986 resultados para innovation diffusion


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This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations.

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This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations. Keywords: innovation sources; productivity; R&D Cooperation

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An effect of drift is investigated on the segregation pattern in diffusion-limited aggregation (DLA) with two components (A and B species). The sticking probability PAB (=PBA) between the different species is introduced into the DLA model with drift, where the sticking probability PAA (=PBB) between the same species equals 1. By using computer simulation it is found that the drift has an important effect on not only the morphology but also the segregation pattern. Under the drift and the small sticking probability, a characteristic pattern appears where elongated clusters of A species and of B species are periodically dispersed. The period decreases with increasing drift. The periodic structure of the deposits is characterized by an autocorrelation function. The shape of the cluster consisting of only A species (or B species) shows a vertically elongated filamentlike structure. Each cluster becomes vertically longer with decreasing sticking probability PAB. The segregation pattern is distinctly different from that with no drift and a small sticking probability PAA. The effect of the concentration on the segregation pattern is also shown.

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To develop the understanding of innovation processes conceptualized in terms of asso- ciation through the "sociology of translation" (cf. actor-network theory) studies, this article analyses innovation processes in terms of dissociation and detachment mechanisms, exami- ning innovation through "withdrawal;" that is, innovation based on reducing or withdrawing use of a practice-"subtracting," "detaching"-a given artefact. Specifically, it focuses on the shift to farming techniques that have eliminated ploughing, bringing to light four major mechanisms constitutive of dissociation: centrifugal association; making entities and asso- ciations visible; making other entities and associations invisible; bringing together or "asso- ciating" new entities. The study helps refine our understanding of the detachment processes at work in innovation, shedding light in this particular case on transfers between public research institutes, industrial companies, farmers and citizens seeking to develop new farm production models.

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Schizophrenia is a complex psychiatric disorder characterized by disabling symptoms and cognitive deficit. Recent neuroimaging findings suggest that large parts of the brain are affected by the disease, and that the capacity of functional integration between brain areas is decreased. In this study we questioned (i) which brain areas underlie the loss of network integration properties observed in the pathology, (ii) what is the topological role of the affected regions within the overall brain network and how this topological status might be altered in patients, and (iii) how white matter properties of tracts connecting affected regions may be disrupted. We acquired diffusion spectrum imaging (a technique sensitive to fiber crossing and slow diffusion compartment) data from 16 schizophrenia patients and 15 healthy controls, and investigated their weighted brain networks. The global connectivity analysis confirmed that patients present disrupted integration and segregation properties. The nodal analysis allowed identifying a distributed set of brain nodes affected in the pathology, including hubs and peripheral areas. To characterize the topological role of this affected core, we investigated the brain network shortest paths layout, and quantified the network damage after targeted attack toward the affected core. The centrality of the affected core was compromised in patients. Moreover the connectivity strength within the affected core, quantified with generalized fractional anisotropy and apparent diffusion coefficient, was altered in patients. Taken together, these findings suggest that the structural alterations and topological decentralization of the affected core might be major mechanisms underlying the schizophrenia dysconnectivity disorder. Hum Brain Mapp, 36:354-366, 2015. © 2014 Wiley Periodicals, Inc.

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Purpose: The increase of apparent diffusion coefficient (ADC) in treated hepatic malignancies compared to pre-therapeutic values has been interpreted as treatment success; however, the variability of ADC measurements remains unknown. Furthermore, ADC has been usually measured in the whole lesion, while measurements should be probably centered on the area with the most restricted diffusion (MRDA) as it represents potential tumoral residue. Our objective was to compare the inter/intraobserver variability of ADC measurements in the whole lesion and in MRDA. Material and methods: Forty patients previously treated with chemoembolization or radiofrequency were evaluated (20 on 1.5T and 20 on 3.0T). After consensual agreement on the best ADC image, two readers measured the ADC values using separate regions of interest that included the whole lesion and the whole MRDA without exceeding their borders. The same measurements were repeated two weeks later. Spearman test and the Bland-Altman method were used. Results: Interobserver correlation in ADC measurements in the whole lesion and MRDA was as follows: 0.962 and 0.884. Intraobserver correlation was, respectively, 0.992 and 0.979. Interobserver limits of variability (mm2/sec*10-3) were between -0.25/+0.28 in the whole lesion and between -0.51/+0.46 in MRDA. Intraobserver limits of variability were, respectively: -0.25/+0.24 and -0.43/+0.47. Conclusion: We observed a good inter/intraobserver correlation in ADC measurements. Nevertheless, a limited variability does exist, and it should be considered when interpreting ADC values of hepatic malignancies.

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This report is the annual report for the Board of Regents.

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Lutetium zoning in garnet within eclogites from the Zermatt-Saas Fee zone, Western Alps, reveal sharp, exponentially decreasing central peaks. They can be used to constrain maximum Lu volume diffusion in garnets. A prograde garnet growth temperature interval of 450-600 A degrees C has been estimated based on pseudosection calculations and garnet-clinopyroxene thermometry. The maximum pre-exponential diffusion coefficient which fits the measured central peak is in the order of D-0= 5.7*10(-6) m(2)/s, taking an estimated activation energy of 270 kJ/mol based on diffusion experiments for other rare earth elements in garnet. This corresponds to a maximum diffusion rate of D (600 A degrees C) = 4.0*10(-22) m(2)/s. The diffusion estimate of Lu can be used to estimate the minimum closure temperature, T-c, for Sm-Nd and Lu-Hf age data that have been obtained in eclogites of the Western Alps, postulating, based on a literature review, that D (Hf) < D (Nd) < D (Sm) a parts per thousand currency sign D (Lu). T-c calculations, using the Dodson equation, yielded minimum closure temperatures of about 630 A degrees C, assuming a rapid initial exhumation rate of 50A degrees/m.y., and an average crystal size of garnets (r = 1 mm). This suggests that Sm/Nd and Lu/Hf isochron age differences in eclogites from the Western Alps, where peak temperatures did rarely exceed 600 A degrees C must be interpreted in terms of prograde metamorphism.

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We model the effect of contract standardization on the development of markets andthe law. In a setting in which biased judges can distort contract enforcement, we findthat the introduction of a standard contract reduces enforcement distortions relative toreliance on precedents, exerting two effects: i) it statically expands the volume of trade,but ii) it crowds out the use of open-ended contracts, hindering legal evolution. We shedlight on the large-scale commercial codification undertaken in the nineteenth centuryin many countries (even common-law ones) during a period of booming commerce andlong-distance trade.

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The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique-the mapping of apparent diffusion coefficient values-to the more complex, such as diffusion tensor imaging, q-ball imaging, diffusion spectrum imaging, and tractography. The type of structural information obtained differs according to the technique used. To fully understand how diffusion MR imaging works, it is helpful to be familiar with the physical principles of water diffusion in the brain and the conceptual basis of each imaging technique. Knowledge of the technique-specific requirements with regard to hardware and acquisition time, as well as the advantages, limitations, and potential interpretation pitfalls of each technique, is especially useful.

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A model has been developed for evaluating grain size distributions in primary crystallizations where the grain growth is diffusion controlled. The body of the model is grounded in a recently presented mean-field integration of the nucleation and growth kinetic equations, modified conveniently in order to take into account a radius-dependent growth rate, as occurs in diffusion-controlled growth. The classical diffusion theory is considered, and a modification of this is proposed to take into account interference of the diffusion profiles between neighbor grains. The potentiality of the mean-field model to give detailed information on the grain size distribution and transformed volume fraction for transformations driven by nucleation and either interface- or diffusion-controlled growth processes is demonstrated. The model is evaluated for the primary crystallization of an amorphous alloy, giving an excellent agreement with experimental data. Grain size distributions are computed, and their properties are discussed.

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The present paper is aimed at providing a general strategic overview of the existing theoretical models that have applications in the field of financial innovation. Whereas most financialdevelopments have relied upon traditional economic tools, a new stream of research is defining a novel paradigm in which mathematical models from diverse scientific disciplines are being applied to conceptualize and explain economic and financial behavior. Indeed, terms such as ‘econophysics’ or ‘quantum finance’ have recently appeared to embrace efforts in this direction. As a first contact with such research, the project will present a brief description of some of the main theoretical models that have applications in finance and economics, and will try to present, if possible, potential new applications to particular areas in financial analysis, or new applicable models. As a result, emphasiswill be put on the implications of this research for the financial sector and its future dynamics.