22 results on '"Polzin, R."'
Search Results
2. DEA Diagnostic Expert Advisor
- Author
-
Polzin, R, Fritsch, SJ, Sharafutdinov, K, Mayer, H, Barakat, C, Marx, G, Bickenbach, J, Schuppert, A, Polzin, R, Fritsch, SJ, Sharafutdinov, K, Mayer, H, Barakat, C, Marx, G, Bickenbach, J, and Schuppert, A
- Published
- 2023
3. Applications
- Author
-
Petring, D., Polzin, R., Becker, M., Lotsch, H. K. V., Rhodes, William T., editor, Adibi, Ali, editor, Asakura, Toshimitsu, editor, Hänsch, Theodor W., editor, Kamiya, Takeshi, editor, Krausz, Ferenc, editor, Monemar, Bo, editor, Ohtsu, Motoichi, editor, Venghaus, Herbert, editor, Weber, Horst, editor, Weinfurter, Harald, editor, Bachmann, Friedrich, editor, Loosen, Peter, editor, and Poprawe, Reinhart, editor
- Published
- 2007
- Full Text
- View/download PDF
4. Optimierung der mechanischen Triebkopfbremse im ICE der Deutschen Bundesbahn
- Author
-
Fischer, R., Polzin, R., Poprawe, R., Zimmermann, K., and Waidelich, Wilhelm, editor
- Published
- 1994
- Full Text
- View/download PDF
5. Industrielle Anwendungen mit einem 6-kW-CO2-Laser und 3-d-Bearbeitungssystem mit integrierter Strahlführung
- Author
-
Fischer, R., Klein, R., Polzin, R., Poprawe, R., and Waidelich, Wilhelm, editor
- Published
- 1992
- Full Text
- View/download PDF
6. Tailored Hybrid Blanks in Steel and Aluminium
- Author
-
Pircher, H., Mertens, A., Polzin, R., Segala, A., and Wilkinson, B.
- Published
- 2001
7. Applications
- Author
-
Petring, D., primary, Polzin, R., additional, and Becker, M., additional
- Published
- 2007
- Full Text
- View/download PDF
8. Abstract
- Author
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Mache, Ch., Urban, Ch., Sauer, H., Brandesky, G., Meßner, H., Grienberger, H., Becker, H., Slave, I., Hauer, Ch., Pakisch, B., Oberbauer, R., Mokry, M., Ebner, F., Kleinert, R., Schiller, D., Kasparu, H., Schneider, G., Sega, W., Lutz, D., Mader, R. M., Steger, G. G., Sieder, A. E., Ovissi, L., Roth, E., Hamilton, G., Jakesz, R., Rainer, H., Schenk, T., Kornek, G., Schulz, F., Depisch, D., Rosen, H., Sebesta, Ch., Scheithauer, W., Locker, G. J., Czernin, J., Derfler, K., Gnant, M., Schiessel, R., Petru, E., Pickel, H., Heydarfadai, M., Lahousen, M., Haas, J., Sagaster, P., Flamm, J., Umek, H., Essl, R., Teich, G., Micksche, M., Ludwig, H., Ambros, P. F., Lestou, V., Strehl, S., Mann, G., Gadner, H., Eibl, B., Greiter, E., Grünewald, K., Gastl, G., Thaler, J., Aulitzky, W., Lion, T., Henn, T., Gaiger, A., Hofmann, J., Wolf, A., Spitaler, M., Ludescher, Christof, Grunicke, H., Mitterbauer, G., Stangl, E., Geissler, K., Jäger, U., Lechner, K., Mannhalter, C., Haas, Oskar A., Tirita, Anthi, Kahls, P., Haas, O., Hinterberger, W., Linkesch, W., Pober, Michael, Fae, Ingrid, Kyrle, Alexander, Neumeister, Andrea, Panzer, Simon, Kandioler, D., End, A., Grill, R., Karlic, H., Inhauser, T., Chott, A., Pirc-Danoewinata, H., Klepetko, W., Heinz, R., Hopfinger-Limberger, G., Koller, E., Schneider, B., Pittermann, E., Lorber, C., Eichinger, S., Neumann, E., Weidinger, J., Gisslinger, H., Bedford P., Jones D., Cawley J., Catovsky D., Bevan P., Scherrer, R., Bettelheim, P., Knöbl, P., Kyrie, P. A., Lazcika, K., Schwarzinger, I., Sillaber, C., Watzke, H., Dávid, M., Losonczy, H., Matolcsy, A., Papp, M., Prischl, F. C., Schwarzmeier, J. D., Zoubek, Andreas, Harbott, Jochen, Ritterbach, Jutta, Ritter, Jörg, Sillaber, Ch., Agis, H., Spanblöchl, E., Sperr, W. R., Valent, P., Czerwenka, K., Virgolini, I., Li, S. R., Müller, M., Wrann, M., Gaggl, S., Fasching, B., Herold, M., Geissler, D., Nachbaur, D., Huber, Ch., Schwaighofer, H., Pichl, M., Niederwieser, D., Gilly, B., Weissel, H., Lorber, Ch., Schwarzmeier, J., Gasché, C., Reinisch, W., Hilgarth, M., Keil, F., Thomssen, C., Kolb, H. J., Holler, E., Wilmanns, W., Tilg, H., Gächter, A., Panzer-Grümayer, E. R., Majdic, O., Kersey, J. H., Petzer, A. L., Bilgeri, R., Zilian, U., Geisen, F. H., Haun, M., Konwalinka, G., Fuchs, D., Zangerle, R., Artner-Dworzak, E., Weiss, G., Fritsch, P., Tilz, G. P., Dierich, M. P., Wachter, H., Schüller, J., Czejka, M. J., Jäger, W., Meyer, B., Weiss, C., Schernthaner, G., Marosi, Ch., Onderka, E., Schlögl, B., Maca, T., Hanak, R., Mannhalter, Ch., Brenner, B., Mayer, R., Langmann, A., Langmann, G., Slave, J., Poier, E., Stücklschweiger, G., Hackl, A., Fritz, A., Pabinger, I., Willfort, A., Groiss, E., Bernhart, M., Waldner, R., Krieger, O., Nowotny, H., Strobl, H., Michlmayr, G., Mistrik, M., lstvan, L., Kapiotis, S., Laczika, K., Speiser, W., Granena, A., Hermans, J., Zwaan, F., Gratwohl, A., Labar B., Mrsić M., Nemet D., Bogdanić V., Radman I., Zupančić-Šalek Silva, Kovačević-Metelko Jasna, Aurer I., Forstinger, C., Scholten, C., Kier, P., Kalhs, P., Schwinger, W., Slavc, I., Lackner, H., Nussbaumer, W., Fritsch, E., Fink, M., Zechner, O., Kührer, I., Kletter, V., Frey, S., Leitgeb, C., Fritz, E., Silly, H., Brezinschek, R., Kuss, I., Stöger, H., Schmid, M., Samonigg, H., Wilders-Truschnig, M., Schmidt, F., Bauernhofer, T., Kasparek, A. K., Ploner, F., Stoeger, H., Moser, R., Leikauf, W., Klemm, F., Pfeffel, F., Niessner, H., Poschauko, H., Pojer, E., Locker, G. J., Braun, J., Gnant, M. F. X., Michl, I., Pirker, R., Liebhard, A., Zielinski, C., Dittrich, C., Bernát, S. I., Pongrácz, E., Kastner, J., Raderer, M., Jorbenyi, Z., Yilmaz, A., Suardet, L., Lahm, H., Odartchenko, N., Varga, Gy., Sréter, L. A., Oberberg, D., Berdel, W. E., Budiman, R., Brand, C., Berkessy, S., Radványi, G., Pauker, Zs., Nagy, Zs., Karádi, Å., Serti, S., Hainz, R., Kirchweger, P., Prager, C., Prada, J., Neifer, S., Bienzle, U., Kremsner, P., Kämmerer, B., Vetterlein, M., Pohl, W., Letnansky, K., Imre, S. G., Parkas, T., Lakos, Zs., Kiss, A., Telek, B., Felszeghy, E., Kelemen, E., Rak, K., Pfeilstöcker, M., Reisner, R., Salamon, J., Georgopoulos, A., Feistauer, S., Georgopoulos, M., Graninger, W., Klinda, F., Hrubisko, M., Sakalova, A., Weißmann, A., Röhle, R., Fortelny, R., Gutierrez, F., Fritsch, G., Printz, D., Buchinger, P., Buchinger, P., Hoecker, P., Peters, C., Gebauer, E., Katanić, D., Nagy, Á., Szomor, Á., Med. J., Batinić D., Užaervić B., Marušić M., Kovačoević-Metelko Jasminka, Jakić-Razumović Jasminka, Kovačević-Metelko Jasminka, Zuoancić-Šalek Silva, Ihra, G. C., Reinisch, W. W., Hilgarth, M. F., Schwarzmeier, I. D., Várady, E., Molnár, Z. S., Fleischmann, T., Borbényi, Z., Bérczi, M., István, L., Szerafin, L., Jakó, J., Bányai, A., Dankó, K., Szegedi, Gy., Neubauer, M., Frudinger, A., Scholten, Ch., Forstinger, Ch., Dobrić I., Willheim, M., Szépfalusi, Z., Mader, R., Boltz, G., Schwarzmeier, J. D., Nahajevszky, S., Téri, N., Póth, I., Nagy, P., Smanykó, D., Babicz, T., Ujj, Gy., Iványi, J. L., Tóth, F. D., Kiss, J., Konja, J., Petković, I., Kardum, I., Kaštelan, M., Kelečić, J., Feminić, R., Djermanović, M., Bilić, E., Jakovljević, G., Peter, B., Gredelj, G., Senji, P., Thalhammer, F., Floth, A., Etele-Hainz, A., Kainberger, F., Radaszkiewicz, T., Kierner, H., Mód, Anna, Pitlik, E., Gottesman, M., Magócsi, Mária, Sarkadi, B., Knapp, S., Purtscher, B., DelleKarth, G., Jaeger, U., Krieger, O., Berger, W., Elbling, L., Ludescher, C., Hilbe, W., Eisterer, W., Preuß, E., Izraeli, S., Janssen, J. W. G., Walther, J. U., Kovar, H., Ludwig, W. D., Rechavi, G., Bartram, C. R., Rehberger, A., Mittermayer, F., Schauer, E., Kokoschka, E. M., Kammerer, B., Kokron, E., Desser, L., Abdul-Hamid, G., Kroschinksky, F., Luther, Th., Fischer, H., Nowak, R., Wolf, H., Fleischer, J., Wichmann, G., Albercht, S., Adorf, D., Kaboth, W., Nerl, C., Aman, J., Rudolf, G., Peschel, C., Anders, O., Burstein, Ch., Ernst, B., Steiner, H., Konrad, H., Annaloro, U. P., Mozzana, C., Butti, R., Della, C., Volpe A., Soligo D., Uderzo M., Lambertenghi-Deliliers G., Ansari, H., Dickson, D., Hasford, J., Hehlmann, R., Anyanwu, E., Krysa, S., Bülzebrück, H., Vogt-Moykopf, I., Arning, M., Südhoff, Th., Kliche, K. O., Wehmeier, A., Schneider, W., Arnold, R., Bunjes, D., Hertenstein, B., Hueske, D., Stefanic, M., Theobald, M., Wiesneth, M., Heimpel, H., Waldmann, H., Arseniev, L., Bokemeyer, C., Andres, J., Könneke, A., Papageorgiou, E., Kleine, H. -D., Battmer, K., Südmeyer, I., Zaki, M., Schmoll, H. -J., Stangel, W., Poliwoda, H., Link, H., Aul, C., Runde, V., Heyll, A., Germing, U., Gattermann, N., Ebert, A., Feinendegen, L. E., Huhn, D., Bergmann, L., Dönner, H., Hartlapp, J. H., Kreiter, H., Schuhmacher, K., Schalk T., Sparwasser C., Peschel U., Fraaß C. Huber, HIadik, F., Kolbe, K., Irschick, E., Bajko, G., Wozny, T., Hansz, J., Bares, R., Buell, U., Baumann, I., Harms, H., Kuse, R., Wilms, K., Müller-Hermelink, H. K., Baurmann, H., Cherif, D., Berger, R., Becker, K., Zeller, W., Helmchen, U., Hossfeld, D. K., Bentrup, I., Plusczyk, T., Kemkes-Matthes, B., Matthes, K., Bentz, M., Speicher, M., Schröder, M., Moos, M., Döhner, H., Lichter, P., Stilgenbauer, S., Korfel, A., Harnoss, B. -M., Boese-Landgraf, J., May, E., Kreuser, E. -D., Thiel, E., Karacas, T., Jahn, B., Lautenschläger, G., Szepes, S., Fenchel, K., Mitrou, P. S., Hoelzer, D., Heil, G., Lengfelder, E., Puzicha, E., Martin, H., Beyer, J., Kleiner, S., Strohscheer, I., Schwerdtfeger, R., Schwella, N., Schmidt-Wolf, I., Siegert, W., Weyer, C., arzen, G., Risse, G., Miksits, K., Farshidfar, G., Birken, R., Schilling, C. v., Brugger, W., Holldack, J., Mertelsmann, R., Kanz, L., Blanz, J., Mewes, K., Ehninger, G., Zeller, K. -P., Böhme. A., Just G., Bergmann. L., Shah P., Hoelzer D., Stille W., Bohlen, H., Hopff, T., Kapp, U., Wolf, J., Engert, A., Diehl, V., Tesch, H., Schrader, A., van Rhee, J., Köhne-Wömpner, H., Bokemeyer', C., Gonnermann, D., Harstrick, A., Schöffski, P., van Rhee, J., Schuppert, F., Freund, M., Boos, J., Göring, M., Blaschke, G., Borstel, A., Franke, A., Hüller, G., Uhle, R., Weise, W., Brach, Marion A., Gruss, Hans-Jürgen, Herrmann, Friedhelm, deVos, Sven, Brennscheidt, Ulrich, Riedel, Detlev, Klch, Walter, Bonlfer, Renate, Mertelsmann, Roland, Brieaer, J., Appelhans, H., Brückner, S., Siemens, HJ., Wagner, T., Moecklin, W., Mertelsmann, R., Bertz, H., Hecht, T., Mertelsmann, R., Bühl, K., Eichelbaum, M. G., Ladda, E., Schumacher, K., Weimer, A., Bühling, F., Kunz, D., Lendeckel, U., Reinhold, D., Ulmer, A. J., Flad, H. -D., Ansorge, S., Bühring, Hans-Jörg, Broudy¶, Virginia C., Ashman§, Leonie K., Burk, M., Kunecke, H., Dumont, C., Meckenstock, G., Volmer, M., Bucher, M., Manegold, C., Krenpien, B., Fischer, J. R., Drings, P., Bückner, U., Donhuijsen-Ant, R., Eberhardt, B., Westerhausen, M., Busch, F. W., Jaschonek, K., Steinke, B., Calavrezos, A., Hausmann, K., Solbach, M., Woitowitz, H. -P., Hilierdal, G., Heilmann, H. -P., Chen, Z. J., Frickhofen, N., Ellbrück, D., Schwarz, T. F., Körner, K., Wiest, C., Kubanek, B., Seifried, E., Claudé, R., Brücher, J., Clemens, M. R., Bublitz, K., Bieger, O., Schmid, B., Clemetson, K. J., Clemm, Ch., Bamberg, M., Gerl, A., Weißbach, L., Danhauser-Riedl, S., Schick, H. D., Bender, R., Reuter, M., Dietzfelbinger, H., Rastetter, J., Hanauske, A. -R., Decker, Hans-Jochen, Klauck, Sabine, Seizinger, Bernd, Denfeld, Ralf, Pohl, Christoph, Renner, Christoph, Hombach, Andreas, Jung, Wolfram, Schwonzen, Martin, Pfreundschuh, Michael, Derigs, H. Günter, Boswell, H. Scott, Kühn, D., Zafferani, M., Ehrhardt, R., Fischer, K., Schmitt, M., Witt, B., Ho, A. D., Haas, R., Hunstein, W., Dölken, G., Finke, J., Lange, W., Held, M., Schalipp, E., Fauser, A. A., Mertelsmann, R., Donhuijsen, K., Nabavi, D., Leder, L. D., Haedicke, Ch., Freund, H., Hattenberger, S., Dreger, Peter, Grelle, Karen, Schmitz, Norbert, Suttorp, Meinolf, Müller-Ruchholtz, Wolfgang, Löffler, Helmut, Dumoulin, F. L., Jakschies, D., Walther, M., Hunger, P., Deicher, H., von Wussow, P., Dutcher, J. P., Ebell, W., Bender-Götze, C., Bettoni, C., Niethammer, D., Reiter, A., Sauter, S., Schrappe, M., Riehm, H., Niederle, N., Heidersdorf, H., Müller, M. R., Mengelkoch, B., Vanhoefer, U., Stahl, M., Budach, V., loehren, B., Alberti, W., Nowrousian, M. R., Seeber, S., Wilke, H., Stamatis, G., Greschuchna, D., Sack, H., Konietzko, N., Krause, B., Dopfer, R., Schmidt, H., Einsele, H., Müller, C. A., Goldmann, S. F., Grosse-Wilde, H., Waller, H. D., Libal, B., Hohaus, S., Gericke, G., von Eiff, M., Oehme, A., Roth, B., van de Loo, J., von Eiff, K., Pötter, R., Weiß, H., Suhr, B., Koch, P., Roos, H., van de Loo, J., Meuter, V., Heissig, B., Schick, F., Duda, S., Saal, J. G., Klein, R., Steidle, M., Eisner, S., Ganser, A., Seipelt, G., Leonhardt, M., Engelhard, M., Brittinger, G., Gerhartz, H., Meusers, P., Aydemir, Ü., Tintrup, W., Tiemann, H., Lennert, K., Esser, B., Hirsch, F. W., Evers, C., Riess, H., Lübbe, A., Greil, R., Köchling, A., Digel, D., Bross, K. J., Dölken, G., Mertelsmann, R., Gencic S., Ostermann, M., Baum, R. P., Fiebig, H. H., Berger, D. P., Dengler, W. A., Winterhalter, B. R., Hendriks, H., Schwartsmann, G., Pinedo, H. M., Ternes, P., Mertelsmann, R., Dölken, G., Fischbach, W., Zidianakis, Z., Lüke, G., Kirchner, Th., Mössner, J., Fischer, Thomas, Haque, Saikh J., Kumar, Aseem, Rutherford, Michael N., Williams, Bryan R. G., Flohr, T., Decker, T., Thews, A., Hild, F., Dohmen, M., von Wussow, P., Grote-Metke, A., Otremba, B., Fonatsch, C., Binder, T., Imhof, C., Feller, A. C., Fruehauf, S., Moehle, R., Hiddemann Th., Büchner M. Unterhalt, Wörmann, B., Ottmann, O. G., Verbeek, G. W., Seipelt A. Maurer, Geissler, G., Schardt, C., Reutzel, R., Hiddemann, W., Maurer, A., Hess, U., Lindemann, A., Frisch, J., Schulz, G., Mertelsmann, R., Hoelzer, P., Gassmann, W., Sperling, C., Uharek, L., Becher, R., Weh, H. J., Tirier, C., Hagemann, F. G., Fuhr, H. G., Wandt, H., Sauerland, M. C., Gause, A., Spickermann, D., Klein, S., Pfreund-schuh, M., Gebauer, W., Fallgren-Gebauer, E., Geissler, R. G., Mentzel, U., Kleiner, K., Rossol, R., Guba, P., Kojouharoff, G., Gerdau, St., Körholz, D., Klein-Vehne, A., Burdach, St., Gerdemann M., Maurer J., Gerhartz, H. H., Schmetzer, H., Mayer, P., Clemm, C., Hentrich, M., Hartenstein, R., Kohl, P., Gieseler, F., Boege, F., Enttmann, R., Meyer, P., Glass, B., Zeis, M., Loeffler, H., Mueller-Ruchholtz, W., Görg, C., Schwerk, W. B., Köppler, H., Havemann, K., Goldschmitt, J., Goldschmidt, H., Nicolai, M., Richter, Th., Blau, W., Hahn, U., Kappe, R., Leithäuser, F., Gottstein, Claudia, Schön, Gisela, Dünnebacke, Markus, Berthold, Frank, Gramatzki, M., Eger, G., Geiger, M., Burger, R., Zölch, A., Bair, H. J., Becker, W., Griesinger, F., Elfers, H., Griesser, H., Grundner-Culemann, E., Neubauer, V., Fricke, D., Shalitin, C., Benter, T., Mertelsmann, R., Dölken, Gottfried, Mertelsmann, Roland, Günther, W., Schunmm, M., Rieber, P., Thierfelder, S., Gunsilius, E., Kirstein, O., Bommer, M., Serve, H., Hülser, P. -J., Del Valle F., Fischer J. Th., Huberts H., Kaplan E., Haase, D., Halbmayer, W. -M., Feichtinger, Ch., Rubi, K., Fischer, M., Hallek, M., Lepislo, E. M., Griffin, J. D., Emst, T. J., Druker, B., Eder, M., Okuda, K., D.Griffin, J., Kozłowska-Skrzypczak, K., Meyer, B., Reile, D., Scharnofske, M., Hapke, G., Aulenbacher, P., Havemann, K., Becker, N., Scheller, S., Zugmaier, G., Pralle, H., Wahrendorf, J., Heide, Immo, Thiede, Christian, de Kant, Eric, Neubauer, Andreas, Herrmann, Richard, Rochlitz, Christoph, Heiden, B., Depenbrock, H., Block, T., Vogelsang, H., Schneider, P., Fellbaum, Ch., Heidtmann, H. -H., Blings, B., Havemann, K., Fackler-Schwalbe, E., Schlimok, G., Lösch, A., Queißer, W., Löffler, B., Kurrle, E., Chadid, L., Lindemann, A., Mertelsmann, R., Nicolay, U., Gaus, W., Heinemann, V., Jehn, U., Gleixner, B., Wachholz, W., Scholz, P., Plunkett, W., Heinze, B., Novotny, J., Hess, Georg, Gamm, Heinold, Seliger, Barbara, Heuft, H. G., Oettle, H., Zeiler, T., Eckstein, R., Heymanns, J., Havemann, K., Hladik, F., Hoang-Vu, C., Horn, R., Cetin, Y., Scheumann, G., Dralle, H., Köhrle, J., von zur Mühlen, A., Brabant, G., Hochhaus, A., Mende, S., Simon, M., Fonatsch, Ch., Heinze, B., Georgii, A., Hötzl, Ch., Hintermeier-Knabe, R., Kempeni, J., Kaul, M., Hoetzl, Ch., Clemm, Ch., Lauter, H., Hoffknecht, M. M., Eckardt, N., Hoffmann-Fezer, G., Gall, C., Kranz, B., Zengerle, U., Pfoersich, M., Birkenstock, U., Pittenann, E., Heinz, B., Hosten, N., Schörner, W., Kirsch, A., Neumann, K., Felix, R., Humpe, A., Kiss, T., Trümper, L. H., Messner, H. A., Hundt, M., Zielinska-Skowronek, M., Schubert, J., Schmidt, R. E., Huss, R., Storb, R., Deeg, H. J., Issels, R. D., Bosse, D., Abdel-Rahman, S., Jaeger, M., Söhngen, D., Weidmann, E., Schwulera, U., Jakab, I., Fodor, F., Pecze, K., Jaques, G., Schöneberger, H. -J., Wegmann, B., Grüber, A., Bust, K., Pflüger, K. -H., Havemann, K., Faul, C., Wannke, B., Scheurlen, M., Kirchner, M., Dahl, G., Schmits, R., Fohl, C., Kaiser, U., Tuohimaa, P., Wollmer, E., Aumüller, G., Havemann, K., Kolbabek, H., Schölten, C., Popov-Kraupp, B., Emminger, W., Hummel, M., Pawlita, M., v.Kalle, C., Dallenbach, F., Stein, H., Krueger, G. R. F., Müller-Lantzsch, N., Kath, R., Höffken, K., Horn, G., Brockmann, P., Keilholz, U., Stoelben, E., Scheibenbogen, C., Manasterski, M., Tilgen, W., Schlag, P., Görich, J., Kauffmann, G. W., Kempter, B., Rüth, S., Lohse, P., Khalil, R. M., Hültner, L., Mailhammer, R., Luz, A., Hasslinger, M. -A., Omran, S., Dörmer, P., Kienast, J., Kister, K. P., Seifarth, W., Klaassen, U., Werk, S., Reiter, W. W., Klein, G., Beck-Gessert, S., Timpl, R., Hinrichs, H., Lux, E., Döring, G., Scheinichen, D., Döring, G., Wernet, P., Vogeley, K. T., Richartz, G., Südhoff, T., Horstkotte, D., Klocker, J., Trotsenburg, M. v., Schumer, J., Kanatschnig, M., Henning, K., Knauf, W. U., Pottgießer, E., Raghavachar, A., Zeigmeister, B., Bollow, M., Schilling, A., König, H., Koch, M., Volkenandt, M., Seger, Andrea, Banerjee, D., Vogel, J., Bierhoff, E., Heidi, G., Neyses, L., Bertino, J., Kocki, J., Rozynkowa, D. M., M.Rupniewska, Z., Wojcierowski, J., König, V., Hopf, U., Koenigsmann, M., Streit, M., Koeppen, K. M., Martini, I., Poppy, U., Hardel, M., Havemann, K., Havemann, K., Clemm, Ch., Wendt, Th., Gauss, J., Kreienberg, R., Hohenfellner, R., Krieger, O., Istvan, L., Komarnicki, M., Kazmierczak, M., Haertle, D., Korossy, P., Haus, S. Kotlarek, Gabryś, K., Kuliszkiewicz-Janus, M., Krauter, J., Westphal, C., Werner, K., Lang, P., Preissner, K. T., Völler, H., Schröder, K., Uhrig, A., Behles, Ch., Seibt-Jung, H., Besserer, A., Kreutzmann, H., Kröning, H., Kähne, T., Eßbach, U., Kühne, W., Krüger, W. H., Krause, K., Nowicki, B., Stockschläder, M., Peters, S. O., Zander, A. R., Kurowski, V., Schüler, C., Höher, D., Montenarh, M., Lang, W., Schweiger, H., Dölken, Gottfried, Lege, H., Dölken, G., Wex, Th., Frank, K., Hastka, J., Bohrer, M., Leo, R., Peest, D., Tschechne, B., Atzpodien, J., Kirchner, H., Hein, R., Hoffmann, L., Stauch, M., Franks, C. R., Palmer, P. A., Licht, T., Mertelsmann, R., Liersch, T., Vehmeyer, K., Kaboth, U., Maschmeyer, G., Meyer, P., Helmerking, M., Schmitt, J., Adam, D., Prahst, A., Hübner, G., Meisner, M., Seifert, M., Richard, D., Yver, A., Spiekermann, K., Brinkmann, L., Battmer, K., Krainer, M., Löffel, J., Stahl, H., Wust, P., Lübbert, M., Schottelius, A., Mertelsmann, R., Henschler, R., Mertelsmann, R., Mapara, M. Y., Bargou, R., Zugck, C., Krammer, P. H., Dörken, B., Maschek, Hansjörg, Kaloutsi, Vassiliki, Maschek, Hansjörg, Gormitz, Ralf, Meyer, P., Kuntz, B. M. E., Mehl, B., Günther, I., Bülzebruck, H., Menssen, H. D., Mergenthaler, H. -G., Dörmer, P., Heusers, P., Zeller, K. -P., Enzinger, H. M., Neugebauer, T., Klippstein, T., Burkhardt, K. L., Putzicha, E., Möller, Peter, Henne, Christof, Eichelmann, Anette, Brüderlein, Silke, Dhein, Jens, Möstl, M., Krieger, O., Mucke, H., Schinkinger, M., Moiling, J., Daoud, A., Willgeroth, Ch., Mross K., Bewermeier P., Krüger W., Peters S., Berger C., Bohn, C., Edler, L., Jonat, W., Queisser, W., Heidemann, E., Goebel, M., Hamm, K., Markovic-Lipkovski, J., Bitzer, G., Müller, H., Oethinger, M., Grießhammer, M., Tuner, I., Musch E., Malek, M., Peter-Katalinic, J., Hügl, E., Helli, A., Slanicka, M., Filipowicz, A., Nissen, C., Speck, B., Nehls, M. C., Grass, H. -J., Dierbach, H., Mertelsmann, R., Thaller, J., Fiebeler, A., Schmidt, C. A., O'Bryan, J. P., Liu, E., Ritter, M., de Kant, E., Brendel, C., He, M., Dodge, R., George, S., Davey, F., Silver, R., Schiffer, C., Mayer, R., Ball, E., Bloomfield, C., Ramschak, H., Tiran, A., Truschnig-Wilders, M., Nizze, H., Bühring, U., Oelschlägel, U., Jermolow, M., Oertel, J., Weisbach, V., Zingsem, J., Wiens, M., Jessen, J., Osthoff, K., Timm, H., Wilborn, F., Bodak, K., Langmach, K., Bechstein, W., Blumhardt, G., Neuhaus, P., Olek, K., Ottinger, H., Kozole, G., Belka, C., Meusers, P., Hense, J., Papadileris, Stefan, Pasternak, G., Pasternak, L., Karsten, U., Pecherstorfer, M., Zimmer-Roth, I., Poloskey, A., Petrasch, S., Kühnemund, O., Uppenkamp, M., Lütticken, R., Kosco, M., Schmitz, J., Petrides, Petro E., Dittmann, Klaus H., Krieger, O., Pflueger, K. -H., Grueber, A., Schoeneberger, J., Wenzel, E., Havemann, K., Pies, A., Kneba, M., Edel, G., Pohl, S., Bulgay-Mörschel, M., Polzin, R., Issing, W., Clemm, Ch., Schorn, K., Ponta, H., Zöller, M., Hofmann, M., Arch, R., Heider, K. -H., Rudy, W., Tölg, C., Herrlich, P., Prümmer, O., Scherbaum, W. A., Porzsolt, F., Prümmer, O., Krüger, A., Schrezenmeier, H., Schlander, H., Pineo, G., Marin, P., Gluckman, E., Shahidi, N. T., Bacigalupo, A., Ratajczak, M. Z., Gewirtz, A. M., Ratei, R., Borner, K., Bank, U., Bühling, F., Reisbach, G., Bartke, L., Kempkes, B., Kostka, G., Ellwart, X., Birner, A., Bornkamm, G. W., Ullrich, A., Dörmer, P., Henze, G., Parwaresch, R., Müller-Weihrich, S. T., Klingebiel, Th., Odenwald, E., Brandhorst, D., Tsuruo, T., Wetter, O., Renner, C., Pohl, C., Sahin, U., Renner, U., Zeller, K. -P., Repp, R., Valerius, Th., Sendler, A., Kalden, J. R., PIatzer, E., Reuss-Borst, M. A., Bühring, H. J., Reuter, C., der Landwehr, II, U. Auf, der Landwehr, II, U. Auf, Schleyer, E., Rolf, C., Ridwelski, K., Matthias, M., Preiss, R., Riewald, M., Puzo, A., Serke, S., Rohrer, B., Pfeiffer, D., Hepp, H., Romanowski, R., Schött, C., Rüther, U., Rothe, B., Pöllmann, H., Nunnensiek, C., Schöllhammer, T., Ulshöfer, Th., Bader, H., Jipp, P., Müller, H. A. G., Rupp, W., Lüthgens, M., Eisenberger, F., Afflerbach, C., Höller, A., Schwamborn, J. S., Daus, H., Krämer, K., Pees, H., Salat, C., Reinhardt, B., Düll, T., Knabe, H., Hiller, E., Sawinski, K., Schalhorn, A., Kühl, M., Heil, K., Schardt, Ch., Drexler, H. G., Scharf, R. E., Suhijar, D., del Zoppo, G. J., Ruggeri, Z. M., Roll, T., Möhler, T., Giselinger, H., Knäbl, P., Kyrie, P. A., Lazcíka, K., Lechner, X., Scheulen, M. E., Beelen, D. W., Reithmayer, H., Daniels, R., Weiherich, A., Quabeck, K., Schaefer, U. W., Reinhardt J., Grimm M., Unterhalt M., Schliesser, G., Lohmeyer, J., Schlingheider, O., von Eiff, M., Schulze, F., Oehme, C., van de Loo, J., Schlögl E., Bemhart M., Schmeiser, Th., Rozdzinski, E., Kern, W., Reichle, A., Moritz, T., Merk, Bruno, Schmid, R. M., Perkins, N. D., Duckett, C. S., Leung, K., Nabel, G. J., Pawlaczyk-Peter, B., Kellermann-Kegreiß, Schmidt E., Steiert, I., Schmidt-Wolf, G., Schmidt-Wolf, I. G. H., Schlegel, P., Blume, K. G., Chao, N. J., Lefterova, P., Laser, J., Schmitz, G., Rothe, G., Schönfeld, S., Schulz, S., Nyce, J. W., Graf, N., Ludwig, R., Steinhauser, I., Brommer, A. E., Qui, H., Schroeder, M., Grote-Kiehn, J., Bückner, U., Rüger, I., Schröder, J., Meusers, P., Weimar, Ch., Schoch, C., Schröter, G., Stern, H., Buchwald, B., Schick, K., Avril, N., Flierdt, E. v. d., Langhammer, H. R., Pabst, H. W., Alvarado, M., Witte, T., Vogt, H., Schuler, U., Brammer, K., Klann, R. C., Schumm, M., Hahn, J., Günther, W., Wullich, B., Moringlane, J. R., Schöndorf, S., Schwartz, S., Bühring, H. -J., Notter, M., Böttcher, S., Martin, M., Schmid, H., Lübbe, A. S., Leib-Mösch C., Wankmüller, H., Eilbrück, D., Funke, I., Cardoso, M., Duranceyk, H., Seitz, R., Rappe, N., Kraus, H., Egbring, R., Haasberg, M., Havemann, K., Seibach, J., Wollscheid, Ursula, Serke, St., Zimmermann, R., Shirai, T., Umeda, M., Anno, S., Kosuge, T., Katoh, M., Moro, S., Su, C. -Y., Shikoshi, K., Arai, N., Schwieder, G., Silling-Engelhardt, G., Zühlsdorf, M., Aguion-Freire-Innig, E., van de Loo, J., Stockdreher, K., Gatsch, L., Tischler, H. -J., Ringe, B., Diedrich, H., Franzi, A., Kruse, E., Lück, R., Trenn, G., Sykora, J., Wen, T., Fung-Leung, W. P., Mak, T. W., Brady, G., Loke, S., Cossman, J., Gascoyne, R., Mak, T., Urasinski, I., Zdziarska, B., Usnarska-Zubkiewicz, L., Kotlarek-Haus, S., Sciborskl, R., Nowosad, H., Kummer, G., Schleucher, N., Preusser, P., Niebel, W., Achterrath, W., Pott, D., Eigler, F. -W., Venook, A., Stagg, R., Frye, J., Gordon, R., Ring, E., Verschuer, U. v., Baur, F., Heit, W., Corrons, J. L. L. Vives, Vogel, M., Nekarda, H., Remy, W., Bissery, M. C., Aapro, M., Buchwald-Pospiech, A., Kaltwasser, J. P., Jacobi, V., de Vos, Sven, Asano, Yoshinobu, Voss, Harald, Knuth, Alexander, Wiedemann, G., Komischke, B., Horisberger, R., Wussow, P. v., Wanders, L., Senekowitsch, R., Strohmeyer, S., Emmerich, B., Selbach, J., Gutensohn, K., Wacker-Backhaus, G., Winkeimann, M., Send, W., Rösche, J., Weide, R., Parviz, B., Havemann, K., Weidmann, B., Henss, H., Engelhardt, R., Bernards, P., Zeidler, D., Jägerbauer, E., Colajori, E., Kerpel-Fronius, S., Weiss, A., Buchheidt, D., Döring, A., D.Saeger, H., Weissbach, L., Emmler, J., Wermes, R., Meusers, P., Flasshove, M., Skorzec, M., Käding, J., Platow, S., Winkler, Ute, Thorpe, Philip, Winter, S. F., Minna, J. D., Nestor, P. J., Johnson, B. E., Gazdar, A. F., Havemann, K., Carbone, D. P., Wit, M. de, Bittner, S., Hossfeld, D., Wittmann, G., Borchelt, M., Steinhagen-Thiessen, E., Koch, K., Brosch, T., Haas, N., Wölfel, C., Knuth, A., Wölfel, T., Safford, M., Könemann, S., Zurlutter, K., Schreiber, K., Piechotka, K., Drescher, M., Toepker, S., Terstappen, L. W. M. M., Bullerdiek, J., Jox, A., zur Hausen, H., Wolters, B., Stenzinger, W., Woźny, T., Sawiński, K., Kozłowska-Skrzypczak, M., Wussow, P. v., Hochhaus, T., Ansarl, H., Prümmer, O., Zapf, H., Thorban, S., Präuer, H., Zeller, W., Stieglitz, J. v., Dürken, M., Greenshaw, C., Kabisch, H., Reuther, C., Knabbe, C., Lippman, M., Havemann, K., Wellstein, A., Degos, L., Castaigne, S., Fenaux, P., Chomienne, C., Raza, A., Preisler, H. D., PEG Interventional Antimicrobial Strategy Study Group, Interventional Antimicrobial Strategy Study Group of the Paul Ehrlich Society (PEG), and H. Riehm for the BFM study group
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- 1992
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9. Modulare Diodenlaser Strahlwerkzeuge : MDS ; Abschlussbericht ; Laufzeit: 01.07.1998 - 31.04.2004 ; Projekt-Nr. 6700
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Polzin, R. and Litmeyer, M.
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Laserbearbeitung ,Mechanical engineering, power engineering ,Laserdiode ,Feinblech ,Werkstoffbearbeitung, Werkzeugmaschinen: Allgemeines - Abstract
Ill., graph. Darst
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- 2004
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10. Applications.
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Rhodes, William T., Adibi, Ali, Asakura, Toshimitsu, Hänsch, Theodor W., Kamiya, Takeshi, Krausz, Ferenc, Monemar, Bo, Ohtsu, Motoichi, Venghaus, Herbert, Weber, Horst, Weinfurter, Harald, Bachmann, Friedrich, Loosen, Peter, Poprawe, Reinhart, Lotsch, H. K. V., Petring, D., Polzin, R., and Becker, M.
- Abstract
Welding, brazing, and soldering are thermal processes used to join material. Laser technology has been applied for these processes for many years. The main principle of all laser-supported joining technologies is the absorption of laser radiation near to the contact area of the joining partners and — if used — also at the filler material, the transformation of the radiation energy into heat and the transition of part of the irradiated material into the molten (metals) or plasticized (polymers) state. This phase transformation allows the creation of a solid joint by resolidification of the molten or plasticized volume and bridging the gap between the joining partners. This happens spatially behind the interaction zone being moved along the joint track or simply temporally after the laser is switched off. [ABSTRACT FROM AUTHOR]
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- 2007
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11. Transfer of laser processing developments into industrial applications
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Fischer, R., primary, Klein, R., additional, Polzin, R., additional, Poprawe, R., additional, and Zimmermann, K., additional
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- 1992
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12. The effect of diazepam and picrotoxin on brainstem evoked dorsal root potentials
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Polzin, R. and Barnes, C.D.
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- 1976
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13. Promotore -Led Versus Registered Nurse-Led Diabetes Self-Management Education in Mexican Americans: A Randomized Clinical Trial.
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Kopelowicz A, Wali S, Polzin R, Ruiz ME, and Nandy K
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- Adult, Humans, Mexican Americans, Educational Status, Community Health Workers, Diabetes Mellitus, Type 2 therapy, Self-Management
- Abstract
Purpose: The purpose of this study is to compare the benefits of a diabetes self-management program led by registered nurses (RNs) versus community health workers ( promotores ) for Spanish-speaking Mexican Americans with type 2 diabetes (T2DM)., Methods: Three hundred thirty Spanish-speaking Mexican American adults with T2DM were randomly assigned to "Tomando Control de Su Diabetes" delivered for six 2.5-hour sessions either by promotores or RNs. The primary outcome measure was the Summary of Diabetes Self-Care Activities (SDSCA). Evaluations were made at baseline, 6 weeks, and at 3, 6, and 12 months. Mixed-effects regression models were fit to test if participants had differential changes in the SDSCA total score by group over time, controlling for demographic and clinical factors., Results: SDSCA scores were significantly higher at all time points compared to baseline and not statistically different between the 2 groups. Only years of education correlated with improvement in diabetes self-management behaviors. No moderating variables predicted improvement between groups., Conclusions: Spanish-speaking Mexican American adults with T2DM who participated in a diabetes educational program with promotores or RNs demonstrated similar improvements. Promotores may increase the accessibility of effective diabetes self-management training for this difficult-to-reach population.
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- 2023
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14. Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets.
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Sharafutdinov K, Fritsch SJ, Iravani M, Ghalati PF, Saffaran S, Bates DG, Hardman JG, Polzin R, Mayer H, Marx G, Bickenbach J, and Schuppert A
- Abstract
Goal: Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their unproven performance in real-world settings, remain significant constraints to their widespread adoption in clinical practice. One approach to tackle this issue is to base learning on large multi-center datasets. However, such heterogeneous datasets can introduce further biases driven by data origin, as data structures and patient cohorts may differ between hospitals. Methods: In this paper, we demonstrate how mechanistic virtual patient (VP) modeling can be used to capture specific features of patients' states and dynamics, while reducing biases introduced by heterogeneous datasets. We show how VP modeling can be used for data augmentation through identification of individualized model parameters approximating disease states of patients with suspected acute respiratory distress syndrome (ARDS) from observational data of mixed origin. We compare the results of an unsupervised learning method (clustering) in two cases: where the learning is based on original patient data and on data derived in the matching procedure of the VP model to real patient data. Results: More robust cluster configurations were observed in clustering using the model-derived data. VP model-based clustering also reduced biases introduced by the inclusion of data from different hospitals and was able to discover an additional cluster with significant ARDS enrichment. Conclusions: Our results indicate that mechanistic VP modeling can be used to significantly reduce biases introduced by learning from heterogeneous datasets and to allow improved discovery of patient cohorts driven exclusively by medical conditions., Competing Interests: VI.All authors declare no conflicts of interest in this paper. HM is an employee of Bayer AG, Germany. HM has stock ownership with Bayer AG, Germany., (© 2024 The Authors.)
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- 2023
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15. Improving Self-management of Type 2 Diabetes in Latinx Patients: Protocol for a Sequential Multiple Assignment Randomized Trial Involving Community Health Workers, Registered Nurses, and Family Members.
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Kopelowicz A, Nandy K, Ruiz ME, Polzin R, Kurator K, and Wali S
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Background: The rate of Type 2 diabetes mellitus (T2DM) among Mexican American individuals is 16.3%, about twice that of non-Hispanic White individuals. While a number of education approaches have been developed and shown to improve diabetes self-management behaviors and glycemic control for Spanish-speaking Latinx patients with T2DM, there is little research to guide health practitioners regarding which interventions to apply and when so that resources are used efficiently, and treatment outcomes are maximized., Objective: This study aimed to describe an adaptive intervention that integrates community mental health workers, diabetes nurse educators, family members, and patients as partners in care while promoting diabetes self-management for Mexican American individuals with T2DM. The project incorporates four evidence-based, culturally tailored treatments to determine what sequence of intervention strategies work most efficiently and for whom. Given the increasing prevalence of T2DM, achieving better control of diabetes and lowering the associated medical complications experienced disproportionally by Mexican American individuals is a public health priority., Methods: Funded by the National Institute of Nursing Research (National Institutes of Health grant R01 NR015809), this project used a sequential multiple assignment randomized trial and included 330 Spanish-speaking Latinx patients with T2DM. In the first phase of the study, subjects were randomly assigned to an evidence-based diabetes self-management educational program called Tomando Control delivered in a group format for 6, biweekly 1.5-hour sessions, led either by a community health worker or a diabetes nurse educator. In the second phase of the study, those subjects who did not improve their diabetes self-management behaviors were rerandomized to receive either an augmented version of Tomando Control or a multifamily group treatment focused on problem-solving. The primary outcome measure was the "Summary of Diabetes Self-Care Activities." Evaluations were made at baseline and at 3, 6, and 12 months., Results: This study was funded in June 2016 for a period of 5 years. Institutional review board approval was obtained in November 2016. Between March 2017 and September 2020, a total of 330 patients were recruited from the outpatient primary care clinics of Olive View-UCLA Medical Center, with a brief hiatus between May 2020 and July 2020 due to COVID-19 restrictions. The study interventions were completed in December 2020. Data collection began in March 2017 and was completed in December 2021. Data analysis is expected to be completed in Spring 2023, and results will be published in Fall 2023., Conclusions: The results of this trial should help practitioners in selecting the optimal approach for improving diabetes self-management in Spanish-speaking, Latinx patients with T2DM., Trial Registration: ClinicalTrials.gov NCT03092063; https://clinicaltrials.gov/ct2/show/NCT03092063., International Registered Report Identifier (irrid): DERR1-10.2196/44793., (©Alex Kopelowicz, Karabi Nandy, Maria Elena Ruiz, Rhonda Polzin, Kevin Kurator, Soma Wali. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 16.01.2023.)
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- 2023
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16. Application of convex hull analysis for the evaluation of data heterogeneity between patient populations of different origin and implications of hospital bias in downstream machine-learning-based data processing: A comparison of 4 critical-care patient datasets.
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Sharafutdinov K, Bhat JS, Fritsch SJ, Nikulina K, E Samadi M, Polzin R, Mayer H, Marx G, Bickenbach J, and Schuppert A
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Machine learning (ML) models are developed on a learning dataset covering only a small part of the data of interest. If model predictions are accurate for the learning dataset but fail for unseen data then generalization error is considered high. This problem manifests itself within all major sub-fields of ML but is especially relevant in medical applications. Clinical data structures, patient cohorts, and clinical protocols may be highly biased among hospitals such that sampling of representative learning datasets to learn ML models remains a challenge. As ML models exhibit poor predictive performance over data ranges sparsely or not covered by the learning dataset, in this study, we propose a novel method to assess their generalization capability among different hospitals based on the convex hull (CH) overlap between multivariate datasets. To reduce dimensionality effects, we used a two-step approach. First, CH analysis was applied to find mean CH coverage between each of the two datasets, resulting in an upper bound of the prediction range. Second, 4 types of ML models were trained to classify the origin of a dataset (i.e., from which hospital) and to estimate differences in datasets with respect to underlying distributions. To demonstrate the applicability of our method, we used 4 critical-care patient datasets from different hospitals in Germany and USA. We estimated the similarity of these populations and investigated whether ML models developed on one dataset can be reliably applied to another one. We show that the strongest drop in performance was associated with the poor intersection of convex hulls in the corresponding hospitals' datasets and with a high performance of ML methods for dataset discrimination. Hence, we suggest the application of our pipeline as a first tool to assess the transferability of trained models. We emphasize that datasets from different hospitals represent heterogeneous data sources, and the transfer from one database to another should be performed with utmost care to avoid implications during real-world applications of the developed models. Further research is needed to develop methods for the adaptation of ML models to new hospitals. In addition, more work should be aimed at the creation of gold-standard datasets that are large and diverse with data from varied application sites., Competing Interests: HM is an employee of Bayer AG, Germany. HM has stock ownership with Bayer AG, Germany. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sharafutdinov, Bhat, Fritsch, Nikulina, E. Samadi, Polzin, Mayer, Marx, Bickenbach and Schuppert.)
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- 2022
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17. Primary care provider-led group visits for advance care planning in the safety net.
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Schickedanz HB, Polzin R, Vassar SD, Brown AF, and Kim KJ
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- Aged, Culturally Competent Care methods, Feasibility Studies, Female, Humans, Male, Patient Satisfaction, Advance Care Planning, Patient Acceptance of Health Care psychology, Primary Health Care methods, Safety-net Providers methods, Shared Medical Appointments
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- 2021
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18. Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy.
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Marx G, Bickenbach J, Fritsch SJ, Kunze JB, Maassen O, Deffge S, Kistermann J, Haferkamp S, Lutz I, Voellm NK, Lowitsch V, Polzin R, Sharafutdinov K, Mayer H, Kuepfer L, Burghaus R, Schmitt W, Lippert J, Riedel M, Barakat C, Stollenwerk A, Fonck S, Putensen C, Zenker S, Erdfelder F, Grigutsch D, Kram R, Beyer S, Kampe K, Gewehr JE, Salman F, Juers P, Kluge S, Tiller D, Wisotzki E, Gross S, Homeister L, Bloos F, Scherag A, Ammon D, Mueller S, Palm J, Simon P, Jahn N, Loeffler M, Wendt T, Schuerholz T, Groeber P, and Schuppert A
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- Critical Care, Humans, Intensive Care Units, Multicenter Studies as Topic, Quality Improvement, Respiration, Artificial, Respiratory Distress Syndrome diagnosis, Respiratory Distress Syndrome therapy
- Abstract
Introduction: The acute respiratory distress syndrome (ARDS) is a highly relevant entity in critical care with mortality rates of 40%. Despite extensive scientific efforts, outcome-relevant therapeutic measures are still insufficiently practised at the bedside. Thus, there is a clear need to adhere to early diagnosis and sufficient therapy in ARDS, assuring lower mortality and multiple organ failure., Methods and Analysis: In this quality improvement strategy (QIS), a decision support system as a mobile application (ASIC app), which uses available clinical real-time data, is implemented to support physicians in timely diagnosis and improvement of adherence to established guidelines in the treatment of ARDS. ASIC is conducted on 31 intensive care units (ICUs) at 8 German university hospitals. It is designed as a multicentre stepped-wedge cluster randomised QIS. ICUs are combined into 12 clusters which are randomised in 12 steps. After preparation (18 months) and a control phase of 8 months for all clusters, the first cluster enters a roll-in phase (3 months) that is followed by the actual QIS phase. The remaining clusters follow in month wise steps. The coprimary key performance indicators (KPIs) consist of the ARDS diagnostic rate and guideline adherence regarding lung-protective ventilation. Secondary KPIs include the prevalence of organ dysfunction within 28 days after diagnosis or ICU discharge, the treatment duration on ICU and the hospital mortality. Furthermore, the user acceptance and usability of new technologies in medicine are examined. To show improvements in healthcare of patients with ARDS, differences in primary and secondary KPIs between control phase and QIS will be tested., Ethics and Dissemination: Ethical approval was obtained from the independent Ethics Committee (EC) at the RWTH Aachen Faculty of Medicine (local EC reference number: EK 102/19) and the respective data protection officer in March 2019. The results of the ASIC QIS will be presented at conferences and published in peer-reviewed journals., Trial Registration Number: DRKS00014330., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
- Published
- 2021
- Full Text
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19. Heterologous Overexpression of Arabidopsis cel1 Enhances Grain Yield, Biomass and Early Maturity in Setaria viridis .
- Author
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Venkata BP, Polzin R, Wilkes R, Fearn A, Blumenthal D, Rohrbough S, and Taylor NJ
- Abstract
Heterologous overexpression of Arabidopsis cellulase 1 ( Atcel1 ) results in enhanced yield, early maturity, and increased biomass in dicotyledonous species like poplar and eucalyptus but has not been demonstrated in monocots. We produced transgenic Setaria viridis accession A10.1 plants overexpressing a monocotyledonous codon optimized ( MCO) Atcel1 . Agronomic characterization of the transgenic events showed that heterologous overexpression of MCOAtcel1 caused enhanced grain yield, shoot biomass, and accelerated maturation rate in the model grass species S. viridis under growth chamber conditions. The agronomic trait differences observed were consistent with previous reports in dicots but are here described in a monocot species and associated with increased seed yield. Overexpression of Atcel1 in S. viridis was shown to increase the number of panicles and seeds by 24-30%, enhance overall grain yield by up to 26%, and lead to a shoot dry biomass increase of 16-19%. Overexpression also reduced time to plant maturation and senescence by 12.5%. Our findings in S. viridis suggest that manipulation of Atcel1 has potential for developing early-maturing and higher-yielding monocotyledonous biomass crops suitable for climate-smart agriculture., (Copyright © 2020 Venkata, Polzin, Wilkes, Fearn, Blumenthal, Rohrbough and Taylor.)
- Published
- 2020
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20. Arabidopsis Type III Gγ Protein AGG3 Is a Positive Regulator of Yield and Stress Responses in the Model Monocot Setaria viridis .
- Author
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Kaur J, Roy Choudhury S, Vijayakumar A, Hovis L, Rhodes Z, Polzin R, Blumenthal D, and Pandey S
- Abstract
Heterotrimeric G-proteins are key regulators of a multitude of growth and development pathways in eukaryotes. Along with the conserved G-protein components found in all organisms, plants have certain novel variants with unique architecture, which may be involved in the regulation of plant-specific traits. The higher plant-specific type III (or Class C) Gγ protein, which possesses a large C terminal extension, represented by AGG3 in Arabidopsis, is one such variant of canonical Gγ proteins. The type III Gγ proteins are involved in regulation of many agronomically important traits in plants, including seed yield, organ size regulation, abscisic acid (ABA)-dependent signaling and stress responses, and nitrogen use efficiency. However, the extant data, especially in the monocots, present a relatively complex and sometimes contradictory picture of the regulatory role of these proteins. It remains unclear if the positive traits observed in certain naturally occurring populations are due to the presence of specific allelic variants of the proteins or due to the altered expression of the gene itself. To address these possibilities, we have overexpressed the Arabidopsis AGG3 gene in the model monocot Setaria viridis and systematically evaluated its role in conferring agriculturally relevant phenotypes. Our data show that AtAGG3 is indeed functional in Setaria and suggest that a subset of the traits affected by the type III Gγ proteins are indeed positively correlated with the gene expression level, while others might have more complex, allele specific regulation.
- Published
- 2018
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21. Supersensitivity to microiontophoretically applied dopamine and GABA in feline spinal trigeminal and hypoglossal neurons following chronic haloperidol.
- Author
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Felpel LP, Polzin RL, and Huffman RD
- Subjects
- Animals, Cats, Haloperidol administration & dosage, Iontophoresis, Synaptic Transmission drug effects, Dopamine pharmacology, Haloperidol pharmacology, Hypoglossal Nerve drug effects, Neurons drug effects, Trigeminal Nerve drug effects, gamma-Aminobutyric Acid pharmacology
- Published
- 1980
22. Effect of diazepam on GABAergic cuneate neurons.
- Author
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Polzin RL and Barnes CD
- Subjects
- Animals, Bicuculline pharmacology, Cats, Glutamates pharmacology, Picrotoxin pharmacology, Diazepam pharmacology, Medulla Oblongata drug effects, Neurons drug effects, gamma-Aminobutyric Acid physiology
- Published
- 1979
- Full Text
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