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

Your search keyword '"Yan Jie"' showing total 281 results

Start Over Author "Yan Jie" Publication Type Electronic Resources

281 results on '"Yan Jie"'

1. Exploring TRF2-dependent dna distortion through single-DNA manipulation studies

Author: Zhao, Xiaodan, Vogirala, Vinod Kumar, Liu, Meihan, Zhou, Yu, Rhodes, Daniela, Sandin, Sara, Yan, Jie, Zhao, Xiaodan, Vogirala, Vinod Kumar, Liu, Meihan, Zhou, Yu, Rhodes, Daniela, Sandin, Sara, and Yan, Jie
Abstract: TRF2 is a component of shelterin, a telomere-specific protein complex that protects the ends of mammalian chromosomes from DNA damage signaling and improper repair. TRF2 functions as a homodimer and its interaction with telomeric DNA has been studied, but its full-length DNA-binding properties are unknown. This study examines TRF2’s interaction with single-DNA strands and focuses on the conformation of the TRF2-DNA complex and TRF2’s preference for DNA chirality. The results show that TRF2-DNA can switch between extended and compact conformations, indicating multiple DNA-binding modes, and TRF2’s binding does not have a strong preference for DNA supercoiling chirality when DNA is under low tension. Instead, TRF2 induces DNA bending under tension. Furthermore, both the N-terminal domain of TRF2 and the Myb domain enhance its affinity for the telomere sequence, highlighting the crucial role of multivalent DNA binding in enhancing its affinity and specificity for telomere sequence. These discoveries offer unique insights into TRF2’s interaction with telomeric DNA.
Published: 2024
Full Text: View/download PDF

2. Association of Admission Hyperglycemia with Clinical Outcomes in Patients with Symptomatic Intracranial Hemorrhage After Endovascular Treatment for Large Vessel Occlusive Stroke

Author: Yan,Jie, Huang,Jiandi, Pu,Tianqiang, Song,Jiaxing, Yang,Jie, Li,Linyu, Li,Fengli, Zi,Wenjie, Guo,Changwei, Peng,Zhouzhou, Yan,Jie, Huang,Jiandi, Pu,Tianqiang, Song,Jiaxing, Yang,Jie, Li,Linyu, Li,Fengli, Zi,Wenjie, Guo,Changwei, and Peng,Zhouzhou
Abstract: Jie Yan,1,&ast; Jiandi Huang,2,&ast; Tianqiang Pu,3,&ast; Jiaxing Song,2 Jie Yang,2 Linyu Li,2 Fengli Li,2 Wenjie Zi,2 Changwei Guo,2 Zhouzhou Peng2 1Department of Neurology, The First Peopleâs Hospital of Yongzhou City, Yongzhou City, Hunan Province, Peopleâs Republic of China; 2Department of Neurology, Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University, Chongqing City, Peopleâs Republic of China; 3Department of Neurology, The Central Hospital of Guangyuan City, Guangyuan City, Sichuan Province, Peopleâs Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhouzhou Peng; Changwei Guo, Department of Neurology, Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University, Shapingba District, Chongqing City, Peopleâs Republic of China, Email peng_zhouzhou@163.com; changwei_guo@163.comBackground: Symptomatic intracranial hemorrhage (sICH) is a fatal complication after endovascular treatment (EVT) for acute large vessel occlusive (LVO) stroke. The aim of this study was to investigate the association between hyperglycemia and outcomes in patients with postprocedural sICH.Methods: Of the 2567 patients with AIS who underwent EVT from two large multicenter randomized trials and two prospective multicenter registry studies, 324 patients occurred sICH with documented admission glucose were included in this study. The primary outcome was functional independence (defined as a modified Rankin Scale score of 0 to 2) at 90 days. Secondary outcomes included mRS score of 0 to 3, 0 to 1, and mRS score at 90 days. Safety outcome was the mortality within 90 days. Admission hyperglycemia was defined as a plasma blood glucose â¥ 7.8 mmol/L (140 mg/dL) in our analysis.Results: Of 324 eligible participants included in this study, hyperglycemia was observed in 130 (40.1%) patients. The median age was 67 (IQR, 58â 75) years, and median blood glucose level was 7.1 (IQR, 6.0â 9.3) mmol/L. Af
Published: 2024

3. Mechanotransduction through protein stretching

Author: Guo, Yanyu, Yan, Jie, Goult, Benjamin T, Guo, Yanyu, Yan, Jie, and Goult, Benjamin T
Abstract: Cells sense and respond to subtle changes in their physicality, and via a myriad of different mechanosensitive processes, convert these physical cues into chemical and biochemical signals. This process, called mechanotransduction, is possible due to a highly sophisticated machinery within cells. One mechanism by which this can occur is via the stretching of mechanosensitive proteins. Stretching proteins that contain force-dependent regions results in altered geometry and dimensions of the connections, as well as differential spatial organization of signals bound to the stretched protein. The purpose of this mini-review is to discuss some of the intense recent activity in this area of mechanobiology that strives to understand how protein stretching can influence signaling outputs and cellular responses.
Published: 2024

4. Flash healing of laser-induced graphene

Author: Cheng, Le, Yeung, Chi Shun, Huang, Libei, Ye, Ge, Yan, Jie, Li, Wanpeng, Yiu, Chunki, Chen, Fu-Rong, Shen, Hanchen, Tang, Benzhong, Ren, Yang, Yu, Xinge, Ye, Ruquan, Cheng, Le, Yeung, Chi Shun, Huang, Libei, Ye, Ge, Yan, Jie, Li, Wanpeng, Yiu, Chunki, Chen, Fu-Rong, Shen, Hanchen, Tang, Benzhong, Ren, Yang, Yu, Xinge, and Ye, Ruquan
Abstract: The advancement of laser-induced graphene (LIG) technology has streamlined the fabrications of flexible graphene devices. However, the ultrafast kinetics triggered by laser irradiation generates intrinsic amorphous characteristics, leading to high resistivity and compromised performance in electronic devices. Healing graphene defects in specific patterns is technologically challenging by conventional methods. Herein, we report the rapid rectification of LIG’s topological defects by flash Joule heating in milliseconds (referred to as F-LIG), whilst preserving its overall structure and porosity. The F-LIG exhibits a decreased ID/IG ratio from 0.84 – 0.33 and increased crystalline domain from Raman analysis, coupled with a 5-fold surge in conductivity. Pair distribution function and atomic-resolution imaging delineate a broader-range order of F-LIG with a shorter C-C bond of 1.425 Å. The improved crystallinity and conductivity of F-LIG with excellent flexibility enables its utilization in high-performance soft electronics and low-voltage disinfections. Notably, our F-LIG/polydimethylsiloxane strain sensor exhibits a gauge factor of 129.3 within 10% strain, which outperforms pristine LIG by 800%, showcasing significant potential for human-machine interfaces. © The Author(s) 2024.
Published: 2024

5. Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration

Author: Mok, Tony C. W., Li, Zi, Bai, Yunhao, Zhang, Jianpeng, Liu, Wei, Zhou, Yan-Jie, Yan, Ke, Jin, Dakai, Shi, Yu, Yin, Xiaoli, Lu, Le, Zhang, Ling, Mok, Tony C. W., Li, Zi, Bai, Yunhao, Zhang, Jianpeng, Liu, Wei, Zhou, Yan-Jie, Yan, Ke, Jin, Dakai, Shi, Yu, Yin, Xiaoli, Lu, Le, and Zhang, Ling
Abstract: Establishing dense anatomical correspondence across distinct imaging modalities is a foundational yet challenging procedure for numerous medical image analysis studies and image-guided radiotherapy. Existing multi-modality image registration algorithms rely on statistical-based similarity measures or local structural image representations. However, the former is sensitive to locally varying noise, while the latter is not discriminative enough to cope with complex anatomical structures in multimodal scans, causing ambiguity in determining the anatomical correspondence across scans with different modalities. In this paper, we propose a modality-agnostic structural representation learning method, which leverages Deep Neighbourhood Self-similarity (DNS) and anatomy-aware contrastive learning to learn discriminative and contrast-invariance deep structural image representations (DSIR) without the need for anatomical delineations or pre-aligned training images. We evaluate our method on multiphase CT, abdomen MR-CT, and brain MR T1w-T2w registration. Comprehensive results demonstrate that our method is superior to the conventional local structural representation and statistical-based similarity measures in terms of discriminability and accuracy., Comment: Accepted by CVPR2024
Published: 2024

6. CCFC++: Enhancing Federated Clustering through Feature Decorrelation

Author: Yan, Jie, Liu, Jing, Ning, Yi-Zi, Zhang, Zhong-Yuan, Yan, Jie, Liu, Jing, Ning, Yi-Zi, and Zhang, Zhong-Yuan
Abstract: In federated clustering, multiple data-holding clients collaboratively group data without exchanging raw data. This field has seen notable advancements through its marriage with contrastive learning, exemplified by Cluster-Contrastive Federated Clustering (CCFC). However, CCFC suffers from heterogeneous data across clients, leading to poor and unrobust performance. Our study conducts both empirical and theoretical analyses to understand the impact of heterogeneous data on CCFC. Findings indicate that increased data heterogeneity exacerbates dimensional collapse in CCFC, evidenced by increased correlations across multiple dimensions of the learned representations. To address this, we introduce a decorrelation regularizer to CCFC. Benefiting from the regularizer, the improved method effectively mitigates the detrimental effects of data heterogeneity, and achieves superior performance, as evidenced by a marked increase in NMI scores, with the gain reaching as high as 0.32 in the most pronounced case.
Published: 2024

7. CCFC: Bridging Federated Clustering and Contrastive Learning

Author: Yan, Jie, Liu, Jing, Zhang, Zhong-Yuan, Yan, Jie, Liu, Jing, and Zhang, Zhong-Yuan
Abstract: Federated clustering, an essential extension of centralized clustering for federated scenarios, enables multiple data-holding clients to collaboratively group data while keeping their data locally. In centralized scenarios, clustering driven by representation learning has made significant advancements in handling high-dimensional complex data. However, the combination of federated clustering and representation learning remains underexplored. To bridge this, we first tailor a cluster-contrastive model for learning clustering-friendly representations. Then, we harness this model as the foundation for proposing a new federated clustering method, named cluster-contrastive federated clustering (CCFC). Benefiting from representation learning, the clustering performance of CCFC even double those of the best baseline methods in some cases. Compared to the most related baseline, the benefit results in substantial NMI score improvements of up to 0.4155 on the most conspicuous case. Moreover, CCFC also shows superior performance in handling device failures from a practical viewpoint.
Published: 2024

8. Microwave-induced co-processing of coal and biomass

Author: Yan, Jie-Feng
Subjects: 662, TP Chemical technology
Abstract: Pyrolysis is an attractive alternative for the conversion of solid fuels to valuable chemicals and bio-fuels. In order to obtain more H2 and syngas from pyrolysis of coal and biomass, microwave has been adopted to enhance the co-pyrolysis of coal and biomass, which has been investigated systematically in this study. Firstly, conventional pyrolysis of coal and biomass was carried out using a vertical tube furnace. Characterizations of pyrolytic gas, liquid and solid products were conducted to study the different properties of products from the pyrolysis of coal and biomass. More gas products were produced at higher temperatures and biomass samples produced more H2 and syngas than coals. Bio-oils produced from conventional pyrolysis of biomass samples have relatively simpler compositions compared with those produced from conventional pyrolysis of coals. Char samples produced from conventional pyrolysis of coal and biomass samples show different morphologies due to the different nature of original coal and biomass. Secondly, microwave-induced pyrolysis of coal and biomass was carried out and compared with the results of conventional pyrolysis. Microwave-induced pyrolysis was found to produce pyrolytic gas products with higher contents of H2 and syngas than conventional pyrolysis. The bio-oils produced from microwave-induced pyrolysis were not as complicated as those from conventional pyrolysis. The reason for this is believed to be that both microwave irradiation and the longer residence time favour more complete decomposition of large hydrocarbon molecules in coal and biomass, which subsequently results in less complicated composition compared with bio-oil produced via conventional pyrolysis. Char samples from microwave-induced pyrolysis undergo more complete pyrolysis than char samples from conventional pyrolysis, and results in less volatiles remaining. Because of the thermal annealing process by microwave at the later stage of pyrolysis, char samples produced by microwave-induced pyrolysis have higher peak temperatures and burnout temperatures than those produced by conventional pyrolysis. In char samples prepared via microwave-induced pyrolysis of coal and biomass, special structures are found, such as nano-scale fibers in char samples from gumwood and pine, spheres in char samples from coals as well as coal and biomass blends. Based on the analysis of energy balance, it is evident that microwave-induced pyrolysis is a cost-effective and energy saving method for solid fuel conversion.
Published: 2015

9. Search for new heavy neutral gauge bosons in √s = 8 TeV pp collisions with ATLAS

Author: Schnellbach, Yan-Jie
Subjects: 530, QC Physics
Abstract: This thesis describes the search for new heavy neutral gauge bosons decaying into di-electron pairs, focussing on the Z′SSM boson described by the Sequential Standard Model. The analysis uses 20.3fb−1 of pp collisions at √s = 8TeV recorded with the ATLAS detector during the 2012 data taking period at the Large Hadron Collider at CERN. The invariant mass spectrum of di-electron pairs is used as the search variable and is analysed in the region 80 GeV < mee < 4500 GeV. The spectrum is compared to the Standard Model expectation dominated by the neutral current Drell-Yan process. Several novel techniques are developed to improve the description of both, the Drell-Yan process and photon-induced di-lepton production. As no significant excess is found in the data, statistical techniques are used to interpret the result as limits on the production and decay of a new heavy gauge boson. A 95% C.L. Bayesian lower limit is set on the Z′SSM mass at 2.78TeV with a corresponding upper limit on the Z′SSM cross-section times branching ratio σ × Br(Z′SSM → e+e−) of 3.53 × 10−4 pb.
Published: 2014
Full Text: View/download PDF

10. The mechanical response of vinculin

Author: Liu, Xuyao, Wang, Yinan, Yao, Mingxi, Baker, Karen, Klapholz, Benjamin, Brown, Nicholas H., Goult, Benjamin T, Yan, Jie, Liu, Xuyao, Wang, Yinan, Yao, Mingxi, Baker, Karen, Klapholz, Benjamin, Brown, Nicholas H., Goult, Benjamin T, and Yan, Jie
Abstract: Vinculin is a mechanosensitive adapter protein that links the actin network to cell-extracellular matrix adhesions and cell-cell adhesions. It is perhaps the best characterized mechanoeffector, as it is recruited to sites of adhesion in response to force on the mechanotransducers talin and alpha-catenin. Here we examined the mechanical properties of vinculin to assess its potential role as a mechanotransducer. We find that at physiological loading rates, the structural domains of vinculin unfold at forces in the 5-15 pN range and rapidly refold when forces are reduced back to 1 pN. Thus, vinculin domains also have the potential to act as force dependent molecular switches, akin to those in talin and alpha-catenin. As with the force dependent switches in talin, the unfolding of these domains in vinculin introduces large extension changes in the vinculin cytoskeletal linkage up to 150 nm with 20-30 nm steps of unfolding. Modelling of the tension-dependent interactions of the unstructured vinculin linker region with a model protein containing two SH3 domains indicated that even unstructured protein regions can mediate force-dependent interactions with ligands, where the binding of a dual-SH3 model protein is predicted to be significantly suppressed by forces greater than 10 pN. Together, these findings suggest that vinculin has a complex mechanical response with force-dependent interaction sites, suggesting it also acts as a mechanotransducer, recruiting partners in response to force.
Published: 2023

11. 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, Wu Dawei, Candelaria de Haro, Felipe de Jesus Montelongo, Diego De Mendoza, Raúl de Pablo, Gennaro De Pascale, Silvia De Rosa, Maxens Decavèle, Pierre-Louis Declercq, Alberto Deicas, María Del Carmen Campos Moreno, Jean Dellamonica, Benjamin Delmas, Oktay Demirkiran, Hilmi Demirkiran, Tarek Dendane, Rossella di Mussi, Chrysi Diakaki, Anatilde Diaz, Willy Diaz, Yalim Dikmen, Aikaterini Dimoula, Patricia Doble, Nagwa Doha, Guilherme Domingos, Martin Dres, David Dries, Abhijit Duggal, Graeme Duke, Pavel Dunts, Knut Dybwik, Maksym Dykyy, Philippe Eckert, Serdar Efe, Souheil Elatrous, Gülseren Elay, Abubaker S Elmaryul, Mohamed Elsaadany, Hany Elsayed, Samar Elsayed, Malo Emery, Sébastien Ena, Kevin Eng, Joshua A Englert, Elif Erdogan, Perihan Ergin Ozcan, Ege Eroglu, Miguel Escobar, Figen Esen, Arzu Esen Tekeli, Alejandro Esquivel, Helbert Esquivel Gallegos, Hanane Ezzouine, Alberto Facchini, Mohammad Faheem, Vito Fanelli, Maria Fernanda Farina, Muriel Fartoukh, Lutz Fehrle, Feng Feng, Yufeng Feng, Irene Fernandez, Borja Fernandez, Maria Lorena Fernandez-Rodriguez, Carlos Ferrando, Maria João Ferreira da Silva, Mireia Ferreruela, Janet Ferrier, Matias Jesús Flamm Zamorano, Laura Flood, Leda Floris, Martin Fluckiger, Catalina Forteza, Antonella Fortunato, Eric Frans, Antonella Frattari, Sebastian Fredes, Tim Frenzel, Roberto Fumagalli, Mariano Andres Furche, Maurizio Fusari, Edward Fysh, Juan Luis Galeas-Lopez, Louis-Marie Galerneau, Analía Garcia, María Fernanda Garcia, Elisabet Garcia, Pablo Garcia Olivares, Jaroslaw Garlicki, Aude Garnero, Eugenio Garofalo, Prabha Gautam, Andrey Gazenkampf, Stéphanie Gelinotte, Domenico Gelormini, Etienne Ghrenassia, Angelo Giacomucci, Robert Giannoni, Andrea Gigante, Nancy Glober, Paolo Gnesin, Yari Gollo, Dina Gomaa, Rosita Gomero Paredes, Rui Gomes, Raúl Alejandro Gomez, Oscar Gomez, Aroa Gomez, Louise Gondim, Manuel Gonzalez, Isabel Gonzalez, Alejandro Gonzalez-Castro, Orlando Gordillo Romero, Federico Gordo, Philippe Gouin, Jerónimo Graf Santos, Rooney Grainne, Matilde Grando, Sanja Granov Grabovica, Salvatore Grasso, Rinaldo Grasso, Lisa Grimmer, Colin Grissom, Qing Gu, Xiang-Dong Guan, Fabio Guarracino, Neus Guasch, Luca Guatteri, Renaud Gueret, Claude Guérin, Emmanuel Guerot, Pierre-Gildas Guitard, Fethi Gül, Ayca Gumus, Mohan Gurjar, Patricia Gutierrez, Abdelhamid Hachimi, Adi Hadzibegovic, Samantha Hagan, Clare Hammel, Joo Han Song, Gabrielle Hanlon, Serge Heines, Johanna Henriksson, Jean-Etienne Herbrecht, Gabriel Omar Heredia Orbegoso, Andrew Hermon, Rosana Hernandez, Carmen Hernandez, Luis Herrera, Manuel Herrera-Gutierrez, Leo Heunks, Juan Hidalgo, Dianne Hill, Dagmar Holmquist, Marcela Homez, Xia Hongtao, Anil Hormis, Daniel Horner, M Carmen Hornos, Meihong Hou, Stacy House, Brahim Housni, Keith Hugill, Sally Humphreys, Louis Humbert, Stephanie Hunter, Lee Hwa Young, Nicolas Iezzi, Santiago Ilutovich, Volkan Inal, Richard Innes, Panagiotis Ioannides, Giorgio Antonio Iotti, 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 Lagache, Antonio Landaverde Lopez, Michael Lanspa, Valeria Lascari, Matthieu Le Meur, Su Hwan Lee, Young Ju Lee, Jinwoo Lee, Won-Yeon Lee, Jarone Lee, Terje Legernaes, Tamaas Leiner, Virginie Lemiale, Tiago Leonor, Philipp M Lepper, Dahuan Li, Hongbin Li, Oleg Li, Ana Raquel Lima, Dan Lind, Edward Litton, Ning Liu, Ling Liu, Jialin Liu, Jean-François Llitjos, Beatriz Llorente, Rodolfo Lopez, Claudia Elizabeth Lopez, Claudia Lopez Nava, Pablo Lovazzano, Min Lu, Francesca Lucchese, Manuela Lugano, Gustavo Lugo Goytia, Hua Luo, Ceri Lynch, Sebastiano Macheda, Victor Hugo Madrigal Robles, Salvatore Maurizio Maggiore, Mònica Magret Iglesias, Peter Malaga, Harish Mallapura Maheswarappa, Guillermo Malpartida, Andrey Malyarchikov, Helena Mansson, Anaid 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, Ronald Zumaran, 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, Wu Dawei, Candelaria de Haro, Felipe de Jesus Montelongo, Diego De Mendoza, Raúl de Pablo, Gennaro De Pascale, Silvia De Rosa, Maxens Decavèle, Pierre-Louis Declercq, Alberto Deicas, María Del Carmen Campos Moreno, Jean Dellamonica, Benjamin Delmas, Oktay Demirkiran, Hilmi Demirkiran, Tarek Dendane, Rossella di Mussi, Chrysi Diakaki, Anatilde Diaz, Willy Diaz, Yalim Dikmen, Aikaterini Dimoula, Patricia Doble, Nagwa Doha, Guilherme Domingos, Martin Dres, David Dries, Abhijit Duggal, Graeme Duke, Pavel Dunts, Knut Dybwik, Maksym Dykyy, Philippe Eckert, Serdar Efe, Souheil Elatrous, Gülseren Elay, Abubaker S Elmaryul, Mohamed Elsaadany, Hany Elsayed, Samar Elsayed, Malo Emery, Sébastien Ena, Kevin Eng, Joshua A Englert, Elif Erdogan, Perihan Ergin Ozcan, Ege Eroglu, Miguel Escobar, Figen Esen, Arzu Esen Tekeli, Alejandro Esquivel, Helbert Esquivel Gallegos, Hanane Ezzouine, Alberto Facchini, Mohammad Faheem, Vito Fanelli, Maria Fernanda Farina, Muriel Fartoukh, Lutz Fehrle, Feng Feng, Yufeng Feng, Irene Fernandez, Borja Fernandez, Maria Lorena Fernandez-Rodriguez, Carlos Ferrando, Maria João Ferreira da Silva, Mireia Ferreruela, Janet Ferrier, Matias Jesús Flamm Zamorano, Laura Flood, Leda Floris, Martin Fluckiger, Catalina Forteza, Antonella Fortunato, Eric Frans, Antonella Frattari, Sebastian Fredes, Tim Frenzel, Roberto Fumagalli, Mariano Andres Furche, Maurizio Fusari, Edward Fysh, Juan Luis Galeas-Lopez, Louis-Marie Galerneau, Analía Garcia, María Fernanda Garcia, Elisabet Garcia, Pablo Garcia Olivares, Jaroslaw Garlicki, Aude Garnero, Eugenio Garofalo, Prabha Gautam, Andrey Gazenkampf, Stéphanie Gelinotte, Domenico Gelormini, Etienne Ghrenassia, Angelo Giacomucci, Robert Giannoni, Andrea Gigante, Nancy Glober, Paolo Gnesin, Yari Gollo, Dina Gomaa, Rosita Gomero Paredes, Rui Gomes, Raúl Alejandro Gomez, Oscar Gomez, Aroa Gomez, Louise Gondim, Manuel Gonzalez, Isabel Gonzalez, Alejandro Gonzalez-Castro, Orlando Gordillo Romero, Federico Gordo, Philippe Gouin, Jerónimo Graf Santos, Rooney Grainne, Matilde Grando, Sanja Granov Grabovica, Salvatore Grasso, Rinaldo Grasso, Lisa Grimmer, Colin Grissom, Qing Gu, Xiang-Dong Guan, Fabio Guarracino, Neus Guasch, Luca Guatteri, Renaud Gueret, Claude Guérin, Emmanuel Guerot, Pierre-Gildas Guitard, Fethi Gül, Ayca Gumus, Mohan Gurjar, Patricia Gutierrez, Abdelhamid Hachimi, Adi Hadzibegovic, Samantha Hagan, Clare Hammel, Joo Han Song, Gabrielle Hanlon, Serge Heines, Johanna Henriksson, Jean-Etienne Herbrecht, Gabriel Omar Heredia Orbegoso, Andrew Hermon, Rosana Hernandez, Carmen Hernandez, Luis Herrera, Manuel Herrera-Gutierrez, Leo Heunks, Juan Hidalgo, Dianne Hill, Dagmar Holmquist, Marcela Homez, Xia Hongtao, Anil Hormis, Daniel Horner, M Carmen Hornos, Meihong Hou, Stacy House, Brahim Housni, Keith Hugill, Sally Humphreys, Louis Humbert, Stephanie Hunter, Lee Hwa Young, Nicolas Iezzi, Santiago Ilutovich, Volkan Inal, Richard Innes, Panagiotis Ioannides, Giorgio Antonio Iotti, 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 Lagache, Antonio Landaverde Lopez, Michael Lanspa, Valeria Lascari, Matthieu Le Meur, Su Hwan Lee, Young Ju Lee, Jinwoo Lee, Won-Yeon Lee, Jarone Lee, Terje Legernaes, Tamaas Leiner, Virginie Lemiale, Tiago Leonor, Philipp M Lepper, Dahuan Li, Hongbin Li, Oleg Li, Ana Raquel Lima, Dan Lind, Edward Litton, Ning Liu, Ling Liu, Jialin Liu, Jean-François Llitjos, Beatriz Llorente, Rodolfo Lopez, Claudia Elizabeth Lopez, Claudia Lopez Nava, Pablo Lovazzano, Min Lu, Francesca Lucchese, Manuela Lugano, Gustavo Lugo Goytia, Hua Luo, Ceri Lynch, Sebastiano Macheda, Victor Hugo Madrigal Robles, Salvatore Maurizio Maggiore, Mònica Magret Iglesias, Peter Malaga, Harish Mallapura Maheswarappa, Guillermo Malpartida, Andrey Malyarchikov, Helena Mansson, Anaid 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

12. Medium-Term Wind Power Forecasting based on Dynamic Self-Attention Mechanism

Author: Chen, Fuhao, Yan, Jie, Bertling, Lina, Song, Dian, Yan, Yamin, Liu, Yongqian, Chen, Fuhao, Yan, Jie, Bertling, Lina, Song, Dian, Yan, Yamin, and Liu, Yongqian
Abstract: Medium-Term Wind Power Forecasting (MTWPF), with a 7-day forecasting horizon, can provide important support for dispatch plans in the power system and trading strategies in the electricity market. Existing MTWPF methods usually use the Numerical Weather Prediction (NWP) to map the power generated by wind farms. However, the accuracy of the NWP decreases as the forecasting horizon increases, which reduces the performance of the MTWPF. In this paper, we propose a MTWPF model based on multi-head Dynamic Self-Attention mechanism (DSA-MTWPF), which dynamically adjusts the mapping between NWP and wind power according to the change in forecasting horizon. A case study using operational data from one wind farm in China demonstrates that the DSAM-MTWPF outperforms that of the state-of-the-art MTWPF models., Part of ISBN 9781665487788QC 20230919
Published: 2023
Full Text: View/download PDF

13. Improving sustainable Chinese pig production by sharing knowledge from the Netherlands

Author: Hoste, Robert, Yan, Jie, Hoste, Robert, and Yan, Jie
Abstract: Which knowledge transfer would be helpful for pig production in China to increase sustainability and efficiency, and which ways of knowledge exchange are suitable? An analysis of these questions was performed. Knowledge sharing can be directed towards both large companies and middle-sized family farms. Needs regarding topics and approach differ among both types of farms. A train-the-trainer approach seems suitable for middle management (foremen) and family farm owners, making them ambassadors for further dissemination. Dutch companies have a potential role in knowledge transfer to Chinese trade partners, as the Netherlands is seen as a role model for the Chinese pig industry. Research has been performed on the apparently existing knowledge gap in Chinese pig production, against the background of policy and the societal situation, based on limited literature research and on interviews.---Welke kennisoverdracht kan de varkensproductie in China helpen om duurzamer en efficiënter te produceren, en welke manieren van kennisoverdracht zijn bruikbaar? Deze vragen zijn onderzocht. Kennisoverdracht kan plaatsvinden richting zowel grote ondernemingen als middelgrote familiebedrijven. Behoeften ten aanzien van thema’s en aanpak zijn verschillend tussen beide ondernemingstypen. Een train-de-trainer aanpak lijkt bruikbaar voor het middenmanagement en familiebedrijven, waarbij deze ambassadeurs worden voor verdere kennisverspreiding onder de werknemers. Nederlandse bedrijven hebben, vanuit Nederland als rolmodel, een potentiële rol in de kennisoverdracht naar Chinese handelspartners. Onderzoek is gedaan naar de kennelijke kennisleemte in de Chinese varkensproductie, tegen de achtergrond van de politieke en maatschappelijke situatie. Dit is uitgevoerd op basis van beperkt literatuuronderzoek en van interviews.
Published: 2023

14. Beijing Area Study-2019

Author: Administrator, Yan, Jie, Liying Ren, Mingming Shen, Yang, Ming, Administrator, Yan, Jie, Liying Ren, Mingming Shen, and Yang, Ming
Abstract: Beijing Area Study-2019
Published: 2023

15. Conservative State Value Estimation for Offline Reinforcement Learning

Author: Chen, Liting, Yan, Jie, Shao, Zhengdao, Wang, Lu, Lin, Qingwei, Rajmohan, Saravan, Moscibroda, Thomas, Zhang, Dongmei, Chen, Liting, Yan, Jie, Shao, Zhengdao, Wang, Lu, Lin, Qingwei, Rajmohan, Saravan, Moscibroda, Thomas, and Zhang, Dongmei
Abstract: Offline reinforcement learning faces a significant challenge of value over-estimation due to the distributional drift between the dataset and the current learned policy, leading to learning failure in practice. The common approach is to incorporate a penalty term to reward or value estimation in the Bellman iterations. Meanwhile, to avoid extrapolation on out-of-distribution (OOD) states and actions, existing methods focus on conservative Q-function estimation. In this paper, we propose Conservative State Value Estimation (CSVE), a new approach that learns conservative V-function via directly imposing penalty on OOD states. Compared to prior work, CSVE allows more effective state value estimation with conservative guarantees and further better policy optimization. Further, we apply CSVE and develop a practical actor-critic algorithm in which the critic does the conservative value estimation by additionally sampling and penalizing the states \emph{around} the dataset, and the actor applies advantage weighted updates extended with state exploration to improve the policy. We evaluate in classic continual control tasks of D4RL, showing that our method performs better than the conservative Q-function learning methods and is strongly competitive among recent SOTA methods., Comment: Accepted in NeurIPS 2023
Published: 2023

16. The Short and Long Term Consequences of Delayed Cord Clamping on Late Pre-Term Infants

Author: Yan,Jie, Ren,Jian-Dong, Zhang,Jie, Li,Jun, Zhang,Xu, Ma,Yan, Gao,Li, Yan,Jie, Ren,Jian-Dong, Zhang,Jie, Li,Jun, Zhang,Xu, Ma,Yan, and Gao,Li
Abstract: Jie Yan, Jian-Dong Ren, Jie Zhang, Jun Li, Xu Zhang, Yan Ma, Li Gao Department of Neonatology, Suzhou Ninth Peopleâs Hospital, Suzhou, Peopleâs Republic of ChinaCorrespondence: Jian-Dong Ren, Department of Neonatology, Suzhou Ninth Peopleâs Hospital, No. 2666 Ludang Road, Wujiang District, Suzhou, Jiangsu, 215000, Peopleâs Republic of China, Tel +8615050371917, Email renjiandongrjd02@126.comObjective: To explore the effect of delayed cord clamping on preterm infants.Methods: A retrospective analysis was conducted using the clinical data of 163 preterm infants with a gestational age of 34â 36 weeks + 6 who were admitted to the neonatology department within 2 hours after birth. The blood routine examination indices within 2 hours and at 3â 5 days after birth, the biochemical indices and arterial blood gas (ABG) indices within 2 hours after birth, and the hemoglobin level 5â 6 months after birth were compared between the early cord clamping (ECC) group and the delayed cord clamping (DCC) group.Results: Compared with the ECC group, the DCC group had significantly higher venous blood levels of red blood cells, hemoglobin, and hematocrit within 2 hours and at 3â 5 days after birth. The ABG bicarbonate (HCO3) level within 2 hours after birth was obviously higher in the DCC group than in the ECC group, and the ABG absolute base excess(BE) and lactate levels were lower in the DCC group than in the ECC group (P < 0.05). There was no significant difference between the two groups in the incidence of hypothermia, hypoglycemia, respiratory distress, septicemia, feeding intolerance, polycythemia, and hyperbilirubinemia requiring phototherapy during hospitalization (P > 0.05). Compared with the ECC group, the DCC group had a significantly higher venous blood hemoglobin level 5â 6 months after birth. The incidence of anemia in the DCC group was significantly lower than in the ECC group (P < 0.05).Conclusion: Delayed cord clamping can significantly increase
Published: 2023

17. Introspective Tips: Large Language Model for In-Context Decision Making

Author: Chen, Liting, Wang, Lu, Dong, Hang, Du, Yali, Yan, Jie, Yang, Fangkai, Li, Shuang, Zhao, Pu, Qin, Si, Rajmohan, Saravan, Lin, Qingwei, Zhang, Dongmei, Chen, Liting, Wang, Lu, Dong, Hang, Du, Yali, Yan, Jie, Yang, Fangkai, Li, Shuang, Zhao, Pu, Qin, Si, Rajmohan, Saravan, Lin, Qingwei, and Zhang, Dongmei
Abstract: The emergence of large language models (LLMs) has substantially influenced natural language processing, demonstrating exceptional results across various tasks. In this study, we employ ``Introspective Tips" to facilitate LLMs in self-optimizing their decision-making. By introspectively examining trajectories, LLM refines its policy by generating succinct and valuable tips. Our method enhances the agent's performance in both few-shot and zero-shot learning situations by considering three essential scenarios: learning from the agent's past experiences, integrating expert demonstrations, and generalizing across diverse games. Importantly, we accomplish these improvements without fine-tuning the LLM parameters; rather, we adjust the prompt to generalize insights from the three aforementioned situations. Our framework not only supports but also emphasizes the advantage of employing LLM in in-contxt decision-making. Experiments involving over 100 games in TextWorld illustrate the superior performance of our approach., Comment: 22 pages, 4 figures
Published: 2023

18. NoiseTrans: Point Cloud Denoising with Transformers

Author: Hou, Guangzhe, Qin, Guihe, Sun, Minghui, Liang, Yanhua, Yan, Jie, Zhang, Zhonghan, Hou, Guangzhe, Qin, Guihe, Sun, Minghui, Liang, Yanhua, Yan, Jie, and Zhang, Zhonghan
Abstract: Point clouds obtained from capture devices or 3D reconstruction techniques are often noisy and interfere with downstream tasks. The paper aims to recover the underlying surface of noisy point clouds. We design a novel model, NoiseTrans, which uses transformer encoder architecture for point cloud denoising. Specifically, we obtain structural similarity of point-based point clouds with the assistance of the transformer's core self-attention mechanism. By expressing the noisy point cloud as a set of unordered vectors, we convert point clouds into point embeddings and employ Transformer to generate clean point clouds. To make the Transformer preserve details when sensing the point cloud, we design the Local Point Attention to prevent the point cloud from being over-smooth. In addition, we also propose sparse encoding, which enables the Transformer to better perceive the structural relationships of the point cloud and improve the denoising performance. Experiments show that our model outperforms state-of-the-art methods in various datasets and noise environments.
Published: 2023

19. TLN1 contains a cancer-associated cassette exon that alters talin-1 mechanosensitivity

Author: Pathologie Groep Derksen, Cancer, Gallego-Paez, Lina M, Edwards, William J S, Chanduri, Manasa, Guo, Yanyu, Koorman, Thijs, Lee, Chieh-Yu, Grexa, Nina, Derksen, Patrick, Yan, Jie, Schwartz, Martin A, Mauer, Jan, Goult, Benjamin Thomas, Pathologie Groep Derksen, Cancer, Gallego-Paez, Lina M, Edwards, William J S, Chanduri, Manasa, Guo, Yanyu, Koorman, Thijs, Lee, Chieh-Yu, Grexa, Nina, Derksen, Patrick, Yan, Jie, Schwartz, Martin A, Mauer, Jan, and Goult, Benjamin Thomas
Published: 2023

20. ClusterDDPM: An EM clustering framework with Denoising Diffusion Probabilistic Models

Author: Yan, Jie, Liu, Jing, Zhang, Zhong-yuan, Yan, Jie, Liu, Jing, and Zhang, Zhong-yuan
Abstract: Variational autoencoder (VAE) and generative adversarial networks (GAN) have found widespread applications in clustering and have achieved significant success. However, the potential of these approaches may be limited due to VAE's mediocre generation capability or GAN's well-known instability during adversarial training. In contrast, denoising diffusion probabilistic models (DDPMs) represent a new and promising class of generative models that may unlock fresh dimensions in clustering. In this study, we introduce an innovative expectation-maximization (EM) framework for clustering using DDPMs. In the E-step, we aim to derive a mixture of Gaussian priors for the subsequent M-step. In the M-step, our focus lies in learning clustering-friendly latent representations for the data by employing the conditional DDPM and matching the distribution of latent representations to the mixture of Gaussian priors. We present a rigorous theoretical analysis of the optimization process in the M-step, proving that the optimizations are equivalent to maximizing the lower bound of the Q function within the vanilla EM framework under certain constraints. Comprehensive experiments validate the advantages of the proposed framework, showcasing superior performance in clustering, unsupervised conditional generation and latent representation learning.
Published: 2023

21. A Novel Multi-Task Model Imitating Dermatologists for Accurate Differential Diagnosis of Skin Diseases in Clinical Images

Author: Zhou, Yan-Jie, Liu, Wei, Gao, Yuan, Xu, Jing, Lu, Le, Duan, Yuping, Cheng, Hao, Jin, Na, Man, Xiaoyong, Zhao, Shuang, Wang, Yu, Zhou, Yan-Jie, Liu, Wei, Gao, Yuan, Xu, Jing, Lu, Le, Duan, Yuping, Cheng, Hao, Jin, Na, Man, Xiaoyong, Zhao, Shuang, and Wang, Yu
Abstract: Skin diseases are among the most prevalent health issues, and accurate computer-aided diagnosis methods are of importance for both dermatologists and patients. However, most of the existing methods overlook the essential domain knowledge required for skin disease diagnosis. A novel multi-task model, namely DermImitFormer, is proposed to fill this gap by imitating dermatologists' diagnostic procedures and strategies. Through multi-task learning, the model simultaneously predicts body parts and lesion attributes in addition to the disease itself, enhancing diagnosis accuracy and improving diagnosis interpretability. The designed lesion selection module mimics dermatologists' zoom-in action, effectively highlighting the local lesion features from noisy backgrounds. Additionally, the presented cross-interaction module explicitly models the complicated diagnostic reasoning between body parts, lesion attributes, and diseases. To provide a more robust evaluation of the proposed method, a large-scale clinical image dataset of skin diseases with significantly more cases than existing datasets has been established. Extensive experiments on three different datasets consistently demonstrate the state-of-the-art recognition performance of the proposed approach., Comment: MICCAI 2023 early accept
Published: 2023

22. Reprogramming of m6A epitranscriptome is crucial for shaping of transcriptome and proteome in response to hypoxia.

Author: Wang, Yan-Jie, Wang, Yan-Jie, Yang, Bing, Lai, Qiao, Shi, Jun-Fang, Peng, Jiang-Yun, Zhang, Yin, Hu, Kai-Shun, Li, Ya-Qing, Peng, Jing-Wen, Yang, Zhi-Zhi, Li, Yao-Ting, Pan, Yue, Koeffler, H Phillip, Liao, Jian-You, Yin, Dong, Wang, Yan-Jie, Wang, Yan-Jie, Yang, Bing, Lai, Qiao, Shi, Jun-Fang, Peng, Jiang-Yun, Zhang, Yin, Hu, Kai-Shun, Li, Ya-Qing, Peng, Jing-Wen, Yang, Zhi-Zhi, Li, Yao-Ting, Pan, Yue, Koeffler, H Phillip, Liao, Jian-You, and Yin, Dong
Abstract: Hypoxia causes a series of responses supporting cells to survive in harsh environments. Substantial post-transcriptional and translational regulation during hypoxia has been observed. However, detailed regulatory mechanism in response to hypoxia is still far from complete. RNA m6A modification has been proven to govern the life cycle of RNAs. Here, we reported that total m6A level of mRNAs was decreased during hypoxia, which might be mediated by the induction of m6A eraser, ALKBH5. Meanwhile, expression levels of most YTH family members of m6A readers were systematically down-regulated. Transcriptome-wide analysis of m6A revealed a drastic reprogramming of m6A epitranscriptome during cellular hypoxia. Integration of m6A epitranscriptome with either RNA-seq based transcriptome analysis or mass spectrometry (LC-MS/MS) based proteome analysis of cells upon hypoxic stress revealed that reprogramming of m6A epitranscriptome reshaped the transcriptome and proteome, thereby supporting efficient generation of energy for adaption to hypoxia. Moreover, ATP production was blocked when silencing an m6A eraser, ALKBH5, under hypoxic condition, demonstrating that m6A pathway is an important regulator during hypoxic response. Collectively, our studies indicate that crosstalk between m6A and HIF1 pathway is essential for cellular response to hypoxia, providing insights into the underlying molecular mechanisms during hypoxia.
Published: 2021

23. A novel cancer-associated cassette exon in TLN1 alters Talin 1 mechanosensitivity

Author: Gallego-Paez, LM, Edwards, WJS, Guichaoua, Yvan, Chanduri, M, Koorman, T, Lee, C-Y, Grexa, N, Derksen, PWB, Yan, Jie, Schwartz, Martin A., Mauer, Jan, Goult, Benjamin T, Gallego-Paez, LM, Edwards, WJS, Guichaoua, Yvan, Chanduri, M, Koorman, T, Lee, C-Y, Grexa, N, Derksen, PWB, Yan, Jie, Schwartz, Martin A., Mauer, Jan, and Goult, Benjamin T
Abstract: Talin 1 is the core mechanosensitive adapter protein linking integrins to the cytoskeleton. The TLN1 gene is comprised of 57 exons that encode the 2541 amino acid TLN1 protein. TLN1 was previously considered to be expressed as a single isoform. However, through differential pre-mRNA splicing analysis, we discovered a cancer-enriched, non-annotated 51-nucleotide exon in TLN1 between exons 17 and 18, which we refer to as exon 17b. TLN1 is comprised of an N-terminal FERM domain, linked to 13 force-dependent switch domains, R1-R13. Inclusion of exon 17b results in an in-frame insertion of 17 amino acids immediately after Gln665 in the region between R1-R2 which lowers the force required to open the R1-R2 switches potentially altering downstream mechanotransduction. Biochemical analysis of this isoform revealed enhanced vinculin binding, and cells expressing this variant show altered adhesion dynamics. Finally, we show that the TGF-Beta/SMAD3 signaling pathway regulates this isoform switch. Future studies will need to consider the balance of these two TLN1 isoforms.
Published: 2022

24. Privacy-Preserving Federated Deep Clustering based on GAN

Author: Yan, Jie, Liu, Jing, Qi, Ji, Zhang, Zhong-Yuan, Yan, Jie, Liu, Jing, Qi, Ji, and Zhang, Zhong-Yuan
Abstract: Federated clustering (FC) is an essential extension of centralized clustering designed for the federated setting, wherein the challenge lies in constructing a global similarity measure without the need to share private data. Conventional approaches to FC typically adopt extensions of centralized methods, like K-means and fuzzy c-means. However, these methods are susceptible to non-independent-and-identically-distributed (non-IID) data among clients, leading to suboptimal performance, particularly with high-dimensional data. In this paper, we present a novel approach to address these limitations by proposing a Privacy-Preserving Federated Deep Clustering based on Generative Adversarial Networks (GANs). Each client trains a local generative adversarial network (GAN) locally and uploads the synthetic data to the server. The server applies a deep clustering network on the synthetic data to establish $k$ cluster centroids, which are then downloaded to the clients for cluster assignment. Theoretical analysis demonstrates that the GAN-generated samples, shared among clients, inherently uphold certain privacy guarantees, safeguarding the confidentiality of individual data. Furthermore, extensive experimental evaluations showcase the effectiveness and utility of our proposed method in achieving accurate and privacy-preserving federated clustering.
Published: 2022

25. Federated clustering with GAN-based data synthesis

Author: Yan, Jie, Liu, Jing, Qi, Ji, Zhang, Zhong-Yuan, Yan, Jie, Liu, Jing, Qi, Ji, and Zhang, Zhong-Yuan
Abstract: Federated clustering (FC) is an extension of centralized clustering in federated settings. The key here is how to construct a global similarity measure without sharing private data, since the local similarity may be insufficient to group local data correctly and the similarity of samples across clients cannot be directly measured due to privacy constraints. Obviously, the most straightforward way to analyze FC is to employ the methods extended from centralized ones, such as K-means (KM) and fuzzy c-means (FCM). However, they are vulnerable to non independent-and-identically-distributed (non-IID) data among clients. To handle this, we propose a new federated clustering framework, named synthetic data aided federated clustering (SDA-FC). It trains generative adversarial network locally in each client and uploads the generated synthetic data to the server, where KM or FCM is performed on the synthetic data. The synthetic data can make the model immune to the non-IID problem and enable us to capture the global similarity characteristics more effectively without sharing private data. Comprehensive experiments reveals the advantages of SDA-FC, including superior performance in addressing the non-IID problem and the device failures.
Published: 2022

26. Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach

Author: Yan, Jie, Lu, Yunlei, Chen, Liting, Qin, Si, Fang, Yixin, Lin, Qingwei, Moscibroda, Thomas, Rajmohan, Saravan, Zhang, Dongmei, Yan, Jie, Lu, Yunlei, Chen, Liting, Qin, Si, Fang, Yixin, Lin, Qingwei, Moscibroda, Thomas, Rajmohan, Saravan, and Zhang, Dongmei
Abstract: This paper investigates a critical resource allocation problem in the first party cloud: scheduling containers to machines. There are tens of services and each service runs a set of homogeneous containers with dynamic resource usage; containers of a service are scheduled daily in a batch fashion. This problem can be naturally formulated as Stochastic Bin Packing Problem (SBPP). However, traditional SBPP research often focuses on cases of empty machines, whose objective, i.e., to minimize the number of used machines, is not well-defined for the more common reality with nonempty machines. This paper aims to close this gap. First, we define a new objective metric, Used Capacity at Confidence (UCaC), which measures the maximum used resources at a probability and is proved to be consistent for both empty and nonempty machines, and reformulate the SBPP under chance constraints. Second, by modeling the container resource usage distribution in a generative approach, we reveal that UCaC can be approximated with Gaussian, which is verified by trace data of real-world applications. Third, we propose an exact solver by solving the equivalent cutting stock variant as well as two heuristics-based solvers -- UCaC best fit, bi-level heuristics. We experimentally evaluate these solvers on both synthetic datasets and real application traces, demonstrating our methodology's advantage over traditional SBPP optimal solver minimizing the number of used machines, with a low rate of resource violations., Comment: To appear in SIGKDD 2022 as Research Track paper
Published: 2022
Full Text: View/download PDF

27. Uncovering wind power forecasting uncertainty sources and their propagation through the whole modelling chain

Author: Yan, Jie, Möhrlen, Corinna, Göçmen, Tuhfe, Kelly, Mark, Wessel, Arne, Giebel, Gregor, Yan, Jie, Möhrlen, Corinna, Göçmen, Tuhfe, Kelly, Mark, Wessel, Arne, and Giebel, Gregor
Abstract: Wind power forecasting has supported operational decision-making for power system and electricity markets for 30 years. Efforts of improving the accuracy and/or certainty of deterministic or probabilistic wind power forecasts are continuously exerted by academics and industries. Forecast errors and associated uncertainties propagating through the whole forecasting chain, from weather provider to end user, cannot be eliminated completely. Therefore, understanding the uncertainty sources and how these uncertainties propagate throughout the modelling chain is significant to implement more rational and targeted uncertainty mitigation strategies and standardise the forecast and uncertainty validation. This paper presents a qualitative review on wind power forecasting uncertainty. First, the definition of uncertainty sources throughout the forecast modelling chain acts as a guiding line for checking and evaluating the uncertainty of a wind power forecast system/model. For each of the types of uncertainty sources, uncertainty mitigation strategies are provided, starting from the planning phase of wind farms, the establishment of a forecasting system through the operational phase and market phase. Our review finalises with a discussion on uncertainty validation with an example on ramp forecast validation. Highlights are a qualitative review and discussion including: (1) forecasting uncertainty exists and propagates everywhere throughout the entire modelling chain, from the planning phase to the market phase; (2) the mitigation efforts should be exerted in every modelling step; (3) standardised uncertainty validation practice, including why global data samples are required for forecasters to improve model performance and for forecast users to select and evaluate forecast model outputs.
Published: 2022

28. Selective clustering ensemble based on kappa and F-score

Author: Yan, Jie, Liu, Xin, Qi, Ji, You, Tao, Zhang, Zhong-Yuan, Yan, Jie, Liu, Xin, Qi, Ji, You, Tao, and Zhang, Zhong-Yuan
Abstract: Clustering ensemble has an impressive performance in improving the accuracy and robustness of partition results and has received much attention in recent years. Selective clustering ensemble (SCE) can further improve the ensemble performance by selecting base partitions or clusters in according to diversity and stability. However, there is a conflict between diversity and stability, and how to make the trade-off between the two is challenging. The key here is how to evaluate the quality of the base partitions and clusters. In this paper, we propose a new evaluation method for partitions and clusters using kappa and F-score, leading to a new SCE method, which uses kappa to select informative base partitions and uses F-score to weight clusters based on stability. The effectiveness and efficiency of the proposed method is empirically validated over real datasets.
Published: 2022

29. Multi-synchronization and other patterns of multi-rhythmicity in oscillatory biological systems

Author: Goldbeter, Albert, Yan, Jie, Goldbeter, Albert, and Yan, Jie
Abstract: While experimental and theoretical studies have established the prevalence of rhythmic behaviour at all levels of biological organization, less common is the coexistence between multiple oscillatory regimes (multi-rhythmicity), which has been predicted by a variety of models for biological oscillators. The phenomenon of multi-rhythmicity involves, most commonly, the coexistence between two (birhythmicity) or three (trirhythmicity) distinct regimes of self-sustained oscillations. Birhythmicity has been observed experimentally in a few chemical reactions and in biological examples pertaining to cardiac cell physiology, neurobiology, human voice patterns and ecology. The present study consists of two parts. We first review the mechanisms underlying multi-rhythmicity in models for biochemical and cellular oscillations in which the phenomenon was investigated over the years. In the second part, we focus on the coupling of the cell cycle and the circadian clock and show how an additional source of multi-rhythmicity arises from the bidirectional coupling of these two cellular oscillators. Upon bidirectional coupling, the two oscillatory networks generally synchronize in a unique manner characterized by a single, common period. In some conditions, however, the two oscillators may synchronize in two or three different ways characterized by distinct waveforms and periods. We refer to this type of multi-rhythmicity as ‘multi-synchronization’., SCOPUS: re.j, info:eu-repo/semantics/published
Published: 2022

30. Network Analysis of Comorbid Anxiety and Insomnia Among Clinicians with Depressive Symptoms During the Late Stage of the COVID-19 Pandemic: A Cross-Sectional Study

Author: Cai,Hong, Zhao,Yan-jie, Xing,Xiaomeng, Tian,Tengfei, Qian,Wang, Liang,Sixiang, Wang,Zhe, Cheung,Teris, Su,Zhaohui, Tang,Yi-Lang, Ng,Chee H, Sha,Sha, Xiang,Yu-Tao, Cai,Hong, Zhao,Yan-jie, Xing,Xiaomeng, Tian,Tengfei, Qian,Wang, Liang,Sixiang, Wang,Zhe, Cheung,Teris, Su,Zhaohui, Tang,Yi-Lang, Ng,Chee H, Sha,Sha, and Xiang,Yu-Tao
Abstract: Hong Cai,1â 3,&ast; Yan-jie Zhao,1â 3,&ast; Xiaomeng Xing,4,&ast; Tengfei Tian,4,&ast; Wang Qian,4 Sixiang Liang,4 Zhe Wang,4 Teris Cheung,5 Zhaohui Su,6 Yi-Lang Tang,7,8 Chee H Ng,9 Sha Sha,4 Yu-Tao Xiang1â 3 1Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao Special Administrative Region, Peopleâs Republic of China; 2Centre for Cognitive and Brain Sciences, University of Macau, Macao Special Administrative Region, Peopleâs Republic of China; 3Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao Special Administrative Region, Peopleâs Republic of China; 4The National Clinical Research Center for Mental Disorder & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, Peopleâs Republic of China; 5School of Nursing, Hong Kong Polytechnic University, Hong Kong Special Administrative Region, Peopleâs Republic of China; 6School of Public Health, Southeast University, Nanjing, China, Nanjing, Peopleâs Republic of China; 7Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA; 8Atlanta VA Medical Center, Decatur, GA, USA; 9Department of Psychiatry, The Melbourne Clinic and St Vincentâs Hospital, University of Melbourne, Richmond, Victoria, Australia&ast;These authors contributed equally to this workCorrespondence: Sha Sha, The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, School of Mental Health, Beijing, Peopleâs Republic of China, Email sarahbon@163.com Chee H Ng, Department of Psychiatry, The Melbourne Clinic and St Vincentâs Hospital, University
Published: 2022

31. Predictive Value of Red Blood Cell Distribution Width for 1-Year All-Cause Mortality in Critically Ill Patients with Acute Myocardial Infarction

Author: Chen,Min, Liao,Lin, Yan,Jie, Lin,Fa-Quan, Chen,Min, Liao,Lin, Yan,Jie, and Lin,Fa-Quan
Abstract: Min Chen, Lin Liao, Jie Yan, Fa-Quan Lin Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Nanning, Peopleâs Republic of ChinaCorrespondence: Fa-Quan Lin Email fqlin1998@163.comObjective: Red blood cell distribution width (RDW) on admission is a prognostic factor in cardiovascular disease. This study investigated the prognostic value of the RDW measured within 24 hours before discharge (24h dRDW) on 1-year all-cause mortality in critically ill patients with acute myocardial infarction (AMI), and compared the effect of 24h dRDW in anemia and non-anemia patients.Materials and Methods: Altogether, 4088 patients with AMI were studied retrospectively. Data from the MIMIC-III database were collected and analyzed. The KaplanâMeier method, Cox regression models, and receiver operating characteristic (ROC) analysis were used to assess the impact of 24h dRDW on all-cause mortality in AMI patients, and a stratified analysis was performed to investigate the prognostic value of 24h dRDW in anemia and non-anemia patients.Results: Of the 4088 patients, there were 704 non-survivors (17.2%). The non-survivors had a higher RDW than the survivors (p< 0.001). Cox regression analysis showed that 24h dRDW had a significant independent association with 1âyear all-cause mortality in critically ill patients with AMI (quintile 5 vs quintile 1, HR, 95% CI: 2.847, 2.014â 4.023). The area under the ROC curve of 24h dRDW was 0.710 (95% CI, 0.689â 0.730). In the stratified analysis, a significant prognostic value of 24h dRDW was found in anemia patients for 1-year all-cause mortality, but not in non-anemia patients.Conclusion: Elevated 24h dRDW values are significantly associated with increased hazards of allâcause mortality in critically ill patients with AMI. Significant prognostic value of 24h dRDW was found in AMI patients with anemia, but not in those without anemia.Keywords: acute myocardial infarction, anemia, prognostic factors
Published: 2022

32. Brief communication: New radar constraints support presence of ice older than 1.5 Myr at Little Dome C

Author: Lilien, David A, Steinhage, Daniel, Taylor, Drew, Parrenin, Frédéric, Ritz, Catherine, Mulvaney, Robert, Martín, Carlos, Yan, Jie-Bang, O'Neill, Charles, Frezzotti, Massimo, Miller, Heinrich, Gogineni, Prasad, Dahl-Jensen, Dorthe, Eisen, Olaf, Lilien, David A, Steinhage, Daniel, Taylor, Drew, Parrenin, Frédéric, Ritz, Catherine, Mulvaney, Robert, Martín, Carlos, Yan, Jie-Bang, O'Neill, Charles, Frezzotti, Massimo, Miller, Heinrich, Gogineni, Prasad, Dahl-Jensen, Dorthe, and Eisen, Olaf
Abstract: The area near Dome C, East Antarctica, is thought to be one of the most promising targets for recovering a continuous ice-core record spanning more than a million years. The European Beyond EPICA consortium has selected Little Dome C (LDC), an area ∼35 km southeast of Concordia Station, to attempt to recover such a record. Here, we present the results of the final ice-penetrating radar survey used to refine the exact drill site. These data were acquired during the 2019-2020 austral summer using a new, multi-channel highresolution very high frequency (VHF) radar operating in the frequency range of 170-230 MHz. This new instrument is able to detect reflectors in the near-basal region, where previous surveys were largely unable to detect horizons. The radar stratigraphy is used to transfer the timescale of the EPICA Dome C ice core (EDC) to the area of Little Dome C, using radar isochrones dating back past 600 ka. We use these data to derive the expected depth-age relationship through the ice column at the now-chosen drill site, termed BELDC (Beyond EPICA LDC). These new data indicate that the ice at BELDC is considerably older than that at EDC at the same depth and that there is about 375m of ice older than 600 kyr at BELDC. Stratigraphy is well preserved to 2565 m, ∼93% of the ice thickness, below which there is a basal unit with unknown properties. An ice-flow model tuned to the isochrones suggests ages likely reach 1.5 Myr near 2500 m, ∼65m above the basal unit and ∼265m above the bed, with sufficient resolution (19±2 kyrm-1) to resolve 41 kyr glacial cycles.
Published: 2021

33. Geological Characteristics and Petrography of Granite of Baru Area, Malakand, Pakistan

Author: Asim Ali, Yan Jie, Rahman Ullah, XIA Fei, Asim Ali, Yan Jie, Rahman Ullah, and XIA Fei
Abstract: Granites are the key rocks of the continental crust that occur in almost all the orogenic belts of the world. This research paper is focusing on the mineral resources and structural elements of granitic rock of the Baru area of Malakand Agency of Pakistan. Petrographical study and Geological mapping of the study were carried out in several rock units. The study is emphasizing on the regional and local geological setting as well as the origin and evaluation of different granitic rock units in the area of Baru, Malakand Agency, Pakistan. The mineralized fractures are in the form of a single fracture or group of fractures with convergence and divergence phenomena. The mineralized fractures are hosted by the fine-med. grained foliated granite is more pronounced as compared to the fractures in the fine-grained sheared granite/aplite.
Published: 2021

34. Separation and recovery of copper in Cu-As-bearing copper electrorefining black slime by oxidation acid leaching and sulphide precipitation

Author: Shi Mei-Qing, Chai Li-Yuan, Ke Yong, Liang Yan-Jie., Min Xiao-Bo, Shen Chen, Yan Xu, Shi Mei-Qing, Chai Li-Yuan, Ke Yong, Liang Yan-Jie., Min Xiao-Bo, Shen Chen, and Yan Xu
Abstract: A new hydrometallurgical route was developed for the separation and recovery of Cu from Cu−As-bearing copper electro-refining black slime. The proposed process comprised oxidation acid leaching of Cu−As-bearing slime and selective sulphide precipitation of Cu from the leachate. The effects of various process parameters on the leaching and precipitation of Cu and As were investigated. At the first stage, Cu extraction of 95.2% and As extraction of 97.6% were obtained at 80 degrees C after 4 h with initial H2SO4 concentration of 1.0 mol/l and liquid-to-solid ratio of 10 ml/g. In addition, the leaching kinetics of Cu and As was successfully reproduced by the Avrami model, and the apparent activation energies were found to be 33.6 and 35.1 kJ/mol for the Cu and As leaching reaction, respectively, suggesting a combination of chemical reaction and diffusion control. During the selective sulphide precipitation, about 99.4% Cu was recovered as CuS, while only 0.1% As was precipitated under the optimal conditions using sulphide-to-copper ratio of 2.4:1, time of 1.5 h and temperature of 25 degrees C., A new hydrometallurgical route was developed for the separation and recovery of Cu from Cu−As-bearing copper electro-refining black slime. The proposed process comprised oxidation acid leaching of Cu−As-bearing slime and selective sulphide precipitation of Cu from the leachate. The effects of various process parameters on the leaching and precipitation of Cu and As were investigated. At the first stage, Cu extraction of 95.2% and As extraction of 97.6% were obtained at 80 degrees C after 4 h with initial H2SO4 concentration of 1.0 mol/l and liquid-to-solid ratio of 10 ml/g. In addition, the leaching kinetics of Cu and As was successfully reproduced by the Avrami model, and the apparent activation energies were found to be 33.6 and 35.1 kJ/mol for the Cu and As leaching reaction, respectively, suggesting a combination of chemical reaction and diffusion control. During the selective sulphide precipitation, about 99.4% Cu was recovered as CuS, while only 0.1% As was precipitated under the optimal conditions using sulphide-to-copper ratio of 2.4:1, time of 1.5 h and temperature of 25 degrees C.
Published: 2021

35. Recurrent coronal jets observed by SDO/AIA

Author: Zhang, Yan-Jie, Zhang, Qing-Min, Dai, Jun, Xu, Zhe, Ji, Hai-Sheng, Zhang, Yan-Jie, Zhang, Qing-Min, Dai, Jun, Xu, Zhe, and Ji, Hai-Sheng
Abstract: In this paper, we carry out multiwavelength observations of three recurring jets on 2014 November 7. The jets originated from the same region at the edge of AR 12205 and propagated along the same coronal loop. The eruptions were generated by magnetic reconnection, which is evidenced by continuous magnetic cancellation at the jet base. The projected initial velocity of the jet2 is 402 km s. The accelerations in the ascending and descending phases of jet2 are not consistent, the former is considerably larger than the value of solar gravitational acceleration at the solar surface, while the latter is lower than solar gravitational acceleration. There are two possible candidates of extra forces acting on jet2 during its propagation. One is the downward gas pressure from jet1 when it falls back and meets with jet2. The other is the viscous drag from the surrounding plasma during the fast propagation of jet2. As a contrast, the accelerations of jet3 in the rising and falling phases are constant, implying that the propagation of jet3 is not significantly influenced byextra forces.
Published: 2021
Full Text: View/download PDF

36. Fabric beats in radar data across the NEGIS ice stream

Author: Eisen, Olaf, Franke, Steven, Jansen, Daniela, Paden, John, Drews, Reinhard, Ershadi, Mohammadreza, Steinhage, Daniel, Lilien, David, Yan, Jie-Bang, Weikusat, Ilka, Wilhelms, Frank, Dahl-Jensen, Dorthe, Grinsted, Aslak, Hvidberg, Christine Schøtt, Miller, Heinrich, Eisen, Olaf, Franke, Steven, Jansen, Daniela, Paden, John, Drews, Reinhard, Ershadi, Mohammadreza, Steinhage, Daniel, Lilien, David, Yan, Jie-Bang, Weikusat, Ilka, Wilhelms, Frank, Dahl-Jensen, Dorthe, Grinsted, Aslak, Hvidberg, Christine Schøtt, and Miller, Heinrich
Abstract: Crystal anisotropy of ice causes slight birefringence for electromagnetic waves. At the same time, the mechanical anisotropy amounts to several orders of magnitude, thus making fabric properties highly-relevant for internal deformation. To date, bulk anisotropy of glaciers and ice sheets can be determined by geophysical methods, such as polarimetric radar, or direct sampling from ice cores. A shortcoming has been so far that changes of bulk anisotropy could mainly be inferred at single point observations, but less so as continuous profiles. Here, we exploit the effect of birefringence caused by bulk anisotropy in co-polarized airborne radar data to determine the horizontal anisotropy across the North-East Greenland Ice Stream. We base our analysis on the fact that birefringence causes a second-order effect on radar amplitudes, which leads to a beat frequency in the low and medium frequency range (O(100 kHz)), which is proportional to the horizontal anisotropy. Complementing our radar analysis with direct fabric and dielectric property observations we can constrain the range of all three fabric eigenvalues as a function of space across and along the ice stream. Finally, we assess the effect of the inferred fabric distribution on the overall ice rheology in the context of ice stream dynamics. Our overall approach has the advantage that it can be applied to co-polarized radar systems, as commonly used in profiling surveys, and does not require dedicated cross-polarized radar set-up. This provides the opportunity to revisit older data, especially from Greenland and Antarctica, to map fabric anisotropy in ice-dynamically interesting regions.
Published: 2021

37. Brief Communication: New radar constraints support presence of ice older than 1.5 Ma at Little Dome C.

Author: Lilien, David A., Steinhage, Daniel, Taylor, Drew, Parrenin, Frédéric, Ritz, Catherine, Mulvaney, Robert, Martín, Carlos, Yan, Jie-Bang, O'Neill, Charles, Frezzotti, Massimo, Miller, Heinrich, Gogineni, Prasad, Dahl-Jensen, Dorthe, Eisen, Olaf, Lilien, David A., Steinhage, Daniel, Taylor, Drew, Parrenin, Frédéric, Ritz, Catherine, Mulvaney, Robert, Martín, Carlos, Yan, Jie-Bang, O'Neill, Charles, Frezzotti, Massimo, Miller, Heinrich, Gogineni, Prasad, Dahl-Jensen, Dorthe, and Eisen, Olaf
Abstract: The area near Dome C, East Antarctica, is thought to be one of the most promising targets for recovering a continuous ice-core record spanning more than a million years. The European Beyond EPICA consortium has selected Little Dome C, an area ~35 km south-east of Concordia Station, to attempt to recover such a record. Here, we present the results of the final ice-penetrating radar survey used to refine the exact drill site. These data were acquired during the 2019–2020 Austral summer using a new, multi-channel high-resolution VHF radar operating in the frequency range of 170–230 MHz. This new instrument is able to detect reflections in the near-basal region, where previous surveys were unable to trace continuous horizons. The radar stratigraphy is used to transfer the timescale of the EPICA Dome C ice core (EDC) to the area of Little Dome C, using radar isochrones dating back past 600 ka. We use these data to derive the expected depth–age relationship through the ice column at the now-chosen drill site, termed BELDC. These new data indicate that the ice at BELDC is considerably older than that at EDC at the same depth, and that there is about 375 m of ice older than 600 ka at BELDC. Stratigraphy is well preserved to 2565 m, below which there is a basal unit with unknown properties. A simple ice flow model tuned to the isochrones suggests ages likely reach 1.5 Ma near 2525 m, ~40 m above the basal unit and ~240 m above the bed, with sufficient resolution (14±1 ka m−1) to resolve 41 ka glacial cycles.
Published: 2021

38. Knowledge management practices by middle managers to attain organizational ambidexterity

Author: Xiong Jie, Yan Jie, Su Peiran, Bonanni, Carole, Li Qian, Xiong Jie, Yan Jie, Su Peiran, Bonanni, Carole, and Li Qian
Abstract: This study explores how middle managers deal with knowledge inflows whilst striving to achieve ambidexterity. This is enabled through a two-dimensional conceptual framework involving knowledge sources (vertical or horizontal) and acquisition activities (structural and contextual). We based our study upon interviews conducted with 64 managers from hypermarket retailers in China, in addition to field observations and secondary data. Our findings reveal that these middle managers leverage different combinations of structural and contextual mechanisms to govern the vertical (top-down and bottom-up) knowledge inflows within their business units. Structural mechanisms comprise differentiation and integration. For their part, contextual mechanisms consist of a combination of discipline, stretch, support and trust. These combinations also enable horizontal knowledge inflows to be managed from outside the business unit. These also enable middle managers’ ambidexterity, first at the business unit level and second at the organization level. Our findings offer managerial guidelines for handling knowledge inflows from various sources and with different patterns. They also assist middle managers with their contribution to their firms’ pursuit of organizational ambidexterity.
Published: 2021

39. The Epidemiology, Virulence and Antimicrobial Resistance of Invasive Klebsiella pneumoniae at a Children’s Medical Center in Eastern China

Author: Li,Yang, Li,Dan, Xue,Jian, Ji,Xueqiang, Shao,Xuejun, Yan,Jie, Li,Yang, Li,Dan, Xue,Jian, Ji,Xueqiang, Shao,Xuejun, and Yan,Jie
Abstract: Yang Li,1â 4,&ast; Dan Li,5,&ast; Jian Xue,4 Xueqiang Ji,4 Xuejun Shao,4 Jie Yan1â 3 1Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, Peopleâs Republic of China; 2Department of Medical Microbiology and Parasitology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310058, Peopleâs Republic of China; 3Division of Basic Medical Microbiology, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, Peopleâs Republic of China; 4Department of Clinical Laboratory, Childrenâs Hospital of Soochow University, Suzhou, Jiangsu, 215025, Peopleâs Republic of China; 5Department of Clinical Laboratory, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215004, Peopleâs Republic of China&ast;These authors contributed equally to this workCorrespondence: Jie YanDepartment of Medical Microbiology and Parasitology, Zhejiang University School of Medicine, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, Peopleâs Republic of ChinaTel +86-571-88208297Fax +86-571-88208294Email Med_bp@zju.edu.cnXuejun ShaoDepartment of Clinical Laboratory, Childrenâs Hospital of Soochow University, 92 Zhong-Nan Street, Suzhou, Jiangsu, 215025, Peopleâs Republic of ChinaTel +86-512-80691203Email xjshao@suda.edu.cnObjective: This study investigated the epidemiology, virulence and drug resistance of invasive Klebsiella pneumoniae (K. pneumoniae) isolates at a childrenâs medical center in eastern China in order to obtain epidemiologic, virulence, and antimicrobial resistance data that can guide for the selection and development of anti-infection treatments.Methods: A total of 94 invasive K. pneumoniae strains were isolated from children between January 2016 and December 2020 at the Childrenâs Hospital of Soochow University. Th
Published: 2021

40. Inactivation of Clinically Frequently Used Antimicrobial Agents By BacT/ALERT FAN Plus and BACTEC Aerobic and Anaerobic Culture Media in Simulated Blood Cultures: First Comparative Evaluation in China Mainland

Author: Xu,Xiuyu, Wei,Qiang, Wang,Zhu, Yan,Jie, Wang,Huijuan, Xia,Yun, Xu,Xiuyu, Wei,Qiang, Wang,Zhu, Yan,Jie, Wang,Huijuan, and Xia,Yun
Abstract: Xiuyu Xu, Qiang Wei, Zhu Wang, Jie Yan, Huijuan Wang, Yun Xia Department of Laboratory Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of ChinaCorrespondence: Yun XiaDepartment of Laboratory Medicine, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing 400016, People’s Republic of ChinaTel/Fax +86-23-89012513Email Xiayun12cn@aliyun.comPurpose: To evaluate the antimicrobial inactivation capabilities of BacT/ALERT (FA Plus and FN Plus) and BACTEC (Plus Aerobic/F and Lytic/10 Anaerobic/F) media.Patients and Methods: The inactivation capabilities of the commercial blood culture media were compared using 21 microorganism-antimicrobial combinations in simulated adult blood cultures.Results: BacT/ALERT culture media demonstrated higher detection rates than the BACTEC culture media. The recovery rates of the aerobic bottles were 74/115 (64.3%) for FA Plus bottles and 64/115 (55.7%) for BACTEC Aerobic Plus bottles. The BacT/ALERT FAN Plus culture media exhibited a shorter time to detection (TTD). The TTD of FA Plus media was 14.7 h, 4.85 h shorter than the BACTEC Aerobic media (19.55 h), while the TTDs of FN Plus media and BACTEC Anaerobic media were 16.8 h and 18.4 h, respectively.Conclusion: BacT/ALERT (FA Plus and FN Plus) media showed relative, but not absolute, advantages, as it had higher detection rates and shorter TTD and thus can be selectively applied to patients with prior use of antimicrobial agents before blood culture samples are taken.Keywords: antimicrobial inactivation, blood culture, automated system, BacT/ALERT FAN plus media, comparative evaluation
Published: 2021

41. A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints

Author: Yan, Kai, Yan, Jie, Luo, Chuan, Chen, Liting, Lin, Qingwei, Zhang, Dongmei, Yan, Kai, Yan, Jie, Luo, Chuan, Chen, Liting, Lin, Qingwei, and Zhang, Dongmei
Abstract: Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem. However, the criteria by which the prediction model is trained are often inconsistent with the goal of the downstream optimization problem. Recently, decision-focused prediction approaches, such as SPO+ and direct optimization, have been proposed to fill this gap. However, they cannot directly handle the soft constraints with the $max$ operator required in many real-world objectives. This paper proposes a novel analytically differentiable surrogate objective framework for real-world linear and semi-definite negative quadratic programming problems with soft linear and non-negative hard constraints. This framework gives the theoretical bounds on constraints' multipliers, and derives the closed-form solution with respect to predictive parameters and thus gradients for any variable in the problem. We evaluate our method in three applications extended with soft constraints: synthetic linear programming, portfolio optimization, and resource provisioning, demonstrating that our method outperforms traditional two-staged methods and other decision-focused approaches., Comment: 32 pages; published as NeurIPS 2021 poster paper
Published: 2021

42. Brief communication:New radar constraints support presence of ice older than 1.5 Myr at Little Dome C

Author: Lilien, David A., Steinhage, Daniel, Taylor, Drew, Parrenin, Frederic, Ritz, Catherine, Mulvaney, Robert, Martin, Carlos, Yan, Jie-Bang, O'Neill, Charles, Frezzotti, Massimo, Miller, Heinrich, Gogineni, Prasad, Dahl-Jensen, Dorthe, Eisen, Olaf, Lilien, David A., Steinhage, Daniel, Taylor, Drew, Parrenin, Frederic, Ritz, Catherine, Mulvaney, Robert, Martin, Carlos, Yan, Jie-Bang, O'Neill, Charles, Frezzotti, Massimo, Miller, Heinrich, Gogineni, Prasad, Dahl-Jensen, Dorthe, and Eisen, Olaf
Abstract: The area near Dome C, East Antarctica, is thought to be one of the most promising targets for recovering a continuous ice-core record spanning more than a million years. The European Beyond EPICA consortium has selected Little Dome C (LDC), an area similar to 35 km southeast of Concordia Station, to attempt to recover such a record. Here, we present the results of the final ice-penetrating radar survey used to refine the exact drill site. These data were acquired during the 2019-2020 austral summer using a new, multi-channel high-resolution very high frequency (VHF) radar operating in the frequency range of 170-230 MHz. This new instrument is able to detect reflectors in the near-basal region, where previous surveys were largely unable to detect horizons. The radar stratigraphy is used to transfer the timescale of the EPICA Dome C ice core (EDC) to the area of Little Dome C, using radar isochrones dating back past 600 ka. We use these data to derive the expected depth-age relationship through the ice column at the now-chosen drill site, termed BELDC (Beyond EPICA LDC). These new data indicate that the ice at BELDC is considerably older than that at EDC at the same depth and that there is about 375m of ice older than 600 kyr at BELDC. Stratigraphy is well preserved to 2565 m, similar to 93% of the ice thickness, below which there is a basal unit with unknown properties. An ice-flow model tuned to the isochrones suggests ages likely reach 1.5 Myr near 2500 m, similar to 65m above the basal unit and similar to 265m above the bed, with sufficient resolution (19 +/- 2 kyrm(-1)) to resolve 41 kyr glacial cycles.
Published: 2021

43. Urban power load profiles under ageing transition integrated with future EVs charging

Author: Zhang, Haoran, Chen, Jinyu, Yan, Jie, Song, Xuan, Shibasaki, Ryosuke, Yan, Jinyue, Zhang, Haoran, Chen, Jinyu, Yan, Jie, Song, Xuan, Shibasaki, Ryosuke, and Yan, Jinyue
Abstract: Understanding ageing transition caused fine-grained changes of electricity profile is the significant insight for coping with future threatens in grid flexibility management. The research gaps for the hourly-basis knowledge exist due to challenges in microanalysis on user-side behavior. Based on billions of users’ behavior data, we investigated the changes on the load profiles due to population aging. We found that owing to ageing transition, the participation population in high electricity-density activities decreases by about 8%. The corresponding shift in driving behavior rises the 14% difference between peak charging load and valley. We concluded that population aging will dramatically change both the magnitude and shape of future dynamic-load profiles. Therefore, we further suggested a new solution with comprehensive and quantitative management for PVs development and the smart charging market with smooth operation of the grid in coupling the potential challenges caused by the ageing issue.
Published: 2021
Full Text: View/download PDF

44. Group Feature Learning and Domain Adversarial Neural Network for aMCI Diagnosis System Based on EEG

Author: Fan, Chen-Chen, Xie, Haiqun, Peng, Liang, Yang, Hongjun, Ni, Zhen-Liang, Wang, Guan'an, Zhou, Yan-Jie, Chen, Sheng, Fang, Zhijie, Huang, Shuyun, Hou, Zeng-Guang, Fan, Chen-Chen, Xie, Haiqun, Peng, Liang, Yang, Hongjun, Ni, Zhen-Liang, Wang, Guan'an, Zhou, Yan-Jie, Chen, Sheng, Fang, Zhijie, Huang, Shuyun, and Hou, Zeng-Guang
Abstract: Medical diagnostic robot systems have been paid more and more attention due to its objectivity and accuracy. The diagnosis of mild cognitive impairment (MCI) is considered an effective means to prevent Alzheimer's disease (AD). Doctors diagnose MCI based on various clinical examinations, which are expensive and the diagnosis results rely on the knowledge of doctors. Therefore, it is necessary to develop a robot diagnostic system to eliminate the influence of human factors and obtain a higher accuracy rate. In this paper, we propose a novel Group Feature Domain Adversarial Neural Network (GF-DANN) for amnestic MCI (aMCI) diagnosis, which involves two important modules. A Group Feature Extraction (GFE) module is proposed to reduce individual differences by learning group-level features through adversarial learning. A Dual Branch Domain Adaptation (DBDA) module is carefully designed to reduce the distribution difference between the source and target domain in a domain adaption way. On three types of data set, GF-DANN achieves the best accuracy compared with classic machine learning and deep learning methods. On the DMS data set, GF-DANN has obtained an accuracy rate of 89.47%, and the sensitivity and specificity are 90% and 89%. In addition, by comparing three EEG data collection paradigms, our results demonstrate that the DMS paradigm has the potential to build an aMCI diagnose robot system., Comment: This paper has been accepted by 2021 International Conference on Robotics and Automation (ICRA 2021)
Published: 2021

45. Force-dependent interactions between talin and full-length vinculin

Author: Wang, Yinan, Yao, Mingxi, Baker, Karen, Gough, Rosemarie E., Le, Shimin, Goult, Benjamin T, Yan, Jie, Wang, Yinan, Yao, Mingxi, Baker, Karen, Gough, Rosemarie E., Le, Shimin, Goult, Benjamin T, and Yan, Jie
Abstract: Talin and vinculin are part of a multi-component system involved in mechanosensing in cell-matrix adhesions. Both exist in auto-inhibited forms, and activation of vinculin requires binding to mechanically activated talin, yet how forces affect talin’s interaction with vinculin has not been investigated. Here by quantifying the force-dependent talin-vinculin interactions and kinetics using single-molecule analysis, we show that mechanical exposure of a single vinculin binding site (VBS) in talin is sufficient to relieve the autoinhibition of vinculin resulting in high- affinity binding. We provide evidence that the vinculin undergoes dynamic fluctuations between an auto-inhibited closed conformation and an open conformation that is stabilized upon binding to the VBS. Furthermore, we discover an additional level of regulation in which the mechanically exposed VBS binds vinculin significantly more tightly than the isolated VBS alone. Molecular dynamics simulations reveal the basis of this new regulatory mechanism, identifying a sensitive force-dependent change in the conformation of an exposed VBS that modulates binding. Together, these results provide a comprehensive understanding of how the interplay between force and autoinhibition provides exquisite complexity within this major mechanosensing axis.
Published: 2021

46. Talin mechanosensitivity is modulated by a direct interaction with cyclin-dependent kinase-1

Author: Gough, Rosemarie E., Jones, Matt C., Zacharchenko, Thomas, Le, Shimin, Yu, Miao, Jacquemet, Guillaume, Muench, Stephen P., Yan, Jie, Humphries, Jon D., Jørgensen, Claus, Humphries, Martin, Goult, Benjamin Thomas, Gough, Rosemarie E., Jones, Matt C., Zacharchenko, Thomas, Le, Shimin, Yu, Miao, Jacquemet, Guillaume, Muench, Stephen P., Yan, Jie, Humphries, Jon D., Jørgensen, Claus, Humphries, Martin, and Goult, Benjamin Thomas
Abstract: Talin (TLN1) is a mechanosensitive component of adhesion complexes that directly couples integrins to the actin cytoskeleton. In response to force, talin undergoes switch-like behavior of its multiple rod domains that modulate interactions with its binding partners. Cyclin-dependent kinase-1 (CDK1) is a key regulator of the cell cycle, exerting its effects through synchronized phosphorylation of a large number of protein targets. CDK1 activity maintains adhesion during interphase, and its inhibition is a prerequisite for the tightly choreographed changes in cell shape and adhesion that are required for successful mitosis. Using a combination of biochemical, structural, and cell biological approaches, we demonstrate a direct interaction between talin and CDK1 that occurs at sites of integrin-mediated adhesion. Mutagenesis demonstrated that CDK1 contains a functional talin-binding LD motif, and the binding site within talin was pinpointed to helical bundle R8. Talin also contains a consensus CDK1 phosphorylation motif centered on S1589, a site shown to be phosphorylated by CDK1 in vitro. A phosphomimetic mutant of this site within talin lowered the binding affinity of the cytoskeletal adaptor KANK and weakened the response of this region to force as measured by single molecule stretching, potentially altering downstream mechanotransduction pathways. The direct binding of the master cell cycle regulator CDK1 to the primary integrin effector talin represents a coupling of cell proliferation and cell adhesion machineries and thereby indicates a mechanism by which the microenvironment can control cell division in multicellular organisms.
Published: 2021

47. Upregulated MicroRNA-483-3p is an Early Event in Pancreatic Ductal Adenocarcinoma (PDAC) and as a Powerful Liquid Biopsy Biomarker in PDAC

Author: Shao,Huilin, Zhang,Yue, Yan,Jie, Ban,Xinchao, Fan,Xiaojie, Chang,Xiaoyan, Lu,Zhaohui, Wu,Yan, Zong,Liju, Mo,Shengwei, Yu,Shuangni, Chen,Jie, Shao,Huilin, Zhang,Yue, Yan,Jie, Ban,Xinchao, Fan,Xiaojie, Chang,Xiaoyan, Lu,Zhaohui, Wu,Yan, Zong,Liju, Mo,Shengwei, Yu,Shuangni, and Chen,Jie
Abstract: Huilin Shao, Yue Zhang, Jie Yan, Xinchao Ban, Xiaojie Fan, Xiaoyan Chang, Zhaohui Lu, Yan Wu, Liju Zong, Shengwei Mo, Shuangni Yu, Jie Chen Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, People’s Republic of ChinaCorrespondence: Shuangni Yu; Jie Chen Tel +86 10 69159375; +86 10 69159389Email yushn@pumch.cn; chenjie@pumch.cnBackground: There is an urgent need for the development of effective noninvasive biomarkers for early pancreatic cancer diagnosis. MicroRNAs (miRNAs) are promising candidates that can be identified in peripheral blood and can act as “liquid biopsy” biomarkers. miR-483-3p is overexpressed in the tumor tissue of pancreatic duct adenocarcinoma, but its potential as noninvasive biomarker remains unknown.Methods: We conducted locked nucleic acid in situ hybridization (LNA-ISH) for miR-483-3p in archival tissues of 107 patients with PDAC. We also used immunohistochemistry to evaluate SMAD4 expression, the putative miR-483-3p target gene. miR-483-3p expression level was also assessed using quantitative real-time PCR (qRT-PCR) in serum and serum exosome samples from 63 patients with PDAC and 22 healthy individuals.Results: LNA-ISH showed that miR-483-3p was overexpressed in PDAC and PanIN tissues compared to normal pancreatic duct cells. miR-483-3p expression levels correlated with increases in PanIN lesion grade. miR-483-3p expression negatively correlated with Smad4 expression (γ=− 0.770, p< 0.0001) in PDAC and PanIN tissues. Circulating miR-483-3p levels were significantly elevated in the serum and serum exosomes of PDAC patients compared to healthy controls (p< 0.0001 and p< 0.01, respectively). Specifically, serum miR-483-3p levels were able to distinguish patients with early stage (≤ 2cm) PDAC from healthy controls with an AUC of 0.83 [95% CI, 0.70– 0.96]. Higher serum ex
Published: 2021

48. Uterine Artery Embolization with Small-Sized Particles for the Treatment of Symptomatic Adenomyosis: A 42-Month Clinical Follow-Up

Author: Yuan,Kai, Zhang,Jin Long, Yan,Jie Yu, Yuan,Bing, Fu,Jin Xin, Wang,Yan, Sun,Xue Dong, Guan,Yang, Duan,Feng, Wang,Mao Qiang, Yuan,Kai, Zhang,Jin Long, Yan,Jie Yu, Yuan,Bing, Fu,Jin Xin, Wang,Yan, Sun,Xue Dong, Guan,Yang, Duan,Feng, and Wang,Mao Qiang
Abstract: Kai Yuan,1,2 Jin Long Zhang,2 Jie Yu Yan,2 Bing Yuan,1 Jin Xin Fu,2 Yan Wang,2 Xue Dong Sun,3 Yang Guan,2 Feng Duan,2 Mao Qiang Wang1,2 1Medical School of Chinese PLA, Beijing, 100853, Peopleâs Republic of China; 2Department of Interventional Radiology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100853, Peopleâs Republic of China; 3School of Medicine, Nankai University, Tianjin, 300071, Peopleâs Republic of ChinaCorrespondence: Mao Qiang WangDepartment of Interventional Radiology, The Fifth Medical Center, Chinese PLA General Hospital, 28 Fu-Xing Road, Beijing, 100853, Peopleâs Republic of ChinaTel +86 10-66937190Email wangmq@vip.sina.comPurpose: To assess the long-term outcome of performing uterine artery embolization (UAE) using small particles in women with symptomatic adenomyosis (AD).Methods: Twenty-seven consecutive women (median age 42 years, range 29â 53 years) with AD, in eight cases AD combined with fibroids, who underwent UAE between February 2015 and January 2019, were retrospectively analyzed. The embolization was performed using small-sized polyvinyl alcohol particles (100 Î¼m and 300 Î¼m). The patients completed the Uterine Fibroid Symptom and Quality of Life questionnaire at baseline and at a 42-month follow-up (range 24â 71). The junction zone (JZ) thickness and uterine volume were also calculated at baseline and at a three-month follow-up.Results: The total symptom severity score (SSS) decreased from a median of 59 (range 34â 78) at baseline to a median of 9 (range 3â 47) at the end of this study; the health-related quality of life score (HRQOL) increased from a median of 38 (range 23â 49) at baseline to a median of 84 (range 46â 97) at 42 months. Twenty of the 27 patients were asymptomatic. The clinical response of the remaining seven women was little improvement in their symptoms, and one of the seven women underwent a hysterectomy at 35 months. Twenty-six of the 27 (96%) patients had a preserved uterus a
Published: 2021

49. Thick‐Film Low Driving‐Force Indoor Light Harvesters

Author: Yin, Hang, Ma, Lik Kuen, Yan, Jie, Zhang, Zhuoqiong, Cheung, Man Hong Andy, Zhang, Jianquan, Yan, He, So, Shu Kong, Yin, Hang, Ma, Lik Kuen, Yan, Jie, Zhang, Zhuoqiong, Cheung, Man Hong Andy, Zhang, Jianquan, Yan, He, and So, Shu Kong
Abstract: Organic indoor light harvesters require large-area active layers for power-greedy internet of thing (IoT) things due to much weaker light emissions from indoor sources than the standard 1-Sun case. This presents new challenges for the thick-film indoor photovoltaic (IPV) device fabrication to meet the requirements of current leading roll-to-roll (R2R) techniques. Herein, a concept of low driving-force bulk heterojunction (BHJ) into the IPV field is introduced, and a P3TEA:FTTB-PDI4 solar cell is demonstrated with negligible energy offset between donor and acceptor materials for the electron transport that can achieve high efficiencies over 20% in the thick-film region, which is comparable with their optimized thin-film counterpart. In the low driving-force P3TEA:FTTB-PDI4 BHJ film, negative Poole–Frenkel (PF) effect of the electron transport can be observed. Such an effect originates from alternative electron pathways opened up by the donor polymer P3TEA. The negative PF effect results in improved electron extraction in the thick-film BHJs, leading to comparable fill factors (FFs) and efficiencies of thick-film and thin-film devices. From the photothermal deflection spectroscopy measurement, similar but low Urbach energy values of the low driving-force BHJ and the neat acceptor film are observed, indicating reduced defect states for the electron transport in such low driving-force devices.
Published: 2020

50. Physicochemical and environmental properties of arsenic sulphide sludge from copper and lead-zinc smelter

Author: Yao Li-Wei, He Yu-Yang., Ke Yong, Liang Yan-Jie, Lin Zhang, Liu De-Gang, Min Xiao-Bo, Wang Yun-Yan, Xu Hui, Xu Qiu-Jing, Yao Li-Wei, He Yu-Yang., Ke Yong, Liang Yan-Jie, Lin Zhang, Liu De-Gang, Min Xiao-Bo, Wang Yun-Yan, Xu Hui, and Xu Qiu-Jing
Abstract: Physicochemical properties of arsenic sulphide sludge (ASS) from copper smelter (ASS-I) and lead−zinc smelter (ASS-II) were examined by XRD, Raman spectroscopy, SEM−EDS, TG−DTA, XPS and chemical phase analysis method. The toxicity characteristic leaching procedure (TCLP), Chinese standard leaching tests (CSLT), three-stage sequential extraction procedure (BCR) and batch leaching experiments (BLE) were used to investigate the environmental stability. The ASSs from different smelters had obviously different physicochemical and environmental properties. The phase composition and micrograph analysis indicate that ASS-I mainly consists of super refined flocculent particles including amorphous arsenic sulphide adhered with amorphous sulphur and that ASS-II mainly consists of amorphous arsenic sulphide. The valence state of arsenic in both sludges is trivalent, but the valence composition of sulphur is quite different. The ASSs have thermal instability properties. The results of TCLP and CSLT indicate that the concentrations of As and Pd in the leaching solution exceed the standard limits. More than 5% and 90% of arsenic are in the form of acid soluble and oxidisable fractions, respectively, which explains the high arsenic leaching toxicity and environmental activity of ASS. This research provides comprehensive information for the disposal of ASS from copper and lead−zinc smelter. (Authors.), Physicochemical properties of arsenic sulphide sludge (ASS) from copper smelter (ASS-I) and lead−zinc smelter (ASS-II) were examined by XRD, Raman spectroscopy, SEM−EDS, TG−DTA, XPS and chemical phase analysis method. The toxicity characteristic leaching procedure (TCLP), Chinese standard leaching tests (CSLT), three-stage sequential extraction procedure (BCR) and batch leaching experiments (BLE) were used to investigate the environmental stability. The ASSs from different smelters had obviously different physicochemical and environmental properties. The phase composition and micrograph analysis indicate that ASS-I mainly consists of super refined flocculent particles including amorphous arsenic sulphide adhered with amorphous sulphur and that ASS-II mainly consists of amorphous arsenic sulphide. The valence state of arsenic in both sludges is trivalent, but the valence composition of sulphur is quite different. The ASSs have thermal instability properties. The results of TCLP and CSLT indicate that the concentrations of As and Pd in the leaching solution exceed the standard limits. More than 5% and 90% of arsenic are in the form of acid soluble and oxidisable fractions, respectively, which explains the high arsenic leaching toxicity and environmental activity of ASS. This research provides comprehensive information for the disposal of ASS from copper and lead−zinc smelter. (Authors.)
Published: 2020

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Database

Publisher

281 results on '"Yan Jie"'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources