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5. Early safety and efficiency outcomes of a novel interdisciplinary laparoscopic resection rectopexy combined with sacrocolpopexy for women with obstructive defecation syndrome and pelvic organ prolapse: a single center study

Author

Claudia Rudroff, Joshy Madukkakuzhy, Alberto Vega Hernandez, Jakob Otten, Christoph Ulrici, Leonidas Karapanos, and Sebastian Ludwig

Subjects
Obstructed defecation syndrome, Pelvic organ prolapse, Resection rectopexy, Sacrocolpopexy, Synthetic mesh, Biological mesh, Surgery, RD1-811
Abstract

Abstract Background Obstructive defecation syndrome (ODS) defines a disturbed defecation process frequently associated with pelvic organ prolapse (POP) in women that substantially compromises quality of life. Conservative management offers limited relief and a surgical intervention may be required. This is characterized by individual approaches. Aim of the study This retrospective single center study evaluated the surgical and clinical short-term outcome of a novel interdisciplinary laparoscopic resection rectopexy (L-RRP) with mesh- sacrocolpopexy (L-SCP) for women suffering from ODS and POP. Methods The study participants underwent surgery in an interdisciplinary laparoscopic approach. Safety was the primary endpoint, assessed via postoperative morbidity classified by Clavien-Dindo scale. Secondary outcomes included evaluation of bowel function, fecal and urinary incontinence and pelvic organ prolapse status at 12 months follow-up. Additionally, a biological mesh (BM) was offered to women, who asked for an alternative to synthetic mesh material (SM). Results Of the 44 consecutive patients requiring surgery for ODS and POP, 36 patients underwent the interdisciplinary surgical approach; 28 patients with SM and 8 patients with BM. In total 5 complications occurred, four of them were classified as minor. One minor complication was observed in the BM group. One anastomotic leakage occurred in the SM group. The two ODS scores, the bowel dysfunction score, and the incontinence score improved significantly (p = 0.006, p = 0.003, p

Published
2024
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6. Evaluation of the potential of Near Infrared Hyperspectral Imaging for monitoring the invasive brown marmorated stink bug

Author

Ferrari, Veronica, Calvini, Rosalba, Boom, Bas, Menozzi, Camilla, Rangarajan, Aravind Krishnaswamy, Maistrello, Lara, Offermans, Peter, and Ulrici, Alessandro

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

The brown marmorated stink bug (BMSB), Halyomorpha halys, is an invasive insect pest of global importance that damages several crops, compromising agri-food production. Field monitoring procedures are fundamental to perform risk assessment operations, in order to promptly face crop infestations and avoid economical losses. To improve pest management, spectral cameras mounted on Unmanned Aerial Vehicles (UAVs) and other Internet of Things (IoT) devices, such as smart traps or unmanned ground vehicles, could be used as an innovative technology allowing fast, efficient and real-time monitoring of insect infestations. The present study consists in a preliminary evaluation at the laboratory level of Near Infrared Hyperspectral Imaging (NIR-HSI) as a possible technology to detect BMSB specimens on different vegetal backgrounds, overcoming the problem of BMSB mimicry. Hyperspectral images of BMSB were acquired in the 980-1660 nm range, considering different vegetal backgrounds selected to mimic a real field application scene. Classification models were obtained following two different chemometric approaches. The first approach was focused on modelling spectral information and selecting relevant spectral regions for discrimination by means of sparse-based variable selection coupled with Soft Partial Least Squares Discriminant Analysis (s-Soft PLS-DA) classification algorithm. The second approach was based on modelling spatial and spectral features contained in the hyperspectral images using Convolutional Neural Networks (CNN). Finally, to further improve BMSB detection ability, the two strategies were merged, considering only the spectral regions selected by s-Soft PLS-DA for CNN modelling., Comment: Accepted manuscript

Published
2023
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13. Improved fed-batch processes with Wickerhamomyces anomalus WC 1501 for the production of d-arabitol from pure glycerol

Author

Stefano Raimondi, Giorgia Foca, Alessandro Ulrici, Lorenza Destro, Alan Leonardi, Raissa Buzzi, Francesco Candeliere, Maddalena Rossi, and Alberto Amaretti

Subjects
Arabitol, Glycerol, Wickeramomyces anomalus, Biorefinery, Central composite design, Microbiology, QR1-502
Abstract

Abstract Background d-Arabitol, a five-carbon sugar alcohol, represents a main target of microbial biorefineries aiming to valorize cheap substrates. The yeast Wickerhamomyces anomalus WC 1501 is known to produce arabitol in a glycerol-based nitrogen-limited medium and preliminary fed-batch processes with this yeast were reported to yield 18.0 g/L arabitol. Results Fed-batch fermentations with W. anomalus WC 1501 were optimized using central composite design (CCD). Dissolved oxygen had not a significant effect, while optimum values were found for glycerol concentration (114.5 g/L), pH (5.9), and temperature (32.5 °C), yielding 29 g/L d-arabitol in 160 h, a conversion yield of 0.25 g of arabitol per g of consumed glycerol, and a volumetric productivity of 0.18 g/L/h. CCD optimal conditions were the basis for further improvement, consisting in increasing the cellular density (3✕), applying a constant feeding of glycerol, and increasing temperature during production. The best performing fed-batch fermentations achieved 265 g/L d-arabitol after 325 h, a conversion yield of 0.74 g/g, and a volumetric productivity of 0.82 g/L/h. Conclusion W. anomalus WC 1501 confirmed as an excellent producer of d-arabitol, exhibiting a remarkable capability of transforming pure glycerol. The study reports among the highest values ever reported for microbial transformation of glycerol into d-arabitol, in terms of arabitol titer, conversion yield, and productivity. Graphical Abstract

Published
2022
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15. Neonates undergoing pyloric stenosis repair are at increased risk of difficult airway management: secondary analysis of the NEonate and Children audiT of Anaesthesia pRactice IN Europe

Author

Breschan, Christian, Likar, Rudolf, Platzer, Manuela, Edelman, Isole, Eger, Johanes, Heschl, Stefan, Messerer, Brigitte, Vittinghof, Maria, Kroess, Ruth, Stichlberger, Martina, Kahn, David, Pirotte, Thierry, Pregardien, Caroline, Veyckemans, Francis, Stevens, France, Berghmans, Johan, Bauters, Annemie, De Baerdemaeker, Luc, De Hert, Stefan, Lapage, Koen, Parashchanka, Aliaksandra, Van Limmen, Jurgen, Wyffels, Piet, Lauweryns, Julie, Najafi, Nadia, Vundelinckx, Joris, Butković, Diana, Sorić, Ivana Kerovec, Kralik, Sandra, Markić, Ana, Azman, Josip, Markic, Josko, Pupacic, Daniela, Frelich, Michal, Reimer, Petr, Urbanec, René, Cajková, Petra, Mixa, Vladimír, Sedláčková, Yvona, Knoppová, Lenka, Zlámalová (neé Květoňová), Alena, Vavřina, Martin, Žurek, Jiří, Hansen, Tom, Afshari, Arash, Bille, Anders Bastholm, Ellekvist, Marguerite, Ilmoja, Mari-Liis, Moor, Reet, Kikas, Reet, Väli, Merle, Kallio, Kariantti, Reponen, Elisa, Suominen, Pertti, Suvanto, Sami, Vähätalo, Raisa, Kokki, Hannu, Kokki, Merja, Harju, Jarkko, Kokkonen, Miia, Vieri, Jenni, Manner, Tuula, Catherine, Amory, Ludot, Hugues, Bert, Dina, Godart, Juliette, Laffargue, Anne, Dupont, Hervé, Urbina, Benjamin, Baujard, Catherine, Roulleau, Philippe, Staiti, Giuseppe, Bordes, Maryline, Gaulain, Karine Nouette, Hamonic, Yann, Semjen, François, Jacqmarcq, Olivier, Lejus-Bourdeau Cécile Magne, Caroline, Petry, Léa, Ros, Lilica, Zang, Aurélien, Bennis, Mehdi, Coustets, Bernard, Fesseau, Rose, Constant, Isabelle, Khalil, Eliane, Sabourdin, Nada, Audren, Noemie, Descarpentries, Thomas, Fabre, Fanny, Legrand, Aurélien, Druot, Emilie, Orliaguet, Gilles, Sabau, Lucie, Uhrig, Lynn, Brière, François de la, Jonckheer, Karin, Mission, Jean-Paul, Scordo, Lucia, Couchepin, Caroline, Dadure, Christophe, De la Arena, Pablo, Hertz, Laurent, Pirat, Philippe, Sola, Chrystelle, Bellon, Myriam, Dahmani, Souhayl, Julien-Marsollier, Florence, Michelet, Daphne, Depret-Donatien, Veronique, Lesage, Anne, Kaufmann, Jost, Laschat, Michael, Wappler, Frank, Becke, Karin, Brunner, Lena, Oppenrieder, Karin, Badelt, Gregor, Hochmuth, Karin, Koller, Bernhard, Reil, Anita, Richter, Sebastian, Fischer, Thomas, Diers, Anja, Schorer, Clemens, Weyland, Andreas, Cohausz, Ruth, Kretz, Franz-Josef, Löffler, Michaela, Wilbs, Markus, Hoehne, Claudia, Ulrici, Johanna, Goeters, Christiane, Flinspach, Armin, Klages, Matthias, Lindau, Simone, Messroghli, Leila, Zacharowski, Kai, Eisner, Christoph, Mueller, Thomas, Richter, Daniel, Schäfer, Melanie, Weigand, Markus, Weiterer, Sebastian, Ochsenreiter, Miriam, Schöler, Michael, Terboven, Tom, Eggemann, Isabel, Haussmann, Sascha, Leister, Nicolas, Menzel, Christoph, Trieschmann, Uwe, Yücetepe, Sirin, Keilig, Susanna, Kranke, Peter, Jelting, Yvonne, Baehner, Torsten, Ellerkmann, Richard, Ghamari, Shahab, Neumann, Claudia, Söhle, Martin, Chloropoulou, Pelagia, Ntritsou, Vagia, Papagiannopoulou, Pinelopi, Garini, Eleana, Karafotia, Afroditi, Mammi, Panagoula, Bali, Evangelia, Iordanidou, Despoina, Malisiova, Anna, Polyzoi, Artemis, Tsiotou, Adelais, Sapi, Erzsebet, Székely, Edgar, Kosik, Nandor, Maráczi, Veronika, Schnur, Janos, Csillag, Judit, Gál, János, Göbl, Gergely, Hauser, Balázs, Petróczy, András, Tövisházi, Gyula, Blain, Stuart, Gallagher, Sarah, Harte, Sinead, Jackson, Mandy, Meehan, Emma, Nawoor, Zeenat, O’Hare, Brendan, Ross, Mark, Lerro, Daniela, Astuto, Marinella, Grasso, Chiara, Scalisi, Rita, Frasacco, Giulia, Lenares, Elena, Leone, Roberto, Grazzini, Maurizia, Minardi, Carmelo, Zadra, Nicola, Cinnella, Gilda, Cotoia, Antonella, Galante, Dario, De Lorenzo, Brita, Kuppers, Beate, Bottazzi, Giulia, Caramelli, Fabio, Mondardini, Maria Cristina, Rossetti, Emanuele, Picardo, Sergio, Vittori, Alessandro, Camporesi, Anna, Izzo, Francesca, Calderini, Edoardo, Colantonio, Laura Brigitta, Finamore, Simona Anna, Porro, Giuliana Anna, Bonfiglio, Rachele, Disma, Nicola, Kotzeva, Svetlana, Mattioli, Girolamo, Micalizzi, Camilla, Montaguti, Alessia, Pistorio, Angela, Guddo, Anna, Neba, Gerald Rogan, Favarato, Moreno, Locatelli, Bruno Guido, Maffioletti, Micol, Sonzogni, Valter, Garra, Rossella, Sammartino, Maria, Sbaraglia, Fabio, Cortegiani, Andrea, Moscarelli, Alessandra, Attanasi, Elena, Tesoro, Simonetta, Agapiti, Cristina, Pinzoni, Francesca, Vezzoli, Cesare, Federico, Bilotta, Barzdina, Arta, Straume, Zane, Zundane, Anda, Lukosiene, Laura, Maraulaite, Irena, Razlevice, Ilona, Schmitz, Bernd, Mifsud, Stephanie, Aehling, Carolin, Allison, Celia, De Boer, Rients, Emal, Dina, Stevens, Markus, Buitenhuis, Marielle, de Graaff, Jurgen, De Liefde, Inge, Machotta, Andreas, Scoones, Gail, Staals, Lonneke, Tomas, Jeremy, Van der Knijff-van Dortmont, Anouk, Veldhuizen, Marianne, Alders, David, Schafrat, Eva, Schreiber, Jan, Vermeulen, Petronella Mari, Hendriks, Mark, Lako, Sandra, Voet-Lindner, Marieke, Pieters, Barbe, Scheffer, Gert-Jan, Tielens, Luc, Absalom, Anthony R., Bergsma, Margot, De Ruiter, Joke, Meier, Sascha, Volkers, Martin, Zweers, Tjerk, Beukers, Anne M., Boer, Christa, Dertinger, Jurgen, Numan, Sandra, Van Zaane, Bas, Boerke, Wenche B., Ekiz, Nil, Stensrud, Kristoffer, Drage, Inger Marie, Isern, Erik Ramon, Bartkowska-Sniatkowska, Alicja, Grzeskowiak, Malgorzata, Juzwa-Sobieraj, Magdalena, Rosada-Kurasińska, Jowita, Baranowski, Artur, Jakubowska, Karina, Lewandowska, Dorota, Mierzewska-Schmidt, Magdalena, Sawicki, Piotr, Urban-Lechowicz, Magdalena, Przemyslaw, Pomianek, Zielinska, Marzena, Leal, Teresa, Soares, Maria, Pina, Pedro, Pinho, Sílvia, Patuleia, Maria Domingas, Esteves, Catarina Cruz, Salgado, Helena, Santos, Maria João, Badeti, Rodica, Cindea, Iulia, Oana, Loredana, Gurita, Adriana, Ilie, Luminita, Mocioiu, Gabriel, Tabacaru, Radu, Trante, Irina, Munteanu, Valentin, Morariu, Mihai, Nyíri, Emese, Budic, Ivana, Marjanovic, Vesna, Drašković, Biljana, Pandurov, Marina, Ilic, Jordanka, Mandras, Ana, Rados, Zdenka, Stankovic, Nikola, Suica, Maja, Vasiljevic, Sladjana, Knezevic, Mirjana, Milojevic, Irina, Petrov, Ivana, Racic, Selena Puric, Simic, Dusica, Simic, Irena, Stevic, Marija, Vulicevic, Irena, Bystrica, Banská, Cabanová, Barbora, Hanula, Miloslav, Berger, Jelena, Janjatovic, Darja, Štupnik, Špela Pirtovšek, Méndez, Dolores, Pino, Gema, Rubio, Paloma, Izquierdo, Alberto, López, Silvia, Serrano, Cristina González, Cebrián, Jesús, Peleteiro, Ana, Del Rey de Diego, Pilar, García, Ernesto Martínez, Tormo de las Heras, Carolina, Montero, Pablo Troncoso, Arbona, Celia, Artés, David, Chamizo, Alicia, Serrano, Silvia, Comas, Montserrat Suarez, Escribá, Francisco, Auli, Cristina, Pardo, Osvaldo Pérez, Biddle, Natalia Sierra, Castaño, Ceferina Suárez, Villalobos Rico, María Isabel, Muñoz, Susana Manrique, Martínez, Irene García, Estruch, Nuria Montferrer, Ortíz, Elena Vilardell, Poves-Álvarez, Rodrigo, Kohn, Ivan, Lindestam, Ulf, Reinhard, Jarl, Castellheim, Albert, Sandström, Kerstin, Bengt, Sporre, Dörenberg, Rainer, Frykholm, Peter, Garcia, Maria, Kvarnström, Ann, Pontén, Emma, Bruelisauer, Thomas, Erdoes, Gabor, Kaiser, Heiko, Marchon, Mathias, Riva, Thomas, Seiler, Stefan, Bögli, Yann, Dolci, Mirko, Marcucci, Carine, Habre, Walid, Pichon, Isabelle, Vutskits, Laszlo, Casutt, Mattias, Hölzle, Martin, Hurni, Thomas, Jöhr, Martin, Malär, Anna-Ursina, Mauch, Jacqueline, Erb, Thomas, Oeinck, Karin, Akin, Mine, Keskin, Gulsen, Senayli, Yesim, Kaya, Guner, Kendigelen, Pinar, Tutuncu, Ayse Çiğdem, Hatipoğlu, Zehra, Özcengiz, Dilek, Erdost, Hale Aksu, Öçmen, Elvan, Olguner, Çimen, Ayanoglu, Hilmi, Dincer, Pelin Corman, Umuroglu, Tumay, Azizoglu, Mustafa, Birbiçer, Handan, Doruk, Nurcan, Sagun, Aslı, Baris, Sibel, Dmytriiev, Dmytro, Kuchi, Sridevi, Masip, Nuria, Brooks, Peter, Hare, Alison, Ahmad, Nargis, Casey, Michelle, De Silva, Sam, Dobby, Nadine, Krishnan, Prakash, Sogbodjor, L. Amaki, Walker, Ellie, Walker, Suellen, King, Stephanie, Nicholson, Katy, Quinney, Michelle, Stevens, Paul, Blevin, Andrew, Giombini, Mariangela, Goonasekera, Chulananda, Adil, Sadia, Bew, Stephanie, Bodlani, Carol, Gilpin, Dan, Jinks, Stephanie, Malarkkan, Nalini, Miskovic, Alice, Pad, Rebecca, Barry, Juliet Wolfe, Abbott, Joy, Armstrong, James, Cooper, Natalie, Crate, Lindsay, Emery, John, James, Kathryn, King, Hannah, Martin, Paul, Catenacci, Stefano Scalia, Bomont, Rob, Smith, Paul, Mele, Sara, Verzelloni, Alessandra, Dix, Philippa, Bell, Graham, Gordeva, Elena, McKee, Lesley, Ngan, Esther, Scheffczik, Jutta, Tan, Li-En, Worrall, Mark, Cassar, Carmel, Goddard, Kevin, Barlow, Victoria, Oshan, Vimmi, Shah, Khairi, Bell, Sarah, Daniels, Lisa, Gandhi, Monica, Pachter, David, Perry, Chris, Robertson, Andrew, Scott, Carmen, Waring, Lynne, Barnes, David, Childs, Sophie, Norman, Joanne, Sunderland, Robin, Julia, Dowell, Prisca, Feijten, Pierre, Harlet, Sarah, Herbineaux, Brigitte, Leva, Benoît, Plichon, Katalin, Virág, Engelhardt, Thomas, Hansen, Tom G., de Graaff, Jurgen C., and Virag, Katalin

Published
2022
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17. Difficult tracheal intubation in neonates and infants. NEonate and Children audiT of Anaesthesia pRactice IN Europe (NECTARINE): a prospective European multicentre observational study

Author

Breschan, Christian, Likar, Rudolf, Platzer, Manuela, Edelman, Isole, Eger, Johanes, Heschl, Stefan, Messerer, Brigitte, Vittinghof, Maria, Kroess, Ruth, Stichlberger, Martina, Kahn, David, Pirotte, Thierry, Pregardien, Caroline, Veyckemans, Francis, Stevens, France, Berghmans, Johan, Bauters, Annemie, De Baerdemaeker, Luc, De Hert, Stefan, Lapage, Koen, Parashchanka, Aliaksandra, Van Limmen, Jurgen, Wyffels, Piet, Lauweryns, Julie, Najafi, Nadia, Vundelinckx, Joris, Butković, Diana, Kerovec Sorić, Ivana, Kralik, Sandra, Markić, Ana, Azman, Josip, Markic, Josko, Pupacic, Daniela, Frelich, Michal, Reimer, Petr, Urbanec, René, Cajková, Petra, Mixa, Vladimír, Sedláčková, Yvona, Knoppová, Lenka, Zlámalová (neé Květoňová), Alena, Vavřina, Martin, Žurek, Jiří, Hansen, Tom, Afshari, Arash, Bille, Anders Bastholm, Ellekvist, Marguerite, Ilmoja, Mari-Liis, Moor, Reet, Kikas, Reet, Väli, Merle, Kallio, Kariantti, Reponen, Elisa, Suominen, Pertti, Suvanto, Sami, Vähätalo, Raisa, Kokki, Hannu, Kokki, Merja, Harju, Jarkko, Kokkonen, Miia, Vieri, Jenni, Manner, Tuula, Amory, Catherine, Ludot, Hugues, Bert, Dina, Godart, Juliette, Laffargue, Anne, Dupont, Hervé, Urbina, Benjamin, Baujard, Catherine, Roulleau, Philippe, Staiti, Giuseppe, Bordes, Maryline, Nouette Gaulain, Karine, Hamonic, Yann, Semjen, François, Jacqmarcq, Olivier, Lejus-Bourdeau, Caroline, Magne, Cécile, Petry, Léa, Ros, Lilica, Zang, Aurélien, Bennis, Mehdi, Coustets, Bernard, Fesseau, Rose, Constant, Isabelle, Khalil, Eliane, Sabourdin, Nada, Audren, Noemie, Descarpentries, Thomas, Fabre, Fanny, Legrand, Aurélien, Druot, Emilie, Orliaguet, Gilles, Sabau, Lucie, Uhrig, Lynn, de la Brière, François, Jonckheer, Karin, Mission, Jean-Paul, Scordo, Lucia, Couchepin, Caroline, Dadure, Christophe, De la Arena, Pablo, Hertz, Laurent, Pirat, Philippe, Sola, Chrystelle, Bellon, Myriam, Dahmani, Souhayl, Julien-Marsollier, Florence, Michelet, Daphne, Depret-Donatien, Veronique, Lesage, Anne, Kaufmann, Jost, Laschat, Michael, Wappler, Frank, Becke, Karin, Brunner, Lena, Oppenrieder, Karin, Badelt, Gregor, Hochmuth, Karin, Koller, Bernhard, Reil, Anita, Richter, Sebastian, Fischer, Thomas, Diers, Anja, Schorer, Clemens, Weyland, Andreas, Cohausz, Ruth, Kretz, Franz-Josef, Löffler, Michaela, Wilbs, Markus, Hoehne, Claudia, Ulrici, Johanna, Goeters, Christiane, Flinspach, Armin, Klages, Matthias, Lindau, Simone, Messroghli, Leila, Zacharowski, Kai, Eisner, Christoph, Mueller, Thomas, Richter, Daniel, Schäfer, Melanie, Weigand, Markus, Weiterer, Sebastian, Ochsenreiter, Miriam, Schöler, Michael, Terboven, Tom, Eggemann, Isabel, Haussmann, Sascha, Leister, Nicolas, Menzel, Christoph, Trieschmann, Uwe, Yücetepe, Sirin, Keilig, Susanna, Kranke, Peter, Jelting, Yvonne, Baehner, Torsten, Ellerkmann, Richard, Ghamari, Shahab, Neumann, Claudia, Söhle, Martin, Chloropoulou, Pelagia, Ntritsou, Vagia, Papagiannopoulou, Pinelopi, Garini, Eleana, Karafotia, Afroditi, Mammi, Panagoula, Bali, Evangelia, Iordanidou, Despoina, Malisiova, Anna, Polyzoi, Artemis, Tsiotou, Adelais, Sapi, Erzsebet, Székely, Edgar, Kosik, Nandor, Maráczi, Veronika, Schnur, Janos, Csillag, Judit, Gál, János, Göbl, Gergely, Hauser, Balázs, Petróczy, András, Tövisházi, Gyula, Blain, Stuart, Gallagher, Sarah, Harte, Sinead, Jackson, Mandy, Meehan, Emma, Nawoor, Zeenat, O’Hare, Brendan, Ross, Mark, Lerro, Daniela, Astuto, Marinella, Grasso, Chiara, Scalisi, Rita, Frasacco, Giulia, Lenares, Elena, Leone, Roberto, Grazzini, Maurizia, Minardi, Carmelo, Zadra, Nicola, Cinnella, Gilda, Cotoia, Antonella, Galante, Dario, De Lorenzo, Brita, Kuppers, Beate, Bottazzi, Giulia, Caramelli, Fabio, Mondardini, Maria Cristina, Rossetti, Emanuele, Picardo, Sergio, Vittori, Alessandro, Camporesi, Anna, Wolfler, Andrea, Calderini, Edoardo, Colantonio, Laura Brigitta, Finamore, Simona Anna, Porro, Giuliana Anna, Bonfiglio, Rachele, Disma, Nicola, Kotzeva, Svetlana, Mameli, Leila, Mattioli, Girolamo, Micalizzi, Camilla, Montaguti, Alessia, Pistorio, Angela, Zanaboni, Clelia, Guddo, Anna, Neba, Gerald Rogan, Favarato, Moreno, Locatelli, Bruno Guido, Maffioletti, Micol, Sonzogni, Valter, Garra, Rossella, Sammartino, Maria, Sbaraglia, Fabio, Cortegiani, Andrea, Moscarelli, Alessandra, Attanasi, Elena, Tesoro, Simonetta, Agapiti, Cristina, Pinzoni, Francesca, Vezzoli, Cesare, Bilotta, Federico, Barzdina, Arta, Straume, Zane, Zundane, Anda, Lukosiene, Laura, Maraulaite, Irena, Razlevice, Ilona, Schmitz, Bernd, Mifsud, Stephanie, Aehling, Carolin, Allison, Celia, De Boer, Rients, Emal, Dina, Stevens, Markus, Buitenhuis, Marielle, de Graaff, Jurgen, De Liefde, Inge, Machotta, Andreas, Scoones, Gail, Staals, Lonneke, Tomas, Jeremy, Van der Knijff-van Dortmont, Anouk, Veldhuizen, Marianne, Alders, David, Buhre, Wolfgang, Schafrat, Eva, Schreiber, Jan, Vermeulen, Petronella Mari, Hendriks, Mark, Lako, Sandra, Voet-Lindner, Marieke, Pieters, Barbe, Scheffer, Gert-Jan, Tielens, Luc, Absalom, Anthony R., Bergsma, Margot, De Ruiter, Joke, Meier, Sascha, Volkers, Martin, Zweers, Tjerk, Beukers, Anne M., Boer, Christa, Dertinger, Jurgen, Numan, Sandra, Van Zaane, Bas, Boerke, Wenche B., Ekiz, Nil, Stensrud, Kristoffer, Drage, Inger Marie, Isern, Erik Ramon, Bartkowska-Sniatkowska, Alicja, Grzeskowiak, Malgorzata, Juzwa-Sobieraj, Magdalena, Rosada-Kurasińska, Jowita, Baranowski, Artur, Jakubowska, Karina, Lewandowska, Dorota, Mierzewska-Schmidt, Magdalena, Sawicki, Piotr, Urban-Lechowicz, Magdalena, Przemyslaw, Pomianek, Zielinska, Marzena, Leal, Teresa, Soares, Maria, Pina, Pedro, Pinho, Sílvia, Patuleia, Maria Domingas, Esteves, Catarina Cruz, Salgado, Helena, Santos, Maria João, Badeti, Rodica, Cindea, Iulia, Oana, Loredana, Gurita, Adriana, Ilie, Luminita, Mocioiu, Gabriel, Tabacaru, Radu, Trante, Irina, Munteanu, Valentin, Morariu, Mihai, Nyíri, Emese, Budic, Ivana, Marjanovic, Vesna, Drašković, Biljana, Pandurov, Marina, Ilic, Jordanka, Mandras, Ana, Rados, Zdenka, Stankovic, Nikola, Suica, Maja, Vasiljevic, Sladjana, Knezevic, Mirjana, Milojevic, Irina, Petrov, Ivana, Puric Racic, Selena, Simic, Dusica, Simic, Irena, Stevic, Marija, Vulicevic, Irena, Cabanová, Barbora, Hanula, Miloslav, Berger, Jelena, Janjatovic, Darja, Pirtovšek Štupnik, Špela, Méndez, Dolores, Pino, Gema, Rubio, Paloma, Izquierdo, Alberto, López, Silvia, González Serrano, Cristina, Cebrián, Jesús, Peleteiro, Ana, Del Rey de Diego, Pilar, Martínez García, Ernesto, Tormo de las Heras, Carolina, Troncoso Montero, Pablo, Arbona, Celia, Artés, David, Chamizo, Alicia, Serrano, Silvia, Suarez Comas, Montserrat, Escribá, Francisco, Auli, Cristina, Pérez Pardo, Osvaldo, Sierra Biddle, Natalia, Suárez Castaño, Ceferina, Villalobos Rico, María Isabel, Manrique Muñoz, Susana, García Martínez, Irene, Montferrer Estruch, Nuria, Vilardell Ortíz, Elena, Poves-Álvarez, Rodrigo, Kohn, Ivan, Lindestam, Ulf, Reinhard, Jarl, Castellheim, Albert, Sandström, Kerstin, Bengt, Sporre, Dörenberg, Rainer, Frykholm, Peter, Garcia, Maria, Kvarnström, Ann, Pontén, Emma, Bruelisauer, Thomas, Erdoes, Gabor, Kaiser, Heiko, Marchon, Mathias, Riva, Thomas, Seiler, Stefan, Bögli, Yann, Dolci, Mirko, Marcucci, Carine, Habre, Walid, Pichon, Isabelle, Vutskits, Laszlo, Casutt, Mattias, Hölzle, Martin, Hurni, Thomas, Jöhr, Martin, Malär, Anna-Ursina, Mauch, Jacqueline, Erb, Thomas, Oeinck, Karin, Akin, Mine, Keskin, Gulsen, Senayli, Yesim, Kaya, Guner, Kendigelen, Pinar, Tutuncu, Ayse Çiğdem, Hatipoğlu, Zehra, Özcengiz, Dilek, Erdost, Hale Aksu, Öçmen, Elvan, Olguner, Çimen, Ayanoglu, Hilmi, Dincer, Pelin Corman, Umuroglu, Tumay, Azizoglu, Mustafa, Birbiçer, Handan, Doruk, Nurcan, Sagun, Aslı, Baris, Sibel, Dmytriiev, Dmytro, Kuchi, Sridevi, Masip, Nuria, Brooks, Peter, Hare, Alison, Ahmad, Nargis, Casey, Michelle, De Silva, Sam, Dobby, Nadine, Krishnan, Prakash, Sogbodjor, L. Amaki, Walker, Ellie, Walker, Suellen, King, Stephanie, Nicholson, Katy, Quinney, Michelle, Stevens, Paul, Blevin, Andrew, Giombini, Mariangela, Goonasekera, Chulananda, Adil, Sadia, Bew, Stephanie, Bodlani, Carol, Gilpin, Dan, Jinks, Stephanie, Malarkkan, Nalini, Miskovic, Alice, Pad, Rebecca, Wolfe Barry, Juliet, Abbott, Joy, Armstrong, James, Cooper, Natalie, Crate, Lindsay, Emery, John, James, Kathryn, King, Hannah, Martin, Paul, Scalia Catenacci, Stefano, Bomont, Rob, Smith, Paul, Mele, Sara, Verzelloni, Alessandra, Dix, Philippa, Bell, Graham, Gordeva, Elena, McKee, Lesley, Ngan, Esther, Scheffczik, Jutta, Tan, Li-En, Worrall, Mark, Cassar, Carmel, Goddard, Kevin, Barlow, Victoria, Oshan, Vimmi, Shah, Khairi, Bell, Sarah, Daniels, Lisa, Gandhi, Monica, Pachter, David, Perry, Chris, Robertson, Andrew, Scott, Carmen, Waring, Lynne, Barnes, David, Childs, Sophie, Norman, Joanne, Sunderland, Robin, Julia, Dowell, Prisca, Feijten, Pierre, Harlet, Sarah, Herbineaux, Brigitte, Leva, Benoît, Plichon, Katalin, Virág, Virag, Katalin, and Engelhardt, Thomas

Published
2021
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18. Morbidity and mortality after anaesthesia in early life: results of the European prospective multicentre observational study, neonate and children audit of anaesthesia practice in Europe (NECTARINE)

Author

Breschan, Christian, Likar, Rudolf, Platzer, Manuela, Edelman, Isole, Eger, Johanes, Heschl, Stefan, Messerer, Brigitte, Vittinghof, Maria, Kroess, Ruth, Stichlberger, Martina, Kahn, David, Pirotte, Thierry, Pregardien, Caroline, Veyckemans, Francis, Stevens, France, Berghmans, Johan, Bauters, Annemie, De Baerdemaeker, Luc, De Hert, Stefan, Lapage, Koen, Parashchanka, Aliaksandra, Van Limmen, Jurgen, Wyffels, Piet, Lauweryns, Julie, Najafi, Nadia, Vundelinckx, Joris, Butković, Diana, Sorić, Ivana Kerovec, Kralik, Sandra, Markić, Ana, Azman, Josip, Markic, Josko, Pupacic, Daniela, Frelich, Michal, Reimer, Petr, Urbanec, Rene, Cajkova, Petra, Mixa, Vladimir, Sedlačkova, Yvona, Knoppova, Lenka, Zlamalova (nee Květoňova), Alena, Vavřina, Martin, Žurek, Jiři, Hansen, Tom, Afshari, Arash, Bille, Anders B., Ellekvist, Marguerite, Ilmoja, Mari-Liis, Moor, Reet, Kikas, Reet, Vali, Merle, Kallio, Kariantti, Reponen, Elisa, Suominen, Pertti, Suvanto, Sami, Vahatalo, Raisa, Kokki, Hannu, Kokki, Merja, Harju, Jarkko, Kokkonen, Miia, Vieri, Jenni, Manner, Tuula, Amory, Catherine, Ludot, Hugues, Bert, Dina, Godart, Juliette, Laffargue, Anne, Dupont, Herve, Urbina, Benjamin, Baujard, Catherine, Roulleau, Philippe, Staiti, Giuseppe, Bordes, Maryline, Gaulain, Karine Nouette, Hamonic, Yann, Semjen, Francois, Jacqmarcq, Olivier, Lejus-Bourdeau, Caroline, Magne, Cecile, Petry, Lea, Ros, Lilica, Zang, Aurelien, Bennis, Mehdi, Coustets, Bernard, Fesseau, Rose, Constant, Isabelle, Khalil, Eliane, Sabourdin, Nada, Audren, Noemie, Descarpentries, Thomas, Fabre, Fanny, Legrand, Aurelien, Druot, Emilie, Orliaguet, Gilles, Sabau, Lucie, Uhrig, Lynn, de la Briere, Francois, Jonckheer, Karin, Mission, Jean-Paul, Scordo, Lucia, Couchepin, Caroline, Dadure, Christophe, De la Arena, Pablo, Hertz, Laurent, Pirat, Philippe, Sola, Chrystelle, Bellon, Myriam, Dahmani, Souhayl, Julien-Marsollier, Florence, Michelet, Daphne, Depret-Donatien, Veronique, Lesage, Anne, Kaufmann, Jost, Laschat, Michael, Wappler, Frank, Becke, Karin, Brunner, Lena, Oppenrieder, Karin, Badelt, Gregor, Hochmuth, Karin, Koller, Bernhard, Reil, Anita, Richter, Sebastian, Fischer, Thomas, Diers, Anja, Schorer, Clemens, Weyland, Andreas, Cohausz, Ruth, Kretz, Franz-Josef, Loffler, Michaela, Wilbs, Markus, Hoehne, Claudia, Ulrici, Johanna, Goeters, Christiane, Flinspach, Armin, Klages, Matthias, Lindau, Simone, Messroghli, Leila, Zacharowski, Kai, Eisner, Christoph, Mueller, Thomas, Richter, Daniel, Schafer, Melanie, Weigand, Markus, Weiterer, Sebastian, Ochsenreiter, Miriam, Scholer, Michael, Terboven, Tom, Eggemann, Isabel, Haussmann, Sascha, Leister, Nicolas, Menzel, Christoph, Trieschmann, Uwe, Yucetepe, Sirin, Keilig, Susanna, Kranke, Peter, Jelting, Yvonne, Baehner, Torsten, Ellerkmann, Richard, Ghamari, Shahab, Neumann, Claudia, Sohle, Martin, Chloropoulou, Pelagia, Ntritsou, Vagia, Papagiannopoulou, Pinelopi, Garini, Eleana, Karafotia, Afroditi, Mammi, Panagoula, Bali, Evangelia, Iordanidou, Despoina, Malisiova, Anna, Polyzoi, Artemis, Tsiotou, Adelais, Sapi, Erzsebet, Szekely, Edgar, Kosik, Nandor, Maraczi, Veronika, Schnur, Janos, Csillag, Judit, Gal, Janos, Gobl, Gergely, Hauser, Balazs, Petroczy, Andras, Tovishazi, Gyula, Blain, Stuart, Gallagher, Sarah, Harte, Sinead, Jackson, Mandy, Meehan, Emma, Nawoor, Zeenat, O’Hare, Brendan, Ross, Mark, Lerro, Daniela, Astuto, Marinella, Grasso, Chiara, Scalisi, Rita, Frasacco, Giulia, Lenares, Elena, Leone, Roberto, Grazzini, Maurizia, Minardi, Carmelo, Zadra, Nicola, Cinnella, Gilda, Cotoia, Antonella, Galante, Dario, De Lorenzo, Brita, Kuppers, Beate, Bottazzi, Giulia, Caramelli, Fabio, Mondardini, Maria C., Rossetti, Emanuele, Picardo, Sergio, Vittori, Alessandro, Camporesi, Anna, Wolfler, Andrea, Calderini, Edoardo, Colantonio, Laura B., Finamore, Simona A., Porro, Giuliana A., Bonfiglio, Rachele, Disma, Nicola, Kotzeva, Svetlana, Mameli, Leila, Mattioli, Girolamo, Micalizzi, Camilla, Montaguti, Alessia, Pistorio, Angela, Zanaboni, Clelia, Guddo, Anna, Neba, Gerald R., Favarato, Moreno, Locatelli, Bruno G., Maffioletti, Micol, Sonzogni, Valter, Garra, Rossella, Sammartino, Maria, Sbaraglia, Fabio, Cortegiani, Andrea, Moscarelli, Alessandra, Attanasi, Elena, Tesoro, Simonetta, Agapiti, Cristina, Pinzoni, Francesca, Vezzoli, Cesare, Bilotta, Federico, Barzdina, Arta, Straume, Zane, Zundane, Anda, Lukosiene, Laura, Maraulaite, Irena, Razlevice, Ilona, Schmitz, Bernd, Mifsud, Stephanie, Aehling, Carolin, Allison, Celia, De Boer, Rients, Emal, Dina, Stevens, Markus, Buitenhuis, Marielle, de Graaff, Jurgen, De Liefde, Inge, Machotta, Andreas, Scoones, Gail, Staals, Lonneke, Tomas, Jeremy, Van der, Anouk, Dortmont, Knijff-van, Veldhuizen, Marianne, Alders, David, Buhre, Wolfgang, Schafrat, Eva, Schreiber, Jan, Vermeulen, Petronella M., Hendriks, Mark, Lako, Sandra, Voet-Lindner, Marieke, Pieters, Barbe, Scheffer, Gert-Jan, Tielens, Luc, Absalom, Anthony R., Bergsma, Margot, De Ruiter, Joke, Meier, Sascha, Volkers, Martin, Zweers, Tjerk, Beukers, Anne M., Boer, Christa, Dertinger, Jurgen, Numan, Sandra, Van Zaane, Bas, Boerke, Wenche B., Ekiz, Nil, Stensrud, Kristoffer, Drage, Inger M., Isern, Erik R., Bartkowska-Sniatkowska, Alicja, Grzeskowiak, Malgorzata, Juzwa-Sobieraj, Magdalena, Rosada-Kurasińska, Jowita, Baranowski, Artur, Jakubowska, Karina, Lewandowska, Dorota, Mierzewska-Schmidt, Magdalena, Sawicki, Piotr, Urban-Lechowicz, Magdalena, Przemyslaw, Pomianek, Zielinska, Marzena, Leal, Teresa, Soares, Maria, Pina, Pedro, Pinho, Silvia, Patuleia, Maria Domingas, Esteves, Catarina C., Salgado, Helena, Santos, Maria J., Badeti, Rodica, Cindea, Iulia, Oana, Loredana, Gurita, Adriana, Ilie, Luminita, Mocioiu, Gabriel, Tabacaru, Radu, Trante, Irina, Munteanu, Valentin, Morariu, Mihai, Nyiri, Emese, Budic, Ivana, Marjanovic, Vesna, Drašković, Biljana, Pandurov, Marina, Ilic, Jordanka, Mandras, Ana, Rados, Zdenka, Stankovic, Nikola, Suica, Maja, Vasiljevic, Sladjana, Knezevic, Mirjana, Milojevic, Irina, Petrov, Ivana, Racic, Selena Puric, Simic, Dusica, Simic, Irena, Stevic, Marija, Vulicevic, Irena, Cabanova, Barbora, Hanula, Miloslav, Berger, Jelena, Janjatovic, Darja, Štupnik, Špela P., Kohn, Ivan, Lindestam, Ulf, Reinhard, Jarl, Castellheim, Albert, Sandstrom, Kerstin, Bengt, Sporre, Dorenberg, Rainer, Frykholm, Peter, Garcia, Maria, Kvarnstrom, Ann, Ponten, Emma, Bruelisauer, Thomas, Erdoes, Gabor, Kaiser, Heiko, Marchon, Mathias, Riva, Thomas, Seiler, Stefan, Bogli, Yann, Dolci, Mirko, Marcucci, Carine, Habre, Walid, Pichon, Isabelle, Vutskits, Laszlo, Casutt, Mattias, Holzle, Martin, Hurni, Thomas, Johr, Martin, Anna-Ursina, Malar, Mauch, Jacqueline, Erb, Thomas, Oeinck, Karin, Akin, Mine, Keskin, Gulsen, Senayli, Yesim, Kaya, Guner, Kendigelen, Pinar, Tutuncu, Ayse C., Hatipoğlu, Zehra, Ozcengiz, Dilek, Erdost, Hale Aksu, Ocmen, Elvan, Olguner, Cimen, Ayanoglu, Hilmi, Dincer, Pelin C., Umuroglu, Tumay, Azizoglu, Mustafa, Birbicer, Handan, Doruk, Nurcan, Sagun, Aslı, Baris, Sibel, Dmytriiev, Dmytro, Kuchi, Sridevi, Masip, Nuria, Brooks, Peter, Hare, Alison, Ahmad, Nargis, Casey, Michelle, De Silva, Sam, Dobby, Nadine, Krishnan, Prakash, Sogbodjor, L. Amaki, Walker, Ellie, Walker, Suellen, King, Stephanie, Nicholson, Katy, Quinney, Michelle, Stevens, Paul, Blevin, Andrew, Giombini, Mariangela, Goonasekera, Chulananda, Adil, Sadia, Bew, Stephanie, Bodlani, Carol, Gilpin, Dan, Jinks, Stephanie, Malarkkan, Nalini, Miskovic, Alice, Pad, Rebecca, Barry, Juliet W., Abbott, Joy, Armstrong, James, Cooper, Natalie, Crate, Lindsay, Emery, John, James, Kathryn, King, Hannah, Martin, Paul, Catenacci, Stefano S., Bomont, Rob, Smith, Paul, Mele, Sara, Verzelloni, Alessandra, Dix, Philippa, Bell, Graham, Gordeva, Elena, McKee, Lesley, Ngan, Esther, Scheffczik, Jutta, Tan, Li-En, Worrall, Mark, Cassar, Carmel, Goddard, Kevin, Barlow, Victoria, Oshan, Vimmi, Shah, Khairi, Bell, Sarah, Daniels, Lisa, Gandhi, Monica, Pachter, David, Perry, Chris, Robertson, Andrew, Scott, Carmen, Waring, Lynne, Barnes, David, Childs, Sophie, Norman, Joanne, Sunderland, Robin, Virag, Katalin, Hansen, Tom G., Harlet, Pierre, Walker, Suellen M., de Graaff, Jurgen C., and Engelhardt, Thomas

Published
2021
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21. Tracing geographical origin of Lambrusco PDO wines using isotope ratios of oxygen, boron, strontium, lead and their elemental concentration

Author

Lisa Lancellotti, Simona Sighinolfi, Alessandro Ulrici, Laura Maletti, Caterina Durante, Andrea Marchetti, and Lorenzo Tassi

Subjects
Isotopic ratios, Lambrusco PDO wines, Geographic traceability, MC-ICP/MS, Nutrition. Foods and food supply, TX341-641, Food processing and manufacture, TP368-456
Abstract

Wine identification is one of the most important aspects in the classification of wines and consumer protection. In particular, assuring wine authenticity is a crucial issue on which researchers are focusing on. This study aims to evaluate the feasibility of using chemical (B, Pb and Sr concentration) and isotopic compositions (δ11B, 20yPb/20xPb, 87Sr/86Sr and δ18O) of wine samples to trace their geographic origins. Different PDO Lambrusco wines coming from a confined area of northern Italy were analyzed and all the isotopic systematics were monitored by using a multi collector inductively coupled plasma mass spectrometer (MC-ICP/MS).The obtained results showed that boron isotope ratio measurements led to a satisfactory degree of accuracy and precision (measured value, n = 28, 11B/10B of NIST SRM 951a equal to 4.04343 ± 0.00178, (u = 2s) with a certified value of 4.04362 ± 0.00136 (u = 2s). Furthermore, in the present study, it has been possible to highlight significant differences among samples by means of one-way analysis of variance (ANOVA) and post hoc Tukey-Kramer test. Finally, Principal Component Analysis (PCA) was also carried out in order to evaluate to which extent the different PDOs can be distinguished from each other, taking into account the whole set of geographical origin descriptors. Although δ11B provided more sensitive information, the obtained results highlighted the important to consider the synergistic combination of all the investigated parameters to trace the different samples and the need to combine the obtained values with the same parameters evaluated in the soil, water and fertilizer as well.

Published
2021
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24. Dental-dedicated MRI, a novel approach for dentomaxillofacial diagnostic imaging: technical specifications and feasibility

Author

Greiser, Andreas, primary, Christensen, Jennifer, additional, Fuglsig, João M C S, additional, Johannsen, Katrine M, additional, Nixdorf, Donald R, additional, Burzan, Kim, additional, Lauer, Lars, additional, Krueger, Gunnar, additional, Hayes, Carmel, additional, Kettless, Karen, additional, Ulrici, Johannes, additional, and Spin-Neto, Rubens, additional

Published
2023
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25. Multi-target prediction of wheat flour quality parameters with near infrared spectroscopy

Author

Sylvio Barbon Junior, Saulo Martielo Mastelini, Ana Paula A.C. Barbon, Douglas Fernandes Barbin, Rosalba Calvini, Jessica Fernandes Lopes, and Alessandro Ulrici

Subjects
Random forest, Support Vector Machine, Near-infrared spectroscopy, Machine learning, MTRS, DSTARS, Agriculture (General), S1-972, Information technology, T58.5-58.64
Abstract

Near Infrared (NIR) spectroscopy is an analytical technology widely used for the non-destructive characterisation of organic samples, considering both qualitative and quantitative attributes. In the present study, the combination of Multi-target (MT) prediction approaches and Machine Learning algorithms has been evaluated as an effective strategy to improve prediction performances of NIR data from wheat flour samples. Three different Multi-target approaches have been tested: Multi-target Regressor Stacking (MTRS), Ensemble of Regressor Chains (ERC) and Deep Structure for Tracking Asynchronous Regressor Stack (DSTARS). Each one of these techniques has been tested with different regression methods: Support Vector Machine (SVM), Random Forest (RF) and Linear Regression (LR), on a dataset composed of NIR spectra of bread wheat flours for the prediction of quality-related parameters. By combining all MT techniques and predictors, we obtained an improvement up to 7% in predictive performance, compared with the corresponding Single-target (ST) approaches. The results support the potential advantage of MT techniques over ST techniques for analysing NIR spectra.

Published
2020
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26. A transnational cooperation for sustainable use and management of non-native trees in urban, peri-urban and forest ecosystems in the Alpine region (ALPTREES)

Author

Katharina Lapin, Anja Bindewald, Florian Kraxner, Aleksander Marinšek, Nicola La Porta, Reneema Hazarika, Debojyoti Chakraborty, Janine Oettel, Frederic Berger, Patricia Detry, Gordana Kolesaric, Darja Baric, Sonia Abluton, Giovanna Ulrici, Isabel Georges, Karl Manfred Schweinzer, and Silvio Schüler

Subjects
climate change, non-native trees, alpine space, st, Science
Abstract

The expected benefits and potential risks of non-native tree species (NNT) to European geographic regions have polarized the opinions of experts and citizens. Benefits include climate change (CC) mitigation and adaptation, contributions to bioeconomy, urban and peri-urban green infrastructure and mitigation of natural hazards. However, NNT may become invasive and thus may pose risks to native biodiversity, ecosystem functioning or socio-economy. In critical and vulnerable ecosystems such as the Alpine Space (AS), such risks and benefits must be carefully considered before management decisions are made. Experiences in the management of NNT in urban areas, peri-urban, rural territories and forests are often region- or city-specific and rarely shared. Given the challenges in NNT management with respect to both benefits and risks, an European transnational approach is needed to qualify the role of NNT in future AS ecosystems. The objective is to provide a transnational strategy for a responsible use and sustainable management of NNT in the AS with the help of an integrated Decision Support System. The project fits within the context of national and regional site-derived policy aiming at protecting and enhancing biodiversity to ensure ecological connectivity and cultural resources while maintaining a high level of resilience and ecosystem services across the AS. Implementation activities of the ALPTREES project includedeveloping a comprehensive database on NNT,projecting the current and potential distribution of NNT in the AS under CC scenariosdetermining their invasive potential andanalyzing the different ecosystem services provided by NNT to assess the tradeoffs between risks and benefits.ALPTREES will formulate management recommendations for NNT under different climate and economic scenarios based on experience from sample plots combined with model projections, citizen science, and multiple stakeholder meetings. With the help of policy briefs, a handbook of lessons learned, transnational pilot actions for best management practices, and an inter-active online Decision Support System a close stakeholder interaction and -benefit will be ensured Another innovative output of the project is the Open ALPTREES Knowledge Hub, that will support the transnational and interdisciplinary knowledge transfer.

Published
2020
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27. Multivariate Analysis in Microbiome Description: Correlation of Human Gut Protein Degraders, Metabolites, and Predicted Metabolic Functions

Author

Stefano Raimondi, Rosalba Calvini, Francesco Candeliere, Alan Leonardi, Alessandro Ulrici, Maddalena Rossi, and Alberto Amaretti

Subjects
gut microbiota, metagenomics, function prediction, protein fermentation, data fusion, ASCA, Microbiology, QR1-502
Abstract

Protein catabolism by intestinal bacteria is infamous for releasing many harmful compounds, negatively affecting the health status, both locally and systemically. In a previous study, we enriched in protein degraders the fecal microbiota of five subjects, utilizing a medium containing protein and peptides as sole fermentable substrates and we monitored their evolution by 16S rRNA gene profiling. In the present study, we fused the microbiome data and the data obtained by the analysis of the volatile organic compounds (VOCs) in the headspace of the cultures. Then, we utilized ANOVA simultaneous component analysis (ASCA) to establish a relationship between metabolites and bacteria. In particular, ASCA allowed to separately assess the effect of subject, time, inoculum concentration, and their binary interactions on both microbiome and volatilome data. All the ASCA submodels pointed out a consistent association between indole and Escherichia–Shigella, and the relationship of butyric, 3-methyl butanoic, and benzenepropanoic acids with some bacterial taxa that were major determinants of cultures at 6 h, such as Lachnoclostridiaceae (Lachnoclostridium), Clostridiaceae (Clostridium sensu stricto), and Sutterellaceae (Sutterella and Parasutterella). The metagenome reconstruction with PICRUSt2 and its functional annotation indicated that enrichment in a protein-based medium affected the richness and diversity of functional profiles, in the face of a decrease of richness and evenness of the microbial community. Linear discriminant analysis (LDA) effect size indicated a positive differential abundance (p < 0.05) for the modules of amino acid catabolism that may be at the basis of the changes of VOC profile. In particular, predicted genes encoding functions belonging to the superpathways of ornithine, arginine, and putrescine transformation to GABA and eventually to succinyl-CoA, of methionine degradation, and various routes of breakdown of aromatic compounds yielding succinyl-CoA or acetyl-CoA became significantly more abundant in the metagenome of the bacterial community.

Published
2021
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29. Radiation protection issues after 20 years of LHC operation

Author

Forkel-Wirth, D., Magistris, M., Roesler, S., Theis, C., Ulrici, L., Vincke, H., and Vincke, Hz.

Subjects
Physics - Accelerator Physics
Abstract

Since November 2009, the LHC commissioning progresses very well, both with proton and lead beams. It will continue in 2011 and nominal LHC operation is expected to be attained in 2013. In parallel, plans for various LHC upgrades are under discussion, suggesting a High-Luminosity (HL) upgrade first and a High-Energy (HE) upgrade in a later state. Whereas the upgrade in luminosity would require the modification of only some few key accelerator components like the inner triplets, the upgrade in beam energy from 7 TeV to 16.5 TeV would require the exchange of all dipoles and of numerous other accelerator components. The paper gives an overview of the radiation protection issues related to the dismantling of LHC components prior to the installation of the HE-LHC components, i.e. after about 20 years of LHC operation. Two main topics will be discussed: (i) the exposure of workers to ionizing radiation during the dismantling of dipoles, inner triplets or collimators and experiments and (ii) the production, conditioning, interim storage and final disposal of radioactive waste., Comment: 3 pages, contribution to the EuCARD-AccNet-EuroLumi Workshop: The High-Energy Large Hadron Collider, Malta, 14 -- 16 Oct 2010; CERN Yellow Report CERN-2011-003, pp. 134-136

Published
2011

34. Ultra short time to Echo (UTE) MRI for cephalometric analysis-Potential of an x-ray free fast cephalometric projection technique.

Author

Ciamak Abkai, Jan Hourfar, Jörg Glockengießer, Johannes Ulrici, Erich Hell, Volker Rasche, and Björn Ludwig

Subjects
Medicine, Science
Abstract

ObjectivesA novel magnetic resonance imaging (MRI) scan protocol is presented on the basis of ultra-short time to echo (UTE). By this MRI cephalometric projections (MCPs) can be acquired without the need of post processing in one shot. Different technical parameterizations of the protocol are performed. Their impact on the performance of MCPs is evaluated in comparison to the gold standard-the lateral cephalometric radiography (LCR) for cephalometric analysis (CA) in orthodontics.MethodsSeven MCPs with various scan parameters influencing the scan duration and one LCR are used from one subject. 40 expert assessors performed CA for 14 predefined cephalometric landmarks. Relative metric distances and absolute angular measurements were calculated. Statistical analysis is presented and the deviations are highlighted to demonstrate the potential of the method for further analysis.ResultsThe MCPs are acquired in 5-154 seconds, depending on resolution and contrast. Mean relative distances were 2.4-2.7 mm in MCPs and 1.6 mm in LCR, which demonstrate the accuracy and level of agreement of the expert assessors in identifying anatomical landmarks. In comparison to other studies, the presented MCP performed similar in angular analysis and demonstrated on average deviation of 1.2° ±1.1° in comparison to LCR. Despite the point articulare (Ar) and the related gonial angle the calculate distances and angles show outcomes in the range of ±2°/2mm.ConclusionsMCPs can be acquired much faster in comparison to other techniques known from literature for CA. This study demonstrated the potential of the new method and showed first feasible results. Further research is needed to analyze the performance on a broad range of patients.

Published
2021
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36. New Results on DEPFET Pixel Detectors for Radiation Imaging and High Energy Particle Detection

Author

Wermes, N., Andricek, L., Fischer, P., Haerter, M., Heinzinger, K., Herrmann, S., Karagounis, M., Kohrs, R., Krueger, H., Lutz, G., Lechner, P., Peric, I., Porro, M., Richter, R. H., Schaller, G., Schnecke-Radau, M., Schopper, F., Soltau, H., Strueder, L., Trimpl, M., Ulrici, J., and Treis, J.

Subjects
Physics - Instrumentation and Detectors
Abstract

DEPFET pixel detectors are unique devices in terms of energy and spatial resolution because very low noise (ENC = 2.2e at room temperature) operation can be obtained by implementing the amplifying transistor in the pixel cell itself. Full DEPFET pixel matrices have been built and operated for autoradiographical imaging with imaging resolutions of 4.3 +- 0.8 um at 22 keV. For applications in low energy X-ray astronomy the high energy resolution of DEPFET detectors is attractive. For particle physics, DEPFET pixels are interesting as low material detectors with high spatial resolution. For a Linear Collider detector the readout must be very fast. New readout chips have been designed and produced for the development of a DEPFET module for a pixel detector at the proposed TESLA collider (520x4000 pixels) with 50 MHz line rate and 25 kHz frame rate. The circuitry contains current memory cells and current hit scanners for fast pedestal subtraction and sparsified readout. The imaging performance of DEPFET devices as well as present achievements towards a DEPFET vertex detector for a Linear Collider are presented., Comment: 6 pages, 10 figures, Talk given at IEEE2003, Portland OR, October 2003

Published
2003
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37. Readout Concepts for DEPFET Pixel Arrays

Author

Fischer, P., Neeser, W., Trimpl, M., Ulrici, J., and Wermes, N.

Subjects
High Energy Physics - Experiment
Abstract

Field effect transistors embedded into a depleted silicon bulk (DEPFETs) can be used as the first amplifying element for the detection of small signal charges deposited in the bulk by ionizing particles, X-ray photons or visible light. Very good noise performance at room temperature due to the low capacitance of the collecting electrode has been demonstrated. Regular two dimensional arrangements of DEPFETs can be read out by turning on individual rows and reading currents or voltages in the columns. Such arrangements allow the fast, low power readout of larger arrays with the possibility of random access to selected pixels. In this paper, different readout concepts are discussed as they are required for arrays with incomplete or complete clear and for readout at the source or the drain. Examples of VLSI chips for the steering of the gate and clear rows and for reading out the columns are presented., Comment: 8 pages, 9 figures, submitted to Nucl. Instr. and Methods as proceedings of the 9th European Symposium on Semiconductor Detectors, Elmau, June 23-27, 2002

Published
2002
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