Author: "Jia Zheng" / Publication Type: Electronic Resources - Searchworks@Jio Institute Digital Library Search Results

38 results on '"Jia Zheng"'

1. Weaning from mechanical ventilation in intensive care units across 50 countries (WEAN SAFE): a multicentre, prospective, observational cohort study

Author: Tài, Pham, Leo, Heunk, Giacomo, Bellani, Fabiana, Madotto, Irene, Aragao, Gaëtan, Beduneau, Ewan C, Goligher, Giacomo, Grasselli, Jon Henrik, Laake, Jordi, Mancebo, Oscar, Peñuela, Lise, Piquilloud, Antonio, Pesenti, Hannah, Wunsch, Frank, van Haren, Laurent, Brochard, John G, Laffey, Abrough, Fekri, P Acharya, Subhash, 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, Mohammadreza Hashemian, Seyed, Hermans, Greet, M Heunks, Leo, Jovanovic, Bojan, Kurahashi, Kiyoyasu, Henrik Laake, Jon, Matamis, Dimitrio, Moerer, Onnen, Molnar, Zsolt, Ozyilmaz, Ezgi, Panka, Bernardo, Papali, Alfred, Peñuelas, Óscar, Perbet, Sébastien, Piquilloud, Lise, Qiu, Haibo, Abdel Razek, Assem, Rittayamai, Nuttapol, Roldan, Rollin, Serpa Neto, Ary, Szuldrzynski, Konstanty, Talmor, Daniel, Tomescu, Dana, Van Haren, Frank, Villagomez, Asisclo, Ali Zeggwagh, Amine, Abe, Toshikazu, Aboshady, Abdelrhman, Acampo-de Jong, Melanie, Acharya, Subhash, Adderley, Jane, Adiguzel, Nalan, Kumar Agrawal, Vijay, Aguilar, Gerardo, Aguirre, Gaston, Aguirre-Bermeo, Hernan, Ahlström, Björn, Akbas, Türkay, Akker, Mustafa, Al Sadeh, Ghamdan, Alamri, Sultan, Algaba, Angela, Ali, Muneeb, Aliberti, Anna, Manuel Allegue, Jose, Alvarez, Diana, Amador, Joaquin, H Andersen, Finn, Ansari, Sharique, Apichatbutr, Yutthana, Apostolopoulou, Olympia, Arellano, Daniel, Arica, Mestanza, Arikan, Huseyin, Arinaga, Koichi, Arnal, Jean-Michel, Asano, Kengo, Asín-Corrochano, Marta, Milagrito Avalos Cabrera, Jesu, Avila Fuentes, Silvia, Aydemir, Semih, Aygencel, Gulbin, Azevedo, Luciano, Bacakoglu, Feza, Badie, Julio, Baedorf Kassis, Elia, Bai, Gabriela, Balaraj, Govindan, Ballico, Bruno, Banner-Goodspeed, Valerie, Banwarie, Preveen, Barbieri, Rosella, Baronia, Arvind, Barrett, Jonathan, Barrot, Loïc, Emilio Barrueco-Francioni, Jesu, 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, Lui, Benvenuti, Daniela, Bernabe, Laura, Bersten, Andrew, Berta, Giacomo, Bertini, Pietro, Bertram-Ralph, Elliot, Besbes, Mohamed, Roberto Bettini, Lisandro, Beuret, Pascal, Bewley, Jeremy, Bezzi, Marco, Bhakhtiani, Lakshay, Bhandary, Rakesh, Bhowmick, Kaushik, Bihari, Shailesh, Bissett, Bernie, Blythe, David, Bocher, Simon, Boedjawan, Narain, M Bojanowski, Christine, Boni, Elisa, Boraso, Sabrina, Borelli, Massimo, Borello, Silvina, Borislavova, Margarita, J Bosma, Karen, 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, Jesu, Pablo Cardonnet, Lui, 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, Christo, Chang, Youjin, Chaparro, Gustavogcha, Chapman, Carmel, Chau, Simon, Eugenia Chavez, Cecilia, Chelazzi, Cosimo, Chelly, Jonathan, Chemouni, Frank, Chen, Kai, Chena, Ariel, Chiarandini, Paolo, Chilton, Phil, Chiumello, Davide, Chou-Lie, Yvette, Chudeau, Nicola, Cinel, Ismail, Cinnella, Gilda, Clark, Michele, Clark, Thoma, Clementi, Stefano, Coaguila, Lui, Jaspe Codecido, Alexi, Collins, Amy, Colombo, Riccardo, Conde, Juan, Consales, Guglielmo, Cook, Tim, Coppadoro, Andrea, Cornejo, Rodrigo, Cortegiani, Andrea, Coxo, Cristina, Neville Cracchiolo, Andrea, 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, Maxen, Declercq, Pierre-Loui, 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, S Elmaryul, Abubaker, Elsaadany, Mohamed, Elsayed, Hany, Elsayed, Samar, Emery, Malo, Ena, Sébastien, Eng, Kevin, A Englert, Joshua, 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, Fernanda Farina, Maria, Fartoukh, Muriel, Fehrle, Lutz, Feng, Feng, Feng, Yufeng, Fernandez, Irene, Fernandez, Borja, Lorena Fernandez-Rodriguez, Maria, Ferrando, Carlo, João Ferreira da Silva, Maria, Ferreruela, Mireia, Ferrier, Janet, Jesús Flamm Zamorano, Matia, Flood, Laura, Floris, Leda, Fluckiger, Martin, Forteza, Catalina, Fortunato, Antonella, Frans, Eric, Frattari, Antonella, Fredes, Sebastian, Frenzel, Tim, Fumagalli, Roberto, Andres Furche, Mariano, Fusari, Maurizio, Fysh, Edward, Luis Galeas-Lopez, Juan, Galerneau, Louis-Marie, Garcia, Analía, Fernanda Garcia, María, 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, Alejandro Gomez, Raúl, Gomez, Oscar, Gomez, Aroa, Gondim, Louise, Gonzalez, Manuel, Gonzalez, Isabel, Gonzalez-Castro, Alejandro, Gordillo Romero, Orlando, Gordo, Federico, Gouin, Philippe, Graf Santos, Jerónimo, Grainne, Rooney, Grando, Matilde, Granov Grabovica, Sanja, Grasso, Salvatore, Grasso, Rinaldo, Grimmer, Lisa, Grissom, Colin, Gu, Qing, Guan, Xiang-Dong, Guarracino, Fabio, Guasch, Neu, Guatteri, Luca, Gueret, Renaud, Guérin, Claude, Guerot, Emmanuel, Guitard, Pierre-Gilda, Gül, Fethi, Gumus, Ayca, Gurjar, Mohan, Gutierrez, Patricia, Hachimi, Abdelhamid, Hadzibegovic, Adi, Hagan, Samantha, Hammel, Clare, Han Song, Joo, Hanlon, Gabrielle, Heines, Serge, Henriksson, Johanna, Herbrecht, Jean-Etienne, Omar Heredia Orbegoso, Gabriel, Hermon, Andrew, Hernandez, Rosana, Hernandez, Carmen, Herrera, Lui, Herrera-Gutierrez, Manuel, Heunks, Leo, Hidalgo, Juan, Hill, Dianne, Holmquist, Dagmar, Homez, Marcela, Hongtao, Xia, Hormis, Anil, Horner, Daniel, Carmen Hornos, M, Hou, Meihong, House, Stacy, Housni, Brahim, Hugill, Keith, Humphreys, Sally, Humbert, Loui, Hunter, Stephanie, Hwa Young, Lee, Iezzi, Nicola, Ilutovich, Santiago, Inal, Volkan, Innes, Richard, Ioannides, Panagioti, Antonio Iotti, Giorgio, Ippolito, Mariachiara, Irie, Hiromasa, Iriyama, Hiroki, Itagaki, Taiga, Izura, Javier, Izza, Santiago, Jabeen, Rakhshanda, Jamaati, Hamidreza, Jamadarkhana, Sunil, Jamoussi, Amira, Jankowski, Milosz, Alberto Jaramillo, Lui, Jeon, Kyeongman, Jeong Lee, Seok, Jeswani, Deepak, Jha, Simant, Jiang, Liangyan, Jing, Chen, Jochmans, Sébastien, Anders Johnstad, Bror, Jongmin, Lee, Joret, Aurélie, Junhasavasdikul, Detajin, Teresa Jurado, Maria, 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, K Khanna, Ashish, Khorasanee, Reza, Kienhorst, Dieneke, Kirakli, Cenk, Knafelj, Rihard, Kol Kol, Mark, Kongpolprom, Napplika, Kopitko, Csaba, Korkmaz Ekren, Pervin, Kubisz-Pudelko, Agnieszka, Kulcsar, Zoltan, Kumasawa, Junji, Kuriyama, Akira, Kutchak, Fernanda, Labarca, Eduardo, Labat, Françoise, Laborda, César, Alberto Laca Barrera, Manuel, Lagache, Laurie, Landaverde Lopez, Antonio, Lanspa, Michael, Lascari, Valeria, Le Meur, Matthieu, Hwan Lee, Su, Ju Lee, Young, Lee, Jinwoo, Lee, Won-Yeon, Lee, Jarone, Legernaes, Terje, Leiner, Tamaa, Lemiale, Virginie, Leonor, Tiago, M Lepper, Philipp, Li, Dahuan, Li, Hongbin, Li, Oleg, Raquel Lima, Ana, Lind, Dan, Litton, Edward, Liu, Ning, Liu, Ling, Liu, Jialin, Llitjos, Jean-Françoi, Llorente, Beatriz, Lopez, Rodolfo, Elizabeth Lopez, Claudia, Lopez Nava, Claudia, Lovazzano, Pablo, Lu, Min, Lucchese, Francesca, Lugano, Manuela, Lugo Goytia, Gustavo, Luo, Hua, Lynch, Ceri, Macheda, Sebastiano, Hugo Madrigal Robles, Victor, Maurizio Maggiore, Salvatore, Magret Iglesias, Mònica, Malaga, Peter, Mallapura Maheswarappa, Harish, Malpartida, Guillermo, Malyarchikov, Andrey, Mansson, Helena, Manzano, Anaid, Marey, Ismael, Marin, Nathalie, Del Carmen Marin, Maria, 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, Jame, Mcguinness, Shay, Mckown, Andrew, Medve, László, Mei, Chengqing, Mellado Artigas, Ricard, Mendes, Vitor, Khalaf Ebraheim Mervat, Mohamed, Michaux, Isabelle, Mikhaeil, Michael, Milagros, Olga, Milet, Igor, Teresa Millan, Maria, 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, Rolando Morocho Tutillo, Diego, Motherway, Catherine, Mouhssine, Doumiri, Mouloudi, Eleni, Muñoz, Tapia, Munoz de Cabo, Carlo, Mustafa, Mohamed, Muthuchellappan, Radhakrishnan, Muthukrishnan, Muraleekrishnan, Muttini, Stefano, Nagata, Isao, Nahar, Dick, Nakanishi, Misuzu, Nakayama, Izumi, Antonio Namendys-Silva, Silvio, 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, Teresa Oliveira, Maria, Oliveira Filho, Wilson, Oliveri, Carlo, Olmos, Aitor, Omura, Kazuya, Cristina Orlandi, Maria, Orsenigo, Francesca, Ortiz-Ruiz De Gordoa, Laura, Ota, Kei, Ovalle Olmos, Rainier, Öveges, Nándo, Oziemski, Peter, Ozkan Kuscu, Ozlem, Özyilmaz, Ezgi, Pachas Alvarado, Fernando, Pagella, Gonzalo, Palaniswamy, Vijayanand, Luis Palazon Sanchez, Eugenio, Palmese, Salvatore, Pan, Guojun, Pan, Wensen, Papanikolaou, Metaxia, Papavasilopoulou, Theonymfi, Parekh, Ameet, Parke, Rachael, J Parrilla, Francisco, Parrilla, Dácil, Pasha, Taha, Pasin, Laura, Patão, Lui, Patel, Mayur, Patel, Grisma, Kumar Pati, Basanta, Patil, Jayaprakash, Pattnaik, Saroj, Paul, Daniel, Pavesi, Maurizio, Alejandra Pavlotsky, Vanesa, Paz, Graciela, Paz, Enrique, Pecci, Elisabetta, Pellegrini, Carlo, Gabriela Peña Padilla, Andrea, 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, Françoi, Picetti, Edoardo, Pierucci, Elisabetta, Piervincenzi, Edoardo, Pinciroli, Riccardo, Pintado, Maria-Consuelo, Piraino, Thoma, 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, Augusta Rahe Pereira, Maria, Rai, Ashish, Raj Ashok, Sundar, Rajab, Mostafa, Ramdhani, Navin, Ramey, Elizabeth, Ranieri, Marco, Rathod, Darshana, Ray, Banambar, Mahmud Redwanul Huq, Shihan, Regli, Adrian, Reina, Rosa, Resano Sarmiento, Natalia, Reynaud, Faustine, Rialp, Gemma, Ricart, Pilar, Rice, Todd, Richardson, Angu, 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, Yanina Rodriguez Tucto, Xandra, Rogers, Angela, Elena Romano, María, Rørtveit, Linda, Rose, Alastair, Roux, Damien, Rouze, Anahita, Nahuel Rubatto Birri, Paolo, Ruilan, Wang, Ruiz Robledo, Aldana, Luis Ruiz-Aguilar, Antonio, Sadahiro, Tomohito, Saez, Ignacio, Sagardia, Judith, Saha, Rajnish, Saha, Rohit, Saiphoklang, Narongkorn, Saito, Shigeki, Salem, Maie, Sales, Gabriele, Salgado, Patricia, Samavedam, Sriniva, Sami Mebazaa, Mhamed, Samuelsson, Line, San Juan Roman, Nandyelly, Sanchez, Patricia, Sanchez-Ballesteros, Jesu, Sandoval, Yazcitk, Sani, Emanuele, Santos, Martin, Santos, Carla, Sanui, Masamitsu, Saravanabavan, Lakshmikanthcharan, Sari, Sema, Sarkany, Agne, Sauneuf, Bertrand, Savioli, Monica, Sazak, Hilal, Scano, Riccardo, Schneider, Franci, Schortgen, Frédérique, J Schultz, Marcu, Leonie Schwarz, Gabriele, 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, Ignacio Silesky Jimenez, Juan, Silva, Daniel, Silva Sales, Betania, Simons, Koen, Ågot Sjøbø, Brit, Slessor, David, Smiechowicz, Jakub, Smischney, Nathan, Smith, Paul, Smith, Tim, Smith, Mark, Snape, Sarah, Snyman, Lindi, Soetens, Filiep, Sook Hong, Kyung, Ángel Sosa Medellin, Miguel, 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, Teresa Strano, Maria, 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, Nicola, Thakur, Anand, Theerawit, Pongdhep, W Thille, Arnaud, 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, Florencia Valenti, María, Vallverdu, Imma, Van Axel, Alisha, van den Hul, Ingrid, van der Hoeven, Han, Van Der Meer, Nardo, Vanhoof, Marc, Vargas-Ordoñez, Mónica, Vaschetto, Rosanna, Vascotto, Ettore, Vatsik, Maria, Vaz, Ana, Vazquez-Sanchez, Antonia, Ventura, Sara, Wytze Vermeijden, Jan, Vidal, Anxela, Vieira, Jocyelle, Vilela Costa Pinto, Bruno, Villagra, Ana, Villegas Succar, Cristina, Georg Vinorum, Ole, Vitale, Giovanni, Vj, Ramesh, Vochin, Ana, Voiriot, Guillaume, Alberto Volta, Carlo, von Seth, Magnu, Wajdi, Maazouzi, Walsh, Don, Wang, Shouhong, Wardi, Gabriel, Christian Ween-Velken, Nil, 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, Higo Leon Yoshido, Hector, 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, Maria Zerbi, Simone, 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, Laake, Jon Henrik, Mancebo, Jordi, Peñuelas, Oscar, Pesenti, Antonio, Wunsch, Hannah, van Haren, Frank, Laffey, John G, Fekri Abrough, Subhash P Acharya, Pravin Amin, Yaseen Arabi, Irene Aragao, Philippe Bauer, Gaëtan Beduneau, Jeremy Beitler, Johan Berkius, Guillermo Bugedo, Luigi Camporota, Vladimir Cerny, Young-Jae Cho, Kevin Clarkson, Elisa Estenssoro, Ewan Goligher, Giacomo Grasselli, Alexey Gritsan, Seyed Mohammadreza Hashemian, Greet Hermans, Leo M Heunks, Bojan Jovanovic, Kiyoyasu Kurahashi, Jon Henrik Laake, Dimitrios Matamis, Onnen Moerer, Zsolt Molnar, Ezgi Ozyilmaz, Bernardo Panka, Alfred Papali, Óscar Peñuelas, Sébastien Perbet, Lise Piquilloud, Haibo Qiu, Assem Abdel Razek, Nuttapol Rittayamai, Rollin Roldan, Ary Serpa Neto, Konstanty Szuldrzynski, Daniel Talmor, Dana Tomescu, Frank Van Haren, Asisclo Villagomez, Amine Ali Zeggwagh, Toshikazu Abe, Abdelrhman Aboshady, Melanie Acampo-de Jong, Subhash Acharya, Jane Adderley, Nalan Adiguzel, Vijay Kumar Agrawal, Gerardo Aguilar, Gaston Aguirre, Hernan Aguirre-Bermeo, Björn Ahlström, Türkay Akbas, Mustafa Akker, Ghamdan Al Sadeh, Sultan Alamri, Angela Algaba, Muneeb Ali, Anna Aliberti, Jose Manuel Allegue, Diana Alvarez, Joaquin Amador, Finn H Andersen, Sharique Ansari, Yutthana Apichatbutr, Olympia Apostolopoulou, Daniel Arellano, Mestanza Arica, Huseyin Arikan, Koichi Arinaga, Jean-Michel Arnal, Kengo Asano, Marta Asín-Corrochano, Jesus Milagrito Avalos Cabrera, Silvia Avila Fuentes, Semih Aydemir, Gulbin Aygencel, Luciano Azevedo, Feza Bacakoglu, Julio Badie, Elias Baedorf Kassis, Gabriela Bai, Govindan Balaraj, Bruno Ballico, Valerie Banner-Goodspeed, Preveen Banwarie, Rosella Barbieri, Arvind Baronia, Jonathan Barrett, Loïc Barrot, Jesus Emilio Barrueco-Francioni, Jeffrey Barry, Harshal Bawangade, Sarah Beavis, Eduardo Beck, Nina Beehre, Alberto Belenguer Muncharaz, Giacomo Bellani, Mirko Belliato, Agrippino Bellissima, Rodrigo Beltramelli, Asma Ben Souissi, Adela Benitez-Cano, Mohamed Benlamin, Abdellatif Benslama, Luis Bento, Daniela Benvenuti, Laura Bernabe, Andrew Bersten, Giacomo Berta, Pietro Bertini, Elliot Bertram-Ralph, Mohamed Besbes, Lisandro Roberto Bettini, Pascal Beuret, Jeremy Bewley, Marco Bezzi, Lakshay Bhakhtiani, Rakesh Bhandary, Kaushik Bhowmick, Shailesh Bihari, Bernie Bissett, David Blythe, Simon Bocher, Narain Boedjawan, Christine M Bojanowski, Elisa Boni, Sabrina Boraso, Massimo Borelli, Silvina Borello, Margarita Borislavova, Karen J Bosma, Maurizio Bottiroli, Owen Boyd, Suha Bozbay, Arturo Briva, Laurent Brochard, Cédric Bruel, Andrea Bruni, Ulrike Buehner, Pierre Bulpa, Karen Burt, Mathieu Buscot, Stefania Buttera, Jorge Cabrera, Roberta Caccese, Pietro Caironi, Ivan Canchos Gutierrez, Nancy Canedo, Alma Cani, Iacopo Cappellini, Jesus Carazo, Luis Pablo Cardonnet, David Carpio, Demetrio Carriedo, Ramón Carrillo, João Carvalho, Eliana Caser, Antonio Castelli, Manuel Castillo Quintero, Heloisa Castro, Nuno Catorze, Melike Cengiz, Enrique Cereijo, Helga Ceunen, Christos Chaintoutis, Youjin Chang, Gustavogcha Chaparro, Carmel Chapman, Simon Chau, Cecilia Eugenia Chavez, Cosimo Chelazzi, Jonathan Chelly, Frank Chemouni, Kai Chen, Ariel Chena, Paolo Chiarandini, Phil Chilton, Davide Chiumello, Yvette Chou-Lie, Nicolas Chudeau, Ismail Cinel, Gilda Cinnella, Michele Clark, Thomas Clark, Stefano Clementi, Luis Coaguila, Alexis Jaspe Codecido, Amy Collins, Riccardo Colombo, Juan Conde, Guglielmo Consales, Tim Cook, Andrea Coppadoro, Rodrigo Cornejo, Andrea Cortegiani, Cristina Coxo, Andrea Neville Cracchiolo, Mónica Crespo Ramirez, Philippe Crova, José Cruz, Lucia Cubattoli, Zafer Çukurova, Francesco Curto, Piotr Czempik, Rocco D'Andrea, Fernando da Silva Ramos, Laurence Dangers, Marc Danguy des Déserts, Pierre-Eric Danin, Fabianne Dantas, Cédric Daubin, 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Mariachiara Ippolito, Hiromasa Irie, Hiroki Iriyama, Taiga Itagaki, Javier Izura, Santiago Izza, Rakhshanda Jabeen, Hamidreza Jamaati, Sunil Jamadarkhana, Amira Jamoussi, Milosz Jankowski, Luis Alberto Jaramillo, Kyeongman Jeon, Seok Jeong Lee, Deepak Jeswani, Simant Jha, Liangyan Jiang, Chen Jing, Sébastien Jochmans, Bror Anders Johnstad, Lee Jongmin, Aurélie Joret, Detajin Junhasavasdikul, Maria Teresa Jurado, Elisa Kam, Hidenobu Kamohara, Caroline Kane, Iskender Kara, Sait Karakurt, Cherdkiat Karnjanarachata, Jun Kataoka, Shinshu Katayama, Shuchi Kaushik, Nermin Kelebek Girgin, Kathryn Kerr, Ian Kerslake, Prakash Khairnar, Abidi Khalid, Akram Khan, Ashish K Khanna, Reza Khorasanee, Dieneke Kienhorst, Cenk Kirakli, Rihard Knafelj, Mark Kol Kol, Napplika Kongpolprom, Csaba Kopitko, Pervin Korkmaz Ekren, Agnieszka Kubisz-Pudelko, Zoltan Kulcsar, Junji Kumasawa, Akira Kuriyama, Fernanda Kutchak, Eduardo Labarca, Françoise Labat, César Laborda, Manuel Alberto Laca Barrera, Laurie 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Maseda, Eleni Massa, Anna Mattsson, Jessica Maugeri, Victoria McCredie, James McCullough, Shay McGuinness, Andrew McKown, László Medve, Chengqing Mei, Ricard Mellado Artigas, Vitor Mendes, Mohamed Khalaf Ebraheim Mervat, Isabelle Michaux, Michael Mikhaeil, Olga Milagros, Igor Milet, Maria Teresa Millan, Zhang Minwei, Lucia Mirabella, Sanghamitra Mishra, Giovanni Mistraletti, Katsunori Mochizuki, Arif Moghal, Francesco Mojoli, Alexandre Molin, Raquel Montiel, Luca Montini (ORCID:0000-0003-4602-5134), Gianmario Monza, Maria Mora Aznar, Sunthiti Morakul, Maria Morales, Daniel Moreno Torres, Diego Rolando Morocho Tutillo, Catherine Motherway, Doumiri Mouhssine, Eleni Mouloudi, Tapia Muñoz, Carlos Munoz de Cabo, Mohamed Mustafa, Radhakrishnan Muthuchellappan, Muraleekrishnan Muthukrishnan, Stefano Muttini, Isao Nagata, Dick Nahar, Misuzu Nakanishi, Izumi Nakayama, Silvio Antonio Namendys-Silva, Rahul Nanchal, Sivakumar Nandakumar, Alessandra Nasi, Kamal Nasir, Paolo Navalesi, Tayyba Naz 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Joret, Aurélie, Junhasavasdikul, Detajin, Teresa Jurado, Maria, 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, K Khanna, Ashish, Khorasanee, Reza, Kienhorst, Dieneke, Kirakli, Cenk, Knafelj, Rihard, Kol Kol, Mark, Kongpolprom, Napplika, Kopitko, Csaba, Korkmaz Ekren, Pervin, Kubisz-Pudelko, Agnieszka, Kulcsar, Zoltan, Kumasawa, Junji, Kuriyama, Akira, Kutchak, Fernanda, Labarca, Eduardo, Labat, Françoise, Laborda, César, Alberto Laca Barrera, Manuel, Lagache, Laurie, Landaverde Lopez, Antonio, Lanspa, Michael, Lascari, Valeria, Le Meur, Matthieu, Hwan Lee, Su, Ju Lee, Young, Lee, Jinwoo, Lee, Won-Yeon, Lee, Jarone, Legernaes, Terje, Leiner, Tamaa, Lemiale, Virginie, Leonor, Tiago, M Lepper, Philipp, Li, Dahuan, Li, Hongbin, Li, Oleg, Raquel Lima, Ana, Lind, Dan, Litton, Edward, Liu, Ning, Liu, Ling, Liu, Jialin, Llitjos, Jean-Françoi, Llorente, Beatriz, Lopez, Rodolfo, Elizabeth Lopez, Claudia, Lopez Nava, Claudia, Lovazzano, Pablo, Lu, Min, Lucchese, Francesca, Lugano, Manuela, Lugo Goytia, Gustavo, Luo, Hua, Lynch, Ceri, Macheda, Sebastiano, Hugo Madrigal Robles, Victor, Maurizio Maggiore, Salvatore, Magret Iglesias, Mònica, Malaga, Peter, Mallapura Maheswarappa, Harish, Malpartida, Guillermo, Malyarchikov, Andrey, Mansson, Helena, Manzano, Anaid, Marey, Ismael, Marin, Nathalie, Del Carmen Marin, Maria, 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, Jame, Mcguinness, Shay, Mckown, Andrew, Medve, László, Mei, Chengqing, Mellado Artigas, Ricard, Mendes, Vitor, Khalaf Ebraheim Mervat, Mohamed, Michaux, Isabelle, Mikhaeil, 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Manzano, Ismael Marey, Nathalie Marin, Maria Del Carmen Marin, Eliana Markman, Felix Martin, Alex Martin, Cristina Martin Dal Gesso, Felipe Martinez, Conchita Martínez-Fidalgo, Ignacio Martin-Loeches, Arantxa Mas, Sakuraya Masaaki, Emilio Maseda, Eleni Massa, Anna Mattsson, Jessica Maugeri, Victoria McCredie, James McCullough, Shay McGuinness, Andrew McKown, László Medve, Chengqing Mei, Ricard Mellado Artigas, Vitor Mendes, Mohamed Khalaf Ebraheim Mervat, Isabelle Michaux, Michael Mikhaeil, Olga Milagros, Igor Milet, Maria Teresa Millan, Zhang Minwei, Lucia Mirabella, Sanghamitra Mishra, Giovanni Mistraletti, Katsunori Mochizuki, Arif Moghal, Francesco Mojoli, Alexandre Molin, Raquel Montiel, Luca Montini (ORCID:0000-0003-4602-5134), Gianmario Monza, Maria Mora Aznar, Sunthiti Morakul, Maria Morales, Daniel Moreno Torres, Diego Rolando Morocho Tutillo, Catherine Motherway, Doumiri Mouhssine, Eleni Mouloudi, Tapia Muñoz, Carlos Munoz de Cabo, Mohamed Mustafa, Radhakrishnan Muthuchellappan, Muraleekrishnan Muthukrishnan, Stefano Muttini, Isao Nagata, Dick Nahar, Misuzu Nakanishi, Izumi Nakayama, Silvio Antonio Namendys-Silva, Rahul Nanchal, Sivakumar Nandakumar, Alessandra Nasi, Kamal Nasir, Paolo Navalesi, Tayyba Naz Aslam, Thuy Nga Phan, Alistair Nichol, Shuhei Niiyama, Sofia Nikolakopoulou, Elena Nikolic, Kenichi Nitta, Marko Noc, Stephanie Nonas, Saad Nseir, Ayse Nur Soyturk, Yukako Obata, Richard Oeckler, Moe Oguchi, Shinichiro Ohshimo, Marina Oikonomou, Agueda Ojados, Maria Teresa Oliveira, Wilson Oliveira Filho, Carlo Oliveri, Aitor Olmos, Kazuya Omura, Maria Cristina Orlandi, Francesca Orsenigo, Laura Ortiz-Ruiz De Gordoa, Kei Ota, Rainier Ovalle Olmos, Nándo Öveges, Peter Oziemski, Ozlem Ozkan Kuscu, Ezgi Özyilmaz, Fernando Pachas Alvarado, Gonzalo Pagella, Vijayanand Palaniswamy, Eugenio Luis Palazon Sanchez, Salvatore Palmese, Guojun Pan, Wensen Pan, Metaxia Papanikolaou, Theonymfi Papavasilopoulou, Ameet Parekh, Rachael Parke, Francisco J Parrilla, Dácil Parrilla, Taha Pasha, Laura Pasin, Luis Patão, Mayur Patel, Grisma Patel, Basanta Kumar Pati, Jayaprakash Patil, Saroj Pattnaik, Daniel Paul, Maurizio Pavesi, Vanesa Alejandra Pavlotsky, Graciela Paz, Enrique Paz, Elisabetta Pecci, Carlos Pellegrini, Andrea Gabriela Peña Padilla, Gaetano Perchiazzi, Tiago Pereira, Vera Pereira, Manuel Perez, Cesar Perez Calvo, Meisy Perez Cheng, Ronald Perez Maita, Rodrigo Pérez-Araos, Purificación Perez-Teran, David Perez-Torres, Gavin Perkins, Paolo Persona, Tananchai Petnak, Marina Petrova, Tai Pham, François Philippart, Edoardo Picetti, Elisabetta Pierucci, Edoardo Piervincenzi, Riccardo Pinciroli, Maria-Consuelo Pintado, Thomas Piraino, Stephanie Piras, Claudio Piras, Pattarin Pirompanich, Luigi Pisani, Enrique Platas, Gustavo Plotnikow, Willy Porras, Virginia Porta, Mariana Portilla, José Portugal, Pedro Povoa, Gwenael Prat, Romina Pratto, Gabriel Preda, Isidro Prieto, Estefania Prol-Silva, Richard Pugh, Yupeng Qi, Chuanyun Qian, Tiehe Qin, Hongping Qu, Teobaldo Quintana, Rosari Quispe Sierra, Rocio Quispe Soto, Raihan Rabbani, Mohamed Rabee, Ahmed Rabie, Maria Augusta Rahe Pereira, Ashish Rai, Sundar Raj Ashok, Mostafa Rajab, Navin Ramdhani, Elizabeth Ramey, Marco Ranieri, Darshana Rathod, Banambar Ray, Shihan Mahmud Redwanul Huq, Adrian Regli, Rosa Reina, Natalia Resano Sarmiento, Faustine Reynaud, Gemma Rialp, Pilar Ricart, Todd Rice, Angus Richardson, Marcelo Rieder, Martin Rinket, Fernando Rios, Alejandro Risso Vazquez, Ivano Riva, Monaly Rivette, Oriol Roca, Ferran Roche-Campo, Covadonga Rodriguez, Gabriel Rodriguez, Daniel Rodriguez Gonzalez, Xandra Yanina Rodriguez Tucto, Angela Rogers, María Elena Romano, Linda Rørtveit, Alastair Rose, Damien Roux, Anahita Rouze, Paolo Nahuel Rubatto Birri, Wang Ruilan, Aldana Ruiz Robledo, Antonio Luis Ruiz-Aguilar, Tomohito Sadahiro, Ignacio Saez, Judith Sagardia, Rajnish Saha, Rohit Saha, Narongkorn Saiphoklang, Shigeki Saito, Maie Salem, Gabriele Sales, Patricia Salgado, Srinivas Samavedam, Mhamed Sami Mebazaa, Line Samuelsson, Nandyelly San Juan Roman, Patricia Sanchez, Jesus Sanchez-Ballesteros, Yazcitk Sandoval, Emanuele Sani, Martin Santos, Carla Santos, Masamitsu Sanui, Lakshmikanthcharan Saravanabavan, Sema Sari, Agnes Sarkany, Bertrand Sauneuf, Monica Savioli, Hilal Sazak, Riccardo Scano, Francis Schneider, Frédérique Schortgen, Marcus J Schultz, Gabriele Leonie Schwarz, Faruk Seçkin Yücesoy, Andrew Seely, Frederik Seiler, Yasemin Seker Tekdos, Kim Seok Chan, Luca Serano, Wojciech Serednicki, Mariano Setten, Asim Shah, Bhagyesh Shah, You Shang, Pradeep Shanmugasundaram, Konstantin Shapovalov, Eman Shebl, Takuya Shiga, Nobuaki Shime, Phil Shin, Jack Short, Chen Shuhua, Sughrat Siddiqui, Juan Ignacio Silesky Jimenez, Daniel Silva, Betania Silva Sales, Koen Simons, Brit Ågot Sjøbø, David Slessor, Jakub Smiechowicz, Nathan Smischney, Paul Smith, Tim Smith, Mark Smith, Sarah Snape, Lindi Snyman, Filiep Soetens, Kyung Sook Hong, Miguel Ángel Sosa Medellin, Giovanna Soto, Xavier Souloy, Elsa Sousa, Stefania Sovatzis, Didem Sozutek, Savino Spadaro, Marco Spagnoli, Martin Spångfors, Nick Spittle, Mike Spivey, Andrew Stapleton, Branislava Stefanovic, Lorraine Stephenson, Elizabeth Stevenson, Kristian Strand, Maria Teresa Strano, Slavenka Straus, Chenliang Sun, Rongqing Sun, Venkat Sundaram, Tai SunPark, Elisabeth Surlemont, Yuda Sutherasan, Zsuzsanna Szabo, Christopher Tainter, Akihiro Takaba, Mandy Tallott, Tamasato Tamasato, Zhanhong Tang, Viratch Tangsujaritvijit, Leandro Taniguchi, Daisuke Taniguchi, Fabio Tarantino, Krittika Teerapuncharoen, Susana Temprano, Pierpaolo Terragni, Nicolas Terzi, Anand Thakur, Pongdhep Theerawit, Arnaud W Thille, Matt Thomas, Poungrat Thungtitigul, Martial Thyrault, Nejla Tilouch, Karina Timenetsky, Juna Tirapu, Manuel Todeschini, Roser Tomas, Christian Tomaszewski, Tommaso Tonetti, Alexandre Tonnelier, John Trinder, Konlawij Trongtrakul, Jonathon Truwit, Betty Tsuei, Aiman Tulaimat, Sema Turan, Melda Turkoglu, Sanjeev Tyagi, Alejandro Ubeda, Federica Vagginelli, María Florencia Valenti, Imma Vallverdu, Alisha Van Axel, Ingrid van den Hul, Hans van der Hoeven, Nardo Van Der Meer, Marc Vanhoof, Mónica Vargas-Ordoñez, Rosanna Vaschetto, Ettore Vascotto, Maria Vatsik, Ana Vaz, Antonia Vazquez-Sanchez, Sara Ventura, Jan Wytze Vermeijden, Anxela Vidal, Jocyelle Vieira, Bruno Vilela Costa Pinto, Ana Villagra, Cristina Villegas Succar, Ole Georg Vinorum, Giovanni Vitale, Ramesh Vj, Ana Vochin, Guillaume Voiriot, Carlo Alberto Volta, Magnus von Seth, Maazouzi Wajdi, Don Walsh, Shouhong Wang, Gabriel Wardi, Nils Christian Ween-Velken, Bi-Lin Wei, Dolf Weller, Deborah Welsh, Ingeborg Welters, Michael Wert, Simon Whiteley, Elizabeth Wilby, Erin Williams, Karen Williams, Antoinette Wilson, Jadwiga Wojtas, Jin Won Huh, David Wrathall, Christopher Wright, Jian-Feng Wu, Guo Xi, Zheng-Jiang Xing, Hongyang Xu, Kotaro Yamamoto, Jie Yan, Julio Yáñez, Xiaobo Yang, Elliot Yates, Ozlem Yazicioglu Mocin, Zhenglong Ye, Fatma Yildirim, Norifumi Yoshida, Hector Higo Leon Yoshido, Bo Young Lee, Rongguo Yu, Gong Yu, Tao Yu, Boyun Yuan, Nadwipa Yuangtrakul, Tetsuya Yumoto, Xie Yun, Graciela Zakalik, Ahmad Zaki, Begoña Zalba-Etayo, Massimo Zambon, Bin Zang, Gianluca Zani, Jonathan Zarka, Simone Maria Zerbi, Avsar Zerman, Harald Zetterquist, Jiuzhi Zhang, Hongwen Zhang, Wei Zhang, Guoxiu Zhang, Weixin Zhang, Hongsheng Zhao, Jia Zheng, Bin Zhu, and Ronald Zumaran
Abstract: Background: Current management practices and outcomes in weaning from invasive mechanical ventilation are poorly understood. We aimed to describe the epidemiology, management, timings, risk for failure, and outcomes of weaning in patients requiring at least 2 days of invasive mechanical ventilation. Methods: WEAN SAFE was an international, multicentre, prospective, observational cohort study done in 481 intensive care units in 50 countries. Eligible participants were older than 16 years, admitted to a participating intensive care unit, and receiving mechanical ventilation for 2 calendar days or longer. We defined weaning initiation as the first attempt to separate a patient from the ventilator, successful weaning as no reintubation or death within 7 days of extubation, and weaning eligibility criteria based on positive end-expiratory pressure, fractional concentration of oxygen in inspired air, and vasopressors. The primary outcome was the proportion of patients successfully weaned at 90 days. Key secondary outcomes included weaning duration, timing of weaning events, factors associated with weaning delay and weaning failure, and hospital outcomes. This study is registered with ClinicalTrials.gov, NCT03255109. Findings: Between Oct 4, 2017, and June 25, 2018, 10 232 patients were screened for eligibility, of whom 5869 were enrolled. 4523 (77·1%) patients underwent at least one separation attempt and 3817 (65·0%) patients were successfully weaned from ventilation at day 90. 237 (4·0%) patients were transferred before any separation attempt, 153 (2·6%) were transferred after at least one separation attempt and not successfully weaned, and 1662 (28·3%) died while invasively ventilated. The median time from fulfilling weaning eligibility criteria to first separation attempt was 1 day (IQR 0-4), and 1013 (22·4%) patients had a delay in initiating first separation of 5 or more days. Of the 4523 (77·1%) patients with separation attempts, 2927 (64·7%) had a short wean (≤1 d
Published: 2023

2. MILP Acceleration: A Survey from Perspectives of Simplex Initialization and Learning-Based Branch and Bound

Author: Huang, Mengyu, Huang, Lingying, Zhong, Yuxing, Yang, Huiwen, Chen, Xiaomeng, Huo, Wei, Wang, Jia-Zheng, Zhang, Fan, Bai, Bo, Shi, Ling, Huang, Mengyu, Huang, Lingying, Zhong, Yuxing, Yang, Huiwen, Chen, Xiaomeng, Huo, Wei, Wang, Jia-Zheng, Zhang, Fan, Bai, Bo, and Shi, Ling
Abstract: Mixed integer linear programming (MILP) is an NP-hard problem, which can be solved by the branch and bound algorithm by dividing the original problem into several subproblems and forming a search tree. For each subproblem, linear programming (LP) relaxation can be solved to find the bound for making the following decisions. Recently, with the increasing dimension of MILPs in different applications, how to accelerate the solution process becomes a huge challenge. In this survey, we summarize techniques and trends to speed up MILP solving from two perspectives. First, we present different approaches in simplex initialization, which can help to accelerate the solution of LP relaxation for each subproblem. Second, we introduce the learning-based technologies in branch and bound algorithms to improve decision making in tree search. We also propose several potential directions and extensions to further enhance the efficiency of solving different MILP problems. © 2023, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature.
Published: 2023

3. Distance and orientation-based formation control of UAVs and coordination with UGVs

Author: Universitat Politècnica de Catalunya. Departament d'Enginyeria Química, Lunds universitet, Pérez González, Juan Jesús, Robertsson, Anders, Olofsson, Björn, Jia, Zheng, Omodolor, Stevedan Ogochukwu, Universitat Politècnica de Catalunya. Departament d'Enginyeria Química, Lunds universitet, Pérez González, Juan Jesús, Robertsson, Anders, Olofsson, Björn, Jia, Zheng, and Omodolor, Stevedan Ogochukwu
Abstract: Nowadays, research in autonomous drones has increased thanks to the advancement of drone technology. Nevertheless, there are still limitations when performing specific missions due to flight duration, computational load and mission complexity. This thesis investigates ways to solve this problem by taking advantage of multiple UAVs and UGVs. This thesis aims to implement and evaluate strategies for formation and coordination of multiple UAVs and UGVs. Firstly, we present a brief review of state of the art on formation and flocking control, further specifying the advantages and limitations of each approach. Secondly, we use a behaviour-based approach to obtain multi-UAV formation control. We adapt the algorithm to apply it to a single integrator system model to control the UGVs’ formation. We then propose an extension to the original algorithm to consider orientation during formation and a leader-follower strategy to coordinate the interaction between the units using a cluster-based approach. Finally, we tested our proposed control laws in simulation and in experiments. The simulations were done in Matlab, while the real-implementation experiments were performed using the Crazyflie quadcopters and three-wheeled omniwheel robots
Published: 2022

4. The Wheelbot: A Jumping Reaction Wheel Unicycle

Author: Geist, A. René, Fiene, Jonathan, Tashiro, Naomi, Jia, Zheng, Trimpe, Sebastian, Geist, A. René, Fiene, Jonathan, Tashiro, Naomi, Jia, Zheng, and Trimpe, Sebastian
Abstract: Combining off-the-shelf components with 3D-printing, the Wheelbot is a symmetric reaction wheel unicycle that can jump onto its wheels from any initial position. With non-holonomic and under-actuated dynamics, as well as two coupled unstable degrees of freedom, the Wheelbot provides a challenging platform for nonlinear and data-driven control research. This paper presents the Wheelbot's mechanical and electrical design, its estimation and control algorithms, as well as experiments demonstrating both self-erection and disturbance rejection while balancing., Comment: Erratum: In the initial publication, Equation (3) was wrong and has been corrected in this version. Equation (3) relates to the transform from averaged body rates ${}^{\text{B}}\omega_i$ to Euler rates. Importantly, the results in this papers are not affected by the wrong transform. More details are found in the projects github repo: https://github.com/AndReGeist/wheelbot-v2.5
Published: 2022

5. Investigating the use of eye fixation data for emotion classification in VR

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eyetracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’s circumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification
Published: 2021

6. Investigating the use of eye fixation data for emotion classification in VR

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eyetracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’s circumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification
Published: 2021

7. Investigating the use of eye fixation data for emotion classification in VR

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eyetracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’s circumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification
Published: 2021

8. Investigating the use of eye fixation data for emotion classification in VR

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eyetracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’s circumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification
Published: 2021

9. Investigating the use of eye fixation data for emotion classification in VR

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eyetracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’s circumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification
Published: 2021

10. Investigating the use of eye fixation data for emotion classification in VR

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eyetracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’s circumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification
Published: 2021

11. A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Research on emotion recognition that relies purely on eye-tracking data is very limited although the usability of eye-tracking technology has great potential for emotional recognition. This paper proposes a novel approach for 4-class emotion classification using eye-tracking data solely in virtual reality (VR) with machine learning algorithms. We classify emotions into four specific classes using VR stimulus. Eye fixation data was used as the emotional-relevant feature in this investigation. A presentation of 360 0 videos, which contains four different sessions, was played in VR to evoke the user’s emotions. The eye-tracking data was collected and recorded using an add-on eye-tracker in the VR headset. Three classifiers were used in the experiment, which are k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). The findings showed that RF has the best performance among the classifiers, and achieved the highest accuracy of 80.55%.
Published: 2021

12. A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Research on emotion recognition that relies purely on eye-tracking data is very limited although the usability of eye-tracking technology has great potential for emotional recognition. This paper proposes a novel approach for 4-class emotion classification using eye-tracking data solely in virtual reality (VR) with machine learning algorithms. We classify emotions into four specific classes using VR stimulus. Eye fixation data was used as the emotional-relevant feature in this investigation. A presentation of 360 0 videos, which contains four different sessions, was played in VR to evoke the user’s emotions. The eye-tracking data was collected and recorded using an add-on eye-tracker in the VR headset. Three classifiers were used in the experiment, which are k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). The findings showed that RF has the best performance among the classifiers, and achieved the highest accuracy of 80.55%.
Published: 2021

13. A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Research on emotion recognition that relies purely on eye-tracking data is very limited although the usability of eye-tracking technology has great potential for emotional recognition. This paper proposes a novel approach for 4-class emotion classification using eye-tracking data solely in virtual reality (VR) with machine learning algorithms. We classify emotions into four specific classes using VR stimulus. Eye fixation data was used as the emotional-relevant feature in this investigation. A presentation of 360 0 videos, which contains four different sessions, was played in VR to evoke the user’s emotions. The eye-tracking data was collected and recorded using an add-on eye-tracker in the VR headset. Three classifiers were used in the experiment, which are k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). The findings showed that RF has the best performance among the classifiers, and achieved the highest accuracy of 80.55%.
Published: 2021

14. A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Research on emotion recognition that relies purely on eye-tracking data is very limited although the usability of eye-tracking technology has great potential for emotional recognition. This paper proposes a novel approach for 4-class emotion classification using eye-tracking data solely in virtual reality (VR) with machine learning algorithms. We classify emotions into four specific classes using VR stimulus. Eye fixation data was used as the emotional-relevant feature in this investigation. A presentation of 360 0 videos, which contains four different sessions, was played in VR to evoke the user’s emotions. The eye-tracking data was collected and recorded using an add-on eye-tracker in the VR headset. Three classifiers were used in the experiment, which are k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). The findings showed that RF has the best performance among the classifiers, and achieved the highest accuracy of 80.55%.
Published: 2021

15. Cell-Penetrating Peptide-Modified Graphene Oxide Nanoparticles Loaded with Rictor siRNA for the Treatment of Triple-Negative Breast Cancer

Author: Yang,Yun-Yun, Zhang,Wei, Liu,Hui, Jiang,Jun-Jie, Wang,Wen-Jie, Jia,Zheng-Yan, Yang,Yun-Yun, Zhang,Wei, Liu,Hui, Jiang,Jun-Jie, Wang,Wen-Jie, and Jia,Zheng-Yan
Abstract: Yun-Yun Yang,1 Wei Zhang,2 Hui Liu,2 Jun-Jie Jiang,2 Wen-Jie Wang,3 Zheng-Yan Jia4 1Outpatient Comprehensive Treatment, Cangzhou Central Hospital, Cangzhou, Hebei Province, Peopleâs Republic of China; 2Department of Thyroid and Breast I, Cangzhou Central Hospital, Cangzhou, Hebei Province, Peopleâs Republic of China; 3Department of General Surgery, Botou Hospital, Cangzhou, Hebei Province, Peopleâs Republic of China; 4Department of General Surgery, Qingxian Peopleâs Hospital, Cangzhou, Hebei Province, Peopleâs Republic of ChinaCorrespondence: Wei ZhangDepartment of Thyroid and Breast I, Cangzhou Central Hospital, Cangzhou, Hebei Province, Peopleâs Republic of ChinaEmail weiesiz685125@163.comIntroduction: Breast cancer is a malignant tumor that seriously threatens womenâs life and health.Methods: In this study, we proposed to use graphene nanoparticles loaded with siRNA that can silence Rictor molecules essential for the mammalian target of rapamycin (mTOR) complex 2 (mTORC2) complex to enhance gene delivery to tumor cells through modification of cell-penetrating peptide (CPP) for the treatment of breast cancer.Results: Remarkably, we successfully synthesized graphene oxide (GO)/polyethyleneimine (PEI)/polyethylene glycol (PEG)/CPP/small interfering RNA (siRNA) system, and the results were observed by atomic force microscopy (AFM) and ultraviolet visible (UV-Vis) absorption spectra. The optimum mass ratio of siRNA to GO-PEI-PEG-CPP was 1:0.5. We screened out Rictor siRNA-2 from 9 candidates, which presented the highest inhibition rate, and this siRNA was selected for the subsequent experiments. We validated that Rictor siRNA-2 significantly reduced the Rictor expression in triple negative breast cancer (TNBC) cells. Confocal fluorescence microscope and flow cytometry analysis showed that GO-PEI-PEG-CPP/siRNA was able to be effectively uptake by TNBC cells. GO-PEI-PEG-CPP/siRNA improved the effect of siRNA on the inhibition of TNBC cell viability and the
Published: 2021

16. Distributed Estimation, Control and Coordination of Quadcopter Swarm Robots

Author: Jia, Zheng, Hamer, Michael, D'Andrea, Raffaello, Jia, Zheng, Hamer, Michael, and D'Andrea, Raffaello
Abstract: In this thesis we are interested in applying distributed estimation, control and optimization techniques to enable a group of quadcopters to fly through openings. The quadcopters are assumed to be equipped with a simulated bearing and distance sensor for localization. Some quadcopters are designated as leaders who carry global position sensors. We assume quadcopters can communicate information with each other.
Published: 2021

17. An Economy Efficiency Analysis of Non Pearl River Delta Region and nearby cities in Guangdong of China

Author: Jia-Zheng Lin, Dr. Hyung-Ho Kim, Jia-Zheng Lin, and Dr. Hyung-Ho Kim
Abstract: The Non Pearl River delta region is the weak zone of economy development in Guangdong province and it's lack of discussion about economic efficiency all the time. The purpose of this study is aim to evaluate the economy efficiency of Non Pearl River Delta Region cities relatively, so the nearby cities such as Foshan, Huizhou, Zhongshan, Jiangmen and Zhaoqing were brought in, by analyzed the data from Guangdong year book in 2014-2018 with DEA-Malmquist and SSBM analysis method, the results show that the efficiency of economic development difference between each city is bigger, north region and east region is generally low and some problems had be found. In this study three aspects were presented according the analysis result, such as the allocation of resources, scientific and technological innovation, coordinated development between regions. Those recommendations would be useful for the region's manager to make an efficient decision of economy development and balance the development level of the cities in Guangdong province China.
Published: 2021

18. An Economy Efficiency Analysis of Non Pearl River Delta Region and nearby cities in Guangdong of China

Author: Jia-Zheng Lin, Dr. Hyung-Ho Kim, Jia-Zheng Lin, and Dr. Hyung-Ho Kim
Abstract: The Non Pearl River delta region is the weak zone of economy development in Guangdong province and it's lack of discussion about economic efficiency all the time. The purpose of this study is aim to evaluate the economy efficiency of Non Pearl River Delta Region cities relatively, so the nearby cities such as Foshan, Huizhou, Zhongshan, Jiangmen and Zhaoqing were brought in, by analyzed the data from Guangdong year book in 2014-2018 with DEA-Malmquist and SSBM analysis method, the results show that the efficiency of economic development difference between each city is bigger, north region and east region is generally low and some problems had be found. In this study three aspects were presented according the analysis result, such as the allocation of resources, scientific and technological innovation, coordinated development between regions. Those recommendations would be useful for the region's manager to make an efficient decision of economy development and balance the development level of the cities in Guangdong province China.
Published: 2021

19. Investigating the Use of Eye Fixation Data for Emotion Classification in VR

Author: et.al, Lim Jia Zheng and et.al, Lim Jia Zheng
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eye-tracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’scircumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification.
Published: 2021

20. Investigating the Use of Eye Fixation Data for Emotion Classification in VR

Author: et.al, Lim Jia Zheng and et.al, Lim Jia Zheng
Abstract: Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eye-tracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’scircumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification.
Published: 2021

21. Red-phosphorus-impregnated carbon nanofibers for sodium-ion batteries and liquefaction of red phosphorus.

Author: Liu, Yihang, Liu, Yihang, Liu, Qingzhou, Jian, Cheng, Cui, Dingzhou, Chen, Mingrui, Li, Zhen, Li, Teng, Nilges, Tom, He, Kai, Jia, Zheng, Zhou, Chongwu, Liu, Yihang, Liu, Yihang, Liu, Qingzhou, Jian, Cheng, Cui, Dingzhou, Chen, Mingrui, Li, Zhen, Li, Teng, Nilges, Tom, He, Kai, Jia, Zheng, and Zhou, Chongwu
Abstract: Red phosphorus offers a high theoretical sodium capacity and has been considered as a candidate anode for sodium-ion batteries. Similar to silicon anodes for lithium-ion batteries, the electrochemical performance of red phosphorus is plagued by the large volume variation upon sodiation. Here we perform in situ transmission electron microscopy analysis of the synthesized red-phosphorus-impregnated carbon nanofibers with the corresponding chemo-mechanical simulation, revealing that, the sodiated red phosphorus becomes softened with a liquid-like mechanical behaviour and gains superior malleability and deformability against pulverization. The encapsulation strategy of the synthesized red-phosphorus-impregnated carbon nanofibers has been proven to be an effective method to minimize the side reactions of red phosphorus in sodium-ion batteries, demonstrating stable electrochemical cycling. Our study provides a valid guide towards high-performance red-phosphorus-based anodes for sodium-ion batteries.
Published: 2020

22. Four-class emotion classification in virtual reality using pupillometry

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Background: Emotion classifcation remains a challenging problem in afective computing. The large majority of emotion classifcation studies rely on electroencephalography (EEG) and/or electrocardiography (ECG) signals and only classifes the emotions into two or three classes. Moreover, the stimuli used in most emotion classifcation studies utilize either music or visual stimuli that are presented through conventional displays such as computer display screens or television screens. This study reports on a novel approach to recognizing emotions using pupillometry alone in the form of pupil diameter data to classify emotions into four distinct classes according to Russell’s Circumplex Model of Emotions, utilizing emotional stimuli that are presented in a virtual reality (VR) environment. The stimuli used in this experiment are 360° videos presented using a VR headset. Using an eye-tracker, pupil diameter is acquired as the sole classifcation feature. Three classifers were used for the emotion classifcation which are Support Vector Machine (SVM), k-Nearest Neighbor (KNN), and Random Forest (RF). Findings: SVM achieved the best performance for the four-class intra-subject classifcation task at an average of 57.05% accuracy, which is more than twice the accuracy of a random classifer. Although the accuracy can still be signifcantly improved, this study reports on the frst systematic study on the use of eye-tracking data alone without any other supplementary sensor modalities to perform human emotion classifcation and demonstrates that even with a single feature of pupil diameter alone, emotions could be classifed into four distinct classes to a certain level of accuracy. Moreover, the best performance for recognizing a particular class was 70.83%, which was achieved by the KNN classifer for Quadrant 3 emotions. Conclusion: This study presents the frst systematic investigation on the use of pupillometry as the sole feature to classify emotions into four distinct classes usi
Published: 2020

23. Comparing Eye-Tracking versus EEG Features for Four-Class Emotion Classification in VR Predictive Analytics

Author: Lim, Jia Zheng, James Mountstephens, Jason Teo, Lim, Jia Zheng, James Mountstephens, and Jason Teo
Abstract: This paper presents a novel emotion recognition approach using electroencephalography (EEG) brainwave signals augmented with eye-tracking data in virtual reality (VR) to classify 4-quadrant circumplex model of emotions. 3600 videos are used as the stimuli to evoke user’s emotions (happy, angry, bored, calm) with a VR headset and a pair of earphones. EEG signals are recorded via a wearable EEG brain-computer interfacing (BCI) device and pupil diameter is collected also from a wearable portable eye-tracker. We extract 5 frequency bands which are Delta, Theta, Alpha, Beta, and Gamma from EEG data as well as obtaining pupil diameter from the eye-tracker as the chosen as the eye-related feature for this investigation. Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel is used as the classifier. The best accuracies based on EEG brainwave signals and pupil diameter are 98.44% and 58.30% respectively.
Published: 2020

24. Four class emotion classifcation in virtual reality using pupillometry

Author: Lim, Jia Zheng, James Mountstephens, Jason Teo, Lim, Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Background: Emotion classifcation remains a challenging problem in afective computing. The large majority of emotion classifcation studies rely on electroencephalography (EEG) and/or electrocardiography (ECG) signals and only classifes the emotions into two or three classes. Moreover, the stimuli used in most emotion classifcation studies utilize either music or visual stimuli that are presented through conventional displays such as computer display screens or television screens. This study reports on a novel approach to recognizing emotions using pupillometry alone in the form of pupil diameter data to classify emotions into four distinct classes according to Russell’s Circumplex Model of Emotions, utilizing emotional stimuli that are presented in a virtual reality (VR) environment. The stimuli used in this experiment are 360° videos presented using a VR headset. Using an eye-tracker, pupil diameter is acquired as the sole classifcation feature. Three classifers were used for the emotion classifcation which are Support Vector Machine (SVM), k-Nearest Neighbor (KNN), and Random Forest (RF). Findings: SVM achieved the best performance for the four-class intra-subject classifcation task at an average of 57.05% accuracy, which is more than twice the accuracy of a random classifer. Although the accuracy can still be signifcantly improved, this study reports on the frst systematic study on the use of eye-tracking data alone without any other supplementary sensor modalities to perform human emotion classifcation and demonstrates that even with a single feature of pupil diameter alone, emotions could be classifed into four distinct classes to a certain level of accuracy. Moreover, the best performance for recognizing a particular class was 70.83%, which was achieved by the KNN classifer for Quadrant 3 emotions. Conclusion: This study presents the frst systematic investigation on the use of pupillometry as the sole feature to classify emotions into four distinct classes usi
Published: 2020

25. Four-class emotion classification in virtual reality using pupillometry

Author: Lim Jia Zheng, James Mountstephens, Jason Teo, Lim Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Background: Emotion classifcation remains a challenging problem in afective computing. The large majority of emotion classifcation studies rely on electroencephalography (EEG) and/or electrocardiography (ECG) signals and only classifes the emotions into two or three classes. Moreover, the stimuli used in most emotion classifcation studies utilize either music or visual stimuli that are presented through conventional displays such as computer display screens or television screens. This study reports on a novel approach to recognizing emotions using pupillometry alone in the form of pupil diameter data to classify emotions into four distinct classes according to Russell’s Circumplex Model of Emotions, utilizing emotional stimuli that are presented in a virtual reality (VR) environment. The stimuli used in this experiment are 360° videos presented using a VR headset. Using an eye-tracker, pupil diameter is acquired as the sole classifcation feature. Three classifers were used for the emotion classifcation which are Support Vector Machine (SVM), k-Nearest Neighbor (KNN), and Random Forest (RF). Findings: SVM achieved the best performance for the four-class intra-subject classifcation task at an average of 57.05% accuracy, which is more than twice the accuracy of a random classifer. Although the accuracy can still be signifcantly improved, this study reports on the frst systematic study on the use of eye-tracking data alone without any other supplementary sensor modalities to perform human emotion classifcation and demonstrates that even with a single feature of pupil diameter alone, emotions could be classifed into four distinct classes to a certain level of accuracy. Moreover, the best performance for recognizing a particular class was 70.83%, which was achieved by the KNN classifer for Quadrant 3 emotions. Conclusion: This study presents the frst systematic investigation on the use of pupillometry as the sole feature to classify emotions into four distinct classes usi
Published: 2020

26. Comparing Eye-Tracking versus EEG Features for Four-Class Emotion Classification in VR Predictive Analytics

Author: Lim, Jia Zheng, James Mountstephens, Jason Teo, Lim, Jia Zheng, James Mountstephens, and Jason Teo
Abstract: This paper presents a novel emotion recognition approach using electroencephalography (EEG) brainwave signals augmented with eye-tracking data in virtual reality (VR) to classify 4-quadrant circumplex model of emotions. 3600 videos are used as the stimuli to evoke user’s emotions (happy, angry, bored, calm) with a VR headset and a pair of earphones. EEG signals are recorded via a wearable EEG brain-computer interfacing (BCI) device and pupil diameter is collected also from a wearable portable eye-tracker. We extract 5 frequency bands which are Delta, Theta, Alpha, Beta, and Gamma from EEG data as well as obtaining pupil diameter from the eye-tracker as the chosen as the eye-related feature for this investigation. Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel is used as the classifier. The best accuracies based on EEG brainwave signals and pupil diameter are 98.44% and 58.30% respectively.
Published: 2020

27. Four class emotion classifcation in virtual reality using pupillometry

Author: Lim, Jia Zheng, James Mountstephens, Jason Teo, Lim, Jia Zheng, James Mountstephens, and Jason Teo
Abstract: Background: Emotion classifcation remains a challenging problem in afective computing. The large majority of emotion classifcation studies rely on electroencephalography (EEG) and/or electrocardiography (ECG) signals and only classifes the emotions into two or three classes. Moreover, the stimuli used in most emotion classifcation studies utilize either music or visual stimuli that are presented through conventional displays such as computer display screens or television screens. This study reports on a novel approach to recognizing emotions using pupillometry alone in the form of pupil diameter data to classify emotions into four distinct classes according to Russell’s Circumplex Model of Emotions, utilizing emotional stimuli that are presented in a virtual reality (VR) environment. The stimuli used in this experiment are 360° videos presented using a VR headset. Using an eye-tracker, pupil diameter is acquired as the sole classifcation feature. Three classifers were used for the emotion classifcation which are Support Vector Machine (SVM), k-Nearest Neighbor (KNN), and Random Forest (RF). Findings: SVM achieved the best performance for the four-class intra-subject classifcation task at an average of 57.05% accuracy, which is more than twice the accuracy of a random classifer. Although the accuracy can still be signifcantly improved, this study reports on the frst systematic study on the use of eye-tracking data alone without any other supplementary sensor modalities to perform human emotion classifcation and demonstrates that even with a single feature of pupil diameter alone, emotions could be classifed into four distinct classes to a certain level of accuracy. Moreover, the best performance for recognizing a particular class was 70.83%, which was achieved by the KNN classifer for Quadrant 3 emotions. Conclusion: This study presents the frst systematic investigation on the use of pupillometry as the sole feature to classify emotions into four distinct classes usi
Published: 2020

28. Comparing Eye-Tracking versus EEG Features for Four-Class Emotion Classification in VR Predictive Analytics

Author: Lim, Jia Zheng, James Mountstephens, Jason Teo, Lim, Jia Zheng, James Mountstephens, and Jason Teo
Abstract: This paper presents a novel emotion recognition approach using electroencephalography (EEG) brainwave signals augmented with eye-tracking data in virtual reality (VR) to classify 4-quadrant circumplex model of emotions. 3600 videos are used as the stimuli to evoke user’s emotions (happy, angry, bored, calm) with a VR headset and a pair of earphones. EEG signals are recorded via a wearable EEG brain-computer interfacing (BCI) device and pupil diameter is collected also from a wearable portable eye-tracker. We extract 5 frequency bands which are Delta, Theta, Alpha, Beta, and Gamma from EEG data as well as obtaining pupil diameter from the eye-tracker as the chosen as the eye-related feature for this investigation. Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel is used as the classifier. The best accuracies based on EEG brainwave signals and pupil diameter are 98.44% and 58.30% respectively.
Published: 2020

29. Comparing Eye-Tracking versus EEG Features for Four-Class Emotion Classification in VR Predictive Analytics

Author: Lim, Jia Zheng, James Mountstephens, Jason Teo, Lim, Jia Zheng, James Mountstephens, and Jason Teo
Abstract: This paper presents a novel emotion recognition approach using electroencephalography (EEG) brainwave signals augmented with eye-tracking data in virtual reality (VR) to classify 4-quadrant circumplex model of emotions. 3600 videos are used as the stimuli to evoke user’s emotions (happy, angry, bored, calm) with a VR headset and a pair of earphones. EEG signals are recorded via a wearable EEG brain-computer interfacing (BCI) device and pupil diameter is collected also from a wearable portable eye-tracker. We extract 5 frequency bands which are Delta, Theta, Alpha, Beta, and Gamma from EEG data as well as obtaining pupil diameter from the eye-tracker as the chosen as the eye-related feature for this investigation. Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel is used as the classifier. The best accuracies based on EEG brainwave signals and pupil diameter are 98.44% and 58.30% respectively.
Published: 2020

30. Comparing Eye-Tracking versus EEG Features for Four-Class Emotion Classification in VR Predictive Analytics

Author: Lim, Jia Zheng, James Mountstephens, Jason Teo, Lim, Jia Zheng, James Mountstephens, and Jason Teo
Abstract: This paper presents a novel emotion recognition approach using electroencephalography (EEG) brainwave signals augmented with eye-tracking data in virtual reality (VR) to classify 4-quadrant circumplex model of emotions. 3600 videos are used as the stimuli to evoke user’s emotions (happy, angry, bored, calm) with a VR headset and a pair of earphones. EEG signals are recorded via a wearable EEG brain-computer interfacing (BCI) device and pupil diameter is collected also from a wearable portable eye-tracker. We extract 5 frequency bands which are Delta, Theta, Alpha, Beta, and Gamma from EEG data as well as obtaining pupil diameter from the eye-tracker as the chosen as the eye-related feature for this investigation. Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel is used as the classifier. The best accuracies based on EEG brainwave signals and pupil diameter are 98.44% and 58.30% respectively.
Published: 2020

31. Clean Enzymatic Oxidation of 12α-Hydroxysteroids to 12-Oxo-Derivatives Catalyzed by Hydroxysteroid Dehydrogenase

Author: Tonin, F. (author), Alvarenga Da Silva, N. (author), Ye, Jia Zheng (author), Arends, I.W.C.E. (author), Hanefeld, U. (author), Tonin, F. (author), Alvarenga Da Silva, N. (author), Ye, Jia Zheng (author), Arends, I.W.C.E. (author), and Hanefeld, U. (author)
Abstract: The C12 specific oxidation of hydroxysteroids is an essential reaction required for the preparation of pharmaceutical ingredients like ursodeoxycholic acid (UDCA) and chenodeoxycholic acid (CDCA), which can be synthesized by Wolff-Kishner reduction of the obtained 12-oxo-hydroxysteroids. 12α-hydroxysteroid dehydrogenases (12α-HSDHs) have been shown to perform this reaction with high yields, under mild conditions and without the need of protection and deprotection steps, required in chemical synthesis. Here, the recombinant expression and biochemical characterization of the nicotinamide adenine dinucleotide (NAD + )-dependent HSDH from Eggerthella lenta (El12α-HSDH) are reported. This enzyme shows comparable properties with the well-known nicotinamide adenine dinucleotide phosphate (NADP + )-dependent enzyme from Clostridium sp. 48–50. In order to perform a viable and atom efficient enzymatic hydroxysteroid oxidation, NAD(P)H oxidase (NOX) was employed as cofactor regeneration system: NOX uses oxygen (O 2 ) as sacrificial substrate and produces only water as side product. 10 mM of cholic acid was fully and selectively converted to 12-oxo-CDCA in 24 h. The possibility to employ this system on UCA and 7-oxo-deoxycholic acid (7-oxo-DCA) as substrates was additionally investigated. The performance of the El12α-HSDH was evaluated also in combination with a “classical” regeneration system (oxaloacetate/malate dehydrogenase) showing full conversion in 4 h. Finally, the feasibility of a catalytic aerobic-NAD + -dependent enzymatic oxidation was shown on a preparative scale (oxidation of CA to 12-oxo-CDCA) employing the El12α-HSDH-NOX system in a segmented-flow-reactor. (Figure presented.)., BT/Biocatalysis
Published: 2019
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32. Earth as an Exoplanet: A Two-dimensional Alien Map

Author: Fan, Siteng, Li, Cheng, Li, Jia-Zheng, Bartlett, Stuart, Jiang, Jonathan H., Natraj, Vijay, Crisp, David, Yung, Yuk L., Fan, Siteng, Li, Cheng, Li, Jia-Zheng, Bartlett, Stuart, Jiang, Jonathan H., Natraj, Vijay, Crisp, David, and Yung, Yuk L.
Abstract: Resolving spatially-varying exoplanet features from single-point light curves is essential for determining whether Earth-like worlds harbor geological features and/or climate systems that influence habitability. To evaluate the feasibility and requirements of this spatial feature resolving problem, we present an analysis of multi-wavelength single-point light curves of Earth, where it plays the role of a proxy exoplanet. Here, ~10,000 DSCOVR/EPIC frames collected over a two-year period were integrated over the Earth's disk to yield a spectrally-dependent point source and analyzed using singular value decomposition. We found that, between the two dominant principal components (PCs), the second PC contains surface-related features of the planet, while the first PC mainly includes cloud information. We present the first two-dimensional (2D) surface map of Earth reconstructed from light curve observations without any assumptions of its spectral properties. This study serves as a baseline for reconstructing the surface features of Earth-like exoplanets in the future., Comment: Accepted by ApJL, 7 pages, 4 figures
Published: 2019
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33. Earth as an Exoplanet: A Two-dimensional Alien Map

Author: Fan, Siteng, Li, Cheng, Li, Jia-Zheng, Bartlett, Stuart, Jiang, Jonathan H., Natraj, Vijay, Crisp, David, Yung, Yuk L., Fan, Siteng, Li, Cheng, Li, Jia-Zheng, Bartlett, Stuart, Jiang, Jonathan H., Natraj, Vijay, Crisp, David, and Yung, Yuk L.
Abstract: Resolving spatially-varying exoplanet features from single-point light curves is essential for determining whether Earth-like worlds harbor geological features and/or climate systems that influence habitability. To evaluate the feasibility and requirements of this spatial feature resolving problem, we present an analysis of multi-wavelength single-point light curves of Earth, where it plays the role of a proxy exoplanet. Here, ~10,000 DSCOVR/EPIC frames collected over a two-year period were integrated over the Earth's disk to yield a spectrally-dependent point source and analyzed using singular value decomposition. We found that, between the two dominant principal components (PCs), the second PC contains surface-related features of the planet, while the first PC mainly includes cloud information. We present the first two-dimensional (2D) surface map of Earth reconstructed from light curve observations without any assumptions of its spectral properties. This study serves as a baseline for reconstructing the surface features of Earth-like exoplanets in the future., Comment: Accepted by ApJL, 7 pages, 4 figures
Published: 2019
Full Text: View/download PDF

34. Failure Mechanics of Functional Nanostructures in Advanced Technologies

Author: Jia, Zheng and Jia, Zheng
Abstract: The past decade has seen a surge of interest in developing novel functional nanostructures to enable advanced technologies, such as flexible electronics and high performance lithium-ion batteries. Examples of such functional nanostructures include organic/inorganic multi-layer thin films in flexible electronics and nano-sized silicon/tin-based anodes in lithium/sodium ion batteries. Widespread implementation of these advanced technologies with novel functional nanostructures in the future will broadly impact human's daily life. However, grand challenges for developing robust novel functional nanostructures still exist. During operating cycles, these functional nanostructures undergo large deformation and high stresses, which may cause fracture and pulverization of the nanostructures, thereby leading to degradation and mechanical failure of the flexible devices or battery cells. Therefore, enhancing mechanical durability of the novel functional nanostructures in a mechanically demanding environment remains a significant challenge to the nanostructure design. This dissertation aims to shed lights on capturing the characteristics of the failure mechanisms of some novel functional nanostructures by theoretical and computational mechanics approach, The novel functional nanostructures investigated in my thesis includes inorganic/organic multilayer nanostructures, polyimide-supported brittle ITO films, substrate-supported ductile metal films and nanobead/nanowall/nanowire/nanoparticle electrodes in high-performance batteries. More importantly, we also explore possible solutions to effectively enhance the mechanical durability of these functional nanostructures.
Published: 2014

35. Cyclone shelters and cyclone resilient design in coastal areas of Bangladesh

Author: James L. Wescoat, Jr., Massachusetts Institute of Technology. Dept. of Urban Studies and Planning., Jia, Zheng, M.C.P. Massachusetts Institute of Technology, James L. Wescoat, Jr., Massachusetts Institute of Technology. Dept. of Urban Studies and Planning., and Jia, Zheng, M.C.P. Massachusetts Institute of Technology
Abstract: Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2012., Cataloged from PDF version of thesis., Includes bibliographical references (p. 203-210)., Bangladesh is one of those countries that are most vulnerable to tropical cyclones. In recent decades, cyclone mitigations by the Government of Bangladesh and international organizations have greatly increased the coastal communities' resistance to cyclones. This thesis focuses on cyclone shelter programs, one of the most important cyclone mitigating measures. Although cyclone shelters have proven to be effective, they are currently not adequate, which requires more research and development for a more resilient future. This thesis has five chapters: an introduction that defines the problem, a broad review of settlement history and hazards in coastal Bangladesh, a planning chapter that zooms in on the issues at five spatial scales, followed by a design chapter that zooms out from proposals for improving shelter site planning to a more comprehensive analysis of the spatial network of shelters, and larger-scale coastal environmental planning and policy. The conclusion highlights the main contributions of this research: 1) developing a multi-scale integrative approach; 2) expanding the range of choice for structural cyclone mitigations; and 3) addressing environmental and cultural diversity and specificity in physical planning and design. This research can contribute to the improvement of cyclone shelters in Bangladesh and so as to make a successful program even more successful. Keywords: Bangladesh, cyclone shelters, flood hazards, mitigation, disaster resilient design, by Zheng Jia., M.C.P.
Published: 2013

36. Cyclone shelters and cyclone resilient design in coastal areas of Bangladesh

Author: James L. Wescoat, Jr., Massachusetts Institute of Technology. Dept. of Urban Studies and Planning., Jia, Zheng, M.C.P. Massachusetts Institute of Technology, James L. Wescoat, Jr., Massachusetts Institute of Technology. Dept. of Urban Studies and Planning., and Jia, Zheng, M.C.P. Massachusetts Institute of Technology
Abstract: Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2012., Cataloged from PDF version of thesis., Includes bibliographical references (p. 203-210)., Bangladesh is one of those countries that are most vulnerable to tropical cyclones. In recent decades, cyclone mitigations by the Government of Bangladesh and international organizations have greatly increased the coastal communities' resistance to cyclones. This thesis focuses on cyclone shelter programs, one of the most important cyclone mitigating measures. Although cyclone shelters have proven to be effective, they are currently not adequate, which requires more research and development for a more resilient future. This thesis has five chapters: an introduction that defines the problem, a broad review of settlement history and hazards in coastal Bangladesh, a planning chapter that zooms in on the issues at five spatial scales, followed by a design chapter that zooms out from proposals for improving shelter site planning to a more comprehensive analysis of the spatial network of shelters, and larger-scale coastal environmental planning and policy. The conclusion highlights the main contributions of this research: 1) developing a multi-scale integrative approach; 2) expanding the range of choice for structural cyclone mitigations; and 3) addressing environmental and cultural diversity and specificity in physical planning and design. This research can contribute to the improvement of cyclone shelters in Bangladesh and so as to make a successful program even more successful. Keywords: Bangladesh, cyclone shelters, flood hazards, mitigation, disaster resilient design, by Zheng Jia., M.C.P.
Published: 2013

37. A novel ionic liquid-supported Schiff base ligand applied in the Pd-catalyzed Suzuki–Miyaura coupling reaction

Author: Yi-Qun Li, Yi-Qun Li, Bin Li, Jia Zheng, Yi-Qun Li, Yi-Qun Li, Bin Li, and Jia Zheng
Abstract: ARKIVOC: vol. 2010, no. 9, (issn) 1551-7012, (dlps) 5550190.0011.915, This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 License. Please contact mpub-help@umich.edu to use this work in a way not covered by the license.
Published: 2010

38. A novel ionic liquid-supported Schiff base ligand applied in the Pd-catalyzed Suzuki–Miyaura coupling reaction

Author: Yi-Qun Li, Yi-Qun Li, Bin Li, Jia Zheng, Yi-Qun Li, Yi-Qun Li, Bin Li, and Jia Zheng
Abstract: ARKIVOC: vol. 2010, no. 9, (issn) 1551-7012, (dlps) 5550190.0011.915, This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 License. Please contact mpub-help@umich.edu to use this work in a way not covered by the license.
Published: 2010

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