477 results on '"Bruining, J."'
Search Results
2. Modeling low saline carbonated water flooding including surface complexes
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Alvarez, A. C., Bruining, J., and Marchesin, D.
- Subjects
Physics - Fluid Dynamics - Abstract
Carbonated water flooding (CWI) increases oil production due to favorable dissolution effects and viscosity reduction. Accurate modeling of CWI performance requires a simulator with the ability to capture the true physics of such process. In this study, compositional modeling coupled with surface complexation modeling (SCM) are done, allowing a unified study of the influence in oil recovery of reduction of salt concentration in water. The compositional model consists of the conservation equations of total carbon, hydrogen, oxygen, chloride and decane. The coefficients of such equations are obtained from the equilibrium partition of chemical species that are soluble both in oleic and the aqueous phases. SCM is done by using the PHREEQC program, which determines concentration of the master species. Estimation of the wettability as a function of the Total Bound Product (TBP) that takes into account the concentration of the complexes in the aqueous, oleic phases and in the rock walls is performed. We solve analytically and numerically these equations in $1-$D in order to elucidate the effects of the injection of low salinity carbonated water into a reservoir containing oil equilibrated with high salinity carbonated water.
- Published
- 2023
3. Nonlinear wave interactions in geochemical modeling
- Author
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Alvarez, A. C., Bruining, J., and Marchesin, D.
- Subjects
Mathematics - Analysis of PDEs - Abstract
This paper is concerned with the study of the main wave interactions in a system of conservation laws in geochemical modeling. We study the modeling of the chemical complexes on the rock surface. The presence of stable surface complexes affects the relative permeability. We add terms representing surface complexes to the accumulation function in the model presented in \cite{lambert2019nonlinear1}. This addition allows to take into account the interaction of ions with the rock surface in the modeling of the oil recovery by the injection of carbonated water. Compatibility hypotheses with the modeling are made on the coefficients of the system to obtain meaningful solutions. We developed a Riemann solver taking into account the complexity of the interactions and bifurcations of nonlinear waves. Such bifurcations occur at the inflection and resonance surfaces. We present the solution of a generalized eigenvalue problem in a (n+1)-dimensional case, which allows the construction of rarefaction curves. A method to find the discontinuous solutions is also presented. We find the solution path for some examples.
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- 2022
4. Nonlinear wave interactions in geochemical modeling
- Author
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Alvarez, A.C., Bruining, J., and Marchesin, D.
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- 2023
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5. On the sustainability of CO2 storage through CO2 – Enhanced oil recovery
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Farajzadeh, R., Eftekhari, A.A., Dafnomilis, G., Lake, L.W., and Bruining, J.
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- 2020
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6. Combustion in miscible displacement for high-pressure air injection
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Gargar, N. Khoshnevis, Bruining, J., Kokubun, M. A. Endo, Marchesin, D., and Mailybaev, A. A.
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- 2020
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7. Mathematical Theory of Two-Phase Geochemical Flow with Chemical Species
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Lambert, W. J., Alvarez, A. C., Marchesin, D., Bruining, J., Klingenberg, Christian, editor, and Westdickenberg, Michael, editor
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- 2018
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8. Life-cycle assessment of water injection into hydrocarbon reservoirs using exergy concept
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Farajzadeh, R., Zaal, C., van den Hoek, P., and Bruining, J.
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- 2019
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9. Nonlinear wave analysis of geochemical injection for multicomponent two phase flow in porous media
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Lambert, W.J., Alvarez, A.C., Matos, V., Marchesin, D., and Bruining, J.
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- 2019
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10. Analytical and numerical validation of a model for flooding by saline carbonated water
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Alvarez, A.C., Blom, T., Lambert, W.J., Bruining, J., and Marchesin, D.
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- 2018
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11. Effect of fines migration on oil–water relative permeability during two-phase flow in porous media
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Zeinijahromi, Abbas, Farajzadeh, Rouhi, (Hans) Bruining, J., and Bedrikovetsky, Pavel
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- 2016
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12. Mathematical Theory of Two-Phase Geochemical Flow with Chemical Species
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Lambert, W. J., primary, Alvarez, A. C., additional, Marchesin, D., additional, and Bruining, J., additional
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- 2018
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13. ZDHHC11 and ZDHHC11B are critical novel components of the oncogenic MYC-miR-150-MYB network in Burkitt lymphoma
- Author
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Dzikiewicz-Krawczyk, A, Kok, K, Slezak-Prochazka, I, Robertus, J-L, Bruining, J, Tayari, M M, Rutgers, B, de Jong, D, Koerts, J, Seitz, A, Li, J, Tillema, B, Guikema, J E, Nolte, I M, Diepstra, A, Visser, L, Kluiver, J, and van den Berg, A
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- 2017
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14. Improved oil recovery techniques and their role in energy efficiency and reducing CO2 footprint of oil production
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Farajzadeh, R., primary, Glasbergen, G., additional, Karpan, V., additional, Mjeni, R., additional, Boersma, D.M., additional, Eftekhari, A.A., additional, Casquera Garcia, A., additional, and Bruining, J., additional
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- 2022
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15. Chemical Enhanced Oil Recovery and the Dilemma of More and Cleaner Energy
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Farajzadeh, R. (author), Eftekhari, Ali Akbar (author), Kahrobaei, Siavash (author), Mjeni, Rifaat (author), Boersma, Diederik (author), Bruining, J. (author), Farajzadeh, R. (author), Eftekhari, Ali Akbar (author), Kahrobaei, Siavash (author), Mjeni, Rifaat (author), Boersma, Diederik (author), and Bruining, J. (author)
- Abstract
We develop a method based on concept of exergy-return on exergy-investment (ERoEI) to determine the energy efficiency and CO2 footprint of polymer and surfactant enhanced oil recovery (EOR). This integrated approach considers main surface and subsurface elements of the chemical EOR methods. The main energy investment in oil recovery by water injection is mainly related to circulation of water with respect to exergy of the oil produced. At large water cuts of >90%, more than 70% of the total invested energy is spent on pumping the fluids. Consequently, production of barrels of oil is associated with large amounts of CO2 emission for mature oil fields with large water cuts. Our analysis shows that injection of polymer increases the energy efficiency of the oil recovery system. Because of additional oil (exergy gain) and less water circulation (exergy investment), the project-time averaged energy invested (and consequently CO2 emitted) to produce one barrel of oil from polymer flooding is less than that of the water flooding at large water cuts. We conclude that polymer injection into reservoirs with high water cut can be a solution for two major challenges of the transition period: (1) meet the global energy demand via an increase in oil recovery and (2) reduce the CO2 footprint of oil production (more and cleaner oil). For surfactant-polymer EOR, the extent of improvement in energy efficiency depends on the incremental gain and the simplicity of the formulations., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Reservoir Engineering
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- 2022
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16. Improved oil recovery techniques and their role in energy efficiency and reducing CO2 footprint of oil production
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Farajzadeh, R., Glasbergen, G., Karpan, V., Mjeni, R., Boersma, D. M., Eftekhari, A. A., Casquera Garcia, A., Bruining, J., Farajzadeh, R., Glasbergen, G., Karpan, V., Mjeni, R., Boersma, D. M., Eftekhari, A. A., Casquera Garcia, A., and Bruining, J.
- Abstract
Production of mature oil fields emits significant amount of CO2 related to circulation and handling of large volumes of gas and water. This can be reduced either by (1) using a low-carbon energy source and/or (2) reducing the volumes of the non-hydrocarbon produced/injected fluids. This paper describes how improved oil recovery techniques can be designed to reduce CO2 intensity (kgCO2/bbl oil) of oil production by efficient use of the injectants. It is shown that CO2 emissions associated with injection of chemicals is strongly influenced by water cut at the start of the project, extent of the water cut reduction, and chemical utilization factor defined as the volume of produced oil per mass or volume of the injectant. As an example, for the oil field considered in this study, 3–8% reduction in water cut can result in 50–80% reduction in its CO2 intensity. In addition to the incremental oil production with lower CO2 intensity, the earlier implementation of enhanced oil recovery methods can extend the lifetime of the mature fields if carbon emission cut-offs are applied. In case of CO2 enhanced oil recovery (EOR), the large storage potential for CO2 can significantly reduce the overall CO2 emissions of oil, albeit at a large energetic cost. For CO2 EOR using CO2 captured from gas power plants, improving the utilization factor from 2 bbl/tCO2 to 4 bbl/tCO2 can reduce the CO2 intensity of the produced oil from 120 kgCO2/bbl to 80 kgCO2/bbl (33% reduction).
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- 2022
17. Exergy Return on Exergy Investment and CO2Intensity of the Underground Biomethanation Process
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Farajzadeh, R. (author), Lomans, Bartholomeus Petrus (author), Hajibeygi, H. (author), Bruining, J. (author), Farajzadeh, R. (author), Lomans, Bartholomeus Petrus (author), Hajibeygi, H. (author), and Bruining, J. (author)
- Abstract
This paper presents an assessment of the life-cycle exergetic efficiency and CO2 footprint of the underground biomethanation process. The subsurface formation, hosting microorganisms required for the reaction, is utilized to convert CO2 and green (produced from renewable energy) hydrogen to the so-called "green"or synthetic methane. The net exergy gain and CO2 intensity of the biomethanation process are compared to the alternative options of (1) green H2 storage (no energy upgrading process to CH4) and (2) fossil-based CH4 with carbon capture and storage (CCS), i.e., blue CH4. It is found that with the current state of the technology and within the assumptions of this study, the exergy return on the exergy invested for underground biomethanation does not outperform the direct storage and utilization of green H2. The maximum exergetic efficiency of the biomethanation process is calculated to be 15-33% for electricity and 36-47% for heating, while the overall exergetic efficiency of the direct use of H2 for electricity is estimated to be between 20 and 61%. Moreover, the energy produced from the underground biomethanation process has the largest CO2 intensity among the studied options. Depending on the technology used in the CCS and hydrogen production stages, the CO2 intensity of the electricity generated from synthetic CH4 can be as large as 142 g CO2/MJe, which is at least 56-73% larger than those of the two other studied cases., Reservoir Engineering
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- 2022
- Full Text
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18. Improved oil recovery techniques and their role in energy efficiency and reducing CO2 footprint of oil production
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Farajzadeh, R. (author), Glasbergen, G. (author), Karpan, V. (author), Mjeni, R. (author), Boersma, D. M. (author), Eftekhari, A. A. (author), Casquera Garcia, A. (author), Bruining, J. (author), Farajzadeh, R. (author), Glasbergen, G. (author), Karpan, V. (author), Mjeni, R. (author), Boersma, D. M. (author), Eftekhari, A. A. (author), Casquera Garcia, A. (author), and Bruining, J. (author)
- Abstract
Production of mature oil fields emits significant amount of CO2 related to circulation and handling of large volumes of gas and water. This can be reduced either by (1) using a low-carbon energy source and/or (2) reducing the volumes of the non-hydrocarbon produced/injected fluids. This paper describes how improved oil recovery techniques can be designed to reduce CO2 intensity (kgCO2/bbl oil) of oil production by efficient use of the injectants. It is shown that CO2 emissions associated with injection of chemicals is strongly influenced by water cut at the start of the project, extent of the water cut reduction, and chemical utilization factor defined as the volume of produced oil per mass or volume of the injectant. As an example, for the oil field considered in this study, 3–8% reduction in water cut can result in 50–80% reduction in its CO2 intensity. In addition to the incremental oil production with lower CO2 intensity, the earlier implementation of enhanced oil recovery methods can extend the lifetime of the mature fields if carbon emission cut-offs are applied. In case of CO2 enhanced oil recovery (EOR), the large storage potential for CO2 can significantly reduce the overall CO2 emissions of oil, albeit at a large energetic cost. For CO2 EOR using CO2 captured from gas power plants, improving the utilization factor from 2 bbl/tCO2 to 4 bbl/tCO2 can reduce the CO2 intensity of the produced oil from 120 kgCO2/bbl to 80 kgCO2/bbl (33% reduction)., Reservoir Engineering
- Published
- 2022
- Full Text
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19. Improved Oil Recovery Techniques and Their Role in Energy Efficiency and Reducing CO2 Footprint of Oil Production
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Farajzadeh, R., additional, Glasbergen, G., additional, Karpan, V., additional, Mjeni, R., additional, Boersma, D., additional, Eftekhari, A. A., additional, Casquera García, A., additional, and Bruining, J., additional
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- 2022
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20. Energy Loss and Dispersion of Electromagnetic Signals in Fluid-Saturated Porous Media Due to Frequency Dependence of Complex Dielectric Permittivity
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Nguyen, Buu-Long, Geels, A. M., Bruining, J., Slob, E. C., Gottlieb, Johannes, editor, Hötzl, Heinz, editor, Huck, Karin, editor, and Niessner, Reinhard, editor
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- 1997
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21. FILTRATION COMBUSTION IN WET POROUS MEDIUM
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BRUINING, J., MAILYBAEV, A. A., and MARCHESIN, D.
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- 2009
22. An empirical theory for gravitationally unstable flow in porous media
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Farajzadeh, R., Meulenbroek, B., Daniel, D., Riaz, A., and Bruining, J.
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- 2013
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23. Recovery of Light Oil by Medium Temperature Oxidation
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Mailybaev, A. A., Bruining, J., and Marchesin, D.
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- 2013
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24. Modelling Mineral-Scaling in Geothermal Reservoirs Using Both a Local Equilibrium and a Kinetics Approach
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Hussain, A.A.A. (author), Khoshnevis Gargar, N. (author), Meulenbroek, B.J. (author), van der Star, Wouter R L (author), Bruining, J. (author), Claringbould, Johan (author), Reerink, Ayla (author), Wolf, K.H.A.A. (author), Hussain, A.A.A. (author), Khoshnevis Gargar, N. (author), Meulenbroek, B.J. (author), van der Star, Wouter R L (author), Bruining, J. (author), Claringbould, Johan (author), Reerink, Ayla (author), and Wolf, K.H.A.A. (author)
- Abstract
Applied Geophysics and Petrophysics, Petroleum Engineering, Mathematical Physics
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- 2021
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25. Chemical enhanced oil recovery and the dilemma of more and cleaner energy
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Farajzadeh, R. (author), Kahrobaei, Siavash (author), Eftekhari, Ali Akbari (author), Mjeni, Rifaat A. (author), Boersma, Diederik (author), Bruining, J. (author), Farajzadeh, R. (author), Kahrobaei, Siavash (author), Eftekhari, Ali Akbari (author), Mjeni, Rifaat A. (author), Boersma, Diederik (author), and Bruining, J. (author)
- Abstract
A method based on the concept of exergy-return on exergy-investment is developed to determine the energy efficiency and CO2 intensity of polymer and surfactant enhanced oil recovery techniques. Exergy is the useful work obtained from a system at a given thermodynamics state. The main exergy investment in oil recovery by water injection is related to the circulation of water required to produce oil. At water cuts (water fraction in the total liquid produced) greater than 90%, more than 70% of the total invested energy is spent on injection and lift pumps, resulting in large CO2 intensity for the produced oil. It is shown that injection of polymer with or without surfactant can considerably reduce CO2 intensity of the mature waterflood projects by decreasing the volume of produced water and the exergy investment associated with its circulation. In the field examples considered in this paper, a barrel of oil produced by injection of polymer has 2–5 times less CO2 intensity compared to the baseline waterflood oil. Due to large manufacturing exergy of the synthetic polymers and surfactants, in some cases, the unit exergy investment for production of oil could be larger than that of the waterflooding. It is asserted that polymer injection into reservoirs with large water cut can be a solution for two major challenges of the energy transition period: (1) meet the global energy demand via an increase in oil recovery and (2) reduce the CO2 intensity of oil production (more and cleaner energy)., Petroleum Engineering
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- 2021
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26. Traveling waves in a finite condensation rate model for steam injection
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Bruining, J. and Duijn, C. J. van
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- 2006
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27. Analysis of Nitrogen and Steam Injection in a Porous Medium with Water
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Bruining, J. and Marchesin, D.
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- 2006
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28. An engineering approach to study the effect of saturation-dependent capillary diffusion on radial Buckley-Leverett flow
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Meulenbroek, B.J. (author), Khoshnevis Gargar, N. (author), Bruining, J. (author), Meulenbroek, B.J. (author), Khoshnevis Gargar, N. (author), and Bruining, J. (author)
- Abstract
1D water oil displacement in porous media is usually described by the Buckley-Leverett equation or the Rapoport-Leas equation when capillary diffusion is included. The rectilinear geometry is not representative for near well oil displacement problems. It is therefore of interest to describe the radially symmetric Buckley-Leverett or Rapoport-Leas equation in cylindrical geometry (radial Buckley-Leverett problem). We can show that under appropriate conditions, one can apply a similarity transformation (r, t) → η= r2/ (2 t) that reduces the PDE in radial geometry to an ODE, even when capillary diffusion is included (as opposed to the situation in the rectilinear geometry (Yortsos, Y.C. (Phys. Fluids 30(10),2928–2935 1987)). We consider two cases (1) where the capillary diffusion is independent of the saturation and (2) where the capillary diffusion is dependent on the saturation. It turns out that the solution with a constant capillary diffusion coefficient is fundamentally different from the solution with saturation-dependent capillary diffusion. Our analytical approach allows us to observe the following conspicuous difference in the behavior of the dispersed front, where we obtain a smoothly dispersed front in the constant diffusion case and a power-law behavior around the front for a saturation-dependent capillary diffusion. We compare the numerical solution of the initial value problem for the case of saturation-dependent capillary diffusion obtained with a finite element software package to a partially analytical solution of the problem in terms of the similarity variable η., Mathematical Physics, Petroleum Engineering
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- 2020
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29. LifeTime and improving European healthcare through cell-based interceptive medicine
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Rajewsky, N. (Nikolaus), Almouzni, G. (Geneviève), Gorski, S.A. (Stanislaw A.), Aerts, S. (Stein), Amit, I. (Ido), Bertero, M.G. (Michela G.), Bock, C. (Christoph), Bredenoord, A.L. (Annelien L.), Cavalli, G. (Giacomo), Chiocca, S. (Susanna), Clevers, H.C. (Hans), Strooper, B. (Bart) de, Eggert, A. (Angelika), Ellenberg, J. (Jan), Fernández, X.M. (Xosé M.), Figlerowicz, M. (Marek), Gasser, S.M. (Susan M.), Hübner, N. (Norbert), Kjems, J. (Jørgen), Knoblich, J.A. (Jürgen A.), Krabbe, G. (Grietje), Lichter, P. (Peter), Linnarsson, S. (Sten), Marine, J.-C. (J.), Marioni, J. (John), Marti-Renom, M.A. (Marc A.), Netea, M.G. (Mihai), Nickel, D. (Dörthe), Nollmann, M. (Marcelo), Novak, H.R. (Halina R.), Parkinson, H. (Helen), Piccolo, S. (Stefano), Pinheiro, I. (Inês), Pombo, A. (Ana), Popp, C. (Christian), Reik, W. (Wolf), Roman-Roman, S. (Sergio), Rosenstiel, P. (Philip), Schultze, J.L. (Joachim), Stegle, O. (Oliver), Tanay, A. (Amos), Testa, G. (Giuseppe), Thanos, D. (Dimitris), Theis, F. (Fabian), Torres-Padilla, M.-E. (Maria-Elena), Valencia, A. (Alfonso), Vallot, C. (Céline), van Oudenaarden, A. (Alexander), Vidal, M. (Marie), Voet, T. (Thierry), Alberi, L. (Lavinia), Alexander, S. (Stephanie), Alexandrov, T. (Theodore), Arenas, E. (Ernest), Bagni, C. (Claudia), Balderas, R. (Robert), Bandelli, A. (Andrea), Becher, B. (Burkhard), Becker, M. (Matthias), Beerenwinkel, N. (Niko), Benkirame, M. (Monsef), Beyer, M. (Marc), Bickmore, W. (Wendy), Biessen, E.E.A.L. (Erik E.A.L.), Blomberg, N. (Niklas), Blumcke, I. (Ingmar), Bodenmiller, B. (Bernd), Borroni, B. (Barbara), Boumpas, D.T. (Dimitrios T.), Bourgeron, T. (Thomas), Bowers, S. (Sarion), Braeken, D. (Dries), Brooksbank, C. (Catherine), Brose, N. (Nils), Bruining, J. (Hans), Bury, J. (Jo), Caporale, N. (Nicolo), Cattoretti, G. (Giorgio), Chabane, N. (Nadia), Chneiweiss, H. (Hervé), Cook, S.A. (Stuart A.), Curatolo, P. (Paolo), Jonge, M.I. (Marien) de, Deplancke, B. (Bart), De Strooper, B. (Bart), de Witte, P. (Peter), Dimmeler, S. (Stefanie), Draganski, B. (Bogdan), Drews, A.-D. (Anna-Dorothee), Dumbrava, C. (Costica), Engelhardt, S. (Stefan), Gasser, T. (Thomas), Giamarellos-Bourboulis, E. (Evangelos), Graff, C. (Caroline), Grün, D. (Dominic), Gut, I. (Ivo), Hansson, O. (Oskar), Henshall, D.C. (David C.), Herland, A. (Anna), Heutink, P. (Peter), Heymans, S. (Stephane), Heyn, H. (Holger), Huch, M. (Meritxell), Huitinga, I. (Inge), Jackowiak, P. (Paulina), Jongsma, K.R. (Karin), Journot, L. (Laurent), Junker, J.P. (Jan Philipp), Katz, S. (Shauna), Kehren, J. (Jeanne), Kempa, S. (Stefan), Kirchhof, P. (Paulus), Klein, C. (Christoph), Koralewska, N. (Natalia), Korbel, J.O. (Jan), Kühnemund, M. (Malte), Lamond, A.I. (Angus I.), Lauwers, E. (Elsa), Le Ber, I. (Isabelle), Leinonen, V. (Ville), Tobon, A.L. (Alejandro Lopez), Lundberg, E. (Emma), Lunkes, A. (Astrid), Maatz, H. (Henrike), Mann, M. (Mathias), Marelli, L. (Luca), Matser, V. (Vera), Matthews, P.M. (P.), Mechta-Grigoriou, F. (Fatima), Menon, R. (Radhika), Nielsen, A.F. (Anne F.), Pagani, M. (Massimiliano), Pasterkamp, R.J. (Jeroen), Pitkanen, A. (Asla), Popescu, V. (Valentin), Pottier, C. (Cyril), Puisieux, A. (Alain), Rademakers, R. (Rosa), Reiling, D. (Dory), Reiner, O. (Orly), Remondini, D. (Daniel), Ritchie, C. (Craig), Rohrer, J.D. (Jonathan D.), Saliba, A.-E. (Antione-Emmanuel), Sánchez-Valle, R. (Raquel), Santosuosso, A. (Amedeo), Sauter, A. (Arnold), Scheltema, R.A. (Richard A.), Scheltens, P. (Philip), Schiller, H.B. (Herbert B.), Schneider, A. (Anja), Seibler, P. (Philip), Sheehan-Rooney, K. (Kelly), Shields, D. (David), Sleegers, K. (Kristel), Smit, G. (Guus), Smith, K.G.C. (Kenneth G. C.), Smolders, I. (Ilse), Synofzik, M. (Matthis), Tam, W.L. (Wai Long), Teichmann, S. (Sarah), Thom, M. (Maria), Turco, M.Y. (Margherita Y.), Beusekom, H.M.M. (Heleen) van, Vandenberghe, R. (Rik), den Hoecke, S.V. (Silvie Van), Van de Poel, E. (Ellen), der Ven, A. (Andre van), van der Zee, J. (Julie), van Lunzen, J. (Jan), van Minnebruggen, G. (Geert), Van Paesschen, W. (Wim), Swieten, J.C. (John) van, van Vught, R. (Remko), Verhage, M. (Matthijs), Verstreken, P. (Patrik), Villa, C.E. (Carlo Emanuele), Vogel, J. (Jörg), Kalle, C. (Christof) von, Walter, J. (Jörn), Weckhuysen, S. (Sarah), Weichert, W. (Wilko), Wood, L. (Louisa), Ziegler, A.-G. (Anette-Gabriele), Zipp, F. (Frauke), Rajewsky, N. (Nikolaus), Almouzni, G. (Geneviève), Gorski, S.A. (Stanislaw A.), Aerts, S. (Stein), Amit, I. (Ido), Bertero, M.G. (Michela G.), Bock, C. (Christoph), Bredenoord, A.L. (Annelien L.), Cavalli, G. (Giacomo), Chiocca, S. (Susanna), Clevers, H.C. (Hans), Strooper, B. (Bart) de, Eggert, A. (Angelika), Ellenberg, J. (Jan), Fernández, X.M. (Xosé M.), Figlerowicz, M. (Marek), Gasser, S.M. (Susan M.), Hübner, N. (Norbert), Kjems, J. (Jørgen), Knoblich, J.A. (Jürgen A.), Krabbe, G. (Grietje), Lichter, P. (Peter), Linnarsson, S. (Sten), Marine, J.-C. (J.), Marioni, J. (John), Marti-Renom, M.A. (Marc A.), Netea, M.G. (Mihai), Nickel, D. (Dörthe), Nollmann, M. (Marcelo), Novak, H.R. (Halina R.), Parkinson, H. (Helen), Piccolo, S. (Stefano), Pinheiro, I. (Inês), Pombo, A. (Ana), Popp, C. (Christian), Reik, W. (Wolf), Roman-Roman, S. (Sergio), Rosenstiel, P. (Philip), Schultze, J.L. (Joachim), Stegle, O. (Oliver), Tanay, A. (Amos), Testa, G. (Giuseppe), Thanos, D. (Dimitris), Theis, F. (Fabian), Torres-Padilla, M.-E. (Maria-Elena), Valencia, A. (Alfonso), Vallot, C. (Céline), van Oudenaarden, A. (Alexander), Vidal, M. (Marie), Voet, T. (Thierry), Alberi, L. (Lavinia), Alexander, S. (Stephanie), Alexandrov, T. (Theodore), Arenas, E. (Ernest), Bagni, C. (Claudia), Balderas, R. (Robert), Bandelli, A. (Andrea), Becher, B. (Burkhard), Becker, M. (Matthias), Beerenwinkel, N. (Niko), Benkirame, M. (Monsef), Beyer, M. (Marc), Bickmore, W. (Wendy), Biessen, E.E.A.L. (Erik E.A.L.), Blomberg, N. (Niklas), Blumcke, I. (Ingmar), Bodenmiller, B. (Bernd), Borroni, B. (Barbara), Boumpas, D.T. (Dimitrios T.), Bourgeron, T. (Thomas), Bowers, S. (Sarion), Braeken, D. (Dries), Brooksbank, C. (Catherine), Brose, N. (Nils), Bruining, J. (Hans), Bury, J. (Jo), Caporale, N. (Nicolo), Cattoretti, G. (Giorgio), Chabane, N. (Nadia), Chneiweiss, H. (Hervé), Cook, S.A. (Stuart A.), Curatolo, P. (Paolo), Jonge, M.I. (Marien) de, Deplancke, B. (Bart), De Strooper, B. (Bart), de Witte, P. (Peter), Dimmeler, S. (Stefanie), Draganski, B. (Bogdan), Drews, A.-D. (Anna-Dorothee), Dumbrava, C. (Costica), Engelhardt, S. (Stefan), Gasser, T. (Thomas), Giamarellos-Bourboulis, E. (Evangelos), Graff, C. (Caroline), Grün, D. (Dominic), Gut, I. (Ivo), Hansson, O. (Oskar), Henshall, D.C. (David C.), Herland, A. (Anna), Heutink, P. (Peter), Heymans, S. (Stephane), Heyn, H. (Holger), Huch, M. (Meritxell), Huitinga, I. (Inge), Jackowiak, P. (Paulina), Jongsma, K.R. (Karin), Journot, L. (Laurent), Junker, J.P. (Jan Philipp), Katz, S. (Shauna), Kehren, J. (Jeanne), Kempa, S. (Stefan), Kirchhof, P. (Paulus), Klein, C. (Christoph), Koralewska, N. (Natalia), Korbel, J.O. (Jan), Kühnemund, M. (Malte), Lamond, A.I. (Angus I.), Lauwers, E. (Elsa), Le Ber, I. (Isabelle), Leinonen, V. (Ville), Tobon, A.L. (Alejandro Lopez), Lundberg, E. (Emma), Lunkes, A. (Astrid), Maatz, H. (Henrike), Mann, M. (Mathias), Marelli, L. (Luca), Matser, V. (Vera), Matthews, P.M. (P.), Mechta-Grigoriou, F. (Fatima), Menon, R. (Radhika), Nielsen, A.F. (Anne F.), Pagani, M. (Massimiliano), Pasterkamp, R.J. (Jeroen), Pitkanen, A. (Asla), Popescu, V. (Valentin), Pottier, C. (Cyril), Puisieux, A. (Alain), Rademakers, R. (Rosa), Reiling, D. (Dory), Reiner, O. (Orly), Remondini, D. (Daniel), Ritchie, C. (Craig), Rohrer, J.D. (Jonathan D.), Saliba, A.-E. (Antione-Emmanuel), Sánchez-Valle, R. (Raquel), Santosuosso, A. (Amedeo), Sauter, A. (Arnold), Scheltema, R.A. (Richard A.), Scheltens, P. (Philip), Schiller, H.B. (Herbert B.), Schneider, A. (Anja), Seibler, P. (Philip), Sheehan-Rooney, K. (Kelly), Shields, D. (David), Sleegers, K. (Kristel), Smit, G. (Guus), Smith, K.G.C. (Kenneth G. C.), Smolders, I. (Ilse), Synofzik, M. (Matthis), Tam, W.L. (Wai Long), Teichmann, S. (Sarah), Thom, M. (Maria), Turco, M.Y. (Margherita Y.), Beusekom, H.M.M. (Heleen) van, Vandenberghe, R. (Rik), den Hoecke, S.V. (Silvie Van), Van de Poel, E. (Ellen), der Ven, A. (Andre van), van der Zee, J. (Julie), van Lunzen, J. (Jan), van Minnebruggen, G. (Geert), Van Paesschen, W. (Wim), Swieten, J.C. (John) van, van Vught, R. (Remko), Verhage, M. (Matthijs), Verstreken, P. (Patrik), Villa, C.E. (Carlo Emanuele), Vogel, J. (Jörg), Kalle, C. (Christof) von, Walter, J. (Jörn), Weckhuysen, S. (Sarah), Weichert, W. (Wilko), Wood, L. (Louisa), Ziegler, A.-G. (Anette-Gabriele), and Zipp, F. (Frauke)
- Abstract
LifeTime aims to track, understand and target human cells during the onset and progression of complex diseases and their response to therapy at single-cell resolution. This mission will be implemented through the development and integration of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during progression from health to disease. Analysis of such large molecular and clinical datasets will discover molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. Timely detection and interception of disease embedded in an ethical and patient-centered vision will be achieved through interactions across academia, hospitals, patient-associations, health data management systems and industry. Applying this strategy to key medical challenges in cancer, neurological, infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.
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- 2020
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30. Study of surface complexation modeling on a novel hybrid enhanced oil recovery (EOR) method; smart-water assisted foam-flooding
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Hassan, A.M. (author), Ayoub, M. (author), Eissa, M. (author), Bruining, J. (author), Zitha, P.L.J. (author), Hassan, A.M. (author), Ayoub, M. (author), Eissa, M. (author), Bruining, J. (author), and Zitha, P.L.J. (author)
- Abstract
This contribution focuses on surface complexes in the calcite-brine-surfactant system. This is relevant for the recovery of oil when using a new hybrid enhanced oil recovery (EOR) method, which combines smart-water (i.e., ionically modified brine) and foam-flooding (SWAF) of light oil with dissolved carbon dioxide (CO2) at high pressure in carbonate (i.e., calcite) reservoirs. Using this new hybrid EOR-method (i.e., the SWAF-process) is not only economically attractive (i.e., it reduces opex costs) but also enhances the effectiveness of the production process, and thus reduces the environmental impact. Ionically modified brine (i.e., low-salinity) has a dual improvement effect. It not only leads to more stable foam lamellae, but also helps to change the carbonate rock wettability, leading for some conditions to more favorable relative permeability behavior. The mechanism for the modified permeability behavior in the presence of ionically modified brine is only partly understood. Therefore, we study this process initially in a zero dimensional (thermodynamics) setting, which can be used for the one dimensional (1D) displacement process with an oleic phase that contains carbon dioxide (CO2) and an aqueous phase that contains both carbon dioxide (CO2) and all the ionic substances. Using DLVO theory and surface complexation modeling to better understand the mechanism(s) of ionically modified brine as wettability modifier and foam stabilizer. We perform simulations using both (NaCl) and (MgCl2) to show the effect of a divalent ion at the high-salinity (8500 mmol/kg-w) and low-salinity (0.4 mmol/kg-w) for both ambient-conditions at (25°C) and at the reservoir-conditions (80°C). We confine our analysis to a description that uses the Dzombak-Morel model of surface complexes, which is based on the Debye-Hückel theory (i.e., valid up to ionic strength of 0.3 (mol/kilogram of water)). We also investigate the effect of carbon dioxi, Petroleum Engineering
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- 2020
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31. Experimental investigation and performance evaluation of modified viscoelastic surfactant (VES) as a new thickening fracturing fluid
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Chieng, Z. H. (author), Mohyaldinn, Mysara Eissa (author), Hassan, A.M. (author), Bruining, J. (author), Chieng, Z. H. (author), Mohyaldinn, Mysara Eissa (author), Hassan, A.M. (author), and Bruining, J. (author)
- Abstract
In hydraulic fracturing, fracturing fluids are used to create fractures in a hydrocarbon reservoir throughout transported proppant into the fractures. The application of many fields proves that conventional fracturing fluid has the disadvantages of residue(s), which causes serious clogging of the reservoir's formations and, thus, leads to reduce the permeability in these hydrocarbon reservoirs. The development of clean (and cost-effective) fracturing fluid is a main driver of the hydraulic fracturing process. Presently, viscoelastic surfactant (VES)-fluid is one of the most widely used fracturing fluids in the hydraulic fracturing development of unconventional reservoirs, due to its non-residue(s) characteristics. However, conventional single-chain VES-fluid has a low temperature and shear resistance. In this study, two modified VES-fluid are developed as new thickening fracturing fluids, which consist of more single-chain coupled by hydrotropes (i.e., ionic organic salts) through non-covalent interaction. This new development is achieved by the formulation of mixing long chain cationic surfactant cetyltrimethylammonium bromide (CTAB) with organic acids, which are citric acid (CA) and maleic acid (MA) at a molar ratio of (3:1) and (2:1), respectively. As an innovative approach CTAB and CA are combined to obtain a solution (i.e., CTAB-based VES-fluid) with optimal properties for fracturing and this behaviour of the CTAB-based VES-fluid is experimentally corroborated. A rheometer was used to evaluate the visco-elasticity and shear rate & temperature resistance, while sand-carrying suspension capability was investigated by measuring the settling velocity of the transported proppant in the fluid. Moreover, the gel breaking capability was investigated by determining the viscosity of broken VES-fluid after mixing with ethanol, and the degree of core damage (i.e., permeability performance) caused by VES-fluid was evaluated while using core-flooding test. The experim, Petroleum Engineering
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- 2020
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32. Process-based upscaling of reactive flow in geological formations
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Meulenbroek, B.J. (author), Farajzadeh, R. (author), Bruining, J. (author), Meulenbroek, B.J. (author), Farajzadeh, R. (author), and Bruining, J. (author)
- Abstract
Recently, there is an increased interest in reactive flow in porous media, in groundwater, agricultural and fuel recovery applications. Reactive flow modeling involves vastly different reaction rates, i.e., differing by many orders of magnitude. Solving the ensuing model equations can be computationally intensive. Categorizing reactions according to their speeds makes it possible to greatly simplify the relevant model equations. Indeed some reactions proceed so slow that they can be disregarded. Other reactions occur so fast that they are well described by thermodynamic equilibrium in the time and spatial region of interest. At intermediate rates kinetics needs to be taken into account. In this paper, we categorize selected reactions as slow, fast or intermediate. We model 2D radially symmetric reactive flow with a reaction-convection-diffusion equation. We show that we can subdivide the PeDaII phasespace in three regions. Region I (slow reaction); reaction can be ignored, region II (intermediate reaction); initially kinetics need to be taken into account, region III (fast reaction); all reaction takes places in a very narrow region around the injection point. We investigate these aspects for a few specific examples. We compute the location in phase space of a few selected minerals depending on salinity and temperature. We note that the conditions, e.g., salinity and temperature may be essential for assigning the reaction to the correct region in phase space. The methodology described can be applied to any mineral precipitation/decomposition problem and consequently greatly simplifies reactive flow modeling in porous media., Mathematical Physics, Petroleum Engineering
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- 2020
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33. On the sustainability of CO2 storage through CO2 – Enhanced oil recovery
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Farajzadeh, R. (author), Eftekhari, A. A. (author), Dafnomilis, I. (author), Lake, L. W. (author), Bruining, J. (author), Farajzadeh, R. (author), Eftekhari, A. A. (author), Dafnomilis, I. (author), Lake, L. W. (author), and Bruining, J. (author)
- Abstract
This work uses pilot examples of CO2 enhanced oil recovery to analyze whether and under which circumstances it is exergetically favorable to sequester CO2 through enhanced oil recovery. We find that the net storage efficiency (ratio between the stored and captured CO2) of the carbon capture and storage (CCS)-only projects is maximally 6–56% depending on the fuel used in the power plants. With the current state of technology, the CCS process will re-emit a minimum of 0.43–0.94 kg of CO2 per kg of CO2 stored. From thermodynamics point of view, CO2 enhanced oil recovery (EOR) with CCS option is not sustainable, i.e., during the life cycle of the process more energy is consumed than the energy produced from oil. For the CCS to be efficient in reducing CO2 levels (1) the exergetic cost of CO2 separation from flue gas should be reduced, and/or (2) the capture process should not lead to additional carbon emission. Furthermore, we find that the exergy recovery factor of CO2-EOR depends on the CO2 utilization factor, which is currently in the low range of 2–4 bbl/tCO2 based on the field data. Exergetically, CO2 EOR with storage option produces 30–40% less exergy compared to conventional CO2 enhanced oil recovery projects with CO2 supplied from natural sources; however, this leads to storage of >400 kg of extra CO2 per barrel of oil produced., Petroleum Engineering, Applied Sciences
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- 2020
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34. Capillary pressure for the sand–CO 2–water system under various pressure conditions. Application to CO 2 sequestration
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Plug, W.-J. and Bruining, J.
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- 2007
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35. A model for a viscous preflush prior to gelation in a porous medium
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Vermolen, F.J., Zitha, P.L.J., and Bruining, J.
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- 2002
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36. Gel Placement in Porous Media: Constant Injection Rate
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Vermolen, F. J., Bruining, J., and van Duijn, C. J.
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- 2001
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37. Visualization experiments of iron precipitates: Application for in-situ arsenic remediation
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Darwish, M.I.M., van Beek, V.M., and Bruining, J.
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- 2006
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38. Upscaling of small-scale heterogeneities to flow units for reservoir modelling
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Mikes, D., Barzandji, O.H.M., Bruining, J., and Geel, C.R.
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- 2006
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39. Standard flow cells to incorporate small-scale heterogeneity (crossbedding) in a reservoir model
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Mikes, D. and Bruining, J.
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- 2006
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40. In situ CO 2–coal reactions in view of carbon dioxide storage in deep unminable coal seams
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Mazumder, S., van Hemert, P., Bruining, J., Wolf, K.-H.A.A., and Drabe, Karel
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- 2006
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41. Uniqueness conditions in a hyperbolic model for oil recovery by steamdrive
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Bruining, J. and van Duijn, C.J.
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- 2000
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42. Effect of hydrolyzed infant formula vs conventional formula on risk of type 1 diabetes the TRIGR randomized clinical trial
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Knip M., Akerblom H. K., Altaji E., Becker D., Bruining J., Castano L., Danne T., De Beaufort C., Dosch H. -M., Dupre J., Fraser W. D., Howard N., Ilonen J., Konrad D., Kordonouri O., Krischer J. P., Lawson M. L., Ludvigsson J., Madacsy L., Mahon J. L., Ormisson A., Palmer J. P., Pozzilli P., Savilahti E., Serrano-Rios M., Songini M., Taback S., Vaarala O., White N. H., Virtanen S. M., Wasikowa R., Mandrup-Poulsen T., Arjas E., Lernmark A., Laara E., Schmidt B., Hyytinen M., Koski K., Koski M., Merentie K., Pajakkala E., Reunanen A., Salonen M., Terhonen T., Virkkunen S., Cuthbertson D., Gainer B., Hadley D., Malloy J., Nallamshetty L., Shanker L., Bradley B., Lough G., Fraser W., Sermer M., Taback S. P., Franciscus M., Nucci A., Palmer J., Alahuhta K., Barlund S., Korhonen T., Kovanen L., Lehtonen E., Niinisto S., Pekkala M., Sorkio S., Toivanen L., Vahatalo L., Uusitalo U., Ohman T., Bongiorno R., Catteau J., Fraser G., Lloyd M., Crock P., Giles M., Siech K., See D. W., Brown C., Craig M., Johnston A., Bere L. J., Clarson C. L., Jenner M., McManus R., Renato N., Lovell M., Higo D., Kent N., Kwan J., Marshall C., Metzger D., Chanoine J. -P., Stewart L., Thompson D., Edwards A., Lange I., Mercer J., Pacaud D., Josephine H., Schwarz W., Stephure D. K., Boer J., Chatur T., Chick C., Couch B., Demianczuk N., Girgis R., Marks S., Ryan E., Thompson M., Dean H. J., Grant L., Hamelin K., LaForte J., Murphy L., Catte D., Schneider C., Sellers E. A. C., Woo V., Boland A., Clark H. D., Cooper T., Gruslin A., Karovitch A., Keely E., Malcolm J. C., Sauro V., Tawagi G. F., Andrighetti S., Arnold G., Barrett J., Blumer I., Daneman D., Donat D., Ehrlich R., Feig D., Gottesman I., Gysler M., Karkanis S., Kenshole A., Knight B., Lackie E., Lewis V., Martin M. J., Maxwell C., Oliver G., Panchum P., Shilletto N., Simone A., Skidmore M., Turrini T., Wong S., Allen C., Belanger L., Bouchard I., Ferland S., Frenette L., Garrido-Russo M., Leblanc M., Imbeault J., Morin V., Olivier G., Weisnagell J., Costain G., Dornan J., Heath K., MacSween M. -C., McGibbon A., Ramsay C., Sanderson F., Sanderson S., Benabdesselam L., Gonthier M., Huot C., Thibeault M., Laforte D., Legault L., Perron P., Armson A., Canning P., Cummings E. A., Ivanko V., McLeod L., Mokashi A., Scott K., Bridger T., Crane J., Crummell C., Curtis J. C., Dawson C., Joyce C., Newhook L. A., Newman S., Druken E., Begum-Hasan J., Breen A., Houlden R., Woods M., Carrson G., Kelly S., Martel M. J., Penner M., Sankaran K., Hardy-Brown K., King N., White R. A., Park M., Popkin J., Robson L., Coles K., Al Taji E., Cerna M., Cerny M., Francova H., Hainerova I., Kothankova H., Koukalova R., Krakorova V., Mendlova P., Sitova R., Stechova K., Vavrinec J., Vosahlo J., Zlatohlavkova B., Brazdova L., Faksova P., Gregorova D., Kantor L., Malkova K., Venhacova J., Venhacova P., Cipra A., Skvor J., Budejovice C., Tomsikova Z., Botkova-Krauseova H., Mockova A., Paterova P., Gogelova P., Kandrnalova J., Einberg U., Jakovlev U., Posiadlo S., Rannaste E., Raukas R., Riikjarv M. -A., Valla K., Astover V., Kirss A., Retpap J., Taht E., Tillmann V., Vahtra S., Heikkila M., Hirvasniemi M., Luopajarvi K., Johansson S., Kleemola P., Laukkanen E., Parkkola A., Pigg H. -M., Puttonen H., Renlund M., Salonen K., Suomalainen H., Tenkula T., Teramo K., Jarvenpaa A. -L., Hamalainen A. -M., Jussila R., Kiiveri S., Haavisto H., Holopainen S., Kupiainen H., Leeve T., Lumme K., Nironen T., Tenhola S., Tiilikainen T., Keinonen H., Lautala P., Salonen P., Vesanto M., Aspholm A. S., Asunta P., Ikavalko H., Jason E., Jaminki S., Kekki P., Koskinen M., Lehtimaki S., Lahde J., Makela M., Peltoniemi S., Poutiainen L., Ranta K., Salonsaari T., Sarviharju-Tujula S. -L., Selvenius J., Siljander H., Haanpaa P. -L., Holm C., Juutilainen A., Jarvelainen V., Kangaskolkka-Keskilohko A. -M., Laino E., Marjamaki L., Suominen E., Ylitalo S., Hokkanen M., Lounamaa R., Matikainen M., Nuuja A., Paalanen I., Puupponen A. R., Salo-Edwards H., Alanne S., Kultti T., Linjama H., Muhonen K., Vaaraniemi M., Talvitie T., Backman M., Hanhijarvi R., Koivula P., Lindstrom K., Martikainen A., Nurmi P., Bjork A., Huopio H., Komulainen J., Lehtomaki S., Muikku E., Pesola J., Sankilampi U., Arkkola T., Hekkala A., Jurvakainen S., Koivikko M. -L., Kahonen M., Leinonen E., Mykkanen T., Pohjola H., Riikonen K., Niittyvuopio A., Stenius A., Tapanainen P., Veijola R., Alar A., Jovio S., Korpela P., Makinen E., Hietanen L., Kivisto J., Kaar M. -L., Lehtimaki P., Mustila T., Popov E., Saatela S., Taittonen L., Ahtiainen K., Laaksonen N., Luoto M., Viitala J., Virransalo R., Nykanen P., Paajanen S., Parkkinen S., Pyrhonen H., Sarkka T., Aschemeier B., Bektas S., Biester T., Datz N., Deiss D., Fath M., Lupke K., Muller B., Nestoris C., Rothes S., Sadeghian E., Semler K., Arato A., Krikovszky D., Nobilis A., Szenasi J., Benevento D., Anguissola G. B., Biagioni M., Bizzarri C., Cherubini V., Ferrito L., Giordano C., Giorgetti C., Khazrai Y. M., Kyanvash S., Maddaloni E., Napoli A., Piergiovanni F., Pitocco D., Suraci T., Tabacco G., Valente L., Visalli N., Carboni M. B., Cavallo R., Cau V., Isola C., Ledda A., Loddo M., Mannu C., Pettinau M., Pisano S., Porceddu M., Putzu C., Rita A., Peters D., Schierloh U., Bisschoff M., Blonk L., Lappenschaar T., Manai B., Seesink M., Sperling-Conrad M., Verhagen M., Zoethout J. A., Basiak A., Chalas M., Chesiak M., Gramza A., Iwankiewicz J., Sieradzan E., Wikiera B., Ciechanowska M., Dziatkowiak H., Futona B., Gorska A., Glowacka-Wony M., Kaim I., Klich B., Starzyk J., Wolanin M., Tokarska L., Chucherco D., Deja G., Firek-Pedras M., Jarosz-Chobot P., Kalina M., Kutrowska-Adamusiak K., Minkina-Pedras M., Muchaka-Bianga M., Bodalski J., Mlynarski W., Szadkowska A., Cieslak A., Cypryk K., Dziatosz K., Jastzebowska J., Krysiak A., Szymanska U., Wilcznski J., Zawodniak-Szalapska M., Aguay A., Bilbao J. R., Chueca M., Cortazar A., Echarte G., Frutos T. G., Jimenez P., Martul P., Moreno A., Oyarzabal M., Rica I., Salgado Y., Martinez-Larrad M. T., Hawkins F. G., Hernandez R., Herranz L., Pallardo L. F., Deibarra L. S., Fernandez B. H., Luis J. L., Ortiz-Quintana L., Recarte P. P., Arnau D. R., Aronsson L., Boden S., Fredriksson J., Isacsson E., Johansson I., Karlsson E., Lock C., Sandstrom A. -M., Konefal M. S., Andreasson C., Dahlstrom U., Hanas R., Lundqvist K., Windell L., Jansson I., Karlsson A. -K., Lindbladh B., Odenman I., Pettersson C., Sundberg F., Sundqvist M., Aronsson S., Bellman I., Bengtsson A. -B., Lyden G. -B., Nilsson N. -O., Soderblom M., Unt C., Augustsson M., Bengtsson M., Fors H., Helmrich A., Johansson T. O., Andersson A. -C., Boiard-Stomlid A., Hellgren G., Kallsholm H., Lindqvist J., Nilsson M., Nordwall M., Stromstedt C., Ahsberg C., Lindh A., Lindhe C., Samuelsson C., Wiik A., Edenwall H., Ljumgcrantz M., Persson I. -B., Strigard E., Svensson B. -L., Aman J., Breivik G. -E., Detlofsson I. -L., Kroon M., Sarnblad S., Johansson C., Ilvered R., Lundberg A., Akesson K., Beccarelli A., Gadient M., Rappold-Amrein C., Schoenle E., Daftary A., Damagro-Elias M. E., Gilmour C., Klein M. B., Lain C., Salerno D., Smith M. E., Vats K., Pfaff D. J., Malone P., Mansfield P., Munns M., Nickel K., Pompilio K., Siemion W., Taculad R., Van Horn K., Zdanadewic M., Chambliss C., Jones J., Sadler M., Tanner-Blasiar M., Bell C., Camper N., Devaskar S., Devaskar U., Horowitz H., Rogers L., Shannahan R., Silk K., Bermudez Z., Colon R., Frazer T., Martinez-Nieves B., Torres J., Vega J., Chan M., Cook S., Goland R., Greenberg E., Jules N., Montes J., Nelson M., Parra-Valencia Z., Schachner H., Softness B., Kiviniemi M., Suomenin R., Alexander A., Hyrckowian E., Nichol L., Trucco M., Karjalainen E., Louhio T., Sarnesto A., Valtonen E., Davydova B., Helander S., Hamalainen J., Harkonen T., Joutsjoki L., Kararic M., Latva-Koivisto M., Lonn E., Nurmi T., Ollila I., Rinkinen J., Ronkainen M., Tukiainen H., Cederlof A., Kiikeri M., Tsupari S., Cheng R., Bryant K., Chan Y., Maezawa Y., Paltser G., Rasavi R., Tsui H., Winer S., Wu P., Yantha J., Pediatrics, Knip M., Akerblom H.K., Altaji E., Becker D., Bruining J., Castano L., Danne T., De Beaufort C., Dosch H.-M., Dupre J., Fraser W.D., Howard N., Ilonen J., Konrad D., Kordonouri O., Krischer J.P., Lawson M.L., Ludvigsson J., Madacsy L., Mahon J.L., Ormisson A., Palmer J.P., Pozzilli P., Savilahti E., Serrano-Rios M., Songini M., Taback S., Vaarala O., White N.H., Virtanen S.M., Wasikowa R., Mandrup-Poulsen T., Arjas E., Lernmark A., Laara E., Schmidt B., Hyytinen M., Koski K., Koski M., Merentie K., Pajakkala E., Reunanen A., Salonen M., Terhonen T., Virkkunen S., Cuthbertson D., Gainer B., Hadley D., Malloy J., Nallamshetty L., Shanker L., Bradley B., Lough G., Fraser W., Sermer M., Taback S.P., Franciscus M., Nucci A., Palmer J., Alahuhta K., Barlund S., Korhonen T., Kovanen L., Lehtonen E., Niinisto S., Pekkala M., Sorkio S., Toivanen L., Vahatalo L., Uusitalo U., Ohman T., Bongiorno R., Catteau J., Fraser G., Lloyd M., Crock P., Giles M., Siech K., See D.W., Brown C., Craig M., Johnston A., Bere L.J., Clarson C.L., Jenner M., McManus R., Renato N., Lovell M., Higo D., Kent N., Kwan J., Marshall C., Metzger D., Chanoine J.-P., Stewart L., Thompson D., Edwards A., Lange I., Mercer J., Pacaud D., Josephine H., Schwarz W., Stephure D.K., Boer J., Chatur T., Chick C., Couch B., Demianczuk N., Girgis R., Marks S., Ryan E., Thompson M., Dean H.J., Grant L., Hamelin K., LaForte J., Murphy L., Catte D., Schneider C., Sellers E.A.C., Woo V., Boland A., Clark H.D., Cooper T., Gruslin A., Karovitch A., Keely E., Malcolm J.C., Sauro V., Tawagi G.F., Andrighetti S., Arnold G., Barrett J., Blumer I., Daneman D., Donat D., Ehrlich R., Feig D., Gottesman I., Gysler M., Karkanis S., Kenshole A., Knight B., Lackie E., Lewis V., Martin M.J., Maxwell C., Oliver G., Panchum P., Shilletto N., Simone A., Skidmore M., Turrini T., Wong S., Allen C., Belanger L., Bouchard I., Ferland S., Frenette L., Garrido-Russo M., Leblanc M., Imbeault J., Morin V., Olivier G., Weisnagell J., Costain G., Dornan J., Heath K., MacSween M.-C., McGibbon A., Ramsay C., Sanderson F., Sanderson S., Benabdesselam L., Gonthier M., Huot C., Thibeault M., Laforte D., Legault L., Perron P., Armson A., Canning P., Cummings E.A., Ivanko V., McLeod L., Mokashi A., Scott K., Bridger T., Crane J., Crummell C., Curtis J.C., Dawson C., Joyce C., Newhook L.A., Newman S., Druken E., Begum-Hasan J., Breen A., Houlden R., Woods M., Carrson G., Kelly S., Martel M.J., Penner M., Sankaran K., Hardy-Brown K., King N., White R.A., Park M., Popkin J., Robson L., Coles K., Al Taji E., Cerna M., Cerny M., Francova H., Hainerova I., Kothankova H., Koukalova R., Krakorova V., Mendlova P., Sitova R., Stechova K., Vavrinec J., Vosahlo J., Zlatohlavkova B., Brazdova L., Faksova P., Gregorova D., Kantor L., Malkova K., Venhacova J., Venhacova P., Cipra A., Skvor J., Budejovice C., Tomsikova Z., Botkova-Krauseova H., Mockova A., Paterova P., Gogelova P., Kandrnalova J., Einberg U., Jakovlev U., Posiadlo S., Rannaste E., Raukas R., Riikjarv M.-A., Valla K., Astover V., Kirss A., Retpap J., Taht E., Tillmann V., Vahtra S., Heikkila M., Hirvasniemi M., Luopajarvi K., Johansson S., Kleemola P., Laukkanen E., Parkkola A., Pigg H.-M., Puttonen H., Renlund M., Salonen K., Suomalainen H., Tenkula T., Teramo K., Jarvenpaa A.-L., Hamalainen A.-M., Jussila R., Kiiveri S., Haavisto H., Holopainen S., Kupiainen H., Leeve T., Lumme K., Nironen T., Tenhola S., Tiilikainen T., Keinonen H., Lautala P., Salonen P., Vesanto M., Aspholm A.S., Asunta P., Ikavalko H., Jason E., Jaminki S., Kekki P., Koskinen M., Lehtimaki S., Lahde J., Makela M., Peltoniemi S., Poutiainen L., Ranta K., Salonsaari T., Sarviharju-Tujula S.-L., Selvenius J., Siljander H., Haanpaa P.-L., Holm C., Juutilainen A., Jarvelainen V., Kangaskolkka-Keskilohko A.-M., Laino E., Marjamaki L., Suominen E., Ylitalo S., Hokkanen M., Lounamaa R., Matikainen M., Nuuja A., Paalanen I., Puupponen A.R., Salo-Edwards H., Alanne S., Kultti T., Linjama H., Muhonen K., Vaaraniemi M., Talvitie T., Backman M., Hanhijarvi R., Koivula P., Lindstrom K., Martikainen A., Nurmi P., Bjork A., Huopio H., Komulainen J., Lehtomaki S., Muikku E., Pesola J., Sankilampi U., Arkkola T., Hekkala A., Jurvakainen S., Koivikko M.-L., Kahonen M., Leinonen E., Mykkanen T., Pohjola H., Riikonen K., Niittyvuopio A., Stenius A., Tapanainen P., Veijola R., Alar A., Jovio S., Korpela P., Makinen E., Hietanen L., Kivisto J., Kaar M.-L., Lehtimaki P., Mustila T., Popov E., Saatela S., Taittonen L., Ahtiainen K., Laaksonen N., Luoto M., Viitala J., Virransalo R., Nykanen P., Paajanen S., Parkkinen S., Pyrhonen H., Sarkka T., Aschemeier B., Bektas S., Biester T., Datz N., Deiss D., Fath M., Lupke K., Muller B., Nestoris C., Rothes S., Sadeghian E., Semler K., Arato A., Krikovszky D., Nobilis A., Szenasi J., Benevento D., Anguissola G.B., Biagioni M., Bizzarri C., Cherubini V., Ferrito L., Giordano C., Giorgetti C., Khazrai Y.M., Kyanvash S., Maddaloni E., Napoli A., Piergiovanni F., Pitocco D., Suraci T., Tabacco G., Valente L., Visalli N., Carboni M.B., Cavallo R., Cau V., Isola C., Ledda A., Loddo M., Mannu C., Pettinau M., Pisano S., Porceddu M., Putzu C., Rita A., Peters D., Schierloh U., Bisschoff M., Blonk L., Lappenschaar T., Manai B., Seesink M., Sperling-Conrad M., Verhagen M., Zoethout J.A., Basiak A., Chalas M., Chesiak M., Gramza A., Iwankiewicz J., Sieradzan E., Wikiera B., Ciechanowska M., Dziatkowiak H., Futona B., Gorska A., Glowacka-Wony M., Kaim I., Klich B., Starzyk J., Wolanin M., Tokarska L., Chucherco D., Deja G., Firek-Pedras M., Jarosz-Chobot P., Kalina M., Kutrowska-Adamusiak K., Minkina-Pedras M., Muchaka-Bianga M., Bodalski J., Mlynarski W., Szadkowska A., Cieslak A., Cypryk K., Dziatosz K., Jastzebowska J., Krysiak A., Szymanska U., Wilcznski J., Zawodniak-Szalapska M., Aguay A., Bilbao J.R., Chueca M., Cortazar A., Echarte G., Frutos T.G., Jimenez P., Martul P., Moreno A., Oyarzabal M., Rica I., Salgado Y., Martinez-Larrad M.T., Hawkins F.G., Hernandez R., Herranz L., Pallardo L.F., Deibarra L.S., Fernandez B.H., Luis J.L., Ortiz-Quintana L., Recarte P.P., Arnau D.R., Aronsson L., Boden S., Fredriksson J., Isacsson E., Johansson I., Karlsson E., Lock C., Sandstrom A.-M., Konefal M.S., Andreasson C., Dahlstrom U., Hanas R., Lundqvist K., Windell L., Jansson I., Karlsson A.-K., Lindbladh B., Odenman I., Pettersson C., Sundberg F., Sundqvist M., Aronsson S., Bellman I., Bengtsson A.-B., Lyden G.-B., Nilsson N.-O., Soderblom M., Unt C., Augustsson M., Bengtsson M., Fors H., Helmrich A., Johansson T.O., Andersson A.-C., Boiard-Stomlid A., Hellgren G., Kallsholm H., Lindqvist J., Nilsson M., Nordwall M., Stromstedt C., Ahsberg C., Lindh A., Lindhe C., Samuelsson C., Wiik A., Edenwall H., Ljumgcrantz M., Persson I.-B., Strigard E., Svensson B.-L., Aman J., Breivik G.-E., Detlofsson I.-L., Kroon M., Sarnblad S., Johansson C., Ilvered R., Lundberg A., Akesson K., Beccarelli A., Gadient M., Rappold-Amrein C., Schoenle E., Daftary A., Damagro-Elias M.E., Gilmour C., Klein M.B., Lain C., Salerno D., Smith M.E., Vats K., Pfaff D.J., Malone P., Mansfield P., Munns M., Nickel K., Pompilio K., Siemion W., Taculad R., Van Horn K., Zdanadewic M., Chambliss C., Jones J., Sadler M., Tanner-Blasiar M., Bell C., Camper N., Devaskar S., Devaskar U., Horowitz H., Rogers L., Shannahan R., Silk K., Bermudez Z., Colon R., Frazer T., Martinez-Nieves B., Torres J., Vega J., Chan M., Cook S., Goland R., Greenberg E., Jules N., Montes J., Nelson M., Parra-Valencia Z., Schachner H., Softness B., Kiviniemi M., Suomenin R., Alexander A., Hyrckowian E., Nichol L., Trucco M., Karjalainen E., Louhio T., Sarnesto A., Valtonen E., Davydova B., Helander S., Hamalainen J., Harkonen T., Joutsjoki L., Kararic M., Latva-Koivisto M., Lonn E., Nurmi T., Ollila I., Rinkinen J., Ronkainen M., Tukiainen H., Cederlof A., Kiikeri M., Tsupari S., Cheng R., Bryant K., Chan Y., Maezawa Y., Paltser G., Rasavi R., Tsui H., Winer S., Wu P., Yantha J., University of Zurich, and Knip, Mikael
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Male ,Risk ,medicine.medical_specialty ,Casein ,Breastfeeding ,030209 endocrinology & metabolism ,610 Medicine & health ,2700 General Medicine ,Endocrinology and Diabetes ,Disease-Free Survival ,law.invention ,Follow-Up Studie ,Nutrition Policy ,03 medical and health sciences ,0302 clinical medicine ,Randomized controlled trial ,Double-Blind Method ,SDG 3 - Good Health and Well-being ,law ,Internal medicine ,Diabetes mellitus ,medicine ,Humans ,Cumulative incidence ,030212 general & internal medicine ,Child ,Infant Nutritional Physiological Phenomena ,Original Investigation ,2. Zero hunger ,Type 1 diabetes ,business.industry ,Hazard ratio ,Absolute risk reduction ,Infant, Newborn ,Caseins ,General Medicine ,ta3121 ,medicine.disease ,Infant Formula ,3. Good health ,Diabetes Mellitus, Type 1 ,Infant formula ,10036 Medical Clinic ,Endokrinologi och diabetes ,Female ,business ,Human ,Follow-Up Studies - Abstract
IMPORTANCE Early exposure to complex dietary proteins may increase the risk of type 1 diabetes in children with genetic disease susceptibility. There are no intact proteins in extensively hydrolyzed formulas. OBJECTIVE To test the hypothesis that weaning to an extensively hydrolyzed formula decreases the cumulative incidence of type 1 diabetes in young children. DESIGN, SETTING, AND PARTICIPANTS An international double-blind randomized clinical trial of 2159 infants with human leukocyte antigen-conferred disease susceptibility and a first-degree relative with type 1 diabetes recruited from May 2002 to January 2007 in 78 study centers in 15 countries; 1081 were randomized to be weaned to the extensively hydrolyzed casein formula and 1078 to a conventional formula. The follow-up of the participants ended on February 28, 2017. INTERVENTIONS The participants received either a casein hydrolysate or a conventional adapted cows milk formula supplemented with 20% of the casein hydrolysate. The minimum duration of study formula exposure was 60 days by 6 to 8 months of age. MAIN OUTCOMES AND MEASURES Primary outcome was type 1 diabetes diagnosed according to World Health Organization criteria. Secondary outcomes included age at diabetes diagnosis and safety (adverse events). RESULTS Among 2159 newborn infants (1021 female [47.3%]) who were randomized, 1744 (80.8%) completed the trial. The participants were observed for a median of 11.5 years (quartile [Q] 1-Q3, 10.2-12.8). The absolute risk of type 1 diabetes was 8.4% among those randomized to the casein hydrolysate (n = 91) vs 7.6% among those randomized to the conventional formula (n = 82) (difference, 0.8%[95% CI, -1.6% to 3.2%]). The hazard ratio for type 1 diabetes adjusted for human leukocyte antigen risk group, duration of breastfeeding, duration of study formula consumption, sex, and region while treating study center as a random effect was 1.1 (95% CI, 0.8 to 1.5; P = .46). The median age at diagnosis of type 1 diabetes was similar in the 2 groups (6.0 years [Q1-Q3, 3.1-8.9] vs 5.8 years [Q1-Q3, 2.6-9.1]; difference, 0.2 years [95% CI, -0.9 to 1.2]). Upper respiratory infections were the most common adverse event reported (frequency, 0.48 events/year in the hydrolysate group and 0.50 events/year in the control group). CONCLUSIONS AND RELEVANCE Among infants at risk for type 1 diabetes, weaning to a hydrolyzed formula compared with a conventional formula did not reduce the cumulative incidence of type 1 diabetes after median follow-up for 11.5 years. These findings do not support a need to revise the dietary recommendations for infants at risk for type 1 diabetes. Funding Agencies|Eunice Kennedy Shriver National Institute of Child Health and Development (NICHD); National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health [HD040364, HD042444, HD051997]; Canadian Institutes of Health Research; Commission of the European Communities [QLK1-2002-00372]; European Foundation for the Study of Diabates/JDRF/Novo Nordisk; Academy of Finland (Centre of Excellence in Molecular Systems Immunology and Physiology Research) [250114]; Dutch Diabetes Research Foundation; Finnish Diabetes Research Foundation; JDRF
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- 2018
43. The Modeling of Velocity Enhancement in Polymer Flooding
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Bartelds, G. A., Bruining, J., and Molenaar, J.
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- 1997
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44. Dielectric mixing rules from groundwater analytic element computations
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de Zwart, A.H., primary, Gorriti, A.G., additional, Bruining, J., additional, and Slob, E.C., additional
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- 2002
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45. Functional effects of a heterozygous gain-of-function mutation in the sulphonylurea receptor SUR1 (ABCC8) that causes neonatal diabetes: A2
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Shimomura, K, Proks, P, de Wet, H, Larkin, B, Girard, C, Ellard, S, Bruining, J, Hattersley, A T, and Ashcroft, F M
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- 2006
46. A heterozygous gain-of-function mutation in the sulphonylurea receptor SUR1 (ABCC8) causes neonatal diabetes: A1
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Ellard, S, Flanagan, S E, Arnold, A L, Colclough, K, Giraud, C, Ashcroft, F M, Bruining, J, and Hattersley, A T
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- 2006
47. T-cell reactivity to 38 kD insulin-secretory granule protein in patients with recent onset type 1 diabetes
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Roep, B. O., Kallan, A. A., Hazenbos, W. L. W., Bruining, J. G., Bailyes, E. M., Arden, S. D., Hutton, J. C., De Vries, R. R. P., Bonifacio, Ezio, and Boitard, Christian
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- 1994
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48. Exergy return on exergy investment analysis of natural-polymer (Guar-Arabic gum) enhanced oil recovery process
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Hassan, A.M. (author), Ayoub, M. (author), Eissa, M. (author), Musa, T. (author), Bruining, J. (author), Farajzadeh, R. (author), Hassan, A.M. (author), Ayoub, M. (author), Eissa, M. (author), Musa, T. (author), Bruining, J. (author), and Farajzadeh, R. (author)
- Abstract
It has been estimated that 17% of the recovered hydrocarbon exergy in oil fields [1]is spent on fluid handling and recovery costs. Therefore, improving the efficiency of oil production can give an some contribution to more efficient energy usage and therefore minimizing to some extent the carbon footprint. By way of example we present in this paper a work-flow, which can serve as a template for computing the fluid handling and recovery costs for natural polymer (Guar-Arabic Gum)flooding. The main contributors to the exergy investment in an Exergy Return on Exergy Investment analysis (ERoEI)are, the fluid circulation costs, the steel costs of the tubing and casing and to some degree the drilling costs. The main contributor to the exergy gain is the exergy of the produced oil. The fluid circulation costs represent the largest exergy investment and usually approximately accounts for 80% of the exergy used for the recovery of oil. For quantifying the circulation costs, the paper uses a 1-D displacement model of polymer flooding of oil to compare the enhanced oil recovery (EOR)history for three scenarios, i.e., (1)water injection, (2)natural-polymer water injection and (3)natural-polymer slug injection. The advantage of a 1-D model is that it allows multiple comparisons of many scenario's avoiding time consuming simulations but this goes at the expense of ignoring 3-D effects. The 1-D model can be extended to a 2-D or 3-D model, which makes it possible to include the improvement of vertical and areal sweep-efficiency. A numerical solution of the EOR model is obtained with COMSOL. We analyze the exergy balance of viscosified water, e.g., with natural-polymer. A comparison as to the displacement efficiency is made between the three scenarios, viz., water, Guar-Arabic gum, and slug injection. The viscosity behavior of Guar-Arabic gum is obtained from laboratory data. It is argued that an ERoEI analysis, which is used on its own or complementary to an economic analysis, can, Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Petroleum Engineering
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- 2019
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49. Life-cycle assessment of water injection into hydrocarbon reservoirs using exergy concept
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Farajzadeh, R. (author), Zaal, CAE (author), van den Hoek, P. (author), Bruining, J. (author), Farajzadeh, R. (author), Zaal, CAE (author), van den Hoek, P. (author), and Bruining, J. (author)
- Abstract
Water injection into hydrocarbon reservoirs has been studied in great detail both from the subsurface and from surface perspectives, usually aiming at maximizing the production of low-cost oil. Here, the exergy concept is used to examine the potential life-cycle impact of injecting water into hydrocarbon reservoirs by considering the energy requirements of the process. It is found that the exergy recovery factor, being the ratio between the produced exergy corrected for material and process exergy requirements for its extraction and the gross exergy of the source decreases with time. Usually the process exergy requirements to produce the exergy increases with time. In the case of water injection the main contributors to the process exergy are due to treatment of water and the pumping of reservoir fluids. The method presented in this paper can also quantify the amount of CO2 per unit volume of the produced oil. It is contended that the volume of water required to produce the oil is an important indicator of the efficiency of water drive recovery of oil. Moreover, the amount of carbon dioxide produced for the extraction of one barrel of oil depends strongly on the water cut fw.in the producers. Below fw = 80% little CO2 is produced; however, when fw> 90% a small increase in the water cut leads to a large increase of carbon dioxide production. This emphasizes the importance of water management in water drive recovery of oil., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Petroleum Engineering
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- 2019
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50. Development of an integrated RFID-IC technology for on-line viscosity measurements in enhanced oil recovery processes
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Hassan, A.M. (author), Ayoub, M. (author), Eissa, M. (author), Musa, T. (author), Bruining, J. (author), Zitha, P.L.J. (author), Hassan, A.M. (author), Ayoub, M. (author), Eissa, M. (author), Musa, T. (author), Bruining, J. (author), and Zitha, P.L.J. (author)
- Abstract
This paper deals with on line viscosity measurements using integrated circuit technology, and is building on a previous paper on the use radio frequency identifier (RFID) technology for determining dielectric coefficients. It is asserted that the progress in RFID technology and integrated circuits, in particular in micro–electro–mechanical system (MEMS) makes it possible to combine them to perform physico-chemical property measurements using devices on centimeter scale. It can even be expected that these devices can be made increasingly smaller. An important property of interest is the viscosity, in this specific case, for the use of Arabic gum in enhanced oil recovery. Arabic gum, is an environmentally acceptable natural product. Natural-polymer solutions 1000 [ppm] are more viscous and therefore more efficient oil displacement agents. They require less invested exergy than non-viscosified water to recover oil. However, polymers, in particular environmentally acceptable natural-polymers (e.g., Guar–Arabic gum) available in large quantities in India and Sudan, are susceptible to microbial degradation. It is therefore important to monitor its quality at the injection and production side for real-time quality control. Natural-polymers based on plant products are promising EOR agents. They may have a lower environmental footprint because of the biodegradability. To provide a proof of concept, we use a state of the art acoustic wave sensor (AWS), which can determine acoustic viscosities. It is asserted that RFID technology can be used to record the acoustic wave signal (SenGenuity vismart acoustic wave Sensor AWS) to determine the viscosity at some distance (meters) away from the measurement device. A calibration with solutions of known viscosity behavior (i.e., Glycerol) can be used to relate the acoustic viscosity to the dynamic viscosity. We can calibrate the acoustic wave sensor using Guar–Arabic gum solutions to measurements with the Anton Paar viscometer (MCR-302), Petroleum Engineering
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- 2019
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