14 results on '"Domingos, Guilherme"'
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2. Weaning from mechanical ventilation in intensive care units across 50 countries (WEAN SAFE): a multicentre, prospective, observational cohort study
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Abrough, Fekri, Acharya, Subhash P, Amin, Pravin, Arabi, Yaseen, Aragao, Irene, Bauer, Philippe, Beduneau, Gaëtan, Beitler, Jeremy, Berkius, Johan, Bugedo, Guillermo, Camporota, Luigi, Cerny, Vladimir, Cho, Young-Jae, Clarkson, Kevin, Estenssoro, Elisa, Goligher, Ewan, Grasselli, Giacomo, Gritsan, Alexey, Hashemian, Seyed Mohammadreza, Hermans, Greet, Heunks, Leo M, Jovanovic, Bojan, Kurahashi, Kiyoyasu, Laake, Jon Henrik, Matamis, Dimitrios, Moerer, Onnen, Molnar, Zsolt, Ozyilmaz, Ezgi, Panka, Bernardo, Papali, Alfred, Peñuelas, Óscar, Perbet, Sébastien, Piquilloud, Lise, Qiu, Haibo, Razek, Assem Abdel, Rittayamai, Nuttapol, Roldan, Rollin, Serpa Neto, Ary, Szuldrzynski, Konstanty, Talmor, Daniel, Tomescu, Dana, Van Haren, Frank, Villagomez, Asisclo, Zeggwagh, Amine Ali, Abe, Toshikazu, Aboshady, Abdelrhman, Acampo-de Jong, Melanie, Acharya, Subhash, Adderley, Jane, Adiguzel, Nalan, Agrawal, Vijay Kumar, Aguilar, Gerardo, Aguirre, Gaston, Aguirre-Bermeo, Hernan, Ahlström, Björn, Akbas, Türkay, Akker, Mustafa, Al Sadeh, Ghamdan, Alamri, Sultan, Algaba, Angela, Ali, Muneeb, Aliberti, Anna, Allegue, Jose Manuel, Alvarez, Diana, Amador, Joaquin, Andersen, Finn H, Ansari, Sharique, Apichatbutr, Yutthana, Apostolopoulou, Olympia, Arellano, Daniel, Arica, Mestanza, Arikan, Huseyin, Arinaga, Koichi, Arnal, Jean-Michel, Asano, Kengo, Asín-Corrochano, Marta, Avalos Cabrera, Jesus Milagrito, Avila Fuentes, Silvia, Aydemir, Semih, Aygencel, Gulbin, Azevedo, Luciano, Bacakoglu, Feza, Badie, Julio, Baedorf Kassis, Elias, Bai, Gabriela, Balaraj, Govindan, Ballico, Bruno, Banner-Goodspeed, Valerie, Banwarie, Preveen, Barbieri, Rosella, Baronia, Arvind, Barrett, Jonathan, Barrot, Loïc, Barrueco-Francioni, Jesus Emilio, Barry, Jeffrey, Bawangade, Harshal, Beavis, Sarah, Beck, Eduardo, Beehre, Nina, Belenguer Muncharaz, Alberto, Bellani, Giacomo, Belliato, Mirko, Bellissima, Agrippino, Beltramelli, Rodrigo, Ben Souissi, Asma, Benitez-Cano, Adela, Benlamin, Mohamed, Benslama, Abdellatif, Bento, Luis, Benvenuti, Daniela, Bernabe, Laura, Bersten, Andrew, Berta, Giacomo, Bertini, Pietro, Bertram-Ralph, Elliot, Besbes, Mohamed, Bettini, Lisandro Roberto, Beuret, Pascal, Bewley, Jeremy, Bezzi, Marco, Bhakhtiani, Lakshay, Bhandary, Rakesh, Bhowmick, Kaushik, Bihari, Shailesh, Bissett, Bernie, Blythe, David, Bocher, Simon, Boedjawan, Narain, Bojanowski, Christine M, Boni, Elisa, Boraso, Sabrina, Borelli, Massimo, Borello, Silvina, Borislavova, Margarita, Bosma, Karen J, Bottiroli, Maurizio, Boyd, Owen, Bozbay, Suha, Briva, Arturo, Brochard, Laurent, Bruel, Cédric, Bruni, Andrea, Buehner, Ulrike, Bulpa, Pierre, Burt, Karen, Buscot, Mathieu, Buttera, Stefania, Cabrera, Jorge, Caccese, Roberta, Caironi, Pietro, Canchos Gutierrez, Ivan, Canedo, Nancy, Cani, Alma, Cappellini, Iacopo, Carazo, Jesus, Cardonnet, Luis Pablo, Carpio, David, Carriedo, Demetrio, Carrillo, Ramón, Carvalho, João, Caser, Eliana, Castelli, Antonio, Castillo Quintero, Manuel, Castro, Heloisa, Catorze, Nuno, Cengiz, Melike, Cereijo, Enrique, Ceunen, Helga, Chaintoutis, Christos, Chang, Youjin, Chaparro, Gustavogcha, Chapman, Carmel, Chau, Simon, Chavez, Cecilia Eugenia, Chelazzi, Cosimo, Chelly, Jonathan, Chemouni, Frank, Chen, Kai, Chena, Ariel, Chiarandini, Paolo, Chilton, Phil, Chiumello, Davide, Chou-Lie, Yvette, Chudeau, Nicolas, Cinel, Ismail, Cinnella, Gilda, Clark, Michele, Clark, Thomas, Clementi, Stefano, Coaguila, Luis, Codecido, Alexis Jaspe, Collins, Amy, Colombo, Riccardo, Conde, Juan, Consales, Guglielmo, Cook, Tim, Coppadoro, Andrea, Cornejo, Rodrigo, Cortegiani, Andrea, Coxo, Cristina, Cracchiolo, Andrea Neville, Crespo Ramirez, Mónica, Crova, Philippe, Cruz, José, Cubattoli, Lucia, Çukurova, Zafer, Curto, Francesco, Czempik, Piotr, D'Andrea, Rocco, da Silva Ramos, Fernando, Dangers, Laurence, Danguy des Déserts, Marc, Danin, Pierre-Eric, Dantas, Fabianne, Daubin, Cédric, Dawei, Wu, de Haro, Candelaria, de Jesus Montelongo, Felipe, De Mendoza, Diego, de Pablo, Raúl, De Pascale, Gennaro, De Rosa, Silvia, Decavèle, Maxens, Declercq, Pierre-Louis, Deicas, Alberto, del Carmen Campos Moreno, María, Dellamonica, Jean, Delmas, Benjamin, Demirkiran, Oktay, Demirkiran, Hilmi, Dendane, Tarek, di Mussi, Rossella, Diakaki, Chrysi, Diaz, Anatilde, Diaz, Willy, Dikmen, Yalim, Dimoula, Aikaterini, Doble, Patricia, Doha, Nagwa, Domingos, Guilherme, Dres, Martin, Dries, David, Duggal, Abhijit, Duke, Graeme, Dunts, Pavel, Dybwik, Knut, Dykyy, Maksym, Eckert, Philippe, Efe, Serdar, Elatrous, Souheil, Elay, Gülseren, Elmaryul, Abubaker S, Elsaadany, Mohamed, Elsayed, Hany, Elsayed, Samar, Emery, Malo, Ena, Sébastien, Eng, Kevin, Englert, Joshua A, Erdogan, Elif, Ergin Ozcan, Perihan, Eroglu, Ege, Escobar, Miguel, Esen, Figen, Esen Tekeli, Arzu, Esquivel, Alejandro, Esquivel Gallegos, Helbert, Ezzouine, Hanane, Facchini, Alberto, Faheem, Mohammad, Fanelli, Vito, Farina, Maria Fernanda, Fartoukh, Muriel, Fehrle, Lutz, Feng, Feng, Feng, Yufeng, Fernandez, Irene, Fernandez, Borja, Fernandez-Rodriguez, Maria Lorena, Ferrando, Carlos, Ferreira da Silva, Maria João, Ferreruela, Mireia, Ferrier, Janet, Flamm Zamorano, Matias Jesús, Flood, Laura, Floris, Leda, Fluckiger, Martin, Forteza, Catalina, Fortunato, Antonella, Frans, Eric, Frattari, Antonella, Fredes, Sebastian, Frenzel, Tim, Fumagalli, Roberto, Furche, Mariano Andres, Fusari, Maurizio, Fysh, Edward, Galeas-Lopez, Juan Luis, Galerneau, Louis-Marie, Garcia, Analía, Garcia, María Fernanda, Garcia, Elisabet, Garcia Olivares, Pablo, Garlicki, Jaroslaw, Garnero, Aude, Garofalo, Eugenio, Gautam, Prabha, Gazenkampf, Andrey, Gelinotte, Stéphanie, Gelormini, Domenico, Ghrenassia, Etienne, Giacomucci, Angelo, Giannoni, Robert, Gigante, Andrea, Glober, Nancy, Gnesin, Paolo, Gollo, Yari, Gomaa, Dina, Gomero Paredes, Rosita, Gomes, Rui, Gomez, Raúl Alejandro, Gomez, Oscar, Gomez, Aroa, Gondim, Louise, Gonzalez, Manuel, Gonzalez, Isabel, Gonzalez-Castro, Alejandro, Gordillo Romero, Orlando, Gordo, 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Innes, Richard, Ioannides, Panagiotis, Iotti, Giorgio Antonio, Ippolito, Mariachiara, Irie, Hiromasa, Iriyama, Hiroki, Itagaki, Taiga, Izura, Javier, Izza, Santiago, Jabeen, Rakhshanda, Jamaati, Hamidreza, Jamadarkhana, Sunil, Jamoussi, Amira, Jankowski, Milosz, Jaramillo, Luis Alberto, Jeon, Kyeongman, Jeong Lee, Seok, Jeswani, Deepak, Jha, Simant, Jiang, Liangyan, Jing, Chen, Jochmans, Sébastien, Johnstad, Bror Anders, Jongmin, Lee, Joret, Aurélie, Junhasavasdikul, Detajin, Jurado, Maria Teresa, Kam, Elisa, Kamohara, Hidenobu, Kane, Caroline, Kara, Iskender, Karakurt, Sait, Karnjanarachata, Cherdkiat, Kataoka, Jun, Katayama, Shinshu, Kaushik, Shuchi, Kelebek Girgin, Nermin, Kerr, Kathryn, Kerslake, Ian, Khairnar, Prakash, Khalid, Abidi, Khan, Akram, Khanna, Ashish K, Khorasanee, Reza, Kienhorst, Dieneke, Kirakli, Cenk, Knafelj, Rihard, Kol, Mark Kol, Kongpolprom, Napplika, Kopitko, Csaba, Korkmaz Ekren, Pervin, Kubisz-Pudelko, Agnieszka, Kulcsar, Zoltan, Kumasawa, Junji, Kuriyama, Akira, Kutchak, Fernanda, Labarca, Eduardo, Labat, Françoise, Laborda, César, Laca Barrera, Manuel Alberto, Lagache, Laurie, Landaverde Lopez, Antonio, Lanspa, Michael, Lascari, Valeria, Le Meur, Matthieu, Lee, Su Hwan, Lee, Young Ju, Lee, Jinwoo, Lee, Won-Yeon, Lee, Jarone, Legernaes, Terje, Leiner, Tamaas, Lemiale, Virginie, Leonor, Tiago, Lepper, Philipp M, Li, Dahuan, Li, Hongbin, Li, Oleg, Lima, Ana Raquel, Lind, Dan, Litton, Edward, Liu, Ning, Liu, Ling, Liu, Jialin, Llitjos, Jean-François, Llorente, Beatriz, Lopez, Rodolfo, Lopez, Claudia Elizabeth, Lopez Nava, Claudia, Lovazzano, Pablo, Lu, Min, Lucchese, Francesca, Lugano, Manuela, Lugo Goytia, Gustavo, Luo, Hua, Lynch, Ceri, Macheda, Sebastiano, Madrigal Robles, Victor Hugo, Maggiore, Salvatore Maurizio, Magret Iglesias, Mònica, Malaga, Peter, Mallapura Maheswarappa, Harish, Malpartida, Guillermo, Malyarchikov, Andrey, Mansson, Helena, Manzano, Anaid, Marey, Ismael, Marin, Nathalie, Marin, Maria del Carmen, Markman, Eliana, Martin, Felix, Martin, Alex, Martin Dal Gesso, Cristina, Martinez, Felipe, Martínez-Fidalgo, Conchita, Martin-Loeches, Ignacio, Mas, Arantxa, Masaaki, Sakuraya, Maseda, Emilio, Massa, Eleni, Mattsson, Anna, Maugeri, Jessica, McCredie, Victoria, McCullough, James, McGuinness, Shay, McKown, Andrew, Medve, László, Mei, Chengqing, Mellado Artigas, Ricard, Mendes, Vitor, Mervat, Mohamed Khalaf Ebraheim, Michaux, Isabelle, Mikhaeil, Michael, Milagros, Olga, Milet, Igor, Millan, Maria Teresa, Minwei, Zhang, Mirabella, Lucia, Mishra, Sanghamitra, Mistraletti, Giovanni, Mochizuki, Katsunori, Moghal, Arif, Mojoli, Francesco, Molin, Alexandre, Montiel, Raquel, Montini, Luca, Monza, Gianmario, Mora Aznar, Maria, Morakul, Sunthiti, Morales, Maria, Moreno Torres, Daniel, Morocho Tutillo, Diego Rolando, Motherway, Catherine, Mouhssine, Doumiri, Mouloudi, Eleni, Muñoz, Tapia, Munoz de Cabo, Carlos, Mustafa, Mohamed, Muthuchellappan, Radhakrishnan, Muthukrishnan, Muraleekrishnan, Muttini, Stefano, Nagata, Isao, Nahar, Dick, Nakanishi, Misuzu, Nakayama, Izumi, Namendys-Silva, Silvio Antonio, Nanchal, Rahul, Nandakumar, Sivakumar, Nasi, Alessandra, Nasir, Kamal, Navalesi, Paolo, Naz Aslam, Tayyba, Nga Phan, Thuy, Nichol, Alistair, Niiyama, Shuhei, Nikolakopoulou, Sofia, Nikolic, Elena, Nitta, Kenichi, Noc, Marko, Nonas, Stephanie, Nseir, Saad, Nur Soyturk, Ayse, Obata, Yukako, Oeckler, Richard, Oguchi, Moe, Ohshimo, Shinichiro, Oikonomou, Marina, Ojados, Agueda, Oliveira, Maria Teresa, Oliveira Filho, Wilson, Oliveri, Carlo, Olmos, Aitor, Omura, Kazuya, Orlandi, Maria Cristina, Orsenigo, Francesca, Ortiz-Ruiz De Gordoa, Laura, Ota, Kei, Ovalle Olmos, Rainier, Öveges, Nándo, Oziemski, Peter, Ozkan Kuscu, Ozlem, Pachas Alvarado, Fernando, Pagella, Gonzalo, Palaniswamy, Vijayanand, Palazon Sanchez, Eugenio Luis, Palmese, Salvatore, Pan, Guojun, Pan, Wensen, Papanikolaou, Metaxia, Papavasilopoulou, Theonymfi, Parekh, Ameet, Parke, Rachael, Parrilla, Francisco J, Parrilla, Dácil, Pasha, Taha, Pasin, Laura, Patão, Luis, Patel, Mayur, Patel, Grisma, Pati, Basanta Kumar, Patil, Jayaprakash, Pattnaik, Saroj, Paul, Daniel, Pavesi, Maurizio, Pavlotsky, Vanesa Alejandra, Paz, Graciela, Paz, Enrique, Pecci, Elisabetta, Pellegrini, Carlos, Peña Padilla, Andrea Gabriela, Perchiazzi, Gaetano, Pereira, Tiago, Pereira, Vera, Perez, Manuel, Perez Calvo, Cesar, Perez Cheng, Meisy, Perez Maita, Ronald, Pérez-Araos, Rodrigo, Perez-Teran, Purificación, Perez-Torres, David, Perkins, Gavin, Persona, Paolo, Petnak, Tananchai, Petrova, Marina, Pham, Tai, Philippart, François, Picetti, Edoardo, Pierucci, Elisabetta, Piervincenzi, Edoardo, Pinciroli, Riccardo, Pintado, Maria-Consuelo, Piraino, Thomas, Piras, Stephanie, Piras, Claudio, Pirompanich, Pattarin, Pisani, Luigi, Platas, Enrique, Plotnikow, Gustavo, Porras, Willy, Porta, Virginia, Portilla, Mariana, Portugal, José, Povoa, Pedro, Prat, Gwenael, Pratto, Romina, Preda, Gabriel, Prieto, Isidro, Prol-Silva, Estefania, Pugh, Richard, Qi, Yupeng, Qian, Chuanyun, Qin, Tiehe, Qu, Hongping, Quintana, Teobaldo, Quispe Sierra, Rosari, Quispe Soto, Rocio, Rabbani, Raihan, Rabee, Mohamed, Rabie, Ahmed, Rahe Pereira, Maria Augusta, Rai, Ashish, Raj Ashok, Sundar, Rajab, Mostafa, Ramdhani, Navin, Ramey, Elizabeth, Ranieri, Marco, Rathod, Darshana, Ray, Banambar, Redwanul Huq, Shihan Mahmud, Regli, Adrian, Reina, Rosa, Resano Sarmiento, Natalia, Reynaud, Faustine, Rialp, Gemma, Ricart, Pilar, Rice, Todd, Richardson, Angus, Rieder, Marcelo, Rinket, Martin, Rios, Fernando, Risso Vazquez, Alejandro, Riva, Ivano, Rivette, Monaly, Roca, Oriol, Roche-Campo, Ferran, Rodriguez, Covadonga, Rodriguez, Gabriel, Rodriguez Gonzalez, Daniel, Rodriguez Tucto, Xandra Yanina, Rogers, Angela, Romano, María Elena, Rørtveit, Linda, Rose, Alastair, Roux, Damien, Rouze, Anahita, Rubatto Birri, Paolo Nahuel, Ruilan, Wang, Ruiz Robledo, Aldana, Ruiz-Aguilar, Antonio Luis, Sadahiro, Tomohito, Saez, Ignacio, Sagardia, Judith, Saha, Rajnish, Saha, Rohit, Saiphoklang, Narongkorn, Saito, Shigeki, Salem, Maie, Sales, Gabriele, Salgado, Patricia, Samavedam, Srinivas, Sami Mebazaa, Mhamed, Samuelsson, Line, San Juan Roman, Nandyelly, Sanchez, Patricia, Sanchez-Ballesteros, Jesus, Sandoval, Yazcitk, Sani, Emanuele, Santos, Martin, Santos, Carla, Sanui, Masamitsu, Saravanabavan, Lakshmikanthcharan, Sari, Sema, Sarkany, Agnes, Sauneuf, Bertrand, Savioli, Monica, Sazak, Hilal, Scano, Riccardo, Schneider, Francis, Schortgen, Frédérique, Schultz, Marcus J, Schwarz, Gabriele Leonie, Seçkin Yücesoy, Faruk, Seely, Andrew, Seiler, Frederik, Seker Tekdos, Yasemin, Seok Chan, Kim, Serano, Luca, Serednicki, Wojciech, Setten, Mariano, Shah, Asim, Shah, Bhagyesh, Shang, You, Shanmugasundaram, Pradeep, Shapovalov, Konstantin, Shebl, Eman, Shiga, Takuya, Shime, Nobuaki, Shin, Phil, Short, Jack, Shuhua, Chen, Siddiqui, Sughrat, Silesky Jimenez, Juan Ignacio, Silva, Daniel, Silva Sales, Betania, Simons, Koen, Sjøbø, Brit Ågot, Slessor, David, Smiechowicz, Jakub, Smischney, Nathan, Smith, Paul, Smith, Tim, Smith, Mark, Snape, Sarah, Snyman, Lindi, Soetens, Filiep, Sook Hong, Kyung, Sosa Medellin, Miguel Ángel, Soto, Giovanna, Souloy, Xavier, Sousa, Elsa, Sovatzis, Stefania, Sozutek, Didem, Spadaro, Savino, Spagnoli, Marco, Spångfors, Martin, Spittle, Nick, Spivey, Mike, Stapleton, Andrew, Stefanovic, Branislava, Stephenson, Lorraine, Stevenson, Elizabeth, Strand, Kristian, Strano, Maria Teresa, Straus, Slavenka, Sun, Chenliang, Sun, Rongqing, Sundaram, Venkat, SunPark, Tai, Surlemont, Elisabeth, Sutherasan, Yuda, Szabo, Zsuzsanna, Tainter, Christopher, Takaba, Akihiro, Tallott, Mandy, Tamasato, Tamasato, Tang, Zhanhong, Tangsujaritvijit, Viratch, Taniguchi, Leandro, Taniguchi, Daisuke, Tarantino, Fabio, Teerapuncharoen, Krittika, Temprano, Susana, Terragni, Pierpaolo, Terzi, Nicolas, Thakur, Anand, Theerawit, Pongdhep, Thille, Arnaud W, Thomas, Matt, Thungtitigul, Poungrat, Thyrault, Martial, Tilouch, Nejla, Timenetsky, Karina, Tirapu, Juna, Todeschini, Manuel, Tomas, Roser, Tomaszewski, Christian, Tonetti, Tommaso, Tonnelier, Alexandre, Trinder, John, Trongtrakul, Konlawij, Truwit, Jonathon, Tsuei, Betty, Tulaimat, Aiman, Turan, Sema, Turkoglu, Melda, Tyagi, Sanjeev, Ubeda, Alejandro, Vagginelli, Federica, Valenti, María Florencia, Vallverdu, Imma, Van Axel, Alisha, van den Hul, Ingrid, van der Hoeven, Hans, Van Der Meer, Nardo, Vanhoof, Marc, Vargas-Ordoñez, Mónica, Vaschetto, Rosanna, Vascotto, Ettore, Vatsik, Maria, Vaz, Ana, Vazquez-Sanchez, Antonia, Ventura, Sara, Vermeijden, Jan Wytze, Vidal, Anxela, Vieira, Jocyelle, Vilela Costa Pinto, Bruno, Villagra, Ana, Villegas Succar, Cristina, Vinorum, Ole Georg, Vitale, Giovanni, Vj, Ramesh, Vochin, Ana, Voiriot, Guillaume, Volta, Carlo Alberto, von Seth, Magnus, Wajdi, Maazouzi, Walsh, Don, Wang, Shouhong, Wardi, Gabriel, Ween-Velken, Nils Christian, Wei, Bi-Lin, Weller, Dolf, Welsh, Deborah, Welters, Ingeborg, Wert, Michael, Whiteley, Simon, Wilby, Elizabeth, Williams, Erin, Williams, Karen, Wilson, Antoinette, Wojtas, Jadwiga, Won Huh, Jin, Wrathall, David, Wright, Christopher, Wu, Jian-Feng, Xi, Guo, Xing, Zheng-Jiang, Xu, Hongyang, Yamamoto, Kotaro, Yan, Jie, Yáñez, Julio, Yang, Xiaobo, Yates, Elliot, Yazicioglu Mocin, Ozlem, Ye, Zhenglong, Yildirim, Fatma, Yoshida, Norifumi, Yoshido, Hector Higo Leon, Young Lee, Bo, Yu, Rongguo, Yu, Gong, Yu, Tao, Yuan, Boyun, Yuangtrakul, Nadwipa, Yumoto, Tetsuya, Yun, Xie, Zakalik, Graciela, Zaki, Ahmad, Zalba-Etayo, Begoña, Zambon, Massimo, Zang, Bin, Zani, Gianluca, Zarka, Jonathan, Zerbi, Simone Maria, Zerman, Avsar, Zetterquist, Harald, Zhang, Jiuzhi, Zhang, Hongwen, Zhang, Wei, Zhang, Guoxiu, Zhang, Weixin, Zhao, Hongsheng, Zheng, Jia, Zhu, Bin, Zumaran, Ronald, Pham, Tài, Madotto, Fabiana, Goligher, Ewan C, Mancebo, Jordi, Peñuelas, Oscar, Pesenti, Antonio, Wunsch, Hannah, van Haren, Frank, and Laffey, John G
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- 2023
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3. APPLICATION OF SCRUM METHODOLOGY IN AN ENGINEERING CASE STUDY/ APLICACAO DA METODOLOGIA SCRUM EM UM ESTUDO DE CASO DE ENGENHARIA
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Baldo, Rodrigo Fernando Galzerano, Cerri, Domingos Guilherme Pellegrino, da Silva, Alessandro Lucas, Zuim, Julia Brandino, Mergulhao, Larissa Eichemberguer Martinez, Adolpho, Matheus Normanton, Boschi, Thais Foschini, Garcia, Rhenan Fernandes Hergert, and Favalli, Rafael
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- 2019
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4. Assessing the carbon footprint of beef cattle in Brazil: a case study with 22 farms in the State of Mato Grosso
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Cerri, Carlos Clemente, Moreira, Cindy Silva, Alves, Priscila Aparecida, Raucci, Guilherme Silva, de Almeida Castigioni, Bruno, Mello, Francisco F.C., Cerri, Domingos Guilherme P., and Cerri, Carlos Eduardo P.
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- 2016
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5. Diretriz de Telecardiologia no Cuidado de Pacientes com Síndrome Coronariana Aguda e Outras Doenças Cardíacas
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Mucio Tavares de Oliveira Junior, Manoel Fernandes Canesin, Milena Soriano Marcolino, Antonio Luiz Pinho Ribeiro, Antonio Carlos de Camargo Carvalho, Shankar Reddy, Adson Roberto França dos Santos, Alfredo Manoel da Silva Fernandes, Amaury Zatorre Amaral, Ana Carolina de Rezende, Antonio Nechar Junior, Bruno Ramos do Nascimento, Carlos Alberto Pastore, Chao Lung Wen, Danielle Menosi Gualandro, Domingos Guilherme Napoli, Francisco Faustino A. C. França, Gilson Soares Feitosa-Filho, Jamil Abdalla Saad, Jeanne Pilli, Leonardo Jorge Cordeiro de Paula, Lucas Lodi-Junqueira, Luis Antonio Machado Cesar, Luiz Carlos Bodanese, Marco Antonio Gutierrez, Maria Beatriz Moreira Alkmim, Mauricio Batista Nunes, Orlando Otávio de Medeiros, Ramon Alfredo Moreno, Rosângela Simões Gundim, Sergio Tavares Montenegro, and Willyan Issamu Nazima
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Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Published
- 2015
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6. Assessing the greenhouse gas emissions of Brazilian soybean biodiesel production.
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Carlos Eduardo Pellegrino Cerri, Xin You, Maurício Roberto Cherubin, Cindy Silva Moreira, Guilherme Silva Raucci, Bruno de Almeida Castigioni, Priscila Aparecida Alves, Domingos Guilherme Pellegrino Cerri, Francisco Fujita de Castro Mello, and Carlos Clemente Cerri
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Medicine ,Science - Abstract
Soybean biodiesel (B100) has been playing an important role in Brazilian energy matrix towards the national bio-based economy. Greenhouse gas (GHG) emissions is the most widely used indicator for assessing the environmental sustainability of biodiesels and received particular attention among decision makers in business and politics, as well as consumers. Former studies have been mainly focused on the GHG emissions from the soybean cultivation, excluding other stages of the biodiesel production. Here, we present a holistic view of the total GHG emissions in four life cycle stages for soybean biodiesel. The aim of this study was to assess the GHG emissions of Brazilian soybean biodiesel production system with an integrated life cycle approach of four stages: agriculture, extraction, production and distribution. Allocation of mass and energy was applied and special attention was paid to the integrated and non-integrated industrial production chain. The results indicated that the largest source of GHG emissions, among four life cycle stages, is the agricultural stage (42-51%) for B100 produced in integrated systems and the production stage (46-52%) for B100 produced in non-integrated systems. Integration of industrial units resulted in significant reduction in life cycle GHG emissions. Without the consideration of LUC and assuming biogenic CO2 emissions is carbon neutral in our study, the calculated life cycle GHG emissions for domestic soybean biodiesel varied from 23.1 to 25.8 gCO2eq. MJ-1 B100 and those for soybean biodiesel exported to EU ranged from 26.5 to 29.2 gCO2eq. MJ-1 B100, which represent reductions by 65% up to 72% (depending on the delivery route) of GHG emissions compared with the EU benchmark for diesel fuel. Our findings from a life cycle perspective contributed to identify the major GHG sources in Brazilian soybean biodiesel production system and they can be used to guide mitigation priority for policy and decision-making. Projected scenarios in this study would be taken as references for accounting the environmental sustainability of soybean biodiesel within a domestic and global level.
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- 2017
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7. Correlation of physical and chemical attributes of soil with sugarcane yield
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Domingos Guilherme Pellegrino Cerri and Paulo Sérgio Graziano Magalhães
- Subjects
Saccharum officinarum ,agricultura de precisão ,amostragem de solo ,variação espacial ,estrutura de variação ,Agriculture (General) ,S1-972 - Abstract
The objective of this work was to evaluate the correlation between sugarcane yield and some physical and chemical attributes of soil. For this, a 42‑ha test area in Araras, SP, Brazil, was used. Soil properties were determined from samples collected at the beginning of the 2003/2004 harvest season, using a regular 100x100 m grid. Yield assessment was done with a yield monitor (Simprocana). Correlation analyses were performed between sugarcane yield and the following soil properties: pH, pH CaCl2, N, C, cone index, clay content, soil organic matter, P, K, Ca, Mg, H+AL, cation exchange capacity, and base saturation. Correlation coefficients were respectively ‑0.05, ‑0.29, 0.33, 0.41, ‑0.27, 0.22, 0.44, ‑0.24, trace, ‑0.06, 0.01, 0.32, 0.14, and 0.04. Correlations of chemical and physical attributes of soil with sugarcane yield are weak, and, per se, they are not able to explain sugarcane yield variation, which suggests that other variables, besides soil attributes, should be analysed.
- Published
- 2012
- Full Text
- View/download PDF
8. Análise dos atributos do solo e da produtividade da cultura de cana-de-açúcar com o uso da geoestatística e árvore de decisão Analyze the soil attributes and sugarcane yield culture with the use of geostatistics and decision trees
- Author
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Zigomar Menezes de Souza, Domingos Guilherme Pellegrino Cerri, Marcelo José Colet, Luiz Henrique Antunes Rodrigues, Paulo Sérgio Graziano Magalhães, and Rafael Junqueira Araújo Mandoni
- Subjects
agricultura de precisão ,variabilidade espacial ,mineração de dados ,monitor de produtividade ,precision agriculture ,spatial variability ,data mining ,yield monitor ,Agriculture ,Agriculture (General) ,S1-972 - Abstract
Um dos desafios da agricultura de precisão é oferecer subsídios para a definição de unidades de manejo para posteriores intervenções. Portanto, o objetivo deste trabalho foi avaliar os atributos químicos do solo e a produtividade da cultura de cana-de-açúcar por meio da geoestatística e mineração de dados pela indução da árvore de decisão. A produtividade da cana-de-açúcar foi mapeada em uma área de aproximadamente 23ha, utilizando-se o critério de célula, por meio de um monitor de produtividade que permitiu a elaboração de um mapa digital que representa a superfície de produção para a área em estudo. Para determinar os atributos de um Argissolo Vermelho-Amarelo, foram coletadas as amostras no início da safra 2006/2007, utilizando-se uma grade regular de 50 x 50m, nas profundidades de 0,0-0,2m e 0,2-0,4m. Os dados dos atributos do solo e da produtividade foram analisados por meio da técnica de goestatística e classificados em três níveis de produção para indução de árvore de decisão. A árvore de decisão foi induzida no programa SAS Enterprise Miner, sendo utilizado algoritmo baseado na redução de entropia. As variáveis altitude e potássio apresentaram os maiores valores de correlação com a produtividade de cana-de-açúcar. A indução de árvores de decisão permitiu verificar que a altitude é a variável com maior potencial para interpretar os mapas de produtividade de cana-de-açúcar, auxiliando na agricultura de precisão e mostrando-se uma ferramenta adequada para o estudo de definição de zonas de manejo em área cultivada com essa cultura.One of the challenges of precision agriculture is to offer subsidies for the definition of management units for posterior interventions. Therefore, the objective of this work was to evaluate soil chemical attributes and sugarcane yield with the use of geostatistics and data mining by decision tree induction. Sugarcane yield was mapped in a 23ha field, applying the cell criterion, by using a yield monitor that allowed the elaboration of a digital map representing the surface of production of the studied area. To determine the soil attributes, soil samples were collected at the beginning of the harvest in 2006/2007 using a regular grid of 50 x 50m, in the depths of 0.0-0.2m and 0.2-0.4m. Soil attributes and sugarcane yield data were analyzed by using geostatistics techniques and were classified into three yield levels for the elaboration of the decision tree. The decision tree was induced in the software SAS Enterprise Miner, using an algorithm based on entropy reduction. Altitude and potassium presented the highest values of correlation with sugarcane yield. The induction of decision trees showed that the altitude is the variable with the greatest potential to interpret the sugarcane yield maps, then assisting in precision agriculture and, revealing an adjusted tool for the study of management definition zones in area cropped with sugarcane.
- Published
- 2010
9. Analyze the soil attributes and sugarcane yield culture with the use of geostatistics and decision trees/Analise dos atributos do solo e da produtividade da cultura de cana-de-acucar com o uso da geoestatistica e arvore de decisao
- Author
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de Souza, Zigomar Menezes, Cerri, Domingos Guilherme Pellegrino, Colet, Marcelo Jose, Rodrigues, Luiz Henrique Antunes, Magalhaes, Paulo Sergio Graziano, and Mandoni, Rafael Junqueira Araujo
- Published
- 2010
10. Placement of nasogastric tube complicated by hydropneumothorax
- Author
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Fonseca, Valter R., Domingos, Guilherme, Alves, Pedro, and Ribeiro, Rosa
- Published
- 2015
- Full Text
- View/download PDF
11. APLICAÇÃO DA METODOLOGIA SCRUM EM UM ESTUDO DE CASO DE ENGENHARIA.
- Author
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Galzerano Baldo, Rodrigo Fernando, Pellegrino Cerri, Domingos Guilherme, Lucas da Silva, Alessandro, Brandino Zuim, Julia, Martinez Mergulhão, Larissa Eichemberguer, Normanton Adolpho, Matheus, Foschini Boschi, Thais, Hergert Garcia, Rhenan Fernandes, and Favalli, Rafael
- Subjects
CROSS-functional teams ,PRODUCTION engineering ,SCHOOL environment ,PROJECT management ,KEY performance indicators (Management) ,QUANTUM gates ,GREENHOUSE gardening - Abstract
Copyright of Revista Producao Online is the property of Associacao Brasileira de Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2019
- Full Text
- View/download PDF
12. Torcicolo espasmódico: A propósito de um caso operado
- Author
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Domingos Guilherme da Costa
- Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Published
- 1944
13. Assessing the greenhouse gas emissions of Brazilian soybean biodiesel production.
- Author
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Cerri, Carlos Eduardo Pellegrino, You, Xin, Cherubin, Maurício Roberto, Moreira, Cindy Silva, Raucci, Guilherme Silva, Castigioni, Bruno de Almeida, Alves, Priscila Aparecida, Cerri, Domingos Guilherme Pellegrino, Mello, Francisco Fujita de Castro, and Cerri, Carlos Clemente
- Subjects
SOYBEAN oil industry ,BIODIESEL fuel manufacturing ,GREENHOUSE gases & the environment ,SUSTAINABILITY ,BIOECONOMICS - Abstract
Soybean biodiesel (B100) has been playing an important role in Brazilian energy matrix towards the national bio-based economy. Greenhouse gas (GHG) emissions is the most widely used indicator for assessing the environmental sustainability of biodiesels and received particular attention among decision makers in business and politics, as well as consumers. Former studies have been mainly focused on the GHG emissions from the soybean cultivation, excluding other stages of the biodiesel production. Here, we present a holistic view of the total GHG emissions in four life cycle stages for soybean biodiesel. The aim of this study was to assess the GHG emissions of Brazilian soybean biodiesel production system with an integrated life cycle approach of four stages: agriculture, extraction, production and distribution. Allocation of mass and energy was applied and special attention was paid to the integrated and non-integrated industrial production chain. The results indicated that the largest source of GHG emissions, among four life cycle stages, is the agricultural stage (42–51%) for B100 produced in integrated systems and the production stage (46–52%) for B100 produced in non-integrated systems. Integration of industrial units resulted in significant reduction in life cycle GHG emissions. Without the consideration of LUC and assuming biogenic CO
2 emissions is carbon neutral in our study, the calculated life cycle GHG emissions for domestic soybean biodiesel varied from 23.1 to 25.8 gCO2 eq. MJ-1 B100 and those for soybean biodiesel exported to EU ranged from 26.5 to 29.2 gCO2 eq. MJ-1 B100, which represent reductions by 65% up to 72% (depending on the delivery route) of GHG emissions compared with the EU benchmark for diesel fuel. Our findings from a life cycle perspective contributed to identify the major GHG sources in Brazilian soybean biodiesel production system and they can be used to guide mitigation priority for policy and decision-making. Projected scenarios in this study would be taken as references for accounting the environmental sustainability of soybean biodiesel within a domestic and global level. [ABSTRACT FROM AUTHOR]- Published
- 2017
- Full Text
- View/download PDF
14. Análise dos atributos do solo e da produtividade da cultura de cana-de-açúcar com o uso da geoestatística e árvore de decisão.
- Author
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de Souza, Zigomar Menezes, Cerri, Domingos Guilherme Pellegrino, Colet, Marcelo José, Rodrigues, Luiz Henrique Antunes, Sérgio Graziano^Magalhães, Paulo, and Mandoni, Rafael Junqueira Araújo
- Subjects
- *
SUGARCANE , *SOIL testing , *CROP yields , *AGRICULTURAL productivity , *SOIL productivity , *GEOLOGICAL statistics , *DECISION trees , *DECISION making - Abstract
One of the challenges of precision agriculture is to offer subsidies for the definition of management units for posterior interventions. Therefore, the objective of this work was to evaluate soil chemical attributes and sugarcane yield with the use of geostatistics and data mining by decision tree induction. Sugarcane yield was mapped in a 23ha field, applying the cell criterion, by using a yield monitor that allowed the elaboration of a digital map representing the surface of production of the studied area. To determine the soil attributes, soil samples were collected at the beginning of the harvest in 2006/2007 using a regular grid of 50 x 50m, in the depths of 0.0-0.2m and 0.2-0.4m. Soil attributes and sugarcane yield data were analyzed by using geostatistics techniques and were classified into three yield levels for the elaboration of the decision tree. The decision tree was induced in the software SAS Enterprise Miner, using an algorithm based on entropy reduction. Altitude and potassium presented the highest values of correlation with sugarcane yield. The induction of decision trees showed that the altitude is the variable with the greatest potential to interpret the sugarcane yield maps, then assisting in precision agriculture and, revealing an adjusted tool for the study of management definition zones in area cropped with sugarcane. [ABSTRACT FROM AUTHOR]
- Published
- 2010
- Full Text
- View/download PDF
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