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277 results on '"Lourenco, Ana P."'

1. Constraining the duration of ram pressure stripping features in the optical from the direction of jellyfish galaxy tails

Author

Salinas, Vicente, Jaffé, Yara L., Smith, Rory, Shinn, Jong-Ho, Crossett, Jacob P., Gullieuszik, Marco, González-Torà, Gemma, Piraino-Cerda, Franco, Poggianti, Bianca, Vulcani, Benedetta, Biviano, Andrea, Lourenço, Ana C. C., Bilton, Lawrence E., Kelkar, Kshitija, and Calderón-Castillo, Paula

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Ram pressure stripping is perhaps the most efficient mechanism for removing gas and quenching galaxies in dense environments as they move through the intergalactic medium. Extreme examples of on-going ram pressure stripping are known as jellyfish galaxies, characterized by a tail of stripped material that can be directly observed in multiple wavelengths. Using the largest homogeneous broad-band optical jellyfish candidate sample in local clusters known to date, we measure the angle between the direction of the tails visible in the galaxies, and the direction towards the host cluster center. We find that $33\%$ of the galaxy tails point away from the cluster center, $18\%$ point towards the cluster center, and $49\%$ point elsewhere. Moreover, we find stronger signatures of ram pressure stripping happening on galaxies with a tail pointing away and towards the cluster center, and larger velocity dispersion profiles for galaxies with tails pointing away. These results are consistent with a scenario where ram pressure stripping has a stronger effect for galaxies following radial orbits on first infall. The results also suggest that in many cases, radially infalling galaxies are able to retain their tails after pericenter and continue to experience significant on-going ram pressure stripping. We further constrain the lifespan of the optical tails from the moment they first appear to the moment they disappear, by comparing the observed tail directions with matched N-body simulations through Bayesian parameter estimation. We obtain that galaxy tails appear for the first time at $\sim 1.16$ R$_{200}$ and disappear $\sim660$ Myr after pericenter., Comment: 19 pages, 17 figures

Published
2024
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2. Distribution of merging and post-merging galaxies in nearby galaxy clusters

Author

Kim, Duho, Sheen, Yun-Kyeong, Jaffé, Yara L., Kelkar, Kshitija, Ranjan, Adarsh, Piraino-Cerda, Franco, Crossett, Jacob P., Lourenço, Ana Carolina Costa, Martin, Garreth, Nantais, Julie B., Demarco, Ricardo, Treister, Ezequiel, and Yi, Sukyoung K.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We study the incidence and spatial distribution of galaxies that are currently undergoing gravitational merging (M) or that have signs of a post merger (PM) in six galaxy clusters (A754, A2399, A2670, A3558, A3562, and A3716) within the redshift range, 0.05$\lesssim$$z$$\lesssim$0.08. To this aim, we obtained Dark Energy Camera (DECam) mosaics in $u^{\prime}$, $g^{\prime}$, and $r^{\prime}$-bands covering up to $3\times R_{200}$ of the clusters, reaching 28 mag/arcsec$^2$ surface brightness limits. We visually inspect $u^{\prime}$$g^{\prime}$$r^{\prime}$ color-composite images of volume-limited ($M_r < -20$) cluster-member galaxies to identify whether galaxies are of M or PM types. We find 4% M-type and 7% PM-type galaxies in the galaxy clusters studied. By adding spectroscopic data and studying the projected phase space diagram (PPSD) of the projected clustocentric radius and the line-of-sight velocity, we find that PM-type galaxies are more virialized than M-type galaxies, having 1--5% point higher fraction within the escape-velocity region, while the fraction of M-type was $\sim$10% point higher than PM-type in the intermediate environment. Similarly, on a substructure analysis, M types were found in the outskirt groups, while PM types populated groups in ubiquitous regions of the PPSD. Adopting literature-derived dynamical state indicator values, we observed a higher abundance of M types in dynamically relaxed clusters. This finding suggests that galaxies displaying post-merging features within clusters likely merged in low-velocity environments, including cluster outskirts and dynamically relaxed clusters., Comment: 23 pages, 15 figures, 4 tables, Published in ApJ. For photometric catalogs and associated information, see https://data.kasi.re.kr/vo/DECam_catalogs/

Published
2024
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4. Analysis of full-disc H alpha observations: Carrington maps and filament properties in 1909-2022

Author

Chatzistergos, Theodosios, Ermolli, Ilaria, Banerjee, Dipankar, Barata, Teresa, Chouinavas, Ioannis, Falco, Mariachiara, Gafeira, Ricardo, Giorgi, Fabrizio, Hanaoka, Yoichiro, Krivova, Natalie A., Korokhin, Viktor V., Lourenço, Ana, Marchenko, Gennady P., Malherbe, Jean-Marie, Peixinho, Nuno, Romano, Paolo, and Sakurai, Takashi

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

Full disc observations of the Sun in the H$\alpha$ line provide information about the solar chromosphere and in particular about the filaments, which are dark and elongated features that lie along magnetic field polarity inversion lines. This makes them important for studies of solar magnetism. Since full disc H$\alpha$ observations have been performed at various sites since 1800s, with regular photographic data having started in the beginning of the 20th century, they are an invaluable source of information on past solar magnetism. In this work we aimed at deriving accurate information about filaments from historical and modern full disc H$\alpha$ observations. We have consistently processed observations from 15 H$\alpha$ archives spanning 1909-2022. Our data processing includes photometric calibration of the data stored on photographic plates. We have constructed also Carrington maps from the calibrated H$\alpha$ images. We find that filament areas are affected by the bandwidth of the observation. Thus, cross-calibration of the filament areas derived from different archives is needed. We have produced a composite of filament areas from individual archives by scaling all of them to the Meudon series. Our composite butterfly diagram shows very distinctly the common features of filament evolution, that is the poleward migration as well as a decrease in the mean latitude of filaments as the cycle progresses. We also find that during activity maxima, filaments on average cover about 1% of the solar surface. We see only a weak change in the amplitude of cycles in filament areas, in contrast to sunspot and plage areas. Analysis of H$\alpha$ data for archives with contemporaneous Ca II K observations allowed us to identify and verify archive inconsistencies, which will also have implications for reconstructions of past solar magnetism and irradiance from Ca II K data., Comment: 21 pages, 14 figures, accepted for publication in A&A

Published
2023
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5. An Enigmatic 380 kpc Long Linear Collimated Galactic Tail

Author

Zaritsky, Dennis, Crossett, Jacob P., Jaffé, Yara L., Donnerstein, Richard, Karunakaran, Ananthan, Khim, Donghyeon J., Lourenço, Ana C. C., Spekkens, Kristine, Sun, Ming, and Vulcani, Benedetta

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present an intriguing, serendipitously-detected system consisting of an S0/a galaxy, which we refer to as the "Kite", and a highly-collimated tail of gas and stars that extends over 380 kpc and contains pockets of star formation. In its length, narrowness, and linearity the Kite's tail is an extreme example relative to known tails. The Kite (PGC 1000273) has a companion galaxy, Mrk 0926 (PGC 070409), which together comprise a binary galaxy system in which both galaxies host active galactic nuclei. Despite this systems being previously searched for signs of tidal interactions, the tail had not been discovered prior to our identification as part of the validation process of the SMUDGes survey for low surface brightness galaxies. We confirm the kinematic association between various H$\alpha$ knots along the tail, a small galaxy, and the Kite galaxy using optical spectroscopy obtained with the Magellan telescope and measure a velocity gradient along the tail. The Kite shares characteristics common to those formed via ram pressure stripping ("jellyfish" galaxies) and formed via tidal interactions. However, both scenarios face significant challenges that we discuss, leaving open the question of how such an extreme tail formed. We propose that the tail resulted from a three-body interaction from which the lowest-mass galaxy was ejected at high velocity., Comment: Submitted to publication in MNRAS (comments welcome)

Published
2023
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6. Two striking head-tail galaxies in the galaxy cluster IIZW108: insights into transition to turbulence, magnetic fields and particle re-acceleration

Author

Müller, Ancla, Pfrommer, Christoph, Ignesti, Alessandro, Moretti, Alessia, Lourenco, Ana, Paladino, Rosita, Jaffe, Yara, Gitti, Myriam, Venturi, Tiziana, Gullieuszik, Marco, Poggianti, Bianca, Vulcani, Benedetta, Biviano, Andrea, Adebahr, Björn, and Dettmar, Ralf-Jürgen

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present deep JVLA observations at 1.4 GHz and 2.7 GHz (full polarization), as well as optical OmegaWINGS/WINGS and X-ray observations of two extended radio galaxies in the IIZW108 galaxy cluster at z = 0.04889. They show a bent tail morphology in agreement with a radio lobed galaxy falling into the cluster potential. Both galaxies are found to possess properties comparable with {narrow-angle} tail galaxies in the literature even though they are part of a low mass cluster. We find a spectral index steepening and an increase in fractional polarization through the galaxy jets and an ordered magnetic field component mostly aligned with the jet direction. This is likely caused by either shear due to the velocity difference of the intracluster medium and the jet fluid and/or magnetic draping of the intracluster medium across the galaxy jets. We find clear evidence that one source is showing two active galactic nuclei (AGN) outbursts from which we expect the AGN has never turned off completely. We show that pure standard electron cooling cannot explain the jet length. We demonstrate therefore that these galaxies can be used as a laboratory to study gentle re-acceleration of relativistic electrons in galaxy jets via transition from laminar to turbulent motion., Comment: accepted for publication in MNRAS

Published
2021
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7. Testing the accuracy of Coimbra Astronomical Observatory solar filament historical series (1929-1941)

Author

Lourenço, Ana, Gafeira, Ricardo, Bonifacio, Vitor, Barata, Teresa, Fernandes, Joao, and Silva, Eva

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The present work aims to validate the positions of solar filaments published in the Annals of Coimbra University Astronomical Observatory, currently the Geophysical and Astronomical Observatory of the University of Coimbra, corresponding to years 1929 to 1941. The published Stonyhurst positions were obtained by an original method devised in the early 20th century that used a spherical calculator instrument, a wood-made model of the sun. We used the digital images of the original spectroheliograms to measure the positions of the filaments, and heliographic coordinates were determinate with the routines implemented on python package Sunpy. The correlation coefficients between both sets of coordinates are positive and highly significant. The results validate the method used at the Coimbra observatory and the data published. We conclude that Coimbra solar filaments catalogues are reliable and can therefore be considered for future solar activity studies., Comment: 19 pages, 10 figures, Accepted for publication on Solar Physics

Published
2021
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8. Automatic Myocardial Disease Prediction From Delayed-Enhancement Cardiac MRI and Clinical Information

Author

Lourenço, Ana, Kerfoot, Eric, Grigorescu, Irina, Scannell, Cian M, Varela, Marta, and Correia, Teresa M

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Delayed-enhancement cardiac magnetic resonance (DE-CMR)provides important diagnostic and prognostic information on myocardial viability. The presence and extent of late gadolinium enhancement (LGE)in DE-CMR is negatively associated with the probability of improvement in left ventricular function after revascularization. Moreover, LGE findings can support the diagnosis of several other cardiomyopathies, but their absence does not rule them out, making disease classification by visual assessment difficult. In this work, we propose deep learning neural networks that can automatically predict myocardial disease from patient clinical information and DE-CMR. All the proposed networks achieve very good classification accuracy (>85%). Including information from DE-CMR (directly as images or as metadata following DE-CMR segmentation) is valuable in this classification task, improving the accuracy to 95-100%., Comment: Accepted for the EMIDEC classification challenge; part of the 11th Statistical Atlases and Computational Modelling of the Heart (STACOM 2020), a MICCAI satellite workshop

Published
2020

9. The dynamical state of Abell 2399: a bullet-like cluster

Author

Lourenço, Ana C. C., Lopes, P. A. A., Laganá, T. F., Nascimento, R. S., Machado, R. E. G., Moura, M. T., Jaffé, Y. L., Ribeiro, A. L., Vulcani, B., Moretti, A., and Riguccini, L. A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

While there are many ways to identify substructures in galaxy clusters using different wavelengths, each technique has its own caveat. In this paper, we conduct a detailed substructure search and dynamical state characterisation of Abell 2399, a galaxy cluster in the local Universe ($z \sim 0.0579$), by performing a multi-wavelength analysis and testing the results through hydro-dynamical simulations. In particular, we apply a Gaussian Mixture Model to the spectroscopic data from SDSS, WINGS, and Omega WINGS Surveys to identify substructures. We further use public \textit{XMM-Newton} data to investigate the intracluster medium (ICM) thermal properties, creating temperature, metallicity, entropy, and pressure maps. Finally, we run hydro-dynamical simulations to constrain the merger stage of this system. The ICM is very asymmetrical and has regions of temperature and pressure enhancement that evidence a recent merging process. The optical substructure analysis retrieves the two main X-ray concentrations. The temperature, entropy, and pressure are smaller in the secondary clump than in the main clump. On the other hand, its metallicity is considerably higher. This result can be explained by the scenario found by the hydro-dynamical simulations where the secondary clump passed very near to the centre of the main cluster possibly causing the galaxies of that region to release more metals through the increase of ram-pressure stripping.16, Comment: 16 pages, 11 figures. Accepted in MNRAS

Published
2020
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10. Left atrial ejection fraction estimation using SEGANet for fully automated segmentation of CINE MRI

Author

Lourenço, Ana, Kerfoot, Eric, Dibblin, Connor, Alskaf, Ebraham, Anjari, Mustafa, Bharath, Anil A, King, Andrew P, Chubb, Henry, Correia, Teresa M, and Varela, Marta

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, characterised by a rapid and irregular electrical activation of the atria. Treatments for AF are often ineffective and few atrial biomarkers exist to automatically characterise atrial function and aid in treatment selection for AF. Clinical metrics of left atrial (LA) function, such as ejection fraction (EF) and active atrial contraction ejection fraction (aEF), are promising, but have until now typically relied on volume estimations extrapolated from single-slice images. In this work, we study volumetric functional biomarkers of the LA using a fully automatic SEGmentation of the left Atrium based on a convolutional neural Network (SEGANet). SEGANet was trained using a dedicated data augmentation scheme to segment the LA, across all cardiac phases, in short axis dynamic (CINE) Magnetic Resonance Images (MRI) acquired with full cardiac coverage. Using the automatic segmentations, we plotted volumetric time curves for the LA and estimated LA EF and aEF automatically. The proposed method yields high quality segmentations that compare well with manual segmentations (Dice scores [$0.93 \pm 0.04$], median contour [$0.75 \pm 0.31$] mm and Hausdorff distances [$4.59 \pm 2.06$] mm). LA EF and aEF are also in agreement with literature values and are significantly higher in AF patients than in healthy volunteers. Our work opens up the possibility of automatically estimating LA volumes and functional biomarkers from multi-slice CINE MRI, bypassing the limitations of current single-slice methods and improving the characterisation of atrial function in AF patients., Comment: Accepted at STACOM 2020, a MICCAI workshop

Published
2020

11. Analysis of full disc Ca II K spectroheliograms III. Plage area composite series covering 1892-2019

Author

Chatzistergos, Theodosios, Ermolli, Ilaria, Krivova, Natalie A., Solanki, Sami K., Banerjee, Dipankar, Barata, Teresa, Belik, Marcel, Gafeira, Ricardo, Garcia, Adriana, Hanaoka, Yoichiro, Hegde, Manjunath, Klimeš, Jan, Korokhin, Viktor V., Lourenço, Ana, Malherbe, Jean-Marie, Marchenko, Gennady P., Peixinho, Nuno, Sakurai, Takashi, and Tlatov, Andrey G.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

We derive the plage area evolution over the last 12 solar cycles employing data from all Ca II K archives available publicly in digital form known to us, including several as yet unexplored Ca II K archives. We analyse more than 290,000 full-disc Ca II K observations from 43 datasets spanning the period 1892-2019. All images were consistently processed with an automatic procedure that performs the photometric calibration (if needed) and the limb-darkening compensation. The processing also accounts for artefacts plaguing many of the images, including some very specific artefacts such as bright arcs found in Kyoto and Yerkes data. We have produced a plage area time-series from each analysed dataset. We found that the differences between the plage areas derived from individual archives are mainly due to the differences in the central wavelength and the bandpass used to acquire the data at the various sites. We have empirically cross-calibrated and combined the results obtained from each dataset to produce a composite series of plage areas. "Backbone" series are used to bridge all the series together. We have also shown that the selection of the backbone series has little effect on the final plage area composite. We have quantified the uncertainty of determining the plage areas with our processing due to shifts in the central wavelength and found it to be less than 0.01 in fraction of the solar disc for the average conditions found on historical data. We also found the variable seeing conditions during the observations to slightly increase the plage areas during activity maxima. We provide the so far most complete time series of plage areas based on corrected and calibrated historical and modern Ca II K images. Consistent plage areas are now available on 88% of all days from 1892 onwards and on 98% from 1907 onwards., Comment: 23 pages, 19 figures, accepted for publication in A&A

Published
2020
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13. ACR Appropriateness Criteria® Palpable Breast Masses: 2022 Update

Author

Klein, Katherine A., Kocher, Maddi, Lourenco, Ana P., Niell, Bethany L., Bennett, Debbie L., Chetlen, Alison, Freer, Phoebe, Ivansco, Lillian K., Jochelson, Maxine S., Kremer, Mallory E., Malak, Sharp F., McCrary, Marion, Mehta, Tejas S., Neal, Colleen H., Porpiglia, Andrea, Ulaner, Gary A., and Moy, Linda

Published
2023
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14. ACR Appropriateness Criteria® Imaging After Breast Surgery

Author

Mehta, Tejas S., Lourenco, Ana P., Niell, Bethany L., Bennett, Debbie L., Brown, Ann, Chetlen, Alison, Freer, Phoebe, Ivansco, Lillian K., Jochelson, Maxine S., Klein, Katherine A., Malak, Sharp F., McCrary, Marion, Mullins, David, Neal, Colleen H., Newell, Mary S., Ulaner, Gary A., and Moy, Linda

Published
2022
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17. ACR Appropriateness Criteria® Transgender Breast Cancer Screening

Author

Brown, Ann, Lourenco, Ana P., Niell, Bethany L., Cronin, Beth, Dibble, Elizabeth H., DiNome, Maggie L., Goel, Mita Sanghavi, Hansen, Juliana, Heller, Samantha L., Jochelson, Maxine S., Karrington, Baer, Klein, Katherine A., Mehta, Tejas S., Newell, Mary S., Schechter, Loren, Stuckey, Ashley R., Swain, Mary E., Tseng, Jennifer, Tuscano, Daymen S., and Moy, Linda

Published
2021
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21. A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women Under the Age of 50 Years

Author

Lourenco, Ana P., Benson, Kasey L., Henderson, Meredith C., Silver, Michael, Letsios, Elias, Tran, Quynh, Gordon, Kelly J., Borman, Sherri, Corn, Christa, Mulpuri, Rao, Smith, Wendy, Alpers, Josie, Costantini, Carrie, Rohatgi, Nitin, Yang, Rebecca, Haythem, Ali, Biren, Shah, Morris, Michael, Kass, Fred, and Reese, David E.

Published
2017
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26. Supplementary Tables from A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women over age 50 with BI-RADS 3, 4, or 5 Assessment

Author

Henderson, Meredith C., primary, Silver, Michael, primary, Tran, Quynh, primary, Letsios, Elias E., primary, Mulpuri, Rao, primary, Reese, David E., primary, Lourenco, Ana P., primary, LaBaer, Joshua, primary, Anderson, Karen S., primary, Alpers, Josie, primary, Costantini, Carrie, primary, Rohatgi, Nitin, primary, Ali, Haythem, primary, Baker, Karen, primary, Northfelt, Donald W., primary, Ghosh, Karthik, primary, Grobmyer, Stephen R., primary, Polen, Winnie, primary, and Wolf, Judith K., primary

Published
2023
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27. Figure S4 from A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women over age 50 with BI-RADS 3, 4, or 5 Assessment

Author

Henderson, Meredith C., primary, Silver, Michael, primary, Tran, Quynh, primary, Letsios, Elias E., primary, Mulpuri, Rao, primary, Reese, David E., primary, Lourenco, Ana P., primary, LaBaer, Joshua, primary, Anderson, Karen S., primary, Alpers, Josie, primary, Costantini, Carrie, primary, Rohatgi, Nitin, primary, Ali, Haythem, primary, Baker, Karen, primary, Northfelt, Donald W., primary, Ghosh, Karthik, primary, Grobmyer, Stephen R., primary, Polen, Winnie, primary, and Wolf, Judith K., primary

Published
2023
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41. Outcomes with Finerenone in Participants with Stage 4 CKD and Type 2 Diabetes

Author

Sarafidis, Pantelis, Agarwal, Rajiv, Pitt, Bertram, Wanner, Christoph, Filippatos, Gerasimos, Boletis, John, Tuttle, Katherine R., Ruilope, Luis M., Rossing, Peter, Toto, Robert, Anker, Stefan D., Liu, Zhi-Hong, Joseph, Amer, Ahlers, Christiane, Brinker, Meike, Lawatscheck, Robert, Bakris, George, Aizenberg, Diego, Bartolacci, Inés, Besada, Diego, Bittar, Julio, Chahin, Mariano, Elbert, Alicia, Gelersztein, Elizabeth, Liberman, Alberto, Maffei, Laura, Manghi, Federico Pérez, Sanabria, Hugo, Vallejos, Augusto, Viñes, Gloria, Wassermann, Alfredo, Abhayaratna, Walter, Acharya, Shamasunder, Ekinci, Elif, Lee, Darren, MacIsaac, Richard, Mah, Peak Mann, Nelson, Craig, Packham, David, Pape, Alexia, Roger, Simon, Stephenson, Hugo, Suranyi, Michael, Wittert, Gary, Vale, Elizabeth, Colman, Peter, Colquhoun, David, Ellis, Chris, Joshua, Kim, Pedagogos, Eugenia, Regal, Paul, Topliss, Duncan, Vandeleur, James, Verjans, Johan, Wittert, Gary, Wynne, Katie-Jane, Clodi, Martin, Ebenbichler, Christoph, Fliesser-Görzer, Evelyn, Hanusch, Ursula, Krebs, Michael, Lhotta, Karl, Ludvik, Bernhard, Mayer, Gert, Neudorfer, Peter, Paulweber, Bernhard, Prager, Rudolf, Preiß, Wolfgang, Prischl, Friedrich, Schernthaner, Gerit-Holger, Sourij, Harald, Wiesholzer, Martin, Drexel, Heinz, Oberbauer, Rainer, Schönherr, Hans-Robert, Doubel, Peter, Engelen, Wendy, Gillard, Pieter, Hougardy, Jean-Michel, Krzesinski, Jean-Marie, Maes, Bart, Speeckaert, Marijn, Stas, Koen, van Gaal, Luc, Vanbelleghem, Hilde, Duyck, Francis, Scheen, André, Antunes, Daniela, Botelho, Roberto, Brito, Claudia, Canani, Luis, Canziani, Maria Eugenia, Cerqueira, Maria, de Paula, Rogerio, Eliaschewitz, Freddy, Figueiredo, Carlos Eduardo, Forti, Adriana, Hissa, Miguel, Leite, Emerson Lima Maurilo, Noronha, Irene, Paolino, Bruno, Paschoalin, Nathalia, Paschoalin, Raphael, Filho, Roberto Pecoits, Pereira, Marcio, Portes, Evandro, Precoma, Dalton, Rea, Rosangela, Riella, Miguel, Salles, Joao Eduardo, Vasconcellos, Eduardo, Vencio, Sergio, Bacci, Marcelo, Maia, Lilia, Villacorta, Aline, Apostolova, Emiliya, Boshnyashka, Radostina, Farah, Ghassan, Georgiev, Dimitar, Gushterova, Valentina, Klyuchkova, Neli, Lucheva, Mariya, Manova, Petya, Minkova, Dotska, Nonchev, Boyan, Pichmanova, Mariyana, Prakova, Zhulieta, Rangelov, Rangel, Rashkov, Rosen, Stanchev, Pavel, Stoyanovska-Elencheva, Bilyana, Tagarev, Zhivko, Temelkova-Kurktschieva, Theodora, Vasileva, Svetla, Yoncheva-Mihaylova, Mariana, Marinchev, Angel, Miteva, Mariya, Barre, Paul, Carlson, Brian, Conway, James, Cournoyer, Serge, Dumas, Richard, Fikry, Sameh, Goluch, Richard, Hamet, Pavel, Hart, Randolph, Henein, Sam, Liutkus, Joanne, Madore, Francois, Martinho, Valdemar, Mazza, Giuseppe, McFarlane, Philip, Keefe, Dennis O′, Peterson, Sean, Schwartz, Daniel, Shu, Daniel, Steele, Andrew, Tellier, Guy, Tennankore, Karthik, Tobe, Sheldon, Tsoukas, George, Tytus, Richard, Vitou, Louise, Walsh, Michael, Weisnagel, Stanley, Wilderman, Igor, Yale, Jean-Francois, El Boreky, Fadia, Kelly, Alan, Leiter, Lawrence, Teitelbaum, Ivor, Cobos, Jorge, Godoy, Juan, González, Fernando, Lobos, Sergio, Palma, Juan Carlos, Prieto Dominguez, Juan Carlos, Reyes, Eliana, Romero, Carmen, Saavedra, Victor, Vega, Mario, Medina, Marcelo, Varleta, Paola, Bu, Ruifang, Cai, Hanqing, Chen, Nan, Chen, Qinkai, Chen, Dejun, Cheng, Jinluo, Dong, Youping, Dong, Junwu, Guan, Tianjun, Hao, Chuanming, Huang, Wen, Jiang, Fangfang, Lei, Minxiang, Li, Ling, Li, Zhonghe, Li, Xuemei, Li, Jingmei, Li, Yan, Liang, Xinling, Liang, Bo, Liu, Fang, Liu, Yinghong, Liu, Yuantao, Liu, Zhihong, Long, Gang, Lu, Guoyuan, Lu, Weiping, Lu, Yibing, Luo, Ping, Ma, Jianhua, Mo, Zhaohui, Niu, Jianying, Peng, Ai, Shen, Jiansong, Shen, Feixia, Shi, Bingyin, Su, Qing, Sun, Zhuxing, Tang, Shuifu, Tong, Nanwei, Wang, Hao, Wang, Xinjun, Wang, Guixia, Wang, Jianqin, Wang, Yangang, Wang, Li, Wei, Jiali, Wu, Tianfeng, Wu, Chaoqing, Xing, Changying, Xiong, Fei, Xu, Xudong, Xu, Ning, Yan, Tiekun, Yang, Jinkui, Yin, Aiping, Zeng, Longyi, Zhang, Hao, Zhang, Yanlin, Zhang, Ying, Zhao, Wenjing, Zhao, Zhiquan, Zheng, Hongguang, Zhong, Ling, Zhu, Dalong, Zhuang, Yongze, Du, Yuming, Fang, Yi, Guo, Weiying, Jiang, Sheng, Kuang, Jian, Li, Dongmei, Li, Hongmei, Li, Yinan, Li, Yuxiu, Liu, Jian, Liu, Yu, Miao, Heng, Peng, Wen, Wang, Lihua, Xu, Mingtong, Zhong, Liyong, Zhu, Jun, Arango, Clara, Barrera, Sandra, López, Nelly Beltrán, Benitez, Diego, Blanco, Guillermo, Cadena, Andrés, Coronel, Julian, Cure, Carlos, Durán, Carlos, González, Alexander, Guzmán, Gustavo, Hernández, Eric, Ibarra, Jaime, Jaramillo, Carlos, Jaramillo, Nicolás, Kattah, William, Molina, Dora, Sánchez, Gregorio, Terront, Mónica, Trujillo, Freddy, Urina, Miguel, Vargas, Ruben, Villegas, Iván, Yupanqui, Hernán, Arcos, Edgar, Aroca, Gustavo, Barreto, Germán, Bermudez, Andres, Botero, Rodrigo, Cárdenas, Tatiana, Figueroa, Wilmer, Jaramillo, Mónica, Liévano, Manuel, López, Mónica, Molina, Dora, Rosero, Ricardo, Trillos, Pedro, Alferi, Dino, Brada, Michal, Brezina, Jiri, Bucek, Petr, Edelsberger, Tomas, Gulakova, Drahomira, Zapletalova, Jitka Hasalova, Hola, Olga, Hornova, Lucie, Houdova, Jana, Hrmova, Helena, Karasek, David, Kopecka, Sarka, Kovar, Richard, Krcova, Eva, Kuchar, Jiri, Kutejova, Vlasta, Lubanda, Hana, Matyasek, Ivo, Mokrejsova, Magdalena, Okenka, Libor, Prazny, Martin, Pumprla, Jiri, Tomanek, Pavel, Andersen, Ulla, Andries, Alin, Bech, Jesper, Faber, Jens, Gislason, Gunnar, Hangaard, Jørgen, Pacyk, Grzegorz Jaroslaw, Juhl, Claus, Krarup, Thure, Lindhardt, Morten, Madsbad, Sten, Nielsen, Joan, Pedersen-Bjergaard, Ulrik, Poulsen, Per, Rasmussen, Ole, Rossing, Peter, Schousboe, Karoline, Gram, Jeppe, Lauridsen, Thomas, Pedersen, Erling, Thorsteinsson, Birger, Flöjt, Päivi, Honkasalo, Mikko, Honkasalo, Mikko, Humaloja, Kari, Kananen, Kristiina, Kantola, Ilkka, Koistinen, Arvo, Korsoff, Pirkko, Lahtela, Jorma, Nieminen, Sakari, Nieminen, Tuomo, Sadeharju, Karita, Strand, Jorma, Sulosaari, Sakari, Cariou, Bertrand, Chantrel, François, Clavel, Sylvaine, Combe, Christian, Fauvel, Jean-Pierre, Gallouj, Karim, Gouet, Didier, Guerci, Bruno, Guerrot, Dominique, Hourmant, Maryvonne, Klein, Alexandre, Mariat, Christophe, Marre, Michel, Mesbah, Rafik, Le Meur, Yannick, Monier, Arnaud, Moranne, Olivier, Roussel, Ronan, Serusclat, Pierre, Vendrely, Benoit, Verges, Bruno, Zaoui, Philippe, Axthelm, Christoph, Bergmann, Andreas, Birkenfeld, Andreas L., Braun, Hermann, Busch, Klaus, Contzen, Christel, Degenhardt, Stefan, Derwahl, Karl, Giebel, Thomas, Hagenow, Andreas, Haller, Hermann, Hasslacher, Christoph, Horacek, Thomas, Jungmair, Wolfgang, Kloos, Christof, Koch, Thorsten, Krüger, Thilo, Mühlfeld, Anja, Müller, Joachim, Pfützner, Andreas, Pistrosch, Frank, Rinke, Andrea, Rose, Ludger, Rump, Lars, Schettler, Volker, Schiefke, Ingolf, Schlichthaar, Heike, Schröppel, Bernd, Schöll, Norbert, Schubert, Kristin, Schürholz, Thomas, Sigal, Helena, Stemler, Lutz, Strack, Georg, Täschner, Heidrun, Toursarkissian, Nicole, Tschöpe, Diethelm, Ulmer, Achim, van der Giet, Markus, Wanner, Christoph, Winkelmann, Bernhard R., Boletis, Ioannis, Dimitriadis, George, Hatziagelaki, Erifili, Iatrou, Christos, Ioannidis, Ioannis, Kounadi, Theodora, Makriniotou, Ioanna, Papadopoulou, Dorothea, Papagianni, Aikaterini, Passadakis, Ploumis, Piaditis, George, Stefanidis, Ioannis, Ip, Tai Pang, Lee, Paul, Andrea Luk, On Yan, Ma, Ronald, Chow, Wing Sun, Wang, Angela, Yeung, Vincent, Bajcsi, Dora, Danos, Peter, Harcsa, Eleonora, Kalina, Akos, Kazup, Szilvia, Keltai, Katalin, Kirschner, Robert, Kiss, Julianna, Kovacs, Laszlo, Lamboy, Beata, Literati-Nagy, Botond, Mileder, Margit, Nagy, Laszlo, Noori, Ebrahim, Nyirati, Gabor, Petro, Gizella, Schneider, Karoly, Simon, Judit, Szocs, Albert, Vasas, Szilard, Wudi, Krisztina, Zilahi, Zsolt, Zsom, Marianna, Eustace, Joe, Holian, John, Reddan, Donal, Meara, Yvonne O′, Abramof Ness, Rosane, Adawi, Faiad, Armaly, Zaher, Atar, Shaul, Bashkin, Amir, Ben Chetrit, Sydney, Yanay, Noa Berar, Chernin, Gil, Darawsha, Mahmud, Efrati, Shai, Elias, Mazen, Farber, Evgeny, Glandt, Mariela, Grossman, Ehud, Halabi, Majdi, Harman-Boehm, Ilana, Khazim, Khaled, Liberty, Idit, Minuchin, Oscar, Mosenzon, Ofri, Nakhoul, Farid, Nimer, Assy, Schwartz, Doron, Wainstein, Julio, Yagil, Yoram, Zukermann, Robert, Avogaro, Angelo, Battaglia, Giovanni Giorgio, Bevilacqua, Maurizio Tiziano, Bonora, Enzo, Bossi, Carlo Antonio, Calabrò, Paolo, Cavalot, Franco Luigi, Cimino, Roberto, Cozzolino, Mario Gennaro, David, Salvatore, Emdin, Michele, Fiaccadori, Enrico, Fiorina, Paolo, Giorda, Carlo Bruno, Gregorini, Maria Cristina, La Manna, Gaetano, Maggi, Davide Carlo, Manti, Roberta, Meregalli, Giancarla, Pani, Antonello, Parvanova, Aneliy Ilieva, Perico, Norberto, Piatti, PierMarco, Pisani, Antonio, Pontiroli, Antonio Ettore, Ponzani, Paola, Santorelli, Gennaro, Santoro, Domenico, Scanziani, Renzo, Teatini, Ugo, Tonolo, Giancarlo, Trevisan, Roberto, Veronelli, Anna Maria, Viviani, Giorgio Luciano, Araki, Hideo, Bando, Yukihiro, Ebisui, Osamu, Fujita, Naruhiro, Fukasawa, Hirotaka, Furuya, Ryuichi, Hamamoto, Yoshiyuki, Hamasaki, Akihiro, Hasegawa, Kotaro, Hatazaki, Masahiro, Hayashi, Terumasa, Higashi, Takayuki, Hirohata, Yoshihide, Horinouchi, Shuji, Hoshi, Ayumu, Imoto, Hirofumi, Inagaki, Akemi, Inagaki, Masayuki, Inaguma, Daijo, Inoue, Toshihiko, Ishii, Masao, Ishiko, Tamayo, Isono, Motohide, Jinnouchi, Hideaki, Kanai, Hidetoshi, Kanda, Daisuke, Kanehara, Hideo, Kashima, Masayuki, Kataoka, Yuko, Katayama, Shigehiro, Kato, Kiyoe, Katsuki, Takeshi, Kawamitsu, Katsunori, Kawasaki, Satsuki, Kikuchi, Fumi, Kikuchi, Hidetoshi, Kishimoto, Rui, Kobayashi, Kunihisa, Koide, Junko, Komi, Rieko, Kubota, Miyuki, Kuriya, Genpei, Kurose, Takeshi, Kusano, Yoshiro, Hajime, Maeda, Matsubayashi, Sunao, Matsumoto, Kazunari, Matsumura, Naoya, Matsuo, Yasuto, Matsuoka, Naoki, Miyaoka, Hiroaki, Miyata, Satoshi, Morita, Takeshi, Murakami, Isao, Murao, Satoshi, Nakamura, Udai, Nakayama, Mikihiro, Nakazawa, Jun, Nohara, Sakae, Nomiyama, Takashi, Noritake, Masayuki, Oda, Yoshiaki, Ogiwara, Takayuki, Ohashi, Hiroshi, Okamoto, Hideki, Okino, Shinichi, Osonoi, Takeshi, Sasaki, Nobuhiro, Sayo, Yoshitaka, Sekigami, Taiji, Shibasaki, Taro, Shibata, Hirotaka, Shimoyama, Tatsushi, Shinoda, Junji, Sobajima, Hiroshi, Sugitatsu, Kazuya, Sugiura, Toshiyuki, Sugiyama, Toru, Suzuki, Daisuke, Suzuki, Hiroyuki, Suzuki, Masaaki, Takeda, Asami, Tanaka, Asami, Tanaka, Seiichi, Tsunematsu, Izumi, Ueda, Yasuo, Uekihara, Soichi, Ujihara, Makoto, Yajima, Ken, Yamada, Daishiro, Yamada, Masayo, Yamagata, Kazuo, Yamakawa, Ken, Yamakawa, Fumiko, Yamasaki, Yoshimitsu, Yambe, Yuko, Yanagida, Taihei, Yanai, Hidekatsu, Yanase, Toshihiko, Yasuda, Tetsuyuki, Kriauciuniene, Dovile, Lasiene, Jurate, Navickas, Antanas, Radzeviciene, Lina, Urbanaviciene, Egle, Urbonas, Gediminas, Velaviciene, Audrone, Abd Ghani, Rohana, Aziz, Nor Azizah, Lee, Li Yuan, Loh, Chek Loong, Ali, Norhaliza Mohd, Noor, Nurain Mohd, Fatnoon Nik Ahmad, Nik Nur, Ratnasingam, Jeyakantha, Halimi Bin Wan Hasan, Wan Hasnul, Izani Wan Mohamed, Wan Mohd, Khir, Rizmy Najme, Mohamad, Masni, Alexander Tan, Tong Boon, Avila Pardo, Sandro, Adrian, Miriam Bastidas, Wong, Alfredo Chew, Escobedo de la Peña, Jorge, Salmón, Guillermo Fanghänel, Gálvez, Guillermo González, Ochoa, Ramiro Gutiérrez, Santana, Saúl Irizar, Rovalo, Magdalena Madero, Machado, Gustavo Méndez, Ruiz, Luis Nevarez, Ibarra, Denisse Ramos, López, Gabriel Ramos, Reyna, Leobardo Sauque, Ortiz, Gustavo Solache, Ortiz, Rafael Valdez, Mesa, Juan Villagordoa, Salazar, Melchor Alpizar, Hernández, Pedro García, González, José, Soto, José Lazcano, Mendoza, Arturo Saldaña, Santana, Sergio Irizar, Vilchis, Elvira González, Bakker, R.C., Barendregt, J.N.M., Boonstra, A.H., Bos, Willem, Brouwer, C.B., Buren, M. van, Gansevoort, Ron, Kooy, Adriaan, Krekels, Marielle, Leendert, Ruud J.M. van, Lieverse, Louis A.G., Luik, P.T., Penne, E. Lars, Gregoor, Peter Smak, Vogt, Liffert, Born, Bert-Jan van den, Baker, John, Crawford, Veronica, Cutfield, Rick, Dunn, Peter, Krebs, Jeremy, Nirmalaraj, Kingsley, Scott, Russell, Smuts, Nine, Titchener, Janet, Eriksen, Erik, Finnes, Trine, Høivik, Hans, Karlsson, Thomas, Munk, Peter Scott, Radtke, Maria, Risberg, Knut, Rocke, Jan, Solnør, Leidulv, Stenehjem, Aud-Eldrid, Tafjord, Anne-Beathe, Asprusten, Emil, Hagemeier, Robert, Høye, Kjetil, Selsås, Hilde, Thorup, Frode, Wium, Cecilie, Pamugas, Glenda, Panelo, Araceli, Perez, Ronald, Tanque, Maribel, Tirador, Louie, Villa, Michael, Bautista, Albert, Catindig, Elizabeth, Manalo, Carlo, Mirasol, Roberto, Butrymowicz, Patrycja, Ciechanowski, Kazimierz, Cieslik, Grazyna, Franek, Edward, Gumprecht, Janusz, Hoffmann, Michal, Krzykowska, Jolanta, Kurnatowska, Ilona, Landa, Katarzyna, Madrzejewski, Adam, Madziarska, Katarzyna, Mazur, Stanislaw, Napora, Piotr, Nowicki, Michal, Ocicka-Kozakiewicz, Anna, Rewerska, Barbara, Rusicka, Teresa, Ruxer, Jan, Skokowska, Ewa, Stankiewicz, Andrzej, Stompor, Tomasz, Tiuryn-Petrulewicz, Agnieszka, Wasilewska, Katarzyna, Wierusz-Wysocka, Bogna, Wnetrzak-Michalska, Renata, Jedynasty, Krystyna, Anand, Izabela Sein, Almeida, Edgar, Ballesteros, Rosa, Barreto, Carlos, Beirao, Idalina, Birne, Rita, Esteves, Cesar, Guia, Jose, Heitor, Susana, Marques, Olinda, Melo, Pedro, Nolasco, Fernando, Pereira, Amalia, Roque, Cristina, Rosario, Francisco, Silva, Gil, Silva, Ana, Teixeira e Costa, Fernando, Lobos, Ana Vila, Alves, Ana Rita, Brandao, Ilidio, Carvalho, Rui, Coelho, Joao, Lourenco, Ana, Matos, Pedro, Rosario, Vanisa, Neves, Joao Sergio, Cortes-Maisonet, Gregorio, Roman-Miranda, Amaury, Brito-Peguero, Yudit, Colon-Vega, Gildred, Albota, Adrian, Bala, Cornelia, Barbonta, Hortensia, Caceaune, Elena, Catrinoui, Doina, Constantin, Ciprian, Dumitrescu, Adriana, Mindrescu, Nicoleta, Mistode, Cristina, Negrisanu, Gabriela, Onaca, Adriana, Paveliu, Silvia, Pintilei, Ella, Pop, Lavinia, Popa, Amorin, Popescu, Alexandrina, Radulian, Gabriela, Szilagyi, Iosif, Turcu, Liana, Vacaru, Georgeta, Vlad, Adrian, Filimon, Adriana, Veresiu, Ioan, Antsiferov, Mikhail, Arkhipov, Mikhail, Babkin, Andrey, Barbarash, Olga, Baranov, Vitaliy, Chernyavskaya, Elena, Demko, Arkadiy, Dreval, Alexander, Edin, Anton, Ermakova, Polina, Fadeev, Valentin, Galyavich, Albert, Gaysina, Leyla, Gordeev, Ivan, Ipatko, Irina, Kalashnikova, Marina, Khalimov, Yuriy, Klimontov, Vadim, Kobalava, Zhanna, Kosmacheva, Elena, Koziolova, Natalya, Sergey Levashov, Lyudmila Kvitkova, Libis, Roman, Marasaev, Vyacheslav, Malykh, Natalia, Martynenko, Vladimir, Malyutina, Sofya, Merai, Imad, Mkrtumyan, Ashot, Nechaeva, Galina, Petunina, Nina, Palyutin, Shamil, Pimenov, Leonid, Rechkova, Elena, Rodionova, Tatyana, Rymar, Oksana, Sardinov, Ruslan, Semenova, Olga, Sherenkov, Alexander, Solovev, Oleg, Smolyarchuk, Elena, Strongin, Leonid, Ukhanova, Olga, Verlan, Nadezhda, Vorokhobina, Natalya, Yakhontov, Davyd, Yakushin, Sergey, Zakharova, Elena, Zalevskaya, Alsu, Zanozina, Olga, Zhdanova, Elena, Zhukova, Larisa, Zykova, Tatyana, Argunova, Yulia, Nikolaev, Konstantin, Villevalde, Svetlana, Fang Sum, Chee, Suhail, Sufi Muhummad, San Tan, Ru, Vathsala, Anantharaman, Wong, Edmund, Bee, Yong Mong, Babikova, Jana, Buganova, Ingrid, Dzupina, Andrej, Ochodnicka, Zuzana, Sosovec, Dalibor, Spodniakova, Denisa, Minarik, Peter, Ahmed, Fayzal, Amod, Aslam, Bhana, Sindeep, Distiller, Larry, Jansen van Rensburg, Dirkie, Joshi, Mukesh, Joshi, Shaifali, Lakha, Deepak, Mitha, Essack, Podgorski, Gracjan, Ranjith, Naresh, Rayner, Brian, Rheeder, Paul, Sarvan, Mohamed, Seeber, Mary, Siebert, Heidi, Tayob, Mohammed, Trokis, Julien, Urbach, Dorothea, van Zyl, Louis, Jansen van Rensburg, Dirkie, Choi, Bum-Soon, Choi, Moon Gi, Chung, ChoonHee, Hwang, YouCheol, Kim, ChongHwa, Kim, InJoo, Kim, JaeHyeon, Kim, SinGon, Kim, SungGyun, Kim, Tae Hee, Lee, WooJe, Lee, ByungWan, Lee, Kang Wook, Oh, Kook-Hwan, Oh, Ji Eun, Oh, Yun Kyu, Oh, Dong-Jin, Park, Junbeom, Shin, Seok Joon, Sung, Su-Ah, Yu, Jae Myung, Chung, HyeSoo, Huh, Ji Hye, Kang, JunGoo, Kim, ChulSik, Kim, HyeSoon, Kim, NamHoon, Lim, Soo, Cho, Young Min, Park, Cheol Young, Agraz, Irene, Ampudia, Francisco Javier, Bouarich, Hanane, Calero, Francesca, Castro, Cristina, Guldris, Secundino Cigarrán, Garrit, Josep Cruzado, de Álvaro, Fernando, Galcerán, Josep, Albarrán, Olga González, Jaras, Julio Hernández, Ibernón, Meritxell, Deben, Francisco Martínez, Ma, Esteban, Dolores Martínez, Pascual Izuel, José María, Martins, Judith, Mediavilla, Juan, Michán, Alfredo, Santos, Julio Pascual, Poch, Esteban, Rusillo, Manuel Polaina, Juan, Carlos Sánchez, Olmo, Rafael Santamaría, Segura de la Morena, José Julián, Soto, Alfonso, Troya, Maribel, Castro, Fernando Cereto, Fernández, Pablo Gómez, Sánchez, Laura Fuentes, Moya, Mercedes González, Marrero, Domingo Hernández, Maroto, Gonzalo Piedrola, Redón, Josep, Seron, Daniel, Bruchfeld, Annette, Curiac, Dan, Eliasson, Ken, Frank, Malin, Guron, Gregor, Hellberg, Olof, Hellgren, Margareta, Larnefeldt, Hans, Lindholm, Carl-Johan, Löndahl, Magnus, Rein-Hedin, Erik, Soveri, Inga, Spaak, Jonas, Tengmark, Bengt-Olov, Lif-Tiberg, Cornelia, Månflod, Johan, Nguyen, Han, Ackermann, Daniel, Bilz, Stefan, Burnier, Michel, Forster, Christian, Kalbermatter, Stefan, Kistler, Andreas, Pechère-Bertschi, Antoinette, Schultes, Bernd, Laimer, Markus, Rudofsky, Gottfried, Strey, Christopher, Wuerzner, Gregoire, Chang, Chiz-Tzung, Hung, Cheng-Chieh, Jiang, Ju-Ying, Lee, Chien-Te, Lin, Shuei-Liong, Tarng, Der-Cherng, Tu, Shih-Te, Wu, Mai-Szu, Wu, Ming-Ju, Chuang, Lee-Ming, Deerochanawong, Chaicharn, Kitiyakara, Chagriya, Ophascharoensuk, Vuddhidej, Pongchaiyakul, Chatlert, Satirapoj, Bancha, Kosachunhanan, Natapong, Sritara, Piyamitr, Eren, Necmi, Gul, Ibrahim, Gulel, Okan, Kocyigit, Ismail, Kumbasar, Abdulbaki, Sahin, Idris, Sari, Ramazan, Sayin, Burak, Tavli, Talat, Ustundag, Sedat, Yenicerioglu, Yavuz, Badak, Ozer, Cayli, Murat, Oguz, Aytekin, Ozdogan, Oner, Sari, Ibrahim, Temizhan, Ahmet, Tigen, Mustafa, Turk, Ugur, Yilmaz, Huseyin, Yilmaz, Mehmet, Bondarets, Iryna, Botsyurko, Volodymyr, Chernikova, Viktoriia, Donets, Oleksandra, Fushtey, Ivan, Grachova, Mariia, Isayeva, Anna, Kogut, Dmytro, Komisarenko, Julia, Kravchun, Nonna, Malyar, Kateryna, Mankovsky, Borys, Martynyuk, Liliya, Maslyanko, Vitaliy, Myshanych, Halyna, Pererva, Larysa, Pertseva, Nataliia, Serhiyenko, Oleksandr, Smirnov, Ivan, Sokolova, Liubov, Stryzhak, Vasyl, Vlasenko, Maryna, Isayeva, Ganna, Larin, Oleksandr, AbouSaleh, Ahmad, Barratt, Jonathan, Dang, Cuong, Kahal, Hassan, Kirk, Adam, Kilvert, Anne, Kon, Sui Phi, McCafferty, Kieran, Patel, Dipesh, Rice, Sam, Vijayaraman, Arutchelvam, Wong, Yuk-ki, Gibson, Martin, Wahba, Mona, Zaidi, Reza, Bilous, Rudy, Johnson, Andrew, Kalathil, Dhanya, Kilvert, Anne, Kyriakidou, Christina, Mathew, Amit, Mukhtar, Rasha, Munsoor, Imrozia, Poterajlo, Anton, Swift, Pauline, Acosta, Idalia, Adams, Atoya, Adler, Sharon, Ajani, Dilawar, Ali, Slamat, Alicic, Radica, Al-Karadsheh, Amer, Alla, Sreedhara, Allison, D., Andrawis, Nabil, Arif, Ahmed, Awad, Ahmed, Azizad, Masoud, Bahrami, Michael, Bansal, Shweta, Barag, Steven, Barakzoy, Ahmad, Barney, Mark, Barzilay, Joshua, Bashir, Khalid, Bautista, Jose, Beddhu, Srinivasan, Belo, Diogo, Benjamin, Sabrina, Berenji, Ramin, Bhargava, Anuj, Birriel, Jose, Brietzke, Stephen, Brosius, Frank, Brusco, Osvaldo, Burgner, Anna, Busch, Robert, Canadas, Rafael, Caramori, Maria, Cardona, Jose, Case, Christopher, Cruz, Humberto, Dandillaya, Ramprasad, Dawoud, Dalia, Din, Zia, Dixon, Bradley, Doshi, Ankur, Drakakis, James, El Shahawy, Mahfouz, El-Meanawy, Ashraf, El-Shahawy, Mohammed, Evans, John, Fadda, George, Farooq, Umar, Fernando, Roland, Fink, Raymond, First, Brian, Fitz-Patrick, David, Flack, John, Fluck, Patrick, Fogelfeld, Leon, Fonseca, Vivian, Frias, Juan, Galphin, Claude, Garcia-Mayol, Luis, Goldstein, Gary, Gonzalez, Edgar, Gonzalez-Abreu, Francisco, Gore, Ashwini, Grant, David, Habwe, Violet, Hamilton, Maxine, Hammoud, Jamal, Handelsman, Stuart, Hartman, Israel, Heigerick, Glenn, Henry, Andrew, Hernandez, German, Hernandez-Cassis, Carlos, Herrera, Carlos, Hertel, Joachim, Huang, Wenyu, Iglesias, Rogelio, Iranmanesh, Ali, Jackson, Timothy, Jain, Mahendra, Jamerson, Kenneth, Johnson, Karen, Judd, Eric, Kaplan, Joshua, Kayali, Zeid, Khan, Bobby, Khan, Muhammad, Kharait, Sourabh, Kirkman, M. Sue, Kopyt, Nelson, Kotzker, Wayne, Kovesdy, Csaba, Kreit, Camil, Krishna, Arvind, Kronfli, Saeed, Lee, Keung, LeJeune, Derek, Lemus, Brenda, Leon-Forero, Carlos, Linfert, Douglas, Lora, Henry, Lurie, Alexander, Maddukuri, Geetha, Magno, Alexander, Maletz, Louis, Mandayam, Sreedhar, Markell, Mariana, Mayfield, Ronald, Mbogua, Caroline, McMullen, Dierdre, Meisner, Carl, Minton, Stephen, Mocherla, Bharat, Mohandas, Rajesh, Montero, Manuel, Moustafa, Moustafa, Nadkarni, Salil, Nakhle, Samer, Navarro, Jesus, Neyra, Nilda, Nica, Romanita, Nicol, Philip, Norwood, Paul, Numrungroad, Visal, Donovan, Richard O′, Odugbesan, A., Paoli-Bruno, Jorge, Parikh, Samir, Patel, Rakesh, Peixoto, Aldo, Pergola, Pablo, Perlman, Alan, Pettis, Karlton, Pisoni, Roberto, Ponduchi, Mirela, Posada, Jorge, Prabhakar, Sharma, Radhakrishnan, Jai, Rahman, Mahboob, Raina, Rupesh, Rastogi, Anjay, Reisin, Efrain, Rendell, Marc, Robertson, David, Rocco, Michael, Romeu, Hugo, Rosas, Sylvia, Rosenfeld, Jack, Ross, Dennis, Rothman, Jeffrey, Rudolph, Lance, Ruhullah, Yusuf, Ruoff, Gary, Ryu, Jeffrey, Sahani, Mandeep, Sam, Ramin, Samuels, Garfield, Sanchez, William, Santos, Vladimir, Satko, Scott, Saxena, Sanjeev, Scott, David, Seco, Gilberto, Seek, Melvin, Serota, Harvey, Shafi, Tariq, Shahid, Nauman, Shanik, Michael, Sharma, Santosh, Sinha, Arjun, Smelser, James, Smith, Mark, Soe, Kyaw, Solomon, Richard, Soroka, Eugene, Soufer, Joseph, Spinowitz, Bruce, Spry, Leslie, Suarez, Rosa, Subramanian, Bala, Szerlip, Harold, Tamirisa, Aparna, Thomson, Stephen, Tran, Tuan-Huy, Treger, Richard, Trullenque, Gretel, Turk, Thomas, Umpierrez, Guillermo, Urbach, Daniel, Valdes, Martin, Valika, Shujauddin, Vega, Damaris, Weissman, Peter, Whaley-Connell, Adam, Winston, Jonathan, Wise, Jonathan, Wynne, Alan, Zeig, Steven, Abdel-Rahman, Emaad, Abreu, Edel, Awad, Alaa, Bahri, Nader, Bertsch, John, Bleich, David, Bornfreund, Jonathan, Brar, Harjeet, Brian, Susan, Brinson, Cynthia, Bruschetta, Humberto, Carpio, Jose, Cohen, Steven, Cosby, John, Dhanireddy, Soni, Diaz, Jorge, Dunn, Fredrick, Eppanapally, Sabitha, Fayad, Joseph, Goel, Archana, Govindaraju, Kanakadurga, Halpern, Stephen, Jones, Audrey, Kaye, William, Knight, Herbert, Koch, Stanley, Kohli, Nandini, Lastra, Guido, Lerman, Sam, Loredo, Jorge, Lovre, Dragana, Mandviwala, Mustafa, Martin, Earl, Meyer, Jill, Murray, John, Oliver, David, Oparil, Suzanne, Penabad, Jesus, Pereira, Isabel, Popeil, Larry, Quesada, Gonzalo, Ramanathan, Kodangudi, Ramos-Gonez, Luis, Rastegar, Mandana, Rastogi, Padmashri, Rondon, Juan, Roy-Chaudhury, Prabir, Smith, David, Williamson, Don, Womack, Catherine, Yamout, Hala, Yuryev, Michael, Chu, Phuong, Van Hoang, Lam, Khanh, Tran, Phi Nga, Nguyen Thi, Son, Pham Nguyen, Tran, Lan Phuong, Le, Thuy Khuong, Nguyen, Boi Ngoc, Nguyen, Thao, Nui, Nguyen Minh, Nam, Tran Quang, and Tran, Kim Chi

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