5,267 research outputs found

    On some properties of Lagrangian dispersion models with non-Gaussian noise

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    The properties of a stochastic model with non-Gaussian random noise describing turbulent dispersion have been investigated, with reference to its Mathematical structure and to its behaviour simulating the inertial subrange. The process is Markovian, mean-square continuous and with correlated increments. The model is influenced by the turbulence inhomogeneities also at the smallest scales, that is, it does not correctly simulate the existence of a well-developed inertial subrange. Some numerical computations have been performed confirming the theoretical results

    Spin-dependent direct gap emission in tensile-strained Ge films on Si substrates

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    The circular polarization of direct gap emission of Ge is studied in optically-excited tensile-strained Ge-on-Si heterostructures as a function of doping and temperature. Owing to the spin-dependent optical selection rules, the radiative recombinations involving strain-split light (cG-LH) and heavy hole (cG-HH) bands are unambiguously resolved. The fundamental cG-LH transition is found to have a low temperature circular polarization degree of about 85% despite an off-resonance excitation of more than 300 meV. By photoluminescence (PL) measurements and tight binding calculations we show that this exceptionally high value is due to the peculiar energy dependence of the optically-induced electron spin population. Finally, our observation of the direct gap doublet clarifies that the light hole contribution, previously considered to be negligible, can dominate the room temperature PL even at low tensile strain values of about 0.2%

    A framework to characterize multi-actor sustainability-oriented innovations in the agri-food context

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    Sustainability oriented innovation (SOIs) are multi-faceted types of innovation which can address the challenges of the agri-food industry, tapping knowledge into a diverse set of stakeholders with their areas of expertise. There is currently a lack of conceptualization of all the relevant aspects to discriminate among different SOIs, also in terms of type of stakeholders involved and their roles in the innovation development process. We propose a conceptual framework based on three levels of analysis: process, value network and maturity of the innovation system to guide the characterization of SOIs. We obtain confirmatory evidence from 11 pilot projects in Europ

    Mean first passage time analysis reveals rate-limiting steps, parallel pathways and dead ends in a simple model of protein folding

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    We have analyzed dynamics on the complex free energy landscape of protein folding in the FOLD-X model, by calculating for each state of the system the mean first passage time to the folded state. The resulting kinetic map of the folding process shows that it proceeds in jumps between well-defined, local free energy minima. Closer analysis of the different local minima allows us to reveal secondary, parallel pathways as well as dead ends.Comment: 7 page

    Towards an integrated model to explain the factors affecting collaborative innovation processes – insights from the agrifood sector

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    This study explores the relevant factors to involve multiple actors who develop and implement new technologies to build sustainable agrifood systems. By examining 11 cases, we found that technological, organization, environmental, behavioural and interorganizational factors (all mentioned in current literature) as well as collaborative business models (not mentioned in current literature) affect such initiatives. Based on this, we propose an integrated model. The agrifood sector is one of the first sectors in which a collaborative transition unfolds. As other sectors are likely to undergo similar transitions in the near future, lessons learnt from the agrifood sector can guide these transitions

    COLLABORATIVE SUSTAINABLE BUSINESS MODEL ARCHETYPES IN THE AGRI-FOOD SECTOR

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    Farmers are put under pressure to produce more and higher quality food at a lower cost in an environmentally and socially sustainable manner. However, farmers might struggle to benefit from implementing socially and environmentally sustainable practices. Collaborative sustainable business models (CSBMs) offer a promising avenue to overcome these struggles by developing a value creation and value delivery systems together with other value chain actors instead of by the farmer independently. Based on the analysis of the CSBMs of 290 sustainable agri-food start-ups and thirteen interviews, we identify six CSBM archetypes and twelve CSBM sub-archetypes. The developed archetypes provide practical guidance and stimulates thinking for practitioners who can mimic the archetypes within their own organizations and value chains. The practical relevance is highlighted by the use of the CSBM archetypes in twenty-six value chains in a Horizon2020 research project. In terms of theoretical relevance, this research adds a new perspective to (sustainable) business model literature and the archetypes can serve as a reference point for future research

    Prediction of minimum temperatures in an alpine region by linear and non-linear post-processing of meteorological models

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    International audienceModel Output Statistics (MOS) refers to a method of post-processing the direct outputs of numerical weather prediction (NWP) models in order to reduce the biases introduced by a coarse horizontal resolution. This technique is especially useful in orographically complex regions, where large differences can be found between the NWP elevation model and the true orography. This study carries out a comparison of linear and non-linear MOS methods, aimed at the prediction of minimum temperatures in a fruit-growing region of the Italian Alps, based on the output of two different NWPs (ECMWF T511?L60 and LAMI-3). Temperature, of course, is a particularly important NWP output; among other roles it drives the local frost forecast, which is of great interest to agriculture. The mechanisms of cold air drainage, a distinctive aspect of mountain environments, are often unsatisfactorily captured by global circulation models. The simplest post-processing technique applied in this work was a correction for the mean bias, assessed at individual model grid points. We also implemented a multivariate linear regression on the output at the grid points surrounding the target area, and two non-linear models based on machine learning techniques: Neural Networks and Random Forest. We compare the performance of all these techniques on four different NWP data sets. Downscaling the temperatures clearly improved the temperature forecasts with respect to the raw NWP output, and also with respect to the basic mean bias correction. Multivariate methods generally yielded better results, but the advantage of using non-linear algorithms was small if not negligible. RF, the best performing method, was implemented on ECMWF prognostic output at 06:00 UTC over the 9 grid points surrounding the target area. Mean absolute errors in the prediction of 2 m temperature at 06:00 UTC were approximately 1.2°C, close to the natural variability inside the area itself

    Geometric and analytic views in existence theorems for optimal control. II. Distributed and boundary controls

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    Existence theorems are proved for Lagrange problems of optimization in a given domain G with possibly unbounded distributed controls in G and on the boundary of G , and with functional relations on G and on the boundary represented by closed operators, not necessarily linear. The case where the functional relations are partial differential equations is emphasized. Recent work concerning the reduction or elimination of seminormality requirements is taken into account. Many examples are given.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45200/1/10957_2004_Article_BF00933208.pd

    Superelastic behavior and elastocaloric effect in a Ni51.5Fe21.5Ga27.0 ferromagnetic shape memory single crystal under compression

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    Ni51.5Fe21.5Ga27.0 single crystals have been subjected to different heat treatments resulting in a different degree of L21 ordering. Superelastic response has been measured at different temperatures in compression mode. The mechanical behavior strongly depends on axis orientation. In the [001] direction, perfect superelasticity over a wide range of temperatures is found. For the [110] orientation, the material fails by brittle fracture short above austenite transformation finish temperature, Af. A linear dependence of the critical stress with temperature has been found in agreement with Clausius-Clapeyron equation. The slope does not significantly change with the degree of order, but it is notably affected by the crystal orientation. The microstructure of the samples after mechanical tests has been studied by transmission electron microscopy. The superelastic cycling produces dislocations with a Burgers vector that suggests local microplastic deformation of the martensitic phase. Finally, the adiabatic temperature change has been used to chacterize the elastocaloric effect in this alloy. The adiabatic cooling is found to be larger in the [110] than in the [001] orientation at 240 K. However, the brittleness of [110] samples avoid testing the adiabatic temperature change at room temperature. The adiabatic cooling in [001] orientation decreases systematically with temperature, which is related to decrease of the strain and entropy change of transformation
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