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154. Does community of inquiry really matter in understanding online learning? A confirmed perspective using mixed method.

Author

Zhou, Yujie, Wu, Huiping, and Cao, Ge

Subjects
*STUDENT engagement, *EXPECTANCY theories, *ONLINE education, *COMMUNITY of inquiry, *FALSE claims, *VIRTUAL communities
Abstract

High dropout rates in online courses, caused by potential factors such as financial issues, low motivation and poor self‐regulation among learners, pose a significant challenge to the sustainable development of online education. Therefore, continuance of online courses has become a critical topic in both the academic and practical fields. By combining the Community of Inquiry framework (CoI) with Expectation‐Confirmation Theory, this study introduces three new constructs—confirmed teaching presence (CTP), confirmed cognitive presence (CCP) and confirmed social presence (CSP)—into the research model to understand how confirmed expectations towards CoI determine online learners' course continuance intention. Utilizing a mixed‐methods approach, the study conducted quantitative analysis on 409 learner surveys using partial least squares (PLS), followed by semi‐structured interviews, which revealed the depth and breadth of the confirmed CoI expectations on learners' willingness to continue learning. Specifically, the quantitative results uncovered the differential effects of CTP, CCP and CSP on learners' course continuance intentions by elucidating the internal mechanisms. The interviews provided deeper insights by illuminating online learners' initial expectations as well as their pre‐course and post‐course expectations. The findings of the study not only provide evidence of the crucial role of confirmed expectations in shaping online learners' course continuance intention but also offer actionable recommendations for improving online course design and fostering lifelong learning. Practitioner notes What is already known about this topic Online courses have expanded in scale and attracted a large number of learners in recent years, the large base of online learners has brought tremendous and unprecedented challenges to online course development. A high dropout rate is especially considered as a severe issue for online course development. The issue of learners' continuance intention was often explored from a technological perspective and at the platform level by using Information system (IS) theories. The community of inquiry (CoI) framework was extensively utilized as a theoretical basis for understanding online learning experiences and its three elements—teaching, cognitive and social presences—have long been deemed as major antecedents that influence learners' online learning behaviours and intentions. What this paper adds This paper integrated the community of inquiry (CoI) framework with Expectation confirmation theory and proposed three new variables: confirmed teaching presence (CTP), confirmed cognitive presence (CCP) and confirmed social presence (CSP). The study reveals the internal mechanisms by which the three confirmed expectations impact online learners' courses continuance intention. This implies that different confirmed expectations may have varying effects on online learners' learning behaviour. This research collects data from multiple sources to comprehensively explore online learners' expectations and perceptions. It also sheds light on the importance of learners' actual participation in the learning process for predicting their behavioural intentions. Implications for practice and/or policy The finding that learners' confirmed expectations impact their online course continuance intention conveys an important message to course practitioners: exaggerated or false claims for the online course must be avoided to prevent students from forming unrealistic expectations. Improving online learners' course completion rate cannot be hinged upon simply and blindly fostering and extending the three presences. Instead, knowing learners' confirmed expectations of the three presences allows course practitioners to reconsider and organize the important course elements. The research reveals the distinct role that each confirmed presence plays in promoting online learners' course continuance intention and, meanwhile, expands the understanding of learners' learning needs and experiences. Practitioners could make timely and appropriate strategies based on these to better motivate course learners' engagement and retention. What is already known about this topic Online courses have expanded in scale and attracted a large number of learners in recent years, the large base of online learners has brought tremendous and unprecedented challenges to online course development. A high dropout rate is especially considered as a severe issue for online course development. The issue of learners' continuance intention was often explored from a technological perspective and at the platform level by using Information system (IS) theories. The community of inquiry (CoI) framework was extensively utilized as a theoretical basis for understanding online learning experiences and its three elements—teaching, cognitive and social presences—have long been deemed as major antecedents that influence learners' online learning behaviours and intentions. What this paper adds This paper integrated the community of inquiry (CoI) framework with Expectation confirmation theory and proposed three new variables: confirmed teaching presence (CTP), confirmed cognitive presence (CCP) and confirmed social presence (CSP). The study reveals the internal mechanisms by which the three confirmed expectations impact online learners' courses continuance intention. This implies that different confirmed expectations may have varying effects on online learners' learning behaviour. This research collects data from multiple sources to comprehensively explore online learners' expectations and perceptions. It also sheds light on the importance of learners' actual participation in the learning process for predicting their behavioural intentions. Implications for practice and/or policy The finding that learners' confirmed expectations impact their online course continuance intention conveys an important message to course practitioners: exaggerated or false claims for the online course must be avoided to prevent students from forming unrealistic expectations. Improving online learners' course completion rate cannot be hinged upon simply and blindly fostering and extending the three presences. Instead, knowing learners' confirmed expectations of the three presences allows course practitioners to reconsider and organize the important course elements. The research reveals the distinct role that each confirmed presence plays in promoting online learners' course continuance intention and, meanwhile, expands the understanding of learners' learning needs and experiences. Practitioners could make timely and appropriate strategies based on these to better motivate course learners' engagement and retention. [ABSTRACT FROM AUTHOR]

Published
2024
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155. Static and Dynamic Characteristics of 3D-Printed Orthogonal Hybrid Honeycomb Panels with Tunable Poisson's Ratio.

Author

Zhou, Yujie, Zhong, Yifeng, Tang, Yuxin, and Liu, Rong

Subjects
ELASTIC modulus, HONEYCOMB structures, ANISOTROPY, COMPUTER simulation, RESONANCE
Abstract

By adjusting the two wall angles of the orthogonal hybrid honeycomb (OHH), the tunable Poisson's ratio change from negative to positive values and the variation in stiffness can be achieved. To effectively analyze its static and dynamic characteristics, a two-dimensional equivalent Kirchhoff–Love model (2D-EKM) is established based on the variational asymptotic method (VAM).This model aids in effectively addressing the complexity arising from anisotropy. The obtained equivalent orthotropic properties are validated through unit-cell uniaxial compression tests and three-point bending experiments on 3D-printed specimens. The numerical simulation results suggest that the VAM-based 2D-EKM can predict the in-plane and out-of-plane static behaviors of OHH panels, with a maximum error below 10%. Particularly in the dynamic analysis of a four-sided fixed OHH panel, the analysis time required by 2D-EKM is only 0.37% of that needed for the 3D FE model. The OHH-ZPR panel exhibits exceptional resistance to deformation, with a maximum deformation under in-plane tension reaching only 27% of that in the OHH-PPR panel. Moreover, each 1% increase in the height–length ratio results in a respective increase of 275.62% and 281.93% in equivalent bending stiffness along both directions. This highlights that enhancing this ratio effectively boosts the fundamental frequency compared to the elastic modulus ratio, effectively prevents low-frequency resonance occurrences, and offers vital insights for the design and optimization of OHH panels. [ABSTRACT FROM AUTHOR]

Published
2024
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156. MGEoT: A Multi-grained Ensemble Method for Time Series Classification

Author

Wang, Ziyi, Zhou, Yujie, Li, Chun, Shang, Lin, Xue, Bing, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Pham, Duc Nghia, editor, Theeramunkong, Thanaruk, editor, Governatori, Guido, editor, and Liu, Fenrong, editor

Published
2021
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159. Evaluation of a Staged Case-Based Discussion Curriculum in Standardized Residency Training

Author

Liu, Yin, Huang, Mei, Zhou, Yujie, and Cai, Hourong

Abstract

The standardized residency training in China is continuous medical education for postgraduates, which is designed to master basic knowledge, theory, and clinical skills. Case-based discussion (CBD) is one of the main formative curricula used in standardized residency training. The aim of this study was to assess the impact of a novel CBD curriculum on residents' participation, satisfaction, and confidence in clinical skills. This was a prospective study that included 28 internal medicine residents. The traditional CBD contents were adjusted. The innovative approach let residents at different stages prepare and organize the CBD cases by themselves according to different levels of complexity. The surveys were designed to measure conference occurrence and residents' attendance, participation, and satisfaction, as well as their confidence in their clinical skills. Faculty could further engage the residents at any point to deepen the discussion and learning. The surveys indicated that the residents had a high satisfaction rate with the novel-staged CBD teaching method. Our curriculum improved conference occurrence, attendance, and participation; increased residents' self-report of participation in learning; and raised their confidence in their clinical skills, so the CBD was well received by residents and faculty preceptors. In addition, this study demonstrated that the staged CBD increased the knowledge and evidence usage of internal medicine residents. We expect wider application of this kind of CBD in clinical practice, medical education, residency training, and patient education in the future.

Published
2020
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161. Prediction model of coal spontaneous combustion temperature based on data filling

Author

ZHAI Xiaowei, LUO Jinlei, ZHANG Yuchen, SONG Bobo, HAO Le, and ZHOU Yujie

Subjects
coal spontaneous combustion, temperature prediction, index gas, filling in data gaps, k-nearest neighbor filling algorithm, random forest filling algorithm, decision tree regression filling algorithm, support vector regression filling algorithm based on particle swarm optimization, Mining engineering. Metallurgy, TN1-997
Abstract

Most of the existing coal spontaneous combustion temperature prediction models are based on relatively complete index gas sample data. However, the index gas data are affected by instruments or human factors. There are often data missing phenomena, resulting in low accuracy and over-fitting of coal spontaneous combustion temperature prediction. In order to solve the above problems, the paper proposes to apply filling algorithms such as K-nearest neighbor algorithm (KNN), random forest algorithm (RF), decision tree algorithm (DT) and support vector regression algorithm based on particle swarm optimization (PSO-SVR) to fill in the missing values. The missing data and the filled data are trained by RF, SVR and extreme gradient boosting (XGBoost) algorithm respectively. The parameters are optimized by the PSO algorithm. The RF, XGBoost and SVR coal spontaneous combustion temperature prediction models based on data filling are constructed. CO, CO2, CH4, C2H6 and O2 are selected as index gas in coal spontaneous combustion experiment, and six kinds of random data missing are designed. The overall missing rates are designed as 10%, 20% and 30%. The missing rates of CO and CO2 are designed as 40%, 50% and 60%. The average absolute error percentage (MAPE) is used as the filling effect evaluation index. The MAPE, the judgment coefficient R2 and the root mean square error (RMSE) are used as the model performance evaluation index. Four filling algorithms and three prediction models are compared. The results of the comparative analysis show the following points. The DT filling algorithm has better filling effect than the other three algorithms in six kinds of missing data cases. When there are more missing values of CO and CO2, the MAPE between the filling value and the actual values of the RF algorithm is large. The XGBoost model works extremely well in the training set without adjusting the parameters, but it is very prone to overfitting. The prediction effect of SVR model is very poor and the model cannot meet the prediction requirements. In the case of six kinds of data missing, the MAPE of PSO-SVR, RF and PSO-RF coal spontaneous combustion temperature prediction models based on the DT filling algorithm are about 4%. The RF model based on the DT filling algorithm can predict the coal spontaneous combustion temperature without optimization and has good stability.

Published
2023
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163. Angiographic quantitative flow ratio-guided coronary intervention (FAVOR III China): a multicentre, randomised, sham-controlled trial

Author

Xu, Bo, Tu, Shengxian, Song, Lei, Jin, Zening, Yu, Bo, Fu, Guosheng, Zhou, Yujie, Wang, Jian’an, Chen, Yundai, Pu, Jun, Chen, Lianglong, Qu, Xinkai, Yang, Junqing, Liu, Xuebo, Guo, Lijun, Shen, Chengxing, Zhang, Yaojun, Zhang, Qi, Pan, Hongwei, Fu, Xiaogang, Liu, Jian, Zhao, Yanyan, Escaned, Javier, Wang, Yang, Fearon, William F, Dou, Kefei, Kirtane, Ajay J, Wu, Yongjian, Serruys, Patrick W, Yang, Weixian, Wijns, William, Guan, Changdong, Leon, Martin B, Qiao, Shubin, and Stone, Gregg W

Published
2021
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172. Inversion Model Design of Chlorophyll a Based on BP Neural Network and Remote Sensing Image

Author

Zhou, Yujie, Zheng, Jun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Yang, Chao-Tung, editor, Pei, Yan, editor, and Chang, Jia-Wei, editor

Published
2020
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173. Multi-sensor Data Fusion Using Adaptive Kalman Filter

Author

Guo, Yinjing, Zhang, Manlin, Kang, Fong, Yang, Wenjian, Zhou, Yujie, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, Jia, Min, editor, and Zhang, Baoju, editor

Published
2020
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174. Oral Mucosal Microbes

Author

Ren, Biao, Cheng, Lei, Peng, Xian, Li, Yuqing, Li, Yan, Zhou, Yujie, Zhu, Chengguang, Chen, Xi, Zhou, Xuedong, editor, and Li, Yuqing, editor

Published
2020
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175. Duration of Dual Antiplatelet Therapy for Patients at High Bleeding Risk Undergoing PCI

Author

Valgimigli, Marco, Cao, Davide, Angiolillo, Dominick J., Bangalore, Sripal, Bhatt, Deepak L., Ge, Junbo, Hermiller, James, Makkar, Raj R., Neumann, Franz-Josef, Saito, Shigeru, Picon, Hector, Toelg, Ralph, Maksoud, Aziz, Chehab, Bassem M., Choi, James W., Campo, Gianluca, De la Torre Hernandez, Jose M., Kunadian, Vijay, Sardella, Gennaro, Thiele, Holger, Varenne, Olivier, Vranckx, Pascal, Windecker, Stephan, Zhou, Yujie, Krucoff, Mitchell W., Ruster, Karine, Zheng, Yan, and Mehran, Roxana

Published
2021
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181. Kink-antikink asymmetry and impurity interactions in topological mechanical chains

Author

Zhou, Yujie, Chen, Bryan Gin-ge, Upadhyaya, Nitin, and Vitelli, Vincenzo

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

We study the dynamical response of a diatomic periodic chain of rotors coupled by springs, whose unit cell breaks spatial inversion symmetry. In the continuum description, we derive a nonlinear field theory which admits topological kinks and antikinks as nonlinear excitations but where a topological boundary term breaks the symmetry between the two and energetically favors the kink configuration. Using a cobweb plot, we develop a fixed-point analysis for the kink motion and demonstrate that kinks propagate without the Peierls-Nabarro potential energy barrier typically associated with lattice models. Using continuum elasticity theory, we trace the absence of the Peierls-Nabarro barrier for the kink motion to the topological boundary term which ensures that only the kink configuration, and not the antikink, costs zero potential energy. Further, we study the eigenmodes around the kink and antikink configurations using a tangent stiffness matrix approach appropriate for pre-stressed structures to explicitly show how the usual energy degeneracy between the two no longer holds. We show how the kink-antikink asymmetry also manifests in the way these nonlinear excitations interact with impurities introduced in the chain as disorder in the spring stiffness. Finally, we discuss the effect of impurities in the (bond) spring length and build prototypes based on simple linkages that verify our predictions., Comment: 20 pages, 21 figures

Published
2016
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182. Lipoprotein(a) and Benefit of PCSK9 Inhibition in Patients With Nominally Controlled LDL Cholesterol

Author

Schwartz, Gregory G., Gabriel Steg, P.h., Bhatt, Deepak L., Bittner, Vera A., Diaz, Rafael, Goodman, Shaun G., Harrington, Robert A., Jukema, J. Wouter, Szarek, Michael, White, Harvey D., Zeiher, Andreas M., Tricoci, Pierluigi, Roe, Matthew T., Mahaffey, Kenneth W., Edelberg, Jay M., Hanotin, Corinne, Lecorps, Guillaume, Moryusef, Angèle, Pordy, Robert, Sasiela, William J., Tamby, Jean-François, Aylward, Philip E., Drexel, Heinz, Sinnaeve, Peter, Dilic, Mirza, Lopes, Renato D., Gotcheva, Nina N., Prieto, Juan-Carlos, Yong, Huo, López-Jaramillo, Patricio, Pećin, Ivan, Reiner, Zeljko, Ostadal, Petr, Poulsen, Steen Hvitfeldt, Viigimaa, Margus, Nieminen, Markku S., Danchin, Nicolas, Chumburidze, Vakhtang, Marx, Nikolaus, Liberopoulos, Evangelos, Montenegro Valdovinos, Pablo Carlos, Tse, Hung-Fat, Kiss, Robert Gabor, Xavier, Denis, Zahger, Doron, Valgimigli, Marco, Kimura, Takeshi, Kim, Hyo Soo, Kim, Sang-Hyun, Erglis, Andrejs, Laucevicius, Aleksandras, Kedev, Sasko, Yusoff, Khalid, Ramos López, Gabriel Arturo, Alings, Marco, Halvorsen, Sigrun, Correa Flores, Roger M., Sy, Rody G., Budaj, Andrzej, Morais, Joao, Dorobantu, Maria, Karpov, Yuri, Ristic, Arsen D., Chua, Terrance, Murin, Jan, Fras, Zlatko, Dalby, Anthony J., Tuñón, José, Asita de Silva, H., Hagström, Emil, Landmesser, Ulf, Müller, Christian, Chiang, Chern-En, Sritara, Piyamitr, Guneri, Sema, Parkhomenko, Alexander, Ray, Kausik K., Moriarty, Patrick M., Vogel, Robert, Chaitman, Bernard, Kelsey, Sheryl F., Olsson, Anders G., Rouleau, Jean-Lucien, Simoons, Maarten L., Alexander, Karen, Meloni, Chiara, Rosenson, Robert, Sijbrands, Eric J.G., Alexander, John H., Armaganijan, Luciana, Bagai, Akshay, Bahit, Maria Cecilia, Brennan, J. Matthew, Clifton, Shaun, DeVore, Adam D., Deloatch, Shalonda, Dickey, Sheila, Dombrowski, Keith, Ducrocq, Grégory, Eapen, Zubin, Endsley, Patricia, Eppinger, Arleen, Harrison, Robert W., Hess, Connie Ng, Hlatky, Mark A., Jordan, Joseph Dedrick, Knowles, Joshua W., Kolls, Bradley J., Kong, David F., Leonardi, Sergio, Lillis, Linda, Maron, David J., Marcus, Jill, Mathews, Robin, Mehta, Rajendra H., Mentz, Robert J., Moreira, Humberto Graner, Patel, Chetan B., Pereira, Sabrina Bernardez, Perkins, Lynn, Povsic, Thomas J., Puymirat, Etienne, Jones, William Schuyler, Shah, Bimal R., Sherwood, Matthew W., Stringfellow, Kenya, Sujjavanich, Darin, Toma, Mustafa, Trotter, Charlene, van Diepen, Sean F.P., Wilson, Matthew D., Tze-Kay Yan, Andrew, Schiavi, Lilia B., Garrido, Marcelo, Alvarisqueta, Andrés F., Sassone, Sonia A., Bordonava, Anselmo P., Alves De Lima, Alberto E., Schmidberg, Jorge M., Duronto, Ernesto A., Caruso, Orlando C., Novaretto, Leonardo P., Hominal, Miguel Angel, Montaña, Oscar R., Caccavo, Alberto, Gomez Vilamajo, Oscar A., Lorenzatti, Alberto J., Cartasegna, Luis R., Paterlini, Gustavo A., Mackinnon, Ignacio J., Caime, Guillermo D., Amuchastegui, Marcos, Salomone, Oscar, Codutti, Oscar R., Jure, Horacio O., Bono, Julio O.E., Hrabar, Adrian D., Vallejos, Julio A., Ahuad Guerrero, Rodolfo A., Novoa, Federico, Patocchi, Cristian A., Zaidman, Cesar J., Giuliano, Maria E., Dran, Ricardo D., Vico, Marisa L., Carnero, Gabriela S., Guzman, Pablo N., Medrano Allende, Juan C., Garcia Brasca, Daniela F., Bustamante Labarta, Miguel H., Nani, Sebastian, Blumberg, Eduardo D.S., Colombo, Hugo R., Liberman, Alberto, Fuentealba, Victorino, Luciardi, Hector L., Waisman, Gabriel D., Berli, Mario A., Garcia Duran, Ruben O., Cestari, Horacio G., Luquez, Hugo A., Giordano, Jorge A., Saavedra, Silvia S., Zapata, Gerardo, Costamagna, Osvaldo, Llois, Susana, Waites, Jonathon H., Collins, Nicholas, Soward, Allan, Hii, Chris L.S., Shaw, James, Arstall, Margaret A., Horowitz, John, Ninio, Daniel, Rogers, James F., Colquhoun, David, Oqueli Flores, Romulo E., Roberts-Thomson, Philip, Raffel, Owen, Lehman, Sam J., Aroney, Constantine, Coverdale, Steven G.M., Garrahy, Paul J., Starmer, Gregory, Sader, Mark, Carroll, Patrick A., Dick, Ronald, Zweiker, Robert, Hoppe, Uta, Huber, Kurt, Berger, Rudolf, Delle-Karth, Georg, Frey, Bernhard, Faes, Dirk, Hermans, Kurt, Pirenne, Bruno, Leone, Attilio, Hoffer, Etienne, Vrolix, Mathias C.M., De Wolf, Luc, Wollaert, Bart, Castadot, Marc, Dujardin, Karl, Beauloye, Christophe, Vervoort, Geert, Striekwold, Harry, Convens, Carl, Roosen, John, Barbato, Emanuele, Claeys, Marc, Cools, Frank, Terzic, Ibrahim, Barakovic, Fahir, Midzic, Zlatko, Pojskic, Belma, Fazlibegovic, Emir, Durak-Nalbantic, Azra, Kulić, Mehmed, Vulic, Dusko, Muslibegovic, Adis, Goronja, Boris, Reis, Gilmar, Sousa, Luciano, Nicolau, Jose C., Giorgeto, Flavio E., Silva, Ricardo P., Maia, Lilia Nigro, Rech, Rafael, Rossi, Paulo R.F., Cerqueira, Maria José A.G., Duda, Norberto, Kalil, Renato, Kormann, Adrian, Abrantes, José Antonio M., Filho, Pedro Pimentel, Soggia, Ana Priscila, de Santos, Mayler O.N., Neuenschwander, Fernando, Bodanese, Luiz C., Michalaros, Yorghos L., Eliaschewitz, Freddy G., Vidotti, Maria H., Leaes, Paulo E., Botelho, Roberto V., Kaiser, Sergio, Fernandes Manenti, Euler Roberto F., Precoma, Dalton B., Moura Jorge, Jose C., Silva, Pedro, Silveira, Jose A., Saporito, Wladmir, Marin Neto, Jose A., Feitosa, Gilson S., Ritt, Luiz Eduardo F., de Souza, Juliana A., Costa, Fernando, Souza, Weimar K.S.B., Reis, Helder J.L., Machado, Leandro, Aidar Ayoub, José Carlos, Todorov, Georgi V., Nikolov, Fedya P., Velcheva, Elena S., Tzekova, Maria L., Benov, Haralambi O., Petranov, Stanislav L., Tumbev, Haralin S., Shehova-Yankova, Nina S., Markov, Dimitar T., Raev, Dimitar H., Mollov, Mihail N., Kichukov, Kostadin N., Ilieva-Pandeva, Katya A., Ivanova, Raya, Gospodinov, Maryana, Mincheva, Valentina M., Lazov, Petar V., Dimov, Bojidar I., Senaratne, Manohara, Stone, James, Kornder, Jan, Pearce, Stephen, Dion, Danielle, Savard, Daniel, Pesant, Yves, Pandey, Amritanshu, Robinson, Simon, Gosselin, Gilbert, Vizel, Saul, Hoag, Gordon, Bourgeois, Ronald, Morisset, Anne, Sabbah, Eric, Sussex, Bruce, Kouz, Simon, MacDonald, Paul, Diaz, Ariel, Michaud, Nicolas, Fell, David, Leung, Raymond, Vuurmans, Tycho, Lai, Christopher, Nigro, Frank, Davies, Richard, Nogareda, Gustavo, Vijayaraghavan, Ram, Ducas, John, Lepage, Serge, Mehta, Shamir, Cha, James, Dupuis, Robert, Fong, Peter, Lutchmedial, Sohrab, Rodes-Cabau, Josep, Fadlallah, Hussein, Cleveland, David, Huynh, Thao, Bata, Iqbal, Hameed, Adnan, Pincetti, Cristian, Potthoff, Sergio, Prieto, Juan C., Acevedo, Monica, Aguirre, Arnoldo, Vejar, Margarita, Yañez, Mario, Araneda, Guillermo, Fernandez, Mauricio, Perez, Luis, Varleta, Paola, Florenzano, Fernando, Huidobro, Laura, Raffo, Carlos A., Olivares, Claudia, Nahuelpan, Leonardo, Montecinos, Humberto, Chen, Jiyan, Dong, Yugang, Huang, Weijian, Wang, Jianzhong, Huang, Shi'An, Yao, Zhuhua, Li, Xiang, Cui, Lan, Lin, Wenhua, Sun, Yuemin, Wang, Jingfeng, Li, Jianping, Zhang, Xuelian, Zhu, Hong, Chen, Dandan, Huang, Lan, Dong, Shaohong, Su, Guohai, Xu, Biao, Su, Xi, Cheng, Xiaoshu, Lin, Jinxiu, Zong, Wenxia, Li, Huanming, Feng, Yi, Xu, Dingli, Yang, Xinchun, Ke, Yuannan, Lin, Xuefeng, Zhang, Zheng, Zheng, Zeqi, Luo, Zhurong, Chen, Yundai, Ding, Chunhua, Zhong, Yi, Zheng, Yang, Li, Xiaodong, Peng, Daoquan, Zhao, Shuiping, Li, Ying, Liu, Xuebo, Wei, Meng, Liu, Shaowen, Yu, Yihua, Qu, Baiming, Jiang, Weihong, Zhou, Yujie, Zhao, Xingsheng, Yuan, Zuyi, Guo, Ying, Xu, Xiping, Shi, Xubo, Ge, Junbo, Fu, Guosheng, Bai, Feng, Fang, Weiyi, Shou, Xiling, Yang, Xiangjun, Wang, Jian'An, Xiang, Meixiang, Sun, Yingxian, Lu, Qinghua, Zhang, Ruiyan, Zhu, Jianhua, Xu, Yizhou, Fan, Zhongcai, Li, Tianchang, Wu, Chun, Jaramillo, Nicolas, Vallejo, Gregorio Sanchez, Luna Botia, Diana C., Lopez, Rodrigo Botero, Molina De Salazar, Dora I., Cadena Bonfanti, Alberto J., Aroca, Carlos Cotes, Higuera, Juan Diego, Blanquicett, Marco, Barrera Silva, Sandra I., Garcia Lozada, Henry J., Coronel Arroyo, Julian A., Accini Mendoza, Jose L., Fernandez Ruiz, Ricardo L., Quintero Ossa, Alvaro M., Manzur Jatin, Fernando G., Herazo, Aristides Sotomayor, Parada, Jeffrey Castellanos, Arambula, Rafael Suarez, Urina Triana, Miguel A., Fernandez Trujillo, Angela M., Strozzi, Maja, Car, Siniša, Jerić, Melita, Miličić, Davor, Benčić, Martina Lovrić, Pintarić, Hrvoje, Prvulović, Đeiti, Šikić, Jozica, Peršić, Viktor, Mileta, Dean, Štambuk, Kresimir, Babić, Zdravko, Tomulic, Vjekoslav, Lukenda, Josip, Mejic-Krstulovic, Stanka, Starcevic, Boris, Spinar, Jindrich, Horak, David, Velicka, Zdenek, Stasek, Josef, Alan, David, Machova, Vilma, Linhart, Ales, Novotny, Vojtech, Kaucak, Vladimir, Rokyta, Richard, Naplava, Robert, Coufal, Zdenek, Adamkova, Vera, Podpera, Ivo, Zizka, Jiri, Motovska, Zuzana, Marusincova, Ivana, Svab, Premysl, Heinc, Petr, 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Zurab, Ghlonti, Ramaz, Lominadze, Zaza, Khabeishvili, George, Hemetsberger, Rayyan, Edward, Kemala, Rauch-Kröhnert, Ursula, Stratmann, Matthias, Appel, Karl-Friedrich, Schmidt, Ekkehard, Omran, Heyder, Stellbrink, Christoph, Dorsel, Thomas, Lianopoulos, Emmanouil, Vöhringer, Hans Friedrich, Marx, Roger, Zirlik, Andreas, Schellenberg, Detlev, Heitzer, Thomas, Laufs, Ulrich, Werner, Christian, Gielen, Stephan, Nuding, Sebastian, Winkelmann, Bernhard, Behrens, Steffen, Sydow, Karsten, Karakas, Mahir, Simonis, Gregor, Muenzel, Thomas, Werner, Nikos, Leggewie, Stefan, Böcker, Dirk, Braun-Dullaeus, Rüdiger, Toursarkissian, Nicole, Jeserich, Michael, Weißbrodt, Matthias, Schaeufele, Tim, Weil, Joachim, Völler, Heinz, Waltenberger, Johannes, Natour, Mohammed, Schmitt, Susanne, Müller-Wieland, Dirk, Steiner, Stephan, Heidenreich, Lothar, Offers, Elmar, Gremmler, Uwe, Killat, Holger, Rieker, Werner, Patsilinakos, Sotiris, Kartalis, Athanasios, Manolis, Athanassios, Sionis, Dimitrios, Chachalis, Geargios, Skoumas, Ioannis, Athyros, Vasilios, Vardas, Panagiotis, Parthenakis, Frangkiskos, Lekakis, John, Hatzitolios, Apostolos, Fausto Ovando, Sergio R., Arango Benecke, Juan L., Rodriguez De Leon, Edgar R., Yan, Bryan P.Y., Siu, David C.W., Turi, Tibor, Merkely, Bela, Ungi, Imre, Lupkovics, Geza, Nagy, Lajos, Katona, András, Édes, István, Müller, Gábor, Horvath, Iván, Kapin, Tibor, Szigeti, Zsolt, Faluközy, József, Kumbla, Mukund, Sandhu, Manjinder, Annam, Sharath, Proddutur, Naveen Reddy, Regella, Reddy, Premchand, Rajendra K., Mahajan, Ajaykumar, Pawar, Sudhir, Abhyanakar, Atul D., Kerkar, Prafulla, Govinda, Ravishankar A., Oomman, Abraham, Sinha, Dhurjati, Patil, Sachin N., Kahali, Dhiman, Sawhney, Jitendra, Joshi, Abhijeet B., Chaudhary, Sanjeev, Harkut, Pankaj, Guha, Santanu, Porwal, Sanjay, Jujjuru, Srimannarayana, Pothineni, Ramesh B., Monteiro, Minguel R., Khan, Aziz, Iyengar, Shamanna S., Grewal, Jasprakash Singh, Chopda, Manoj, Fulwani, Mahesh C., Patange, Aparna, Sachin, Patil, Chopra, Vijay K., Goyal, Naresh K., Shinde, Rituparna, Manakshe, Gajendra V., Patki, Nitin, Sethi, Sumeet, Munusamy, Vengatesh, Sunil Thanvi, Sunil Karnaand, Adhyapak, Srilakshmi, Patil, Chandrakant, Pandurangi, Ulhas, Mathur, Rishabh, Gupta, Jugal, Kalashetti, Suhas, Bhagwat, Ajit, Raghuraman, Bagirath, Yerra, Shiv Kumar, Bhansali, Prasant, Borse, Rohidas, Rahul, Patil, Das, Srihari, Kumar, Vinay, Abdullakutty, Jabir, Saathe, Shireesh, Palimkar, Priya, Abdullkutty, Jabir, Sathe, Shireesh, Atar, Shaul, Shechter, Michael, Mosseri, Morris, Arbel, Yaron, Ehud, Chorin, Ofer, Havakuk, Lotan, Chaim, Rosenschein, Uri, Katz, Amos, Henkin, Yaakov, Francis, Adi, Klutstein, Marc, Nikolsky, Eugenia, Zukermann, Robert, Turgeman, Yoav, Halabi, Majdi, Marmor, Alon, Kornowski, Ran, Jonas, Michael, Amir, Offer, Hasin, Yonathan, Rozenman, Yoseph, Fuchs, Shmuel, Zvi, Vered, Hussein, Osamah, Gavish, Dov, Vered, Zvi, Caraco, Yoseph, Elias, Mazen, Tov, Naveh, Wolfovitz, Efrat, Lishner, Michael, Elias, Nizar, Piovaccari, Giancarlo, De Pellegrin, Annamaria, Garbelotto, Raffaella, Guardigli, Gabriele, Marco, Valgimigli, Licciardello, Giovanni, Auguadro, Carla, Scalise, Filippo, Cuccia, Claudio, Salvioni, Alessandro, Musumeci, Giuseppe, Senni, Michelle, Calabrò, Paolo, Novo, Salvatore, Faggiano, Pompilio, Metra, Marco, De Cesare, Nicoletta B., Berti, Sergio, Cavallini, Claudio, Puccioni, Enrico, Galvani, Marcello, Tespili, Maurizio, Piatti, Piermarco, Palvarini, Michela, De Luca, Giuseppe, Violini, Roberto, De Leo, Alessandro, Olivari, Zoran, Filardi, Pasquale Perrone, Ferratini, Maurizio, Racca, Vittorio, Dai, Kazuoki, Shimatani, Yuji, Kamiya, Haruo, Ando, Kenji, Takeda, Yoshihiro, Morino, Yoshihiro, Hata, Yoshiki, Kimura, Kazuo, Kishi, Koichi, Michishita, Ichiro, Uehara, Hiroki, Higashikata, Toshinori, Hirayama, Atsushi, Hirooka, Keiji, Doi, Yasuji, Sakagami, Satoru, Taguchi, Shuichi, Koike, Akihiro, Fujinaga, Hiroyuki, Koba, Shinji, Kozuma, Ken, Kawasaki, Tomohiro, Ono, Yujiro, Shimizu, Masatoshi, Katsuda, Yousuke, Wada, Atsuyuki, Shinke, Toshiro, Ako, Junya, Fujii, Kenshi, Takahashi, Toshiyuki, Sakamoto, Tomohiro, Nakao, Koichi, Furukawa, Yutaka, Sugino, Hiroshi, Tamura, Ritsu, Mano, Toshiaki, Uematsu, Masaaki, Utsu, Noriaki, Ito, Kashima, Haraguchi, Takuya, Sato, Katsuhiko, Ueda, Yasunori, Nishibe, Akira, Fujimoto, Kazuteru, Masutani, Motomaru, Yoon, Jung Han, Kim, Hack-Lyoung, Park, Hun Sik, Chae, In-Ho, Kim, Moo Hyun, Jeong, Myung Ho, Rha, Seungwoon, Kim, Chongjin, Kim, Hae Young, Hong, Taekjong, Tahk, Seung-Jea, Kim, Youngkwon, Busmane, Arija, Pontaga, Natalija, Strelnieks, Aldis, Mintale, Iveta, Sime, Iveta, Petrulioniene, Zaneta, Kavaliauskiene, Roma, Jurgaitiene, Ruta, Sakalyte, Gintare, Slapikas, Rimvydas, Norkiene, Sigute, Misonis, Nerijus, Kibarskis, Aleksandras, Kubilius, Raimondas, Bojovski, Stojko, Lozance, Nensi, Kjovkaroski, Aleksandar, Doncovska, Snezana, Ong, Tiong Kiam, Kasim, Sazzli, Maskon, Oteh, Kandasamy, Balachandran, Liew, Houng B., Izani Wan Mohamed, Wan Mohd, Castillo, Armando García, Calvillo, Jorge Carrillo, Campos, Pedro Fajardo, Núñez Fragoso, Juan Carlos, Bayram Llamas, Edmundo Alfredo, Alcocer Gamba, Marco Antonio, Madrigal, Jaime Carranza, González Salas, Luis Gerardo, Rosas, Enrique López, González Díaz, Belinda, Salcido Vázquez, Eduardo, Nacoud Ackar, Alfredo, Antonio Llamas Esperón, Guillermo, Rodolfo Martínez Sánchez, Carlos, Guerrero De Leon, María, Suarez Otero, Rodrigo, Fanghänel Salmón, Guillermo, Pérez Ríos, Jesús Antonio, Garza Ruíz, José Angel, Breedveld, Robert W., Feenema-Aardema, Margriet, Borger-Van Der Burg, Alida, Hoogslag, Pieter A.M., Suryapranata, Harry, Oomen, Antonius, Van Haelst, Paulus, Feenema-Aradema, Margriet, Wiersma, Jacobijne J., Basart, Dirk, Van Der Wal, Ruud M.A., Zwart, Peter, Monraats, Pascalle, Van Kesteren, Henricus, Karalis, Ioannis, Jukema, Johan, Verdel, Gerardus J.E., Brueren, Bart R.G., Troquay, Roland PTh, Viergever, Eric P., Al-Windy, Nadea Y.Y., 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Tomasz, Mirek-Bryniarska, Ewa, Gniot, Jacek, Lubinski, Andrzej, Gorny, Jerzy, Franek, Edward, Raczak, Grzegorz, Szwed, Hanna, Monteiro, Pedro, Bastos, Jose Mesquita, Pereira, Helder H., Martins, Dinis, Seixo, Filipe, Mendonça, Carlos, Botelho, Ana, Caetano, Francisca, Minescu, Bogdan, Istratoaie, Octavian, Tesloianu, Dan N., Cristian, Gabriel, Dumitrescu, Silviu, Podoleanu, Cristian G.C., Constantinescu, Mircea C.A., Bengus, Cristina M., Militaru, Constantin, Rosu, Doina, Parepa, Irinel R., Matei, Adrian V., Alexandru, Tom M., Malis, Mihaela, Coman, Ioan, Stanescu-Cioranu, Rodica, Dimulescu, Doina, Shvarts, Yury, Orlikova, Olga, Kobalava, Zhanna, Barbarash, Olga L., Markov, Valentin, Lyamina, Nadezhda, Gordienko, Alexander, Zrazhevsky, Konstantin, Vishnevsky, Alexander Y., Gurevich, Victor, Stryuk, Raisa, Lomakin, Nikita V., Bokarev, Igor, Khlevchuk, Tatiana, Shalaev, Sergey, Khaisheva, Larisa, Chizhov, Petr, Viktorova, Inna, Osokina, Natalya, Shchekotov, Vladimir, Akatova, Evgenia, Chumakova, Galina, Libov, Igor, Voevoda, Mikhail I., Tretyakova, Tatyana V., Baranov, Evgeny, Shustov, Sergey, Yakushin, Sergey, Gordeev, Ivan, Khasanov, Niiaz, Reshetko, Olga, Sotnikova, Tatiana, Molchanova, Olga, Nikolaev, Konstantin, Gapon, Liudmila, Baranova, Elena, Shogenov, Zaur, Kosmachova, Elena, Karpov, Yuriy, Povzun, Anton, Egorova, Liudmila, Tyrenko, Vadim V., Ivanov, Igor G., Ilya, Masterov, Kanorsky, Sergey, Simic, Dragan, Ivanovic, Nikola, Davidovic, Goran, Tasic, Nebojsa, Asanin, Milika R., Stojic, Stevo, Apostolovic, Svetlana R., Ilic, Stevan, Tosic, Biljana Putnikovic, Stankovic, Aleksandar, Arandjelovic, Aleksandra, Radovanovic, Slavica, Todic, Branislava, Balinovac, Jovan, Dincic, Dragan V., Seferovic, Petar, Karadzic, Ana, Dodic, Slobodan, Dimkovic, Sinisa, Jakimov, Tamara, Poh, Kian-Keong, Ong, Hean Yee, I-Shing, Justin Tang, Micko, Karol, Nociar, Jan, Pella, Daniel, Fulop, Peter, Hranai, Marian, Palka, Juraj, Mazur, Juraj, Majercák, Ivan, Dzupina, Andrej, Fazekas, František, Gonsorcik, Jozef, Bugan, Viliam, Selecky, Juraj, Kamensky, Gabriel, Strbova, Jaroslava, Smik, Rudolf, Dukat, Andrej, Olexa, Peter, Žuran, Ivan, Poklukar, Janez, Šuligoj, Nataša Černič, Cevc, Matija, Cyster, Henry P., Ranjith, Naresh, Corbett, Clive, Bayat, Junaid, Makotoko, Ellen Makoali, du Toit Theron, Hendrik, Kapp, Ilse E., de V Basson, Matthys M., Lottering, Hanlie, Van Aswegen, Dina, Van Zyl, Louis J., Sebastian, Peter J., Pillay, Thayabran, Saaiman, Jan A., Commerford, Patrick J., Cassimjee, Soraya, Riaz, Garda, Ebrahim, Iftikhar O., Sarvan, Mahomed, Mynhardt, Joseph H., Reuter, Helmuth, Moodley, Rajendran, Vida, Manuel, Cequier Fillat, Angel R., Peris, Vicente Bodí, Jimenez, Francisco Fuentes, Marín, Francisco, Cruz Fernández, Jose M., Hidalgo Urbano, Rafael Jesus, Gil-Extremera, Blas, Toledo, Pablo, Diz, Fernando Worner, Garcia-Dorado, David, Iñiguez, Andres, Fernández, José Tuñón, Gonzalez-Juanatey, Jose R., Portales, Javier Fernandez, Murillo, Fernando Civeira, Pericas, Laia Matas, Zamorano, Jose Luis, De Mora Martin, Manuel, Cortada, Jordi Bruguera, Alonso Martin, Joaquin J., Serrano Antolin, Jose Maria, De Berrazueta Fernández, José R., Vázquez de Prada, José Antonio, Díaz Fernández, Jose Francisco, García Lledó, José Alberto, Sales, Juan Cosín, Rodriguez, Javier Botas, Tragant, Gabriel Gusi, Benedicto, Amparo, Gonzalez-Juanatey, Carlos, Potau, Mercedes Camprubí, Perez, Ignacio Plaza, De La Tassa, César Morís, Loma-Osorio Rincon, Pablo, Recena, Javier Balaguer, Escudier, Juan M., Payeras, Antonio Coca, Orcajo, Norberto Alonso, Valdivielso, Pedro, Constantine, Godwin, Haniffa, Ruvaiz, Tissera, Nirmali, Amarasekera, Stanley, Ponnamperuma, Chandrike, Fernando, Nimali, Fernando, Kaputella, Jayawardena, Jayanthimala, Wijeyasingam, Santharaj, Ranasinghe, Gotabhaya, Ekanayaka, Ruvan, Mendis, Sepalika, Senaratne, Vajira, Mayurathan, Gnanamoorthy, Rajapaksha, Ajantha, Sirisena, Thilak, Herath, Jagath I., Amarasena, Naomali, Berglund, Stefan, Rasmanis, Gundars, Vedin, Ola, Witt, Nils, Mourtzinis, Georgios, Nicol, Peter, Hansen, Ole, Romeo, Stefano, Jensen, Steen Agergaard, Torstensson, Ingemar, Ahremark, Ulf, Sundelin, Torbjörn, Moccetti, Tiziano, Mach, Francois, Binde, Ronald, Gämperli, Oliver, Tsai, Wei-Chuan, Ueng, Kwo-Chang, Lai, Wen-Ter, Liu, Ming-En, Hwang, Juey-Jen, Yin, Wei-Hsian, Hsieh, I-Chang, Hsieh, Ming-Jer, Lin, Wei Hsiang, Kuo, Jen-Yuan, Huang, Tsuei-Yuan, Fang, Chih-Yuan, Kaewsuwanna, Pinij, Soonfuang, Wasant, Jintapakorn, Woravut, Sukonthasarn, Apichard, Wongpraparut, Nattawut, Sastravaha, Krisada, Sansanayudh, Nakarin, Kehasukcharoen, Wirash, Piyayotai, Dilok, Chotnoparatpat, Paiboon, Camsari, Ahmet, Kultursay, Hakan, Mutlu, Bulent, Ersanli, Murat, Demirtas, Mustafa, Kirma, Cevat, Ural, Ertan, Koldas, Lale, Karpenko, Oleksandr, Prokhorov, Alexander, Vakaluyk, Ihor, Myshanych, Halyna, Reshotko, Dmytro, Batushkin, Valeriy, Rudenko, Leonid, Kovalskyi, Ihor, Kushnir, Mykola, Tseluyko, Vira, Mostovoy, Yuriy, Stanislavchuk, Mykola, Kyiak, Yulian, Karpenko, Yuriy, Malynovsky, Yaroslav, Klantsa, Andriy, Kutniy, Oles, Amosova, Ekaterina, Tashchuk, Viktor, Leshchuk, Oleh, Rishko, Mykola, Kopytsya, Mykola, Yagensky, Andriy, Vatutin, Mykola, Bagriy, Andriy, Barna, Olga M., Ushakov, Olexiy, Dzyak, Georgiy, Goloborodko, Borys, Rudenko, Anatolii, Zheleznyy, Volodymyr, Trevelyan, Jasper, Zaman, Azfar, Lee, Kaeng, Moriarty, Andrew, Aggarwal, Rajesh K., Clifford, Piers, Wong, Yuk-Ki, Iqbal, Syed M.R., Subkovas, Eduardas, Braganza, Denise, Sarkar, David, Storey, Robert, Griffiths, Huw, Mcclure, Sam, Muthusamy, Rangasamy, Smith, Simon, Kurian, John, Levy, Terry, Barr, Craig, Kadr, Honer, Gerber, Robert, Simaitis, Audrius, Soran, Handrean, Mathur, Anthony, Brodison, Adrian, Ayaz, Mohammad, Cheema, Muhammad, Oliver, Richard, Thackray, Simon, Mudawi, Telal, Rahman, Gohar, Sultan, Ayyaz, Reynolds, Timothy, Sharman, David, david Sprigings, Butler, Rob, Wilkinson, Peter, Lip, Gregory Y.H., Halcox, Julian, Gallagher, Sean, Ossei-Gerning, Nicholas, Vardi, Gil, Baldari, Duccio, Brabham, David, Treasure, Charles, II, Dahl, Charles, Palmer, Bruce, Wiseman, Alan, Khan, Abul, Puri, Sanjeev, Mohart, Ann Elizabeth, Ince, Carlos, Flores, Enrique, Wright, Scott, Cheng, Shi-Chi, Rosenberg, Michael, Rogers, William, Jr., Kosinski, Edward, Forgosh, Les, Waltman, Jonathan, Khan, Misal, Shoukfeh, Mohammad, Dagher, Georges, Cambier, Patrick, Lieber, Ira, Kumar, Priya, East, Cara, Krichmar, Perry, Hasan, Mian, White, Lindsey, Knickelbine, Thomas, Haldis, Thomas, Gillespie, Eve, Amidon, Thomas, Suh, David, Arif, Imran, Abdallah, Mouhamad, Akhter, Faiq, Carlson, Eric, D'Urso, Michael, El-Ahdab, Fadi, Nelson, William, Moriarty, Katie, Harris, Barry, Cohen, Steven, Carter, Luther, Doty, Daniel, Sabatino, Kenneth, Haddad, Tariq, Malik, Amir, Rao, Sunder, Mulkay, Angel, Jovin, Ion, Klancke, Kim, Malhotra, Vinay, Devarapalli, Sai K., Koren, Michael, Chandna, Harish, Dodds, George, III, Goraya, Tauqir, Bengston, James, Janik, Matthew, Moran, Joseph, Sumner, Andrew, Kobayashi, John, Davis, William, Yazdani, Shahram, Pasquini, John, Thakkar, Maitreya, Vedere, Amarnath, Leimbach, Wayne, Rider, James, fenton, Sarah, Singh, Narendra, Shah, Anil V., Janosik, Denise, Pepine, Carl, Berman, Brett, Gelormini, Joseph, Daniels, Christopher, Richard, Kerensky, Keating, Friederike, Kondo, Nicholas I., Shetty, Sanjay, Levite, Howard, Waider, Winfried, Takata, Theodore, Abu-Fadel, Mazen, Shah, Vipul, Aggarwal, Rahul, Izzo, Mark, Kumar, Anil, Hattler, Brack, Do, Rose, Link, Chad, Bortnick, Anna, Kinzfogl, George, III, Ghitis, Arnold, Larry, John, Teufel, Edward, Kuhlman, Peter, Mclaurin, Brent, Zhang, Wenwu, Thew, Stephen, Abbas, Jalal, White, Matthew, Islam, Othman, Subherwal, Sumeet, Ranadive, Nandkishore, Vakili, Babak, Gring, Christian, Henderson, David, Schuchard, Timothy, Farhat, Naim, Kline, Geoffrey, Mahal, Sharan, Whitaker, Jack, Speirs, Shawn, Andersen, Rolf, Daboul, Nizar, Horwitz, Phillip, Zahr, Firas, Ponce, George, Jafar, Zubair, Mcgarvey, Joseph, Jr., Panchal, Vipul, Voyce, Stephen, Blok, Thomas, Sheldon, William, Azizad, Masoud M., Schmalfuss, Carsten, Picone, Mark, Pederson, Robert, Herzog, William, Jr., Friedman, Keith, Lindsey, Jason, Nowins, Rosemary, Timothy, Eichenlaub, Leonard, Parilak, Lepor, Norman, El Shahawy, Mahfouz, Weintraub, Howard, Irimpen, Anand, Alonso, Alvaro, May, Wade, Christopher, Daniels, Galski, Thomas, Chu, Alan, Mody, Freny, Ramin, Ebrahimi, Hodes, Zachary, Rossi, Joseph, Rose, Gregory, Fairlamb, James, Lambert, Charles, Jr., Raisinghani, Ajit, Abbate, Antonio, Vetrovec, George, King, Marilyn, Carey, Charles, Gerber, Jaime, Younis, Liwa, Park, Hyeun, Vidovich, Mladen, Knutson, Thomas, Friedman, Dennis, Chaleff, Fred, Loussararian, Arthur, Rozeman, Phillip, Kimmelstiel, Carey, Kuvin, Jeffrey, Silver, Kevin, Foster, Malcolm, Tonnessen, Glen, Espinoza, Andrey, Amlani, Mohamadali, Wali, Andreas, Malozzi, Christopher, Jong, Geert T., Massey, Clara, Wattanakit, Keattiyoat, O'Donnell, Philip J., Singal, Dinesh, Jaffrani, Naseem, Banuru, Sridhar, Fisher, Daniel, Xenakis, Mark, Perlmutter, Neal, Bhagwat, Ravi, Strader, James, Jr., Blonder, Ronald, Akyea-Djamson, Ayim, Labroo, Ajay, Lee, Kwan, Marais, H. John, Claxton, Edmund, Jr., Weiss, Robert, Kathryn, Rohr, Berk, Martin, Rossi, Peter, Joshi, Parag, Khera, Amit, Khaira, Ajit S., Kumkumian, Greg, Lupovitch, Steven, Purow, Joshua, Welka, Stephen, Hoffman, David, Fischer, Stuart, Soroka, Eugene, Eagerton, Donald, Pancholy, Samir, Ray, Michael, Erenrich, Norman, Farrar, Michael, Pollock, Stewart, French, William J., Diamantis, Steve, Guy, Douglas, Gimple, Lawrence, Neustel, Mark, Schwartz, Steven, Pereira, Edward, Albert, Seals, Spriggs, Douglas, Strain, Janet, Mittal, Suneet, Vo, Anthony, Chane, Majed, Hall, Jason, Vijay, Nampalli, Lotun, Kapildeo, Lester, F. Martin, Nahhas, Ahed, Pope, Theodore, Nager, Paul, Vohra, Rakesh, Sharma, Mukesh, Bashir, Riyaz, Ahmed, Hinan, Berlowitz, Michael, Fishberg, Robert, Barrucco, Robert, Yang, Eric, Radin, Michael, Sporn, Daniel, Stapleton, Dwight, Eisenberg, Steven, Landzberg, Joel, Mcgough, Martin, Turk, Samir, Schwartz, Michael, Sundram, P. Sandy, Jain, Diwakar, Zainea, Mark, Bayron, Carlos, Karlsberg, Ronald, Dohad, Suhail, Lui, Henry, Keen, William, Westerhausen, Donald, Jr., Khurana, Sandeep, Agarwal, Himanshu, Birchem, Jessica, Penny, William, Jr., Chang, Mark, Murphy, Sherrill, Henry, John, Schifferdecker ;John M Gilbert, Branislav, Chalavarya, Gopal, Eaton, Charles, Schmedtje, John F., Jr., Christenson, Stuart, Dotani, Imran, Denham, Douglas, Macdonell, Alexander, Gibson, Paul, Rahman, Aref, Al Joundi, Tammam, Assi, Nizar, Conrad, Gary, Kotha, Purushotham, Love, Michael, Giesler, Gregory, Rubenstein, Howard, Gamil, Dawood, Akright, Laura, Krawczyk, Justine, Cobler, Joanne, Wells, Terry, Welker, James, Foster, Robert, Gilmore, Richard, Anderson, Jay, Jacoby, Douglas, Harris, Bill, Gardner, Geraldine, Dandillaya, Ramprasad, Vora, Kishor, Kostis, John, Hunter, John, Laxson, David, Ball, Eric, Egydio, Flavia, Kawakami, Anelise, Oliveira, Janaina, Wozniak, Julianna, Matthews, Alexander, Ratky, Caroline, Valiris, Janine, Berdan, Lisa, Hepditch, Anita, Quintero, Kirby, Rorick, Tyrus, Westbrook, Melissa, Pascual, Andrea, Rovito, Carla, Bezault, Madeleine, Drouet, Elodie, Simon, Tabassome, Alsweiler, Caroline, Luyten, Anne, Butters, Julie, Griffith, Liddy, Shaw, Michelle, Grunberg, Lena, Islam, Shahidul, Brégeault, Marie-France, Bougon, Nathalie, Faustino, Douglas, Fontecave, Sylvie, Murphy, Judith, Verrier, Melanie, Veronique Agnetti, Andersen, Dorthe, Badreddine, Emmy, Bekkouche, Mhamed, Bouancheau, Cecile, Brigui, Imane, Brocklehurst, Maddy, Cianciarulo, Joseph, Devaul, Dawn, Domokos, Szilvia, Gache, Cecile, Gobillot, Caroline, Guillou, Severine, Healy, Jan, Heath, Megan, Jaiwal, Gayatri, Javierre, Carine, Labeirie, Julien, Monier, Myriam, Morales, Ulises, Mrabti, Asmaa, Mthombeni, Bicky, Okan, Betim, Smith, Lucile, Sheller, Jennifer, Sopena, Sebastien, Pellan, Valerie, Benbernou, Fadela, Bengrait, Nafissa, Lamoureux, Maud, Kralova, Katarina, Scemama, Michel, Bejuit, Raphael, Coulange, Anthony, Berthou, Christelle, Repincay, Jérôme, Lorenzato, Christelle, Etienne, Alexis, Gouet, Valerie, Loizeau, Virginie, Normand, Mickael, Ourliac, Anne, Rondel, Christelle, Adamo, Antony, Beltran, Pascale, Barraud, Pauline, Dubois-Gache, Helene, Halle, Benjamin, Metwally, Lamia, Mourgues, Maxime, Sotty, Marc, Vincendet, Marion, Cotruta, Raluca, Chengyue, Zhu, Fournie-Lloret, Dominique, Morrello, Christine, Perthuis, Aurelie, Picault, Patrick, Zobouyan, Isabelle, Colhoun, Helen M., Dempsey, Michael A., McClanahan, Mark A., Manvelian, Garen, Sinnaeve, Peter R., and Gabriel Steg, Ph

Published
2021
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185. Study on degradation of methyl red dye wastewater by dielectric barrier discharge low temperature plasma

Author

LI Haixia, ZHOU Yujie, WU Ying, WEI Chiyuan, XIE Jingjing, SHI Peixin, and ZHOU Baochang

Subjects
low temperature plasma, dielectric barrier discharge, dye wastewater, methyl red, degradation, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

The degradation of simulated methyl red dye wastewater in a concentric tubular reactor using dielectric barrier discharge low-temperature plasma technology was studied. The effects of discharge power, initial solution concentration, initial pH, treatment time, and atmospheric conditions on the degradation efficiency were studied. The color, pH, and absorbance of methyl red at 521 nm were used to detect the dye concentration, analyze the degradation process, and propose a degradation mechanism for methyl red. The results indicate that (1) in this experiment, the discharge power affects the degradation of methyl red but is limited by temperature and humidity, such that there is no positive correlation between the discharge power and the treatment effect. Therefore, the treatment of the solution at a low discharge power of 115 W is preferable; (2) the higher the initial concentration, the longer the time needed to achieve the same degradation rate as that achieved at lower concentrations; and (3) under the same conditions, a low pH is conducive to the degradation of methyl red, and acidic conditions are conducive to the bond breaking of methyl red.

Published
2023
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191. Near Infrared-Activatable Biomimetic Nanoplatform for Tumor-Specific Drug Release, Penetration and Chemo-Photothermal Synergistic Therapy of Orthotopic Glioblastoma

Author

Li,Ming, Zhang,Xinrui, Zhou,Yujie, Chu,Yuteng, Shen,Jie, Cai,Yue, Sun,Xuanrong, Li,Ming, Zhang,Xinrui, Zhou,Yujie, Chu,Yuteng, Shen,Jie, Cai,Yue, and Sun,Xuanrong

Abstract

Ming Li,* Xinrui Zhang,* Yujie Zhou, Yuteng Chu, Jie Shen, Yue Cai, Xuanrong Sun Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang University of Technology, Hangzhou, 310014, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xuanrong Sun, Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang University of Technology, Hangzhou, 310014, People’s Republic of China, Email sunxr@zjut.edu.cnIntroduction: Glioblastoma multiforme (GBM), a highly invasive and prognostically challenging brain cancer, poses a significant hurdle for current treatments due to the existence of the blood-brain barrier (BBB) and the difficulty to maintain an effective drug accumulation in deep GBM lesions.Methods: We present a biomimetic nanoplatform with angiopep-2-modified macrophage membrane, loaded with indocyanine green (ICG) templated self-assembly of SN38 (AM-NP), facilitating active tumor targeting and effective blood-brain barrier penetration through specific ligand-receptor interaction.Results: Upon accumulation at tumor sites, these nanoparticles achieved high drug concentrations. Subsequent combination of laser irradiation and release of chemotherapy agent SN38 induced a synergistic chemo-photothermal therapy. Compared to bare nanoparticles (NPs) lacking cell membrane encapsulation, AM-NPs significantly suppressed tumor growth, markedly enhanced survival rates, and exhibited excellent biocompatibility with minimal side effects.Conclusion: This NIR-activatable biomimetic camouflaging macrophage membrane-based nanoparticles enhanced drug delivery targeting ability through modifications of macrophage membranes and specific ligands. It simultaneously achieved synergistic chemo-photothermal therapy, enhancing treatment effectiveness. Compared to traditional treatment modalities, it provided a precise, efficient, and synergistic method that mig

Published
2024

192. Development and Validation of a Dynamic Nomogram for Predicting 3-Month Mortality in Acute Ischemic Stroke Patients with Atrial Fibrillation

Author

Yan,Xiaodi, Xia,Peng, Tong,Hanwen, Lan,Chen, Wang,Qian, Zhou,Yujie, Zhu,Huaijun, Jiang,Chenxiao, Yan,Xiaodi, Xia,Peng, Tong,Hanwen, Lan,Chen, Wang,Qian, Zhou,Yujie, Zhu,Huaijun, and Jiang,Chenxiao

Abstract

Xiaodi Yan,1,2 Peng Xia,3 Hanwen Tong,4 Chen Lan,1,2 Qian Wang,1,2 Yujie Zhou,5,* Huaijun Zhu,6 Chenxiao Jiang6,* 1Department of Pharmacy, Nanjing Drum Tower Hospital, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, People’s Republic of China; 2School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, People’s Republic of China; 3Department of Pharmacy, Nanjing Drum Tower Hospital, School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 4Department of Emergency Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China; 5Department of Respiratory Critical Care Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China; 6Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chenxiao Jiang; Yujie Zhou, Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School, Zhongshan Road No. 321, Nanjing, Jiangsu, People’s Republic of China, Tel +86 177 6173 2923 ; +86 137 0140 9863, Email sharejcx@163.com; yujiezhoum@163.comBackground: Acute ischemic stroke (AIS) in patients with atrial fibrillation (AF) carries a substantial risk of mortality, emphasizing the need for effective risk assessment and timely interventions. This study aimed to develop and validate a practical dynamic nomogram for predicting 3-month mortality in AIS patients with AF.Methods: AIS patients with AF were enrolled and randomly divided into training and validation cohorts. The nomogram was developed based on independent risk factors identified by multivariate logistic regression analysis.

Published
2024

193. Value of Absolute Eosinophil Count in Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Author

Wang,Yufei, Ma,Xiaoteng, Yang,Zhiqiang, Li,Qiuxuan, Zhou,Yujie, Gao,Fei, Wang,Zhijian, Wang,Yufei, Ma,Xiaoteng, Yang,Zhiqiang, Li,Qiuxuan, Zhou,Yujie, Gao,Fei, and Wang,Zhijian

Abstract

Yufei Wang,1,* Xiaoteng Ma,1,* Zhiqiang Yang,1,2 Qiuxuan Li,1 Yujie Zhou,1,3 Fei Gao,1,3 Zhijian Wang1,3 1Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Ministry of Education, Beijing, People’s Republic of China; 2Cardio-Metabolic Medicine Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 3The Key Laboratory of Remodeling-Related Cardiovascular Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhijian Wang; Fei Gao, Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, the Key Laboratory of Remodeling-related Cardiovascular Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Anzhen Avenue #2, Chaoyang District, Beijing, 100029, People’s Republic of China, Email zjwang1975@hotmail.com; fgaomd@163.comBackground and Aims: Elevated eosinophils typically indicate hypersensitive inflammation; however, their involvement in cardiovascular events remains incompletely understood. We investigated the association between the absolute eosinophil count (AEC) and major adverse cardiovascular and cerebrovascular events (MACCEs) in patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI). Additionally, we determine whether the integration of AEC with the SYNTAX II score could improve predictive ability.Methods and Results: The AECs of 1711 patients with ACS undergoing PCI from June 2016 to November 2017 were analyzed on admission. All recruitments were splitted into three groups based on AEC tertiles and 101 participants underwent one or more noteworthy outcomings. The association between AEC and MACCEs (defined as a composite of cardiovascular death, myocardial infarction [MI], and stroke) was tes

Published
2024

195. Data-Driven Batch Process Monitoring for Continuous Annealing of Cold-Rolled Strip Steel.

Author

Zhou, Yujie, He, Fei, Zhang, Yutao, and Zhou, Hang

Subjects
STEEL strip, CONTINUOUS processing, BATCH processing, MANUFACTURING processes, UNIFORMITY
Abstract

The continuous annealing process (CAP) is a crucial process of steel production, which has a significant impact on the uniformity and stability of mechanical properties. A novel batch monitoring process based on kernel dissimilarity (KDISSIM) and Kmeans++ is proposed in this paper, focusing on problems such as unequal sample lengths between batches and nonlinearity between variables. First, KDISSIM is used to describe the dissimilarity between batches. Secondly, Kmeans++ is employed to improve the accuracy of clustering tasks based on historical batches. The largest cluster is considered to be at a relatively stable control level, and these batches are further used as training data. Then, the center batch and boundary batch of the training set are used as the reference batch and monitoring threshold for the monitoring model, respectively. Finally, the effectiveness of the proposed method is verified via the actual CAP data, providing a feasible solution for CAP batch monitoring. [ABSTRACT FROM AUTHOR]

Published
2024
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197. Aggregation Enhanced Thermally Activated Delayed Fluorescence through Spin‐Orbit Coupling Regulation.

Author

Zhang, Wei, Li, Shuai, Gong, Yujie, Zhang, Jiachen, Zhou, Yujie, Kong, Jie, Fu, Hongbing, and Zhou, Meng

Subjects
DELAYED fluorescence, ORGANIC light emitting diodes, BAND gaps, EXCITED states
Abstract

Integrating aggregation‐induced emission (AIE) into thermally activated delayed fluorescence (TADF) emitters holds great promise for the advancement of highly efficient organic light emitting diodes (OLEDs). Despite recent advancements, a thorough comprehension of the underlying mechanisms remains imperative for the practical application of such materials. In this work, we introduce a novel approach aimed at modulating the TADF process by manipulating dynamic processes in excited states through aggregation effect. Our findings reveal that aggregation not only enhances both prompt and delayed fluorescence simultaneously but also imposes constraints on molecular reorientation. This constraint reinforces spin‐orbit coupling and reduces the energy gap between singlets and triplets. These insights deepen our understanding of the fundamental mechanisms governing the aggregation effect on TADF materials and provide valuable guidance for the design of high‐efficiency photoluminescent materials. [ABSTRACT FROM AUTHOR]

Published
2024
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198. Lithium-Ion Battery SOH Estimation Method Based on Multi-Feature and CNN-BiLSTM-MHA.

Author

Zhou, Yujie, Zhang, Chaolong, Zhang, Xulong, and Zhou, Ziheng

Subjects
CONVOLUTIONAL neural networks, THERMAL batteries, ENERGY development, CLEAN energy, ELECTRIC vehicles
Abstract

Electric vehicles can reduce the dependence on limited resources such as oil, which is conducive to the development of clean energy. An accurate battery state of health (SOH) is beneficial for the safety of electric vehicles. A multi-feature and Convolutional Neural Network–Bidirectional Long Short-Term Memory–Multi-head Attention (CNN-BiLSTM-MHA)-based lithium-ion battery SOH estimation method is proposed in this paper. First, the voltage, energy, and temperature data of the battery in the constant current charging phase are measured. Then, based on the voltage and energy data, the incremental energy analysis (IEA) is performed to calculate the incremental energy (IE) curve. The IE curve features including IE, peak value, average value, and standard deviation are extracted and combined with the thermal features of the battery to form a complete multi-feature sequence. A CNN-BiLSTM-MHA model is set up to map the features to the battery SOH. Experiments were conducted using batteries with different charging currents, and the results showed that even if the nonlinearity of battery SOH degradation is significant, this method can still achieve a fast and accurate estimation of the battery SOH. The Mean Absolute Error (MAE) is 0.1982%, 0.1873%, 0.1652%, and 0.1968%, and the Root-Mean-Square Error (RMSE) is 0.2921%, 0.2997%, 0.2130%, and 0.2625%, respectively. The average Coefficient of Determination (R2) is above 96%. Compared to the BiLSTM model, the training time is reduced by an average of about 36%. [ABSTRACT FROM AUTHOR]

Published
2024
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199. Astragalin from Thesium chinense : A Novel Anti-Aging and Antioxidant Agent Targeting IGFR/CD38/ Sirtuins.

Author

Wang, Ruifeng, Ding, Anping, Wang, Jiaye, Wang, Jiaxue, Zhou, Yujie, Chen, Miao, Ju, Shuang, Tan, Mingpu, and Xiang, Zengxu

Subjects
MOLECULAR dynamics, AMP-activated protein kinases, SIRTUINS, FISH growth, FISH farming, CAENORHABDITIS elegans
Abstract

Astragalin (AG), a typical flavonoid found in Thesium chinense Turcz (T. chinense), is abundant in various edible plants and possesses high nutritional value, as well as antioxidant and antibacterial effects. In this study, we initially predicted the mechanism of action of AG with two anti-aging and antioxidant-related protein targets (CD38 and IGFR) by molecular docking and molecular dynamics simulation techniques. Subsequently, we examined the anti-aging effects of AG in Caenorhabditis elegans (C. elegans), the antioxidant effects in zebrafish, and verified the related molecular mechanisms. In C. elegans, AG synergistically extended the lifespan of C. elegans by up-regulating the expression of daf-16 through inhibiting the expression of daf-2/IGFR and also activating the AMPK and MAPK pathways to up-regulate the expression of sir-2.1, sir-2.4, and skn-1. In oxidatively damaged zebrafish embryos, AG demonstrated a synergistic effect in augmenting the resistance of zebrafish embryos to oxidative stress by up-regulating the expression levels of SIRT1 and SIRT6 within the zebrafish embryos system via the suppression of CD38 enzymatic activity and then inhibiting the expression of IGFR through high levels of SIRT6. These findings highlight the antioxidant and anti-aging properties of AG and indicate its potential application as a supplementary ingredient in aquaculture for enhancing fish health and growth. [ABSTRACT FROM AUTHOR]

Published
2024
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