983 resultados para automated knowledge visualization


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This paper estimates whether both sourcing knowledge from and/or cooperating on innovation with HEIs (Higher Education Institutions)1 impacts on establishment-level total factor productivity (TFP) using a dataset created by merging the UK government’s Community Innovation Survey (CIS) with the Annual Respondents Database (ARD). It also considers whether higher graduate employment (as a measure of human capital) also impacts positively on TFP at the establishment-level. Many studies have investigated the relationship between university-firm knowledge links and innovation (see, for example, Mansfield, 1991; Becker, 2003; Thorn et al, 2007). Most of these studies find a positive impact. Fewer studies have investigated the impact of university-firm knowledge links on productivity. Belderbos et al. (2004), using the Dutch CIS, find that cooperation with universities has no statistically significant impact on the growth of labour productivity. Medda et al. (2005) find no statistically significant effect of collaborative research undertaken by Italian manufacturing firms and universities on the growth of TFP. Arvanitis et al. (2008), using Swiss data, show that university-firm knowledge and technology transfer has both a direct impact on labour productivity and an indirect impact through its positive impact on innovation. In sum, there is as yet no clear consensus as to the impact of university-firm knowledge links on productivity.

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The recent developments in high magnetic field 13C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of 13C in vivo spectra in the rodent brain, enabling the separation of several 13C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the 13C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to 13 C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13)C2 ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo 13C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo 13C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo 13C spectra. AMARES led to accurate and reliable 13C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different 13C isotopomers were included as prior knowledge in the analysis.

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In this paper we study a model where non-cooperative agents may exchange knowledge in a competitive environment. As a potential factor that could induce the knowledge disclosure between humans we consider the timing of the moves of players. We develop a simple model of a multistage game in which there are only three players and competition takes place only within two stages. Players can share their private knowledge with their opponents and the knowledge is modelled as in uencing their marginal cost of e¤ort. We identify two main mechanisms that work towards knowledge disclosure. One of them is that before the actual competition starts, the stronger player of the rst stage of a game may have desire to share his knowledge with the "observer", be- cause this reduces the valuation of the prize of the weaker player of that stage and as a result his e¤ort level and probability of winning in a ght. Another mechanism is that the "observer" may have sometimes desire to share knowledge with the weaker player of the rst stage, because in this way, by increasing his probability of winning in that stage, he decreases the probability of winning of the stronger player. As a result, in the second stage the "observer" may have greater chances to meet the weaker player rather than the stronger one. Keywords: knowledge sharing, strategic knowledge disclosure, multistage contest game, non-cooperative games

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This paper compares how increases in experience versus increases in knowledge about a public good affect willingness to pay (WTP) for its provision. This is challenging because while consumers are often certain about their previous experiences with a good, they may be uncertain about the accuracy of their knowledge. We therefore design and conduct a field experiment in which treated subjects receive a precise and objective signal regarding their knowledge about a public good before estimating their WTP for it. Using data for two different public goods, we show qualitative equivalence of the effect of knowledge and experience on valuation for a public good. Surprisingly, though, we find that the causal effect of objective signals about the accuracy of a subject’s knowledge for a public good can dramatically affect their valuation for it: treatment causes an increase of $150-$200 in WTP for well-informed individuals. We find no such effect for less informed subjects. Our results imply that WTP estimates for public goods are not only a function of true information states of the respondents but beliefs about those information states.

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In the context of the two-stage threshold model of decision making, with the agent’s choices determined by the interaction Of three “structural variables,” we study the restrictions on behavior that arise when one or more variables are xogenously known. Our results supply necessary and sufficient conditions for consistency with the model for all possible states of partial Knowledge, and for both single- and multivalued choice functions.

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A cardiac-triggered free-breathing three-dimensional (3D) balanced fast field-echo projection renal magnetic resonance (MR) angiographic sequence was investigated for in-stent lumen visualization of a dedicated metallic renal artery stent. Fourteen prototype stents were deployed in the renal arteries of six pigs (in two pigs, three stents were deployed). Projection renal MR angiography was compared with standard contrast material-enhanced 3D breath-hold MR angiography. Artifact-free in-stent lumen visualization was achieved with both projection MR angiography and contrast-enhanced MR angiography. These promising results warrant further studies for visualization of in-stent restenosis.

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The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

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In this paper we are aimed to investigate the relationship between Catalan knowledge and individual earnings in Catalonia. Using data from 2006, we find a positive earning return to Catalan proficiency; however, when accounting for self-selection into Catalan knowledge, we find a higher language return (20% of extra earnings), suggesting that individuals who are more prone to know Catalan are also less remunerated than others (negative selection effect). Moreover, we also find important complementarities between language knowledge and completed education, which means that only more educated individuals benefit from Catalan knowledge.

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This paper investigates the economic value of Catalan knowledge for national and foreign first- and second-generation immigrants in Catalonia. Specifically, drawing on data from the “Survey on Living Conditions and Habits of the Catalan Population (2006)”, we want to quantify the expected earnings differential between individuals who are proficient in Catalan and those who are not, taking into account the potential endogeneity between knowledge of Catalan and earnings. The results indicate the existence of a positive return to knowledge of Catalan, with a 7.5% increase in earnings estimated by OLS; however, when we account for the presence of endogeneity, monthly earnings are around 18% higher for individuals who are able to speak and write Catalan. However, we also find that language and education are complementary inputs for generating earnings in Catalonia, given that knowledge of Catalan increases monthly earnings only for more educated individuals.

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In hyperdiploid acute lymphoblastic leukaemia (ALL), the simultaneous occurrence of specific aneuploidies confers a more favourable outcome than hyperdiploidy alone. Interphase (I) FISH complements conventional cytogenetics (CC) through its sensitivity and ability to detect chromosome aberrations in non-dividing cells. To overcome the limits of manual I-FISH, we developed an automated four-colour I-FISH approach and assessed its ability to detect concurrent aneuploidies in ALL. I-FISH was performed using centromeric probes for chromosomes 4, 6, 10 and 17. Parameters established for automatic nucleus selection and signal detection were evaluated (3 controls). Cut-off values were determined (10 controls, 1000 nuclei/case). Combinations of aneuploidies were considered relevant when each aneuploidy was individually significant. Results obtained in 10 ALL patients (1500 nuclei/patient) were compared with those by CC. Various combinations of aneuploidies were identified. All clones detected by CC were observed by I-FISH. I-FISH revealed numerous additional abnormal clones, ranging between 0.1 % and 31.6%, based on the large number of nuclei evaluated. Four-colour automated I-FISH permits the identification of concurrent aneuploidies of prognostic significance in hyperdiploid ALL. Large numbers of cells can be analysed rapidly by this method. Owing to its high sensitivity, the method provides a powerful tool for the detection of small abnormal clones at diagnosis and during follow up. Compared to CC, it generates a more detailed cytogenetic picture, the biological and clinical significance of which merits further evaluation. Once optimised for a given set of probes, the system can be easily adapted for other probe combinations.

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This paper explores the earnings return to Catalan knowledge for public and private workers in Catalonia. In doing so, we allow for a double simultaneous selection process. We consider, on the one hand, the non-random allocation of workers into one sector or another, and on the other, the potential self-selection into Catalan proficiency. In addition, when correcting the earnings equations, we take into account the correlation between the two selectivity rules. Our findings suggest that the apparent higher language return for public sector workers is entirely accounted for by selection effects, whereas knowledge of Catalan has a significant positive return in the private sector, which is somewhat higher when the selection processes are taken into account.

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The action of various DNA topoisomerases frequently results in characteristic changes in DNA topology. Important information for understanding mechanistic details of action of these topoisomerases can be provided by investigating the knot types resulting from topoisomerase action on circular DNA forming a particular knot type. Depending on the topological bias of a given topoisomerase reaction, one observes different subsets of knotted products. To establish the character of topological bias, one needs to be aware of all possible topological outcomes of intersegmental passages occurring within a given knot type. However, it is not trivial to systematically enumerate topological outcomes of strand passage from a given knot type. We present here a 3D visualization software (TopoICE-X in KnotPlot) that incorporates topological analysis methods in order to visualize, for example, knots that can be obtained from a given knot by one intersegmental passage. The software has several other options for the topological analysis of mechanisms of action of various topoisomerases.