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      This document was automatically generated with bibtex2html 1.96
      (see http://www.lri.fr/~filliatr/bibtex2html/),
      with the following command:
      bibtex2html -r -d -dl -nobibsource -nofooter helma.bib
    %dl
      %dt
        [
        %a{:name => "suenderhof10"}> 1
        ]
      %dd
        Claudia Suenderhauf, Felix Hammann, Andreas Maunz, Christoph Helma, and Jorg
        Huwyler.
        Combinatorial qsar modeling of human intestinal absorption.
        = succeed "," do
          %em Molecular Pharmaceutics
        8(1):213-224, 2011.
        [ 
        %a{:href => "http://dx.doi.org/10.1021/mp100279d"}> DOI
         |
        = succeed " |" do
          %a{:href => "http://arxiv.org/abs/http://pubs.acs.org/doi/pdf/10.1021/mp100279d"} arXiv
        = succeed " ]" do
          %a{:href => "http://pubs.acs.org/doi/abs/10.1021/mp100279d"} http
      %dt
        [
        %a{:name => "maunz10a"}> 2
        ]
      %dd
        Andreas Maunz, Christoph Helma, and Stefan Kramer.
        Efficient mining for structurally diverse subgraph patterns in large
        molecular databases.
        = succeed "," do
          %em Machine Learning
        pages 1-26, 2010.
        [ 
        %a{:href => "http://dx.doi.org/10.1007/s10994-010-5187-6"}> http
        \ ]
      %dt
        [
        %a{:name => "hardy10"}> 3
        ]
      %dd
        Barry Hardy, Nicki Douglas, Christoph Helma, Micha Rautenberg, Nina Jeliazkova,
        Vedrin Jeliazkov, Ivelina Nikolova, Romualdo Benigni, Olga Tcheremenskaia,
        Stefan Kramer, Tobias Girschick, Fabian Buchwald, Joerg Wicker, Andreas
        Karwath, Martin Gutlein, Andreas Maunz, Haralambos Sarimveis, Georgia
        Melagraki, Antreas Afantitis, Pantelis Sopasakis, David Gallagher, Vladimir
        Poroikov, Dmitry Filimonov, Alexey Zakharov, Alexey Lagunin, Tatyana
        Gloriozova, Sergey Novikov, Natalia Skvortsova, Dmitry Druzhilovsky, Sunil
        Chawla, Indira Ghosh, Surajit Ray, Hitesh Patel, and Sylvia Escher.
        Collaborative development of predictive toxicology applications.
        = succeed "," do
          %em Journal of Cheminformatics
        2:7, 2010.
        [ 
        %a{:href => "http://www.jcheminf.com/content/2/1/7"}> http
        \ ]
      %dt
        [
        %a{:name => "maunz08b"}> 4
        ]
      %dd
        A. Maunz and C. Helma.
        Prediction of toxic effects of pharmaceutical agents.
        In K. V. Balakin, editor,
        = succeed "," do
          %em
            Pharmaceutical Data Mining: Approaches
            and Applications for Drug Discovery
        New York, 2009. J. Wiley & Sons, Inc.
        [ 
        %a{:href => "http://www.in-silico.de/articles/chapter_mh.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "maunz09a"}> 5
        ]
      %dd
        A. Maunz, C. Helma, and S. Kramer.
        Large-scale graph mining using backbone refinement classes.
        In
        = succeed "," do
          %em
            Proceedings of the 15th ACM SIGKDD International Conference
            on Knowledge Discovery and Data Mining (KDD-09)
        page in press, 2009.
        [ 
        %a{:href => "http://www.maunz.de/ls_graph_mining_using_bbrcs.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "hammann09a"}> 6
        ]
      %dd
        F. Hammann, H. Gutmann, U. Jecklin, A. Maunz, C. Helma, and J. Drewe.
        Development of decision tree models for substrates, inhibitors and
        inducers of P-glycoprotein.
        = succeed "," do
          %em Current Drug Metabolism
        10:339-46, 2009.
      %dt
        [
        %a{:name => "hammann09b"}> 7
        ]
      %dd
        Felix Hammann, Heike Gutmann, Ulli Baumann, Christoph Helma, and Juergen Drewe.
        Classification of cytochrome p(450) activities using machine learning
        methods.
        = succeed "," do
          %em Molecular pharmaceutics
        6:1920-6, 2009.
      %dt
        [
        %a{:name => "maunz08a"}> 8
        ]
      %dd
        A. Maunz and C. Helma.
        Prediction of chemical toxicity with local support vector regression
        and activity-specific kernels.
        = succeed "," do
          %em SAR QSAR Environ. Res.
        19:413-431, 2008.
        [ 
        %a{:href => "http://www.in-silico.de/articles/mh_tf.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "benigni07"}> 9
        ]
      %dd
        R. Benigni, T. I. Netzeva, E. Benfenati, C. Bossa, R. Franke, C. Helma,
        E. Hulzebos, C. Marchant, A. Richard, Y.-T. Woo, and C. Yang.
        The expanding role of predictive toxicology: an update on the (Q)SAR
        models for mutagens and carcinogens.
        = succeed "," do
          %em J Environ Sci Health C Environ Carcinog Ecotoxicol Rev.
        25:53-97, 2007.
      %dt
        [
        %a{:name => "helma06a"}> 10
        ]
      %dd
        C. Helma.
        Lazy structure-activity relationships (
        %tt> lazar
        ) for the
        prediction of rodent carcinogenicity and
        %em Salmonella
        mutagenicity.
        = succeed "," do
          %em Molecular Diversity
        10:147-158, 2006.
        [ 
        %a{:href => "http://www.in-silico.de/articles/modi020905.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "helma06b"}> 11
        ]
      %dd
        C. Helma and J. Kazius.
        Artificial intelligence and data mining for toxicity prediction.
        = succeed "," do
          %em Current Computer-Aided Drug Design
        2:1-19, 2006.
        [ 
        %a{:href => "http://www.in-silico.de/articles/helma_kazius_ccadd.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "vracko06"}> 12
        ]
      %dd
        M. Vracko, V. Bandelj, P. Barbieri, E. Benfenati, Q. Chaudhry, M. Cronin,
        J. Devillers, A. Gallegos, G. Gini, P. Gramatica, C. Helma, D. Neagu,
        T. Netzeva, M. Pavan, G. Patlevicz, M. Randic, I. Tsakovska, and A. Worth.
        Validation of counter propagation neural network models for
        predictive toxicology according to the OECD principles. A case study.
        = succeed "," do
          %em SAR QSAR Environ. Res.
        17:265-84, 2006.
      %dt
        [
        %a{:name => "helma05a"}> 13
        ]
      %dd
        C. Helma.
        = succeed "." do
          %em Predictive Toxicology
        CRC Press, Boca Raton, 2005.
      %dt
        [
        %a{:name => "helma05b"}> 14
        ]
      %dd
        C. Helma.
        %tt lazar:
        Lazy Structure - Activity Relationships for toxicity
        prediction.
        In C. Helma, editor,
        = succeed "," do
          %em Predictive Toxicology
        pages 479-499. CRC
        Press, Boca Raton, 2005.
      %dt
        [
        %a{:name => "helma05c"}> 15
        ]
      %dd
        C. Helma.
        %em In Silico
        predictive toxicology: The state-of-the-art and
        strategies to predict human health effects.
        = succeed "," do
          %em Current Opinions in Drug Discovery & Development
        8:27-31,
        2005.
        [ 
        %a{:href => "http://www.in-silico.de/articles/helma_coddd.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "helma05d"}> 16
        ]
      %dd
        C. Helma.
        A brief introduction to predictive toxicology.
        In C. Helma, editor,
        = succeed "." do
          %em Predictive Toxicology
        CRC Press, Boca
        Raton, 2005.
      %dt
        [
        %a{:name => "kramer05"}> 17
        ]
      %dd
        S. Kramer and C. Helma.
        Machine learning and data mining.
        In C. Helma, editor,
        = succeed "," do
          %em Predictive Toxicology
        pages 223-254. CRC
        Press, Boca Raton, 2005.
      %dt
        [
        %a{:name => "helma04a"}> 18
        ]
      %dd
        C. Helma, T. Kramer, S. Kramer, and L. DeRaedt.
        Data Mining and Machine Learning techniques for the
        identification of mutagenicity inducing substructures and
        Structure-Activity Relationships of noncongeneric compounds.
        = succeed "," do
          %em J. Chem. Inf. Comput. Sci.
        44:1402-1411, 2004.
        [ 
        %a{:href => "http://pubs3.acs.org/acs/journals/doilookup?in_doi=10.1021/ci034254q"}> http
        \ ]
      %dt
        [
        %a{:name => "helma04b"}> 19
        ]
      %dd
        C. Helma.
        Data mining and knowledge discovery in predictive toxicology.
        = succeed "," do
          %em SAR QSAR Environ. Res.
        15:367-383, 2004.
      %dt
        [
        %a{:name => "helma03a"}> 20
        ]
      %dd
        C. Helma and S. Kramer.
        A survey of the Predictive Toxicology Challenge.
        = succeed "," do
          %em Bioinformatics
        19:1179-1182, 2003.
        [ 
        %a{:href => "http://bioinformatics.oxfordjournals.org/cgi/content/abstract/19/10/1179"}> http
        \ ]
      %dt
        [
        %a{:name => "helma03b"}> 21
        ]
      %dd
        C. Helma, S. Kramer, and L. DeRaedt.
        The molecular feature miner MolFea.
        In M. Hicks and C. Kettner, editors,
        = succeed "," do
          %em
            Proceedings of the
            Beilstein Workshop 2002: Molecular Informatics: Confronting Complexity
        pages 79-93. Beilstein Institut, Frankfurt, 2003.
      %dt
        [
        %a{:name => "toivonen03"}> 22
        ]
      %dd
        H. Toivonen, A. Srinivasan, R. D. King, S. Kramer, and C. Helma.
        Statistical evaluation of the Predictive Toxicology Challenge
        2000-2001.
        = succeed "," do
          %em Bioinformatics
        19:1183-1193, 2003.
        [ 
        %a{:href => "http://bioinformatics.oxfordjournals.org/cgi/content/abstract/19/10/1183"}> http
        \ ]
      %dt
        [
        %a{:name => "helma02a"}> 23
        ]
      %dd
        C. Helma.
        Data mining in toxicology.
        In J.P.V. Heuvel, W.F. Greenlee, G.H. Perdew, and W.B. Mattes,
        editors,
        = succeed "," do
          %em
            Comprehensive Toxicology Vol XX. Cellular and Molecular
            Toxicology
        pages 611-624. Elsevier, 2002.
      %dt
        [
        %a{:name => "kassie02"}> 24
        ]
      %dd
        F. Kassie, S. Rabot, M. Uhl, W. Huber, H.M. Qin, C. Helma, R. Schulte-Hermann,
        and S. Knasmüller.
        Chemoprotective effects of garden cress (lepidium sativum) and its
        constituents towards 2-amino-3-methyl-imidazo[4,5-f]quinoline (IQ)-induced
        genotoxic effects and colonicneoplastic lesions.
        = succeed "," do
          %em Carcinogenesis
        23:1155-1161, 2002.
      %dt
        [
        %a{:name => "kramer02"}> 25
        ]
      %dd
        S. Kramer, E. Frank, and C. Helma.
        Fragment generation and Support Vector Machines for inducing
        SARs.
        = succeed "," do
          %em SAR and QSAR in Environmental Research
        13:509-523, 2002.
      %dt
        [
        %a{:name => "gottmann01"}> 26
        ]
      %dd
        E. Gottmann, S. Kramer, B. Pfahringer, and C. Helma.
        Data quality in predictive toxicology: Reproducibility of rodent
        carcinogenicity experiments.
        = succeed "," do
          %em Environ. Health Perspect.
        109:509-514, 2001.
        [ 
        %a{:href => "http://www.ehponline.org/members/2001/109p509-514gottmann/gottmann-full.html"}> .html
        \ ]
      %dt
        [
        %a{:name => "helma01b"}> 27
        ]
      %dd
        C. Helma, R.D. King, S. Kramer, and A. Srinivasan.
        The Predictive Toxicology Challenge 2000-2001.
        = succeed "," do
          %em Bioinformatics
        17:107-108, 2001.
        [ 
        %a{:href => "http://bioinformatics.oupjournals.org/cgi/reprint/17/1/107.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "kramer01e"}> 28
        ]
      %dd
        S. Kramer, L. De Raedt, and C. Helma.
        Molecular feature mining in HIV data.
        In
        = succeed "," do
          %em
            Proceedings of the Seventh ACM SIGKDD International
            Conference on Knowledge Discovery and Data Mining (KDD-01)
        pages 136-143,
        2001.
      %dt
        [
        %a{:name => "helma00a"}> 29
        ]
      %dd
        C. Helma, S. Kramer, B. Pfahringer, and E. Gottmann.
        Data quality in predictive toxicology: Identification of chemical
        structures and calculation of chemical properties.
        = succeed "," do
          %em Environ. Health Perspect.
        108:1029-1033, 2000.
        [ 
        %a{:href => "http://ehpnet1.niehs.nih.gov/docs/2000/108p1029-1033helma/abstract.html"}> .html
        \ ]
      %dt
        [
        %a{:name => "helma00b"}> 30
        ]
      %dd
        C. Helma, E. Gottmann, and S. Kramer.
        Knowledge discovery and data mining in toxicology.
        = succeed "," do
          %em Stat Methods Med Res.
        9:329-358, 2000.
        [ 
        %a{:href => "http://www.in-silico.de/articles/smmr.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "helma00c"}> 31
        ]
      %dd
        C. Helma, S. Kramer, and B. Pfahringer.
        Carcinogenicity prediction for noncongeneric compounds: Experiments
        with the Machine Learning Program SRT and various sets of chemical
        descriptors.
        In
        = succeed "," do
          %em Molecular Modelling and Prediction of Bioactivity
        page 464,
        2000.
      %dt
        [
        %a{:name => "helma00d"}> 32
        ]
      %dd
        C. Helma and M. Uhl.
        A public domain image analysis program for the single cell gel
        electrophoresis (comet) assay.
        = succeed "," do
          %em Mutation Res.
        466:9-15, 2000.
        [ 
        %a{:href => "http://www.in-silico.de/articles/comet.pdf"}> .pdf
        \ ]
      %dt
        [
        %a{:name => "helma00e"}> 33
        ]
      %dd
        C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer.
        The application of machine learning algorithms to detect chemical
        properties responsible for carcinogenicity.
        In K. Gundertofte and F.S. Jorgensen, editors,
        = succeed "," do
          %em
            Molecular
            Modeling and Prediction of Bioactivity
        pages 464-466, New York, 2000.
        Kluwer Academic/Plenum Publishers.
      %dt
        [
        %a{:name => "helma00f"}> 34
        ]
      %dd
        C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer.
        Artificial Intelligence Methoden zur Vorhersage der
        Kanzerogenität organischer Verbindungen.
        In H. Schöffl, H. Spielmann, and H.A. Tritthart, editors,
        = succeed "," do
          %em
            Ersatz- und Ergänzungsmethoden zu Tierversuchen: Forschung ohne
            Tierversuche
        pages 128-134, Wien-New York, 2000. Springer Verlag.
      %dt
        [
        %a{:name => "uhl00"}> 35
        ]
      %dd
        M. Uhl, C. Helma, and S. Knasmüller.
        Evaluation of the single cell gel electrophoretic assay with human
        hepatoma (HepG2) cells.
        = succeed "," do
          %em Mutation Res.
        468:213-225, 2000.
      %dt
        [
        %a{:name => "helma99a"}> 36
        ]
      %dd
        C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer.
        Data quality issues in toxicological knowledge discovery.
        In
        = succeed "," do
          %em
            Predictive Toxicology of Chemicals: Experiences and Impact of
            AI Tools
        pages 8-11, Menlo Park, California, 1999. AAAI Press.
      %dt
        [
        %a{:name => "pfahringer99"}> 37
        ]
      %dd
        B. Pfahringer, E. Gottmann, C. Helma, and S. Kramer.
        Efficiency/representational issues in toxicological knowledge
        discovery.
        In
        = succeed "," do
          %em
            Predictive Toxicology of Chemicals: Experiences and Impact of
            AI Tools
        pages 86-89, Menlo Park, California, 1999. AAAI Press.
      %dt
        [
        %a{:name => "uhl99"}> 38
        ]
      %dd
        M. Uhl, C. Helma, and S. Knasmüller.
        Single-cell gel electrophoresis assays with human-derived hepatoma
        (HepG2) cells.
        = succeed "," do
          %em Mutation Res.
        441:215-224, 1999.
      %dt
        [
        %a{:name => "helma98a"}> 39
        ]
      %dd
        C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer.
        The application of machine learning algorithms to detect chemical
        properties responsible for carcinogenicity.
        In
        = succeed "," do
          %em
            Molecular Modelling and Prediction of Bioactivity.
            Proceedings of the 12th European Symposium on Quantitative Structure-Activity
            Relationships
        1998.
      %dt
        [
        %a{:name => "helma98b"}> 40
        ]
      %dd
        C. Helma, P. Eckl, E. Gottmann, F. Kassie, W. Rodinger, H. Steinkellner,
        C. Windpassinger, R. Schulte-Hermann, and S. Knasmüller.
        Genotoxic and ecotoxic effects of groundwaters and their relation to
        routinely measured chemical parameters.
        = succeed "," do
          %em Environ. Sci. Technol.
        32:1799-1805, 1998.
      %dt
        [
        %a{:name => "knasmueller98"}> 41
        ]
      %dd
        S. Knasmüller, C. Helma, P. Eckl, E. Gottmann, H. Steinkellner, F. Kassie,
        T. Haider, W. Parzefall, and R. Schulte-Hermann.
        Investigations on genotoxic effects of groundwater from the
        Mitterndorfer Senke from the vicinity of Wiener Neustadt.
        = succeed "," do
          %em Wiener Klinische Wochenschrift
        110:824-833, 1998.
      %dt
        [
        %a{:name => "kramer98"}> 42
        ]
      %dd
        S. Kramer, B. Pfahringer, and C. Helma.
        Stochastic propositionalization of non-determinate background
        knowledge.
        In
        = succeed "," do
          %em
            Proceedings of the 8th International Workshop on Inductive
            Logic Programming (ILP-98)
        pages 80-94, Berlin Heidelberg New York, 1998.
        Springer.
      %dt
        [
        %a{:name => "steinkellner98"}> 43
        ]
      %dd
        H. Steinkellner, M.S. Kong, C. Helma, S. Ecker, T.H. Ma, O. Horak, M. Kundi,
        and S. Knasmüller.
        Genotoxic effects of heavy metals: Comparative investigation with
        plant bioassays.
        = succeed "," do
          %em Environ. Mol. Mutagen.
        31:183-191, 1998.
      %dt
        [
        %a{:name => "helma97a"}> 44
        ]
      %dd
        C. Helma and S. Knasmüller.
        Die Belastung von Gewässern mit gentoxischen Substanzen
        IIa: Die Quellen gentoxischer Kontaminationen (Industrielle
        Emissionen).
        = succeed "," do
          %em UWSF-Z.Umweltchem.Ökotox.
        9:41-48, 1997.
      %dt
        [
        %a{:name => "helma97b"}> 45
        ]
      %dd
        C. Helma and S. Knasmüller.
        Die Belastung von Gewässern mit gentoxischen Substanzen
        IIb: Die Quellen gentoxischer Kontaminationen (Nichtindustrielle
        Emissionen).
        = succeed "," do
          %em UWSF-Z.Umweltchem.Ökotox.
        9:163-168, 1997.
      %dt
        [
        %a{:name => "helma97c"}> 46
        ]
      %dd
        C. Helma.
        Die Situation der Chlorchemie in Östereich: Chlorhältige
        Pflanzenschutz- Holzschutz und Wasserdesinfektionsmittel - Entwicklungen im
        Zeitraum 1993 bis 1997.
        Technical report, Gesellschaft Österreichischer Chemiker, 1997.
      %dt
        [
        %a{:name => "knasmueller97"}> 47
        ]
      %dd
        S. Knasmüller, W. Parzefall, C. Helma, F. Kassie, S. Ecker, and
        R. Schulte-Hermann.
        Toxic effects of griseofulvin: Disease models, mechanisms, and risk
        assessment.
        = succeed "," do
          %em Critical Reviews in Toxicology
        27:495-537, 1997.
      %dt
        [
        %a{:name => "kramer97a"}> 48
        ]
      %dd
        S. Kramer, B. Pfahringer, and C. Helma.
        Mining for causes of cancer: Machine learning experiments at various
        levels of detail.
        In
        = succeed "," do
          %em
            Proceedings of the Third International Conference on
            Knowledge Discovery and Data Mining (KDD-97)
        Menlo Park, CA, 1997. AAAI
        Press.
      %dt
        [
        %a{:name => "helma96a"}> 49
        ]
      %dd
        C. Helma, V. Mersch-Sundermann, V.S. Houk, U. Glasbrenner, C. Klein,
        L. Wenquing, K. Fekadu, R. Schulte-Hermann, and S. Knasmüller.
        Comparative evaluation of four bacterial assays for the detection of
        genotoxic effects in water samples.
        = succeed "," do
          %em Environ. Sci. Technol.
        30:897-907, 1996.
      %dt
        [
        %a{:name => "helma95"}> 50
        ]
      %dd
        C. Helma, L. Kronberg, T.H. Ma, and S. Knasmüller.
        Genotoxic effects of the chlorinated hydroxyfuranones
        3-chloro-4-(dichloromethyl)-5-hydroxy-2[5H]-furanone and
        3,4-dichloro-5-hydroxy-2[5H]-furanone in
        %i Tradescantia
        micronucleus assays.
        = succeed "," do
          %em Mutation Res.
        346:181-186, 1995.
      %dt
        [
        %a{:name => "helma95b"}> 51
        ]
      %dd
        C. Helma.
        Erfahrungen mit dem Einsatz biologischer Mutationstests zur
        Verfahrensoptimierung und Umweltkontrolle.
        In
        = succeed "," do
          %em Handbuch der Umwelttechnik 1995
        pages 266-267. Wien, 1995.
      %dt
        [
        %a{:name => "helma95c"}> 52
        ]
      %dd
        C. Helma.
        Detection of genotoxic contaminations in water.
        In M. Guminska and J. Miedzobrodzki, editors,
        = succeed "," do
          %em
            Molecular Biology
            for Environment and Man
        pages 99-111. 1995.
      %dt
        [
        %a{:name => "helma94a"}> 53
        ]
      %dd
        C. Helma, R. Sommer, R. Schulte-Hermann, and S. Knasmüller.
        Enhanced clastogenicity of contaminated ground water following UV
        irradiation detected by the
        %em Tradescantia
        micronucleus assay.
        = succeed "," do
          %em Mutation Res.
        323:93-98, 1994.
      %dt
        [
        %a{:name => "helma94b"}> 54
        ]
      %dd
        C. Helma, S. Knasmüller, and R. Schulte-Hermann.
        Die Belastung von Wässern mit gentoxischen Substanzen I. Methoden
        zur Prüfung der Gentoxizität.
        = succeed "," do
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      %dt
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      %dd
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        = succeed "," do
          %em
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      %dt
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      %dd
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      %dt
        [
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      %dt
        [
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      %dd
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