3% of participants. Cannabis use by others was overestimated by 21.8% and accurately estimated by 31.6% of participants. Alcohol use by others was overestimated by more than half (53.4%) of participants and accurately estimated by 31.0%. In multivariable models, compared with participants who accurately estimated tobacco use by others, those who overestimated it reported smoking more cigarettes per week (incidence rate ratio [IRR] [95% CI], 1.17 [range, 1.05, 1.32]). There was no difference in the number of cigarettes smoked per week between those underestimating and those accurately estimating tobacco use by others (IRR [95% CI], 0.99 [range, 0.84, 1.17]). Compared with participants accurately estimating cannabis use by others, those who overestimated it reported more days of cannabis use per month (IRR [95% CI], 1.43 [range, 1.21, 1.70]), whereas those who underestimated it reported fewer days of cannabis use per month (IRR [95% CI], 0.62 [range, 0.23, 0.75]). Compared with participants accurately estimating alcohol use by others, those who overestimated it reported consuming more drinks per week (IRR [95% CI], 1.57 [range, 1.43, 1.72]), whereas those who underestimated it reported consuming fewer drinks per week (IRR [95% CI], 0.41 [range, 0.34, 0.50]). CONCLUSIONS: Perceptions of substance use by others are associated with one's own use. In particular, overestimating use by others is frequent among young men and is associated with one's own greater consumption. This association is independent of the substance use environment, indicating that, even in the case of proximity to a heavy-usage group, perception of use by others may influence one's own use. If preventive interventions are to be based on normative feedback, and their aim is to reduce overestimations of use by others, then the prevalence of overestimation indicates that they may be of benefit to roughly half the population; or, in the case of cannabis, to as few as 20%. Such interventions should take into account differing strengths of association across substances.

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The figurative painter accesses very complex levels of knowledge. To produce a painting requires, first, a deep analysis of the image of the reality and, afterwards, the study of the reconstruction of this reality. This is not about a process of copying, but a process of the comprehension of the concepts that appear in the representation. The drawing guides us in the process of the production of the surface and in the distribution of the colours that, after all, are the data with which the vision mechanism builds the visual reality. Knowing the colour and its behaviour have always been a requirement for the figurative painter. From that knowledge we can draw wider conclusions.

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In this paper we try to analyze the role of fiscal policy in fostering a higher participation of the different production factors in the human capital production sector in the long-run. Introducing a tax on physical capital and differentiating both a tax on raw labor wage and a tax on skills or human capital we also attempt to present a way to influence inequality as measured by the skill premium, thus trying to relate the increase in human capital with the decrease in income inequality. We will do that in the context of a non-scale growth model.The model here is capable to alter the shares of private factors devoted to each of the two production sectors, final output and human capital, and affect inequality in a different way according to the different tax changes. The simulation results derived in the paper show how a human capital (skills) tax cut, which could be interpreted as a reduction in progressivity, ends up increasing both the shares of labor and physical capital devoted to the production of knowledge and decreasing inequality. Moreover, a raw labor wage tax decrease, which could also be interpreted as an increase in the progressivity of the system, increases the share of labor devoted to the production of final output and increases inequality. Finally, a physical capital tax decrease reduces the share of physical capital devoted to the production of knowledge and allows for a lower inequality value. Nevertheless, none of the various types of taxes ends up changing the share of human capital in the knowledge production, which will deserve our future attention

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Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

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OBJECTIVES: Women with a history of preeclampsia (PE) are at increased risk of long term cardiovascular and end-stage renal diseases. However, follow up of preeclamptic women is often omitted, mainly due to a weakness of knowledge of maternal caregivers and lack of comprehensive guidelines. The aim of this study was to define the prevalence of albuminuria, high blood pressure, and renal dysfunction 6 weeks after a preeclampsia. METHODS: This is a prospective case-control study comparing women presenting with preeclampsia to an unmatched control group of women with no hypertensive disorders of pregnancy. A complete medical assessment was performed at 6 weeks post-partum. Recruitment started in June 2010. RESULTS: 324 women were included in the PE group and 50 in the control one. Characteristics of both groups and results of the medical work-up at 6 weeks post-partum are presented in Table 1. Women with preeclampsia presented with a higher BMI, higher prevalence of office high blood pressure, pathological albuminuria and renal hyper-filtration than women in the control group. CONCLUSIONS: Prevalence of post-partum hypertension, and renal dysfunction is higher in women with PE than in uncomplicated pregnancies. Systematic assessment of renal risk factors 6 weeks after preeclampsia allows identification of high-risk women and early implementation of preventive and therapeutic strategies. DISCLOSURES: A. Ditisheim: None. B. Ponte: None. G. Wuerzner: None. M. Burnier: None. M. Boulvain: None. A. Pechère-Bertschi: None.

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In this paper we try to analyze the role of fiscal policy in fostering a higher participation of the different production factors in the human capital production sector in the long-run. Introducing a tax on physical capital and differentiating both a tax on raw labor wage and a tax on skills or human capital we also attempt to present a way to influence inequality as measured by the skill premium, thus trying to relate the increase in human capital with the decrease in income inequality. We will do that in the context of a non-scale growth model.The model here is capable to alter the shares of private factors devoted to each of the two production sectors, final output and human capital, and affect inequality in a different way according to the different tax changes. The simulation results derived in the paper show how a human capital (skills) tax cut, which could be interpreted as a reduction in progressivity, ends up increasing both the shares of labor and physical capital devoted to the production of knowledge and decreasing inequality. Moreover, a raw labor wage tax decrease, which could also be interpreted as an increase in the progressivity of the system, increases the share of labor devoted to the production of final output and increases inequality. Finally, a physical capital tax decrease reduces the share of physical capital devoted to the production of knowledge and allows for a lower inequality value. Nevertheless, none of the various types of taxes ends up changing the share of human capital in the knowledge production, which will deserve our future attention

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[cat] Analitzem una economia amb dues característiques principals: la mobilitat dels treballadors implica transferència de coneixement i la productivitat de l’empresa augmenta amb l’intercanvi de coneixement. Cada empresa desenvolupa un tipus de coneixement que serà trasmès a la resta de la indústria mitjançant la mobilitat de treballadors. Estudiem dues estructures de mercat laboral i utilitzant un anàlisi comparatiu derivem les implicacions del model. Els resultats revelen com la mobilitat de treballadors depèn en la varietat i nivell del coneixement, la presència de costos de mobilitat, les institucions, la capacitat d’absorvir coneixement per part de les empreses i la mida de la indústria. Els resultats no depenen de l’estructura del mercat laboral.

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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

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Today's approach to anti-doping is mostly centered on the judicial process, despite pursuing a further goal in the detection, reduction, solving and/or prevention of doping. Similarly to decision-making in the area of law enforcement feeding on Forensic Intelligence, anti-doping might significantly benefit from a more extensive gathering of knowledge. Forensic Intelligence might bring a broader logical dimension to the interpretation of data on doping activities for a more future-oriented and comprehensive approach instead of the traditional case-based and reactive process. Information coming from a variety of sources related to doping, whether directly or potentially, would feed an organized memory to provide real time intelligence on the size, seriousness and evolution of the phenomenon. Due to the complexity of doping, integrating analytical chemical results and longitudinal monitoring of biomarkers with physiological, epidemiological, sociological or circumstantial information might provide a logical framework enabling fit for purpose decision-making. Therefore, Anti-Doping Intelligence might prove efficient at providing a more proactive response to any potential or emerging doping phenomenon or to address existing problems with innovative actions or/and policies. This approach might prove useful to detect, neutralize, disrupt and/or prevent organized doping or the trafficking of doping agents, as well as helping to refine the targeting of athletes or teams. In addition, such an intelligence-led methodology would serve to address doping offenses in the absence of adverse analytical chemical evidence.