Publikationer

Følg med i de senest publicerede videnskabelige artikler fra Faculty of Natural Sciences. Oversigten viser fakultetets publikationer med de nyeste øverst.

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Støckler, K. A. H., Roth, N., Feidenhans'L, A. A., Takahashi, S., Nishibori, E. & Iversen, B. B. (2024). Models of polaron fluctuations in LuFe₂O₄. Physical Review Materials, 8(3), Artikel 034409. https://doi.org/10.1103/PhysRevMaterials.8.034409

Andersen, J. E., Chekhov, L., Norbury, P. & Penner, R. (2015). Models of discretized moduli spaces, cohomological field theories, and Gaussian means. Journal of Geometry and Physics, 98, 312-339. https://doi.org/10.1016/j.geomphys.2015.08.018

Engberg, U. H., Nielsen, M. & Winskel, G. (red.) (1991). Models, Languages and Logics for Concurrent Distributed Systems: CEDISYS Workshop (Aarhus, 1991, May 21-24). Department of Computer Science, Aarhus University. Daimi Report Series (DAIMI PB) Nr. 392

Skjøth, F. (1998). Models for repeated measures in agricultural research. Danish Institute of Agricultural Sciences. Biometry Research Unit.

Barndorff-Nielsen, O. (1979). Models for non-Gaussian variation, with applications to turbulence. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 368(1735), 501-520. https://doi.org/10.1098/rspa.1979.0144

Sassone, V., Nielsen, M. & Winskel, G. (1996). Models for concurrency: towards a classification. Theoretical Computer Science, 170(1-2), 297-348. https://doi.org/10.1016/S0304-3975(96)80710-9

Nielsen, M. & Winskel, G. (1995). Models for Concurrency. I S. Abramsky, D. M. Gabbay & T. S. E. Maibaum (red.), Handbook of Logic in Computer Science: vol. 4: Semantic Modelling (s. 1-148). Oxford University Press.

Winskel, G. & Nielsen, M. (1993). Models for Concurrency. Department of Computer Science, Aarhus University. Daimi Report Series (DAIMI PB) Nr. 429

Nielsen, M. (1991). Models for concurrency. I A. Tarlecki (red.), Mathematical Foundations of Computer Science 1991: 16th International Symposium Kazimierz Dolny, Poland, September 9-13, 1991 Proceedings (s. 43-46). Springer. https://doi.org/10.1007/3-540-54345-7_47

Sorensen, D. & Waagepetersen, R. (2002). Model selection for prediction of breeding values. I Proc. 7th WCGALP, 32: CD-rom Communication No 20-06 (s. 513-520). Editions Quae.

Pelizzola, M., Laursen, R. & Hobolth, A. (2023). Model selection and robust inference of mutational signatures using Negative Binomial non-negative matrix factorization. BMC Bioinformatics, 24(1), Artikel 187. https://doi.org/10.1186/s12859-023-05304-1

Larsen, K. G. (2013). Models and Techniques for Proving Data Structure Lower Bounds. Department of Computer Science, Aarhus University.

Andreassen, C. M. (2013). Models and inference for correlated count data. Department of Mathematics, Aarhus University.

Kristensen, L. E., Ravkilde, T. L., Pineau de Forêts, G., Cabrit, S., Field, D., Sherson, M. G. & Lemaire, J. L. (2007). Model Results for schocked gas in active star forming regions. Molecules in Space and Laboratory, Paris, 2007, 1-4.

Auken, E., Foged, N. & Sørensen, K. I. (2002). Model reconition by 1-D laterally constrained inversion of resistivity data. (s. 0-0).

Tholey, A., Treitz, C., Kussmann, M., Bendixen, E., Schrimpf, S. P. & Hengartner, M. O. (2013). Model organisms proteomics--from holobionts to human nutrition. Proteomics, 13(17), 2537-2541. https://doi.org/10.1002/pmic.201370144

Sneftrup, P. S., Møller, S. H. & Balling, P. (2023). Model of ultrashort-pulse laser excitation of bulk and thin film dielectrics: Coupling material excitation and electric field propagation. Physical Review B, 108(9), Artikel 094307. https://doi.org/10.1103/PhysRevB.108.094307

Nielsen, C. K. (2007). Mode locked fiber lasers: theoretical and experimental developments.

Nielsen, M. (2001). Modelling with Partial Orders - Why and Why Not? I F. Orejas, P. G. Spirakis & J. van Leeuwen (red.), Automata, Languages and Programming: 28th International Colloquium, ICALP 2001 Crete, Greece, July 8-12, 2001 Proceedings (s. 61-63). Springer. https://doi.org/10.1007/3-540-48224-5_5

Strunge, K. (2024). Modelling Vibrational Sum Frequency Generation Spectra of Interfacial Proteins. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Urbina, J. U. M. & Schmiegel, J. (2015). Modelling turbulent time series by BSS-processes. I M. Podolskij, R. Stelzer , S. Thorbjørnsen & A. Veraart (red.), The Fascination of Probability, Statistics and their Applications: In Honour of Ole E. Barndorff-Nielsen (s. 29-52). Springer. https://doi.org/10.1007/978-3-319-25826-3_3

Jungdal-Olesen, G., Piotrowski, J. A., Pedersen, V. K., Damsgaard, A., Fälber, R. & Winsemann, J. (2024). Modelling tunnel valley erosion in northern Germany during the first ice-sheet advance (El-sterian, MIS 12) – a conceptual model and preliminary results. Abstract fra DEUQUA, Salzburg, Østrig.

Haase, K. & Olsen, J. (2018). Modelling time: Applying Bayesian statistics to the chronology of a medieval urban site in Denmark. 159. Poster-session præsenteret på The 23rd International Radiocarbon Conference, Norge. http://www.ntnu.edu/documents/1277442864/0/Radiocarbon_Abstractbook2/84b46c8b-661e-4528-ac83-5dd01741e1d6

Iversen, B. V., Petersen, J. P., Christensen, S., Rasmussen, K. R. & Kjærgaard, C. (2014). Modelling Tile Drainage Discharge Using a Linear Reservoir Model.. Poster-session præsenteret på ASA, CSSA & SSSA International Annual Meeting, Long Beach, California, USA. https://scisoc.confex.com/scisoc/2014am/webprogram/Paper88804.html

Pagonis, V., Ankjærgaard, C., Murray, A. S., Jain, M., Chen, R., Lawless, J. & Greilich, S. (2010). Modelling the thermal quenching mechanism in quartz based on time-resolved optically stimulated luminescence. Journal of Luminescence, 130(5), 902-909. https://doi.org/10.1016/j.jlumin.2009.12.032

Ndayishimiye, J., Greve, M., Stoffelen, P., Bigendako, M. J., De Cannière, C., Svenning, J.-C. & Bogaert, J. (2012). Modelling the spatial distribution of endemic Caesalpinioideae in Central Africa, a contribution to the evaluation of actual protected areas in the region. International Journal of Biodiversity and Conservation, 4(3), 118-129. https://doi.org/10.5897/IJBC11.150

Bazot, M., Creevey, O., Christensen-Dalsgaard, J. & Melendez, J. (2018). Modelling the solar twin 18 Scorpii. Astronomy & Astrophysics (A&A), 619, Artikel 172. https://doi.org/10.1051/0004-6361/201834058

Hale, S. J., Chaplin, W. J., Davies, G. R. & Elsworth, Y. P. (2020). Modelling the response of potassium vapour in resonance scattering spectroscopy. Journal of Physics B: Atomic, Molecular and Optical Physics, 53(8), Artikel 085003. https://doi.org/10.1088/1361-6455/ab7529

Hansen, D. L. & Nielsen, S. B. (2001). Modelling the process of basin inversion. I Terra Nova (s. 0-0)

Topping, C. J., Østergaard, S., Pertoldi, C. & Bach, L. A. (2003). Modelling the loss of genetic diversity in vole populations in a spatially and temporally varying environment. Annales Zoologici Fennici, 40(3), 255-267.

Andersen, J. L., Egholm, D. L., Knudsen, M. F. & Jansen, J. D. (2015). Modelling the Long-term Periglacial Imprint on Mountain Landscapes. Abstract fra INQUA, Nagoya, Japan.

Brandt Hedegaard, G., Christensen, J. H., Geels, C., Gross, A., Hansen, K. M., May, W., Zare, A. & Brandt, J. (2012). Modelling the Impacts of Climate Change on Tropospheric Ozone over three Centuries. Atmospheric and Climate Science, 2(4), 546-561. https://doi.org/10.4236/acs.2012.24050

Rowan, A. V., Egholm, D. L., Quincey, D. J. & Glasser, N. F. (2015). Modelling the feedbacks between mass balance, ice flow and debris transport to predict the response to climate change of debris-covered glaciers in the Himalaya. Earth and Planetary Science Letters, 430, 427-438. https://doi.org/10.1016/j.epsl.2015.09.004

Bernard, M., Steer, P., Gallagher, K. & Egholm, D. L. (2020). Modelling the effects of ice transport and sediment sources on the form of detrital thermochronological age probability distributions from glacial settings. Earth Surface Dynamics, 8(4), 931-953. https://doi.org/10.5194/esurf-8-931-2020

Pollastri, S., Rossi, E., Bonadonna, C. & Merrison, J. P. (2021). Modelling the Effect of Electrification on Volcanic Ash Aggregation. Frontiers of Earth Science, 8, Artikel 574106. https://doi.org/10.3389/feart.2020.574106

Agerbo, E., Mortensen, P. B., Wiuf, C., Pedersen, M. S., McGrath, J., Hollegaard, M. V., Nørgaard-Pedersen, B., Hougaard, D. M., Mors, O. & Pedersen, C. B. (2012). Modelling the contribution of family history and variation in single nucleotide polymorphisms to risk of schizophrenia: A Danish national birth cohort-based study. Schizophrenia Research, 134(2-3), 246-52. https://doi.org/10.1016/j.schres.2011.10.025

Campante et al., T. L. & Karoff, C. (2010). Modelling the autocovariance of the power spectrum of a solar-type oscillator. Royal Astronomical Society. Monthly Notices, 408(542).

von Essen, C., Cellone, S., Mallonn, M., Tingley, B. & Marcussen, M. (2016). Modelling systematics of ground-based transit photometry I. Implications on transit timing variations. ArXiv. http://adsabs.harvard.edu/abs/2016arXiv160703680V

Grombacher, D. (2019). Modelling surface NMR spin-echo experiments in a heterogeneous B₁ field. Geophysical Journal International, 219(2), 1395-1404. https://doi.org/10.1093/gji/ggz388

Piotrowski, J. A., Wspanialy, A. & Ber, A. (2008). Modelling subglacial hydrogeology in the European lowland: Where did all this water go?. Abstract fra 33^rd International Geological Congress, Oslo, Norge.

Piotrowski, J. A., Hermanowski, P., Wspanialy, A., Lulek, A., Munck, F., Kronborg, C. & Rattas, M. (2004). Modelling subglacial groundwater flow at the southern margin of the Scandinavian Ice Sheet: a key to understanding the ice sheet behaviour?. Afhandling præsenteret på April 14-16, 2004, Agricultural University of Norway, Aas.

Avelino, P. P., Cunha, M. S. & Chaplin, W. J. (2020). Modelling stochastic signatures in classical pulsators. Monthly Notices of the Royal Astronomical Society, 492(3), 4477-4483. https://doi.org/10.1093/mnras/staa125

Hobolth, A. & Jensen, E. B. V. (2000). Modelling stochastic chances in curve shape, with an application to cancer diagnostics. Advances in Applied Probability, 32(2), 344-362. https://doi.org/10.1239/aap/1013540167

Jawor, J. A. & Tauris, T. M. (2022). Modelling spin evolution of magnetars. Monthly Notices of the Royal Astronomical Society, 509(1), 634-657. https://doi.org/10.1093/mnras/stab2677

De Ridder, J., Arentoft, T. & Kjeldsen, H. (2006). Modelling space-based high-precision photometry for asteroseismic applications. Royal Astronomical Society. Monthly Notices, 365(2), 595-605.

Pedersen, J. S., Møller, T. L., Raak, N. & Corredig, M. (2023). Modelling scattering data from casein micelles on absolute scale. Poster-session præsenteret på Nordic Rheology Conference 2023, Aarhus, Danmark.

Thorarinsdottir, T. L. & Jensen, E. B. V. (2006). Modelling resting state networks in the human brain. I R. Lechnerová, I. Saxl & V. Benes (red.), Proceedings S⁴G, International Conference on Stereology, Spatial Statistics and Stochastic Geometry (s. 137-147). Union Czech Mathematicians and Physicists.

Camara-Leret, R., Tuomisto, H., Ruokolainen, K., Balslev, H. & Munch Kristiansen, S. (2017). Modelling responses of western Amazonian palms to soil nutrients. Journal of Ecology, 105(2), 367-381. https://doi.org/10.1111/1365-2745.12708

Grombacher, D. & Auken, E. (2017). Modelling relaxation during pulse effects for the complex inversion of surface nmr data; Gaining insight into which rela. I 23rd European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers.

Stassen, P., Møgelberg, R. E., Zwart, M. A., Aguirre, A. & Birkedal, L. (2025). Modelling Recursion and Probabilistic Choice in Guarded Type Theory. Proceedings of the ACM on Programming Languages , 9(POPL), 1417-1445. Artikel 48. https://doi.org/10.1145/3704884

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