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102. A software for Estimating Biodiversity Components (BİÇEB)

Author

Kürşad Özkan, Ecir Küçüksi̇lle, Ahmet Mert, Serkan Gülsoy, Halil Suel, and Murat Başar

Subjects
dissimilarity, shannon, simpson, margalef, sorensen, whittaker, benzemezlik, Forestry, SD1-669.5
Abstract

Biodiversity is of crucial importance for ecosystem health and functioning. It is thus one of the most important topics in the various disiplines of the Naturel Science. Various indices have been improved to measure biodiversity. By using those indices, biodiversity can be estimated at alpha (within a given site), beta (between the sites) and gamma (total) levels. Thanks to presence of many indices for calculating of biodiversity components, the researchers can use these calculation techniques with their alternatives and evaluate the research results more effectively and efficiently. This situation provides an important adventage to arrive more productive and accurate results about biodiversity studies. The information obtained from such studies are particulary important for the identification of the policies and implementations for conservation and sustainability of the biodiversity in the natural ecosystems. In this sense, by thinking as an important demand for the reseachers in Turkey, it was thought that making a sofware called by our study team as “A Software for Measuring Bodiversity Components (BİÇEB)” can be useful. This software includes species richness measures, heterogeneousness measurments and species abundance models at alpha level, and computations between two communities, and among the communities by using binary and abundance data at beta and gamma level. The software is designed in two forms as web and desktop application. In this way, it is aimed to be an easily accessible and user friendly software. In this study, it is aimed to give information about BİÇEB software.

Published
2020

103. Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs

Author

Emily E. Burke, Joshua G. Chenoweth, Joo Heon Shin, Leonardo Collado-Torres, Suel-Kee Kim, Nicola Micali, Yanhong Wang, Carlo Colantuoni, Richard E. Straub, Daniel J. Hoeppner, Huei-Ying Chen, Alana Sellers, Kamel Shibbani, Gregory R. Hamersky, Marcelo Diaz Bustamante, BaDoi N. Phan, William S. Ulrich, Cristian Valencia, Amritha Jaishankar, Amanda J. Price, Anandita Rajpurohit, Stephen A. Semick, Roland W. Bürli, James C. Barrow, Daniel J. Hiler, Stephanie C. Page, Keri Martinowich, Thomas M. Hyde, Joel E. Kleinman, Karen F. Berman, Jose A. Apud, Alan J. Cross, Nicholas J. Brandon, Daniel R. Weinberger, Brady J. Maher, Ronald D. G. McKay, and Andrew E. Jaffe

Subjects
Science
Abstract

Here, authors present results of a hiPSC transcriptomics study on corticogenesis from multiple donors across four transitions in differentiation. They present a bulk data deconvolution method and show that co-culturing human NPCs with rodent astrocytes results in mutually synergistic maturation.

Published
2020
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104. Co-Localization of Resistance and Metabolic Quantitative Trait Loci on Carrot Genome Reveals Fungitoxic Terpenes and Related Candidate Genes Associated with the Resistance to Alternaria dauci

Author

Claude Emmanuel Koutouan, Valérie Le Clerc, Anita Suel, Latifa Hamama, Patricia Claudel, David Halter, Raymonde Baltenweck, Philippe Hugueney, Jean-François Chich, Sitti Anlati Moussa, Clémentine Champlain, Sébastien Huet, Linda Voisine, Sandra Pelletier, Sandrine Balzergue, Wilfried Chevalier, Emmanuel Geoffriau, and Mathilde Briard

Subjects
metabolomic, transcriptomic, antifungal activities, Daucus carota, leaf blight, Microbiology, QR1-502
Abstract

Alternaria leaf blight, caused by the fungus Alternaria dauci, is the most damaging foliar disease of carrot. Some carrot genotypes exhibit partial resistance to this pathogen and resistance Quantitative Trait Loci (rQTL) have been identified. Co-localization of metabolic QTL and rQTL identified camphene, α-pinene, α-bisabolene, β-cubebene, caryophyllene, germacrene D and α-humulene as terpenes potentially involved in carrot resistance against ALB. By combining genomic and transcriptomic analyses, we identified, under the co-localization regions, terpene-related genes which are differentially expressed between a resistant and a susceptible carrot genotype. These genes include five terpene synthases and twenty transcription factors. In addition, significant mycelial growth inhibition was observed in the presence of α-humulene and caryophyllene.

Published
2023
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109. KeyAuth: Bringing Public-key Authentication to the Masses

Author

Suel, Travis Z.

Subjects
Computer Science - Cryptography and Security, Computer Science - Human-Computer Interaction
Abstract

Passwords are a fragile, inadequate, and insecure tool for authenticating users, and are especially fraught with problems when used to secure access to network resources and services. In many cases, passwords provide a false sense of security. Creating passwords which are both secure (i.e., hard for attackers to guess) and easy for humans to remember is, at best, a paradoxical task because these two criteria are diametrically opposed. Fortunately, a far more secure and user-friendly alternative is available. Public-key cryptography provides a means of both identifying and authenticating users without the need for passwords. KeyAuth is a generic and universal implementation of public-key authentication aimed at supplanting password-based authentication and significantly improving the security of network accessible resources by enhancing the usability of frequently used authentication mechanisms. KeyAuth is an application-, language-, operating system-, and protocol-independent public-key authentication service., Comment: 6 pages, 1 figure, 1 table

Published
2012

110. Do poverty and wealth look the same the world over? A comparative study of 12 cities from five high-income countries using street images

Author

Suel, E, Muller, E, Bennett, J, Blakely, T, Doyle, Y, Lynch, J, Mackenbach, J, Middel, A, Mizdrak, A, Nathvani, R, Brauer, M, Ezzati, M, Epidemiology and Data Science, and APH - Health Behaviors & Chronic Diseases

Abstract

Urbanization and inequalities are two of the major policy themes of our time, intersecting in large cities where social and economic inequalities are particularly pronounced. Large scale street-level images are a source of city-wide visual information and allow for comparative analyses of multiple cities. Computer vision methods based on deep learning applied to street images have been shown to successfully measure inequalities in socioeconomic and environmental features, yet existing work has been within specific geographies and have not looked at how visual environments compare across different cities and countries. In this study, we aim to apply existing methods to understand whether, and to what extent, poor and wealthy groups live in visually similar neighborhoods across cities and countries. We present novel insights on similarity of neighborhoods using street-level images and deep learning methods. We analyzed 7.2 million images from 12 cities in five high-income countries, home to more than 85 million people: Auckland (New Zealand), Sydney (Australia), Toronto and Vancouver (Canada), Atlanta, Boston, Chicago, Los Angeles, New York, San Francisco, and Washington D.C. (United States of America), and London (United Kingdom). Visual features associated with neighborhood disadvantage are more distinct and unique to each city than those associated with affluence. For example, from what is visible from street images, high density poor neighborhoods located near the city center (e.g., in London) are visually distinct from poor suburban neighborhoods characterized by lower density and lower accessibility (e.g., in Atlanta). This suggests that differences between two cities is also driven by historical factors, policies, and local geography. Our results also have implications for image-based measures of inequality in cities especially when trained on data from cities that are visually distinct from target cities. We showed that these are more prone to errors for disadvantaged areas especially when transferring across cities, suggesting more attention needs to be paid to improving methods for capturing heterogeneity in poor environment across cities around the world.

Published
2023

111. A EDUCAÇÃO EMPREENDEDORA COMO ATIVIDADE EXTRACURRICULAR NO ENSINO FUNDAMENTAL: PREPARANDO O ALUNO PARA O MERCADO DE TRABALHO.

Author

Olivindo de Sousa, Ana Lívia, Gomes de Lima, Taísa Maria, do Nascimento, Meirilane, de Moura Sá, Jairon Suel, Terceiro de Albuquerque, Anderson, Aguiar Pimenta, Alcineide, Vasconcelos Marques, Francisco Geilson, and Araújo Ramos, Ismael

Subjects
CAREER changes, PHILOSOPHY of education, EDUCATION theory, LABOR market, OCCUPATIONAL mobility
Abstract

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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112. EVIDÊNCIAS SOBRE A CURVA DE KUZNETS AMBIENTAL PARA OS ESTADOS BRASILEIROS.

Author

de Moura Sá, Jairon Suel and Silvino de Carvalho, Queliane

Subjects
KUZNETS curve, PANEL analysis, ECONOMETRICS, HYPOTHESIS, BRAZILIANS
Abstract

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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114. Using Deep Transfer Learning and Satellite Imagery to Estimate Urban Air Quality in Data-Poor Regions

Author

Yadav, Nishant, primary, Sorek-Hamer, Meytar, additional, Von Pohle, Michael, additional, Asanjan, Ata Akbari, additional, Sahasrabhojanee, Adwait, additional, Suel, Esra, additional, Arku, Raphael, additional, Lingenfelter, Violet, additional, Brauer, Michael, additional, Ezzati, Majid, additional, Oza, Nikunj, additional, and Ganguly, Auroop R., additional

Published
2023
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117. Molecular programs of regional specification and neural stem cell fate progression in macaque telencephalon

Author

Micali, Nicola, primary, Ma, Shaojie, additional, Li, Mingfeng, additional, Kim, Suel-Kee, additional, Mato-Blanco, Xoel, additional, Sindhu, Suvimal Kumar, additional, Arellano, Jon I., additional, Gao, Tianliuyun, additional, Shibata, Mikihito, additional, Gobeske, Kevin T., additional, Duque, Alvaro, additional, Santpere, Gabriel, additional, Sestan, Nenad, additional, and Rakic, Pasko, additional

Published
2023
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120. Associations of Street-View Greenspace with Incident Cardiovascular Disease in the US-based Nationwide Nurses’ Health Study from 2000 to 2016

Author

Jimenez, Marcia Pescador, primary, Lin, Pi I Debby, additional, Suel, Esra, additional, Klompmaker, Jochem O, additional, Zhang, Wenwen, additional, Hystad, Perry, additional, Hankey, Steve, additional, Rimm, Eric B, additional, Coull, Brent, additional, Hart, Jaime E, additional, Laden, Francine, additional, and James, Peter, additional

Published
2023
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121. What You See Is What You Breathe? Estimating Air Pollution Spatial Variation Using Street-Level Imagery

Author

Esra Suel, Meytar Sorek-Hamer, Izabela Moise, Michael von Pohle, Adwait Sahasrabhojanee, Ata Akbari Asanjan, Raphael E. Arku, Abosede S. Alli, Benjamin Barratt, Sierra N. Clark, Ariane Middel, Emily Deardorff, Violet Lingenfelter, Nikunj C. Oza, Nishant Yadav, Majid Ezzati, and Michael Brauer

Subjects
computer vision, deep learning, street images, air pollution, data science, transferability, Science
Abstract

High spatial resolution information on urban air pollution levels is unavailable in many areas globally, partially due to the high input data needs of existing estimation approaches. We introduced a computer vision method to estimate annual means for air pollution levels from street-level images. We used annual mean estimates of NO2 and PM2.5 concentrations from locally calibrated models as labels from London, New York, and Vancouver to allow for compilation of a sufficiently large dataset (~250 k images for each city). Our experimental setup is designed to quantify intra- and intercity transferability of image-based model estimates. Performances were high and comparable to traditional land-use regression (LUR) and dispersion models when training and testing images from the same city (R2 values between 0.51 and 0.95 when validated on data from ground monitoring stations). Similar to LUR models, transferability of models between cities in different geographies is more difficult. Specifically, transferability between the three cities (London, New York, and Vancouver), which have similar pollution source profiles, was moderately successful (R2 values between zero and 0.67). Comparatively, performances when transferring models trained on cities with very different source profiles, such as Accra in Ghana and Hong Kong, were lower (R2 between zero and 0.21). This suggests a need for local calibration, using additional measurement data from cities that share similar source profiles.

Published
2022
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125. Multisite evaluation of phenotypic plasticity for specialized metabolites, some involved in carrot quality and disease resistance.

Author

Wilfried Chevalier, Sitti-Anlati Moussa, Miguel Medeiros Netto Ottoni, Cécile Dubois-Laurent, Sébastien Huet, Christophe Aubert, Elsa Desnoues, Brigitte Navez, Valentine Cottet, Guillaume Chalot, Michel Jost, Laure Barrot, Gerald Freymark, Maarten Uittenbogaard, François Chaniet, Anita Suel, Marie-Hélène Bouvier Merlet, Latifa Hamama, Valérie Le Clerc, Mathilde Briard, Didier Peltier, and Emmanuel Geoffriau

Subjects
Medicine, Science
Abstract

Renewed consumer demand motivates the nutritional and sensory quality improvement of fruits and vegetables. Specialized metabolites being largely involved in nutritional and sensory quality of carrot, a better knowledge of their phenotypic variability is required. A metabolomic approach was used to evaluate phenotypic plasticity level of carrot commercial varieties, over three years and a wide range of cropping environments spread over several geographical areas in France. Seven groups of metabolites have been quantified by HPLC or GC methods: sugars, carotenoids, terpenes, phenolic compounds, phenylpropanoids and polyacetylenes. A large variation in root metabolic profiles was observed, in relation with environment, variety and variety by environment interaction effects in decreasing order of importance. Our results show a clear diversity structuration based on metabolite content. Polyacetylenes, β-pinene and α-carotene were identified mostly as relatively stable varietal markers, exhibiting static stability. Nevertheless, environment effect was substantial for a large part of carrot metabolic profile and various levels of phenotypic plasticity were observed depending on metabolites and varieties. A strong difference of environmental sensitivity between varieties was observed for several compounds, particularly myristicin, 6MM and D-germacrene, known to be involved in responses to biotic and abiotic stress. This work provides useful information about plasticity in the perspective of carrot breeding and production. A balance between constitutive content and environmental sensitivity for key metabolites should be reached for quality improvement in carrot and other vegetables.

Published
2021
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126. Development of a Gas Chromatography-Time-of-Flight Method for Detecting Glucosinolate Metabolites and Volatile Organic Compounds in Kimchi

Author

Ho Jin Kim, Mi Jin Lee, Suel Hye Hur, and Min Hee Jeong

Subjects
Analytical chemistry, QD71-142
Abstract

This study examined the volatile organic compounds (VOCs) and metabolites of glucosinolate (GLS) contained in kimchi and analyzed GLS using myrosinase. The analysis was conducted using gas chromatography-time of flight (GC-TOF), and VOC and the metabolite quantities were detected and analyzed. Based on 22 samples, tests were conducted, and 12 metabolites and 52 VOCs were found. When the detected metabolites were compared in general, the rate of isothiocyanate, which is well known for its anticancer effects and various other activities, was the highest. A total of 52 VOCs, including 15 aliphatic hydrocarbons, 7 acids, and 6 alcohols, were detected by GC-TOF. Therefore, the analytical methods provide a good basis to examine VOC and GLS metabolites; furthermore, the methods are of great help to secure excellent kimchi and evaluate its quality.

Published
2021
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127. A Deep Learning Approach for Meter-Scale Air Quality Estimation in Urban Environments Using Very High-Spatial-Resolution Satellite Imagery

Author

Meytar Sorek-Hamer, Michael Von Pohle, Adwait Sahasrabhojanee, Ata Akbari Asanjan, Emily Deardorff, Esra Suel, Violet Lingenfelter, Kamalika Das, Nikunj C. Oza, Majid Ezzati, and Michael Brauer

Subjects
air quality, remote sensing, urban environment, deep learning, satellite imagery, Meteorology. Climatology, QC851-999
Abstract

High-spatial-resolution air quality (AQ) mapping is important for identifying pollution sources to facilitate local action. Some of the most populated cities in the world are not equipped with the infrastructure required to monitor AQ levels on the ground and must rely on other sources, such as satellite derived estimates, to monitor AQ. Current satellite-data-based models provide AQ mapping on a kilometer scale at best. In this study, we focus on producing hundred-meter-scale AQ maps for urban environments in developed cities. We examined the feasibility of an image-based object-detection analysis approach using very high-spatial-resolution (2.5 m) commercial satellite imagery. We fed the satellite imagery to a deep neural network (DNN) to learn the association between visual urban features and air pollutants. The developed model, which solely uses satellite imagery, was tested and evaluated using both ground monitoring observations and land-use regression modeled PM2.5 and NO2 concentrations over London, Vancouver (BC), Los Angeles, and New York City. The results demonstrate a low error with a total RMSE < 2 µg/m3 and highlight the contribution of specific urban features, such as green areas and roads, to continuous hundred-meter-scale AQ estimations. This approach offers promise for scaling to global applications in developed and developing urban environments. Further analysis on domain transferability will enable application of a parsimonious model based merely on satellite images to create hundred-meter-scale AQ maps in developing cities, where current and historical ground data are limited.

Published
2022
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131. Variation of Human Neural Stem Cells Generating Organizer States In Vitro before Committing to Cortical Excitatory or Inhibitory Neuronal Fates

Author

Nicola Micali, Suel-Kee Kim, Marcelo Diaz-Bustamante, Genevieve Stein-O’Brien, Seungmae Seo, Joo-Heon Shin, Brian G. Rash, Shaojie Ma, Yanhong Wang, Nicolas A. Olivares, Jon I. Arellano, Kristen R. Maynard, Elana J. Fertig, Alan J. Cross, Roland W. Bürli, Nicholas J. Brandon, Daniel R. Weinberger, Joshua G. Chenoweth, Daniel J. Hoeppner, Nenad Sestan, Pasko Rakic, Carlo Colantuoni, and Ronald D. McKay

Subjects
neural stem cell, FGF2, BMP, neural transcriptional dynamics, neurogenesis, EGFR, Biology (General), QH301-705.5
Abstract

Summary: Better understanding of the progression of neural stem cells (NSCs) in the developing cerebral cortex is important for modeling neurogenesis and defining the pathogenesis of neuropsychiatric disorders. Here, we use RNA sequencing, cell imaging, and lineage tracing of mouse and human in vitro NSCs and monkey brain sections to model the generation of cortical neuronal fates. We show that conserved signaling mechanisms regulate the acute transition from proliferative NSCs to committed glutamatergic excitatory neurons. As human telencephalic NSCs develop from pluripotency in vitro, they transition through organizer states that spatially pattern the cortex before generating glutamatergic precursor fates. NSCs derived from multiple human pluripotent lines vary in these early patterning states, leading differentially to dorsal or ventral telencephalic fates. This work furthers systematic analyses of the earliest patterning events that generate the major neuronal trajectories of the human telencephalon.

Published
2020
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133. Coatings Based on Gelatin and Chitosan in the Conservation of Papaya (Carica papaya L.) Minimally Processed

Author

Silva, Kátia Gomes da, primary, Cavalcanti, Mônica Tejo, additional, Martinsa, Laesio Pereira, additional, Alves, Rita de Cássia, additional, Lucena, Fernando Azevedo de, additional, Santos, Max Suel Alves, additional, Silva, Samarone Xavier da, additional, Costa, Franciscleudo Bezerra da, additional, Moreira, Inacia dos Santos, additional, and Pereira, Emmanuel Moreira, additional

Published
2023
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141. Clinical features and prognostic factors of listeriosis: the MONALISA national prospective cohort study

Author

Hausfater, Pierre, Pourriat, Jean-Louis, Casalino, Enrique, Riou, Bruno, Pateron, Dominique, Yéni, Patrick, Bricaire, François, Ville, Yves, Azria, Elie, Dommergues, Marc, Bergmann, Jean-François, Wolff, Michel, Mira, Jean-Paul, Guillevin, Loïc, Zuber, Mathieu, Abasse, Soumeth, Aberrane, Saïd, Abgueguen, Pierre, Abokasem, Ayman, Abraham, Bruno, Ache-Papillon, Chantal, Adam, Pascal, Adam, Marie-Noëlle, Adhoute, Xavier, Adoue, Daniel, Afi, Moncef, Afroukh, Nawel, Agha-Mir, Ilhem, Aissa, Nejla, Aissaoui, Liamine, Akerman, Grégory, Akkari, Ali, Al Chaar, Majed, Al Freijat, Faraj, Al-Jalaby, Bachar, Albert, Didier, Albertini, Marie-Thérèse, Albinet, Hélène, Alfonsi, Gwenaël, Ali, Youssef, Chaouche, Zahr-Eddine Ali, Allart, Anne, Alric, Laurent, Améri, Alain, Amoura, Zahir, Ampère, Alexandre, Amroun, Hakim, Ananivi, Amévi, Ancelin, Pascal, André, Thierry, Andremont, Antoine, Andreotti, Dominique, Andriamaneo, Hélinoro, Andriau, Clara, Anglaret, Hélène, Anguel, Nadia, Annaix, Véronique, Anteur, Wassila, Anuset, Delphine, Aoudia, Ourida, Arabi, Miloud, Archambaud, Muriel, Archambaud, Maryse, Ardiet, Emmanuel, Argaud, Laurent, Arista, Sophie, Arlet, Guillaume, Armengaud, Jean, Arnal, Jean-Michel, Arnault, Isabelle, Arsène, Olivier, Assaf, Ziad, Assi, Assi, Assouline, David, Astruc, Dominique, Aubard, Yves, Aubert, Claude, Aubry, Jean-Paul, Auburtin, Marc, Aucher, Philippe, Audeguy, Philippe, Audié, Jean-Pierre, Aumaitre, Hugues, Aumersier, Michel, Auroux, Jean, Autret, Fanny, Auvray, Etienne, Ayach, Badih, Aye, Paul, Ayouz, Khélifa, Bachelier, Marie-Nadège, Badia, Thomas Bachelot Philippe, Badila, Patrice, Bador, Julien, Badurescu, Viorica, Baldesi, Olivier, Bandaly, Françoise, Bandin, Olivia, Bani-Sadr, Firouzé, Bannier, Stéphanie, Baranger, Thierry, Barazer, Isabelle, Barbier, Marie-Christine, Barbier, François, Barbier, Carole, Barbieux, Marianne, Marie, Barboteau, Annick, Barbut, Patricia, Baret, Mylène, Barière, François, Baril, Jean-Yves, Barillot, Isabelle, Barjon, Geneviève, Barnaud, Guilène, Barraduc, Régine, Barraud, Francis, Barraud, Olivier, Barre, Eric, Barrelet, Audrey, Barrier, Jocelyn, Bart, Fréderic, Barthélémy, Gérard, Baty, Gaëlle, Baud, Olivier, Baudel, Jean-Luc, Bay, Jacques-Olivier, Bay, Jérôme, Bazin, Claude, Beague, Sébastien, Beal Ardisson, Dominique, Beaune, Bertrand, Beauplet-Lepage, Anne, Bébéar, Cécile, Bechade, Dominique, Becherrawy, Céline, Becker-Schneider, Michelle, Bednarek, Nathalie, Bedock, Bernard, Begon, Edouard, Bekguesmia, Zaineb, Belaisch-Amart, Joëlle, Belhadj, Karim, Belle, Evelyne, Belmonte, Olivier, Belot, Jean-Pierre, Bemrah, Abdelkader, Ben Soltana, Mouna, Benbara, Amélie, Benddif-Fin, Faiza, Bénézit, François, Benifla, Jean-Louis, Benjelloul, Amine, Benkaci, Yacine, Benkhelil, Abdelaziz, Benoit-Cattin, Thierry, Benoit-Coustou, Sophie, Bensadoun, René-Jean, Bensaid, Thierry, Jacques Bensaude, Raoul, Bérard, Henri, Bercot, Béatrice, Berdin, Bruno, Berger, Marc, Berger, Pierre, Bergheul, Smail, Bergues, Benoît, Berland, Yvon, Bernard, Claude, Bernard, Louis, Bernardaud, Bérangère, Bernardi, Franck, Bernardin, Gilles, Bernasconi, François, Bert-Marcaz, Patrick, Berteaux, Béatrice, Berth-Farges, Anne, Berthelot, Gilles, Berthet, Jean, Bertrand, Kevin, Bertrou, Anne, Besnard, Marianne, Bessede, Emilie, Bethery, Philippe, Beuscart, Claude, Beyne-Rauzy, Odile, Beytout, Jean, Bezian, Marie-Christine, Bicais, Brigitte, Bidart, Sabine, Bidault, Christian, Biessy, Hélène, Bigot, Pierre, Bildea, Adrianna, Bille, Emmanuelle, Billy, Christophe, Biron, Nathalie, Bizet, Jérôme, Blaise, Didier, Blaise, Agathe, Blaison, Gilles, Blaka, Mariam, Blanc, Pierre, Blanc, Stéphane, Blanc-Amrane, Véronique, Blanchard, Pierre, Blanchard-Marche, Geneviève, Blancs, Michèle, Blazejewski, Caroline, Bléher, Yves, Blewoussi, Koffi, Blondet, Romain, Blot, François, Blum, Georges-Fabrice, Bodson, Lucien, Boidin, Emilie, Boileau, Julien, Boileau, Pascal, Boin-Gay, Véronique, Boisseau, Martial, Boisselier, Christine, Bollaert, Pierre-Edouard, Bolot, Pascal, Bonacorsi, Stéphane, Bonfils, Marie, Bonitchi, Pascal, Bonnan, Mickael, Bonnefoy, Philippe, Bonnet, Delphine, Bonnet, Richard, Bonnin, Emmanuelle, Bor, Jacques, Borie, Marie-Françoise, Borstein, Bernard, Bossi, Philippe, Botreau, Yves, Bottero, Julie, Bouasria, Abderrezak, Bouaziz, Radia, Bouchaud, Olivier, Bouche, Flore, Bouchet, Gérard, Bouden, Vincent, Boudhane, Amar, Boudy, Carole-Anne, Boue, François, Bouet, Cédric, Claude Boufetteau, Jean, Bouffandeau, Bernard, Bouhour, Damien, Bouiller, Marc, Bouillet, Laurence, Bouissou, Antoine, Boulain, Luc, Bourgeois, Stéphane, Bourgerette, Evelyne, Bourlet, Anne, Bourlière, Marc, Bourrée, Thomas, Bourrouillou, Aude, Boussekey, Nicolas, Boussier, Remi, Boutoille, David, Bouyer, Jean-Luc, Bouyssou-Destriau, Denise, Bouziges, Nicole, Boyer, Michelle, Braem, Louis, Branger, Bernard, Branger, Catherine, Brasme, Lucien, Bray, Philippe, Brazille, Patricia, Bresson, Violaine, Bret, Laurent, Breton, Anne-Laure, Breuil, Jacques, Brevet, Françoise, Briaud, Michel, Bridoux, Delphine, Briend, Delphine, Briere, Anne-Isabelle, de la Hosseraye, Claire Briere, Brieu, Nathalie, Brieux, Jean-Philippe, Brihier, Hélène, Brisou, Patrick, Brival, Marie-Laure, Broche, David, Brochen, Joëlle, Bron, Camille, Bronet, Nathalie, Bronner, Jacques, Bronowicki, Jean-Pierre, Brosset, François, Brottier-Mancini, Elisabeth, Brovedani, Sophie, Bruley des Varannes, Stanislas, Brunel, Pascale, Brunet, Patrick, Brunet, Xavier, Brunet, Stéphanie, Brung-Lefebvre, Maud, Brunot, Vincent, Brusset, Alain, Burc-Struxiano, Laurence, Burdin, Michèle, Bureau, Thierry, Buron, Fanny, Burucoa, Christophe, Cabalion, Jean, Cabasson, Severine, Cabié, André, Cacheux, Victoria, Cadiergue, Vincent, Cadiot, Guillaume, Caille, Vincent, Cailleaux Pierre-Etienne Cailleux, Vincent, Caillon, Jocelyne, Caillot, Denis, Camara, Mohamed, Cambau, Emmanuelle, Cambonie, Gilles, Camiade, Sabine, Canis, Frederique, Canitrot, Meriem, Canu, Nathalie, Capellier, Gilles, Carbillon, Lionel, Carbonelle, Bernard, Carbonelle, Etienne, Carboni, Marion, Carbonne, Bruno, Carcenac, Francis, Cardot, Florence, Carette, Sylvie, Cariou, Sylvie, Carli, Pierre, Carmagnol, Françoise, Caroli-Bosc, François-Xavier, Caron, François, Cartron, Guillaume, Casali, Patrick, Casanovas, Olivier, Cassignard, Dominique, Castaing, Denis, Castel, Brisse, Castelin, Sandrine, Castelnau, Pierre, Cathebras, Pascal, Catineau, Jean, Catteu, Sylviane, Cattier, Blandine, Cattoen, Christian, Cattoir, Vincent, Caumes, Eric, Caussin, Jean, Cavalié, François, Ceppa, Franck, Cerf, Charles, Ceriez, Anne, Cervantes, Nathalie, Chabanon-Pouget, Bruno, Chabrol, Amélie, Chachaty, Elisabeth, Chahtour, Hanen, Chaix, Fabrice, Challier, Marion, Chalvon-Demersay, Arnaud, Chambreuil, Guy, Chaminade, Bruno, Chamouine, Abdourahim, Chandesris Joséphine Chapalain-Cagnon, Christine, Chapelle, Alain, Chaplain, Chantal, Chapuzet, Claire, Charachon, Sylvie, Charasse, Christophe, Charbonnier, Thierry, Charlier, Franck, Chassin, Olivier, Chassy, Véronique, Chatellier, Delphine, Chatron, Marlène, Chaussade, Hélène, Chavanet, Pascal, Chavel, Pascale, Chekroun, Ali, Chelle, Wladimir, Chelly, Jonathan, Cherlet, Christel, Chevailler, Alain, Chevalet, Pascal, Chevalier, Yannick, Chidiac, Christian, Chimot, Loïc, Chiouk, Nabil, Chiron, Philippe, Chirouze, Catherine, Chopin, Marie-Charlotte, Choukroun, Gabriel, Chouraqui, Martine, Chraibi, Kamilla, Chudersky, Dominique, Chuzeville, Michel, Cingotti, Michel, Cinquetti, Gael, Ciocan, Dragos, Citony, Isabelle, Claise, Catherine, Clarissou-Philippe, Juliette, Claude, Benoît, Clave, Danielle, Clément, Christophe, Climas, Marie-Thérèse, Coetmeur, Daniel, Cognet, Stéphanie, Cohen, Daniel, Coignard, Sophie, Coindre, Jean-Philippe, Coint, Raphaël, Colamarino, Renato, Colingorski, Anne-Marie, Collard, Olivier, Collet, Michel, Collignon, Anne, Collus, Marie-José, Colombani, Jean-Claude, Colombat, Philippe, Combe, Christian, Condominas, Philippe, Conroy, Marie-Chrsitine, Constans, Thierry, Constantin, Nicole, Contamin, Claudine, Corberand, Damien, Cordier, Anne-Marie, Cordonnier, Charlotte, Corneloup, Hélène, Costa, Yannick, Costa, Frédérique, Coste, Mathieu, Costes, Corinne, Cotes, Françoise, Cotteret, Rabea, Couderc, Louis-Jean, Cougoul, Pierre, Coulaud, Jean-Michel, Coulhon, Marie-Pierre, Coulon, Patrice, Courcol, René, Courillon, Florence, Courjon, Johan, Courouble, Jérémie, Courouge-Dorcier, Dominique, Courtade, Henri, Courtois, Stéphanie, Couturier, Pascal, Créange, Alain, Cremet, Lise, Cremniter, Julie, Croize, Jacques, Crombe, Valérie, Croquet, Ingrid, Cua, Eric, Cufi, Marie-Noelle, Cuvillier, Patrice, Dabysing, Marie-Françoise, Dadoun, Karim, Dagada, Corinne, Dahan, Sonia, Dahoumane, Redouane, Daleas, Jacques, Dallay, Dominique, Dalle, Benoît, Damage, Alexandre, Damaj, Lena, Damaj Gandhi, Laurent, Danalaché, Ana, Danin, Pierre-Eric, Danjean, Marie-Pierre, Danquechin Dorval, Etienne, Dao, Anne, Daoud, Patrick, Darchen, Olivier, Dargère, Sylvie, Darre, Bincy, Dassant, Damien, Dassieu, Gilles, Dattin-Dorrière, Valérie, Daupin, Cedric, Daurel, Claire, Dausset, Jean-Claude, Daval Cote, Mélanie, David, Gary, Davido, Benjamin, De Barbeyrac, Bertille, De Biasi, Michel, De Boysson, Hubert, De Clareuil, Edith, De Kermadec, Jean-Michel, De Martino, Sylvie, De Tayrac, Renaud, De Varax, Roland, De Witte, Sten, Debernardi, Anne, Deboutin, Jean-Luc, Debouverie, Marc, Decoene, Christophe, Decoster, Anne, Decousser, Jean-Winoc, Decré, Dominique, Defebvre, Renaud, Degand, Nicolas, Degreff, Jean-Marc, Deiber, Michel, Delaby, Hélène, Delacour, Thierry, Delahaye, Arnaud, Delarbre, Jean-Marie, Delasalle, Chantal, Delbrouck, Claire, Delecalle, Jean-Gilles, Delesalle, Sophie, Delesalle, Chantal, Delhoustal, Laurence, Deligne, Delphine, Delisle Mizon, Françoise, Delobel, Pierre, Delour, Pierre, Delpeuch, Bruno, Demachy, Marie-Claude, Demarchi, Martin, Demarcq, Marie-Joelle, Demontclos, Henri, Dengo, Jean-Christophe, Deprecq, Sophie, Dequin, Pierre-François, Dereeper, Olivier, Deroux, Alban, Derragui, Aicha, Desblache, Julien, Desbois-Nogard, Nicole, Descamps, Dominique, Descamps, Jean-Michel, Deschamps, Christophe, Deschamps, Jacques, Desemerie, Franck, Desfrere, Luc, Desliers, Joelle, Desnoulez, Laurence, Desplaces, Nicole, Després, Nicolas, Dessin, Jean-François, Destors, Marie, Detante, Olivier, Detave, Mathieu, Detourmignies, Laurence, Devaud, Edouard, Devaux, Yves, Devaux, Bruno, Devianne, François, Devidas, Alain, Devos, Philippe, Dewitte, Camille, Dewulf, Gisèle, Dhennain, Chantal, Di Meglio, Chloé, Diallo, Habiboulaye, Diamantis, Sylvain, Dib, Baihas, Didier, Jean-Marc, Dillies, Anne-Françoise, Dingremont, Claire, Djafari, Noureddine, Djeffal, Abdelmajid, Djerad, Hama, Dollon, Christophe, Doloy, Alexandra, Domart, Yves, Donay, Jean-Luc, Dopeux, Loïc, Dorr, Gaelle, Doucet Populaire, Florence, Dournon, Nathalie, Dreyfus, Michel, Dreyfuss, Didier, Du Cheyron, Damien, Dubois, Elodie, Dubois, Nicolas, Dubosc-Marchenay, Nadine, Dubourdieu, Béatrice, Dubroca, Nadine, Dubus, Jean-Christophe, Duche, Catherine, Duchene, Francis, Dudeffant, Patrick, Duez, Jean-Marie, Duhaut, Pierre, Duluc, Françoise, Dumouchel, Hélène, Dumoulard, Bruno, Dupin, Clarisse, Dupon, Michel, Dupont, Mathieu, Dupont, Damien, Dupont, Patrick, Dupre-Narlet, Emmanuelle, Dupretz, Peggy, Dupuy, Claire-Antoinette, Durand, Michel, Durand, Annie, Durliat-Ellie, Solène, Durox, Hélène, Dussopt, Christine, Dutasta, Fabien, Duval, Véronique, Dzeing, Ella, Eboue, Florence, Ede, Cyrille, Eid, Hanna, El Yamani, Abderrazak, Elbez, Annie, Eldeghedy, Mohamed, Elena-Daumas, Martine, Elhadad, Simon, Elharie-Heraux, Zoubida, Eloy, Clarence, Emeriau, Marie-Etiennette, Emond, Jean-Philippe, Equy, Véronique, Erena-Penet, Anne-Sophie, Esnault, Cecilia, Esposito, Laure, Essouri, Sandrine, Estépa, Laurence, Estève, Vincent, Etchemendy, Sabine, Ettahar, Nicolas, Eustache, Marie-Line, Evillard, Mathieu, Evreux, Françoise, Eychene, Jean-Marc, Eyer, Didier, Eymerit, Philippe, Fabre, Jean-Luc, Fabre, Claire, Faibis, Frédéric, Falchero, Lionel, Falguières, Odile, Fallouh, Hassan, Fanjaud, Nicolas, Fantin, Bruno, Farah, Ibrahim, Farto-Bensasson, Fernanda, Fauchais, Anne-Laure, Fauchart, Jean-Pierre, Faucher, Anna, Faucheux, Jean-Marc, Faudon-Gibelin, Anne, Faurie, Pierre, Fèbre, Claudine, Feddal, Toufik, Ferhat Carre, Assia, Ferreira-Maident, Nicole, Ferreyra, Milagros, Ferroni, Agnès, Ferry, Tristan, Feugier, Pierre, Feugier, Jean-Claude, Fezoui, Hacene, Fiette, Hélène, Fille, Alexandra, Filloux, Jean-Michel, Fily, Fabien, Fines, Marguerite, Fissore Magdelein, Cristel, Flahault, Mathilde, Floriot, Christian, Foguem, Clovis, Fonsale, Nathalie, Fontenel, Benoît, Forest, Anne-Marie, Forest, Anne, Forestier, Emmanuel, Fortin, Louise, Fortineau, Nicolas, Fos, Marie-Pierre, Foucart, Saskia, Fouilhoux, Alain-Charles, Fournel, Pierre, Fournier, Damien, Fourrier, François, Fraisse, Thibaut, Fredenucci, Isabelle, Fremin-Batteux, Odile, Frey, Janine, Frimat, Luc, Froidure, Marie, Fruchart, Christophe, Fruleux, Nathalie, Fuhrmann, Christine, Fuillet, Michel, Funakoshi, Nathalie, Fur, Alain, Gabez-Therou, Patricia, Gaborieau, Valerie, Gabriel-Soléan, Sylvie, Gachassin, Laurence, Gaide, Jean-François, Gaillard, Julia, Gaillard, Jean-Louis, Gaillart, Tiphaine, Gaizi, Sad, Gallo, Nicolas, Gameiro, Manuel-Luis, Garandeau, Caroline, Garbi, Aurelie, Garcera, Yves, Gardes, Ghislaine, Garesslin, Olivier, Garnier, Fabien, Garofano, Marie, Garosi, Olivier, Garre, Michel, Garrec, Hélène, Garrigues, Bernard, Gaschet, Anne, Gascon, Alexandre, Gascou, Emmanuel, Gasnault, Jacques, Gatfosse, Marc, Gattault, Jean-François, Gatti, Hélène, Gauche, Bernard, Gaudard, Philippe, Gaudelus, Joel, Gaudry, Stéphane, Gauduchon, Valérie, Gaulthier, Jean-Baptiste, Gauthier, Yvan, Gebeile, Rémi, Geffray, Loïc, Geffroy, Françoise, Geissler, Alain, Gelez, Maud, Gendrin, Vincent, Gengembre, Guy, Gentilhomme, Hervé, Gérart Pons, Sandrine, Germain, Marie-Claude, Gesquière, Julien, Ghedira, Adel, Ghevaert, Christine, Gillot, Jean-Michel, Girard, Edouard, Girard, Serge, Girard, Pierre-Marie, Girard-Buttaz, Isabelle, Giraud, Martine, Glorieux, Isabelle, Goburdhun, Chandrah, Godin, Michel, Godon, Catherine, Goehringer, François, Goffart, Sylvie, Goidin, Isabelle, Goldgran Toledano, Daniele, Golfier, François, Goll, Armand, Gontieron, Olivier, Goquelin, Anne, Got, Laurence, Goudeau, Alain, Goujard, Cécile, Goupil, François, Gouraud, François, Gourlaouen, Alain, Gournay, Jérôme, Goustille, Julien, Goux, Alain, Grandclerc, Benoît, Grange, Jean-Didier, Granger, Thierry, Granier, Françoise, Granier, Michèle, Grasset, Denis, Gravet, Alain, Grawey, Isabelle, Greder Belan, Alix, Grelaud, Jean-Jacques, Grenet, Karine, Gressier, Bernard, Grignon, Bernadette, Grimprel, Emmanuel, Grise, Geneviève, Grobost, Vincent, Gross Goupil, Marine, Grossi, Olivier, Gruffat, Brigitte, Gruson, Anne, Guénard, Yves, Guérard, Arnaud, Guérin, Bruno, Guérin, Mathilde, Guérin, Claude, Guerquin, Bernard, Guerrot, Dominique, Guéry, Benoît, Gueudet, Philippe, Gueugniaud, Pierre-Yves, Guichard, Isabelle, Guichart, François, Guiden, Ozel, Guider, Bertrand, Guillarmé Grossmann, Pascale, Guillemot, François, Guillet, Pierre, Guillet-Caruba, Christelle, Guillois, Bernard, Guilloy, Olivier, Guimard, Thomas, Guimard, Karine, Guimier, Philippe, Guinard, Jérôme, Guinet, François, Guisset, Olivier, Guitteaud, Karine, Gutmann, Laurent, Guyetand, Severine, Haccourt, Fabian, Hacot, Jean-Pierre, Hadou, Tahar, Haiat, Stéphanie, Haioun, Corinne, Hajjar, Mostapha, Hamitou, Zakaria, Hammami, Sarah, Hamon-Charles, Sophie, Hamou-Plotkine, Laurence, Hanouz, Jean-Luc, Harbi, Samia, Harlé, Jean-Robert, Haro, Sophie, Harou, Christian, Harvey, Thierry, Hatem, Ghada, Hausermann, Marie-Hélène, Hauss, Pierre-Alexandre, Hayoun, Fabrice, Hecham, Moussa, Heches, Xavier, Hedjem, Nourredine, Heidt, Anne, Heisel, Nicolas, Heluwaert, Fréderic, Helvadjian, Thierry, Henni, Tawfiq, Henry-Andrieu, Yanne, Hequet, Delphine, Herbecq, Patrick, Herbrecht, Raoul, Hernu, Romain, Herry, Catherine, Herry, Jean-Paul, Herson, Serge, Heurtaux, Marie-Noelle, Heusse, Emmanuelle, Heyraud-Blanchet, Catherine, Hichri, Yoar, Hilbert, Gilles, Hili, Marie-Thérèse, Hiret, Sandrine, Hittinger, Gilles, Hochart, Anne-Cécile, Hodee, Nathalie, Holstein, Anne, Hombrouk-Alet, Cécile, Hominal, Stéphane, Honderlick, Patrick, Honoré Bouakline, Stéphanie, Hory, Bernard, Hourdebaigt-Larrusse, Pierre, Houssaye, Serge, Houssiaux-Maisonneuve, Nathalie, Hrichi, Abdelkader, Hubert, Didier, Huc, Benoît, Humbert, Karine, Hurel, Dominique, Husson-Wetzel, Stéphanie, Hutin, Pascal, Huttin, Bernard, Hyerle, Laura, Iacobelli, Silvia, Ilunga, Serge, Imbert, Guenièvre, Jabre-Sikias, Elias, Jacob, Jean-Louis, Jacobs, Romain, Jacomy, Dominique, Jacquier, Pascal, Jacquier, Hervé, Jaffarbandjee, Marie-Christine, Jamet, Angéline, Jan, Didier, Jang, Guyro, Jaouen, Anne-Christine, Jardel, Henry, Jarlier, Vincent, Jarrige, Luc, Jarrousse, Bernard, Jauhlac, Benoît, Jault, Véronique, Jault, Thierry, Jaunait, Eric, Javouhey, Etienne, Jean, Rodolphe, Jean, Julie, Jean-Pierre, Hélène, Jeanmaire, Eliette, Jeannot, Katy, Jeddi, Hassen, Jego, Mickael, Jennane, Selim, Join-Lambert, Olivier, Joly, Pascal, Jonquet, Olivier, Josien, Eric, Jouatte, Fabienne, Jouffret, Agnès, Jourde-Chiche, Noémie, Jourdes, Emilie, Jouvencel, Philippe, Jouzel, Charlotte, Julienne, Geneviève, Jullian, Eric, Juven, Agnès, Juvin, Philippe, Kaidomar, Michel, Kaiser, Thomas, Kalfon, Pierre, Kaltenbach, Georges, Kamar, Nassim, Kansau, Imad, Kara, Ali, Karaoui, Leila, Karirisi, Apollinaire, Karkous, Bernard, Kassis, Marie, Kayal, Samer, Keller, Marie, Kemenar, Chrystelle, Kennouche, Samir, Kerchache, Aissa, Kerleau, Jean-Marc, Kervegant, Anne-Gaelle, Khalifa-Thellier, Sandrine, Radhouane-Khanjari, Fethi, Kherouf, Hakim, Khodeir, Nordine, Kibbrecht, Eric, Kim, An, Kisterman, Jean-Paul, Kittschke, Bernard, Klapczynski, Frédéric, Kodzin, Marie-José, Konate, Bano, Kouaho, Sylvain, Koulmann, Laurence, Krechiem, Karim, Kubab, Sarah, Kubiak, Charles, Kurtz, Jean-Emmanuel, Labadie, Philippe, Labarrière, Damien, Labaune-Kiss, Andrea, Labé, Aurélie, Labourdette, Isabelle, Labrousse, Philippe, Labussière, Anne-Sophie, Lachenal, Florence, Lacroix, Jérôme, Lafeuillade, Alain, Lafforgue, Marie-Odile, Lafon, Ingrid, Lagasse, Jean-Pierre, Lagrandeur, Julien, Lalot, Jean-Marc, Lalu, Mélissa, Laluque, Simone, Lamache, Sébastien, Lamarca, Richard, Lamberet, Aurore, Lambert, Thierry, Lambiotte, Fabien, Lamia, Bouchra, Lamoine-Gimet, Ghislaine, Lamour, Armelle, Lamy, Brigitte, Lanba, Patrice, Landgraf, Nathalie, Landraud, Luc, Laporte, Jean-Patrick, Larible, Claire, Larrazet, Fabrice, Larroche, Claire, Lasbasses, Claudine, Lassel, Ludovic, Lassere, Bertrand, Laudat, Patrice, Lauque, Dominique, Laurens, Etienne, Laurent, Frédéric, Lauretta, Raphael, Laurin, Max, Lauzanne, Brigitte, Lavalard, Emmanuelle, Lavenu, Isabelle, Lavigne, Jean-Philippe, Le Baron, François, Le Berre, Rozenn, Le Berruyer, Pierre-Yves, Le Bideau, Marc, Le Boterff, Cécile, Le Chevallier, Sylvain, Le Coustumier, Alain, Le Du, Anne, Le Goff, Valérie, Le Henaff, Catherine, Le Lay, Geneviève, Le Maout, Gilles, Le Pierres, Athéna, Le Pimpec, Patricia, Le Poulain, Marguerite, Le Reste, Anne-Marie, Le Sec, Ludovic, Le Turdu, Françoise, Leautez-Nainville, Sophie, Lebas, Eddy, Leblond, Véronique, Lebreton, Marie-Annick, Lebreton, Didier, Lecaillon-Thibon, Evelyne, Lechat, Sylvie, Lechiche, Catherine, Lecis, Alain, Leclercq, Roland, Lecomte, Claire, Lécuyer, Hervé, Ledru, Sylvie, Leduc, Dominique, Leflon, Véronique, Lefort, Christine, Lefranc, Hélène, Lefrant, Jean-Yves, Legendre, Christophe, Legoff, Isabelle, Legout, Laurence, Legrand, Mathieu, Legras, Annick, Legros, Antoine, Leguen, Virginie, Leibinger, Franck, Lelièvre, Jean-Daniel, Lellouche, Franck, Lemaignen, Adrien, Lemarie, Romain, Lemble, Chantal, Lemenand, Olivier, Lemercier, Fanny, Lemery, Didier, Lemmens, Bruno, Lemyze, Malcolm, Leneveu, Michel, Léonetti, Françoise, Léonnet, Caroline, Léotard, Sophie, Lepeletier, Didier, Lepelletier, Didier, Lepeule, Raphael, Lepiller, Quentin, Lequen, Laurence, Leroux, Lionel, Leroux, Stéphane, Leroy, Hélène, Leroy, Vincent, Leroy, Olivier, Lesage, Fabrice, Lescat, Mathilde, Lesecq, Ludovic, Lessene, Aude, Lessinger, Jean-Marc, Letellier, Claire, Letellier, Nicolas, Letouzey, Vincent, Letranchant, Lorraine, Levast, Marion, Leveneur, Yann, Levent, Thierry, Levy, Marie, Levy, Marc, Leysenne, David, Libeau, Benoît, Likose, Ebutu, Lima, Suzanne, Lina, Gérard, Lioger, Bertrand, Lionnet, Benoît, Lipovac, Anne-Sophie, Loffeier, Vincent, Loison, Françoise, Lorchleac'h, Aurélien, Lorge, Fabienne, Loriferne, Jean-François, Lorléa'ch, Aurélien, Louart, Guillaume, Loury-Lariviere, Isabelle, Loustaud, Véronique, Lozniewski, Alain, Luciani, Roger-Charles, Luminitan Elena Lupean, Luca, Lureau, Pierre, Lutz-Murphy, Marie-France, Mbimba, Luwawu, M'Bey, Damien, Maakaroun, Abdallah, Macci, Valérie, Magdoud, Fatma, Mager, Guy, Magna, Théophile, Magny, Jean-François, Mahaza, Chetaou, Mahé, Isabelle, Maillard, Christine, Maillet, Jean-Jacques, Maillet, François, Maillez, Sébastien, Maillot, François, Maisonneuve, Antoine, Makdessi, Solène, Malbrunot, Claire, Malbruny, Brigitte, Malderet, Caroline, Malfuson, Jean-Valère, Malherbe, Philippe, Malherbe, Patrick, Malhiere, Sophie, Mandelbrot, Laurent, Mandin, Laurent, Mandjee, Aziza, Manéglier, Benjamin, Mansouria, Mohammed, Marcu, Elena, Mariette, Jean-Bernard, Mariette, Sylvie, Markarian, Jacques, Marmouset, Carole, Marpeau, Olivier, Marret, Olivier, Marsepoil, Thierry, Marterl-Lafay, Isabelle, Martha, Benoît, Marthelet, Patrick, Martin, Xavier, Martin, Florence, Martin, Pierre, Martin, Régine, Martin, Christian, Martin Lefèvre, Laurent, Martineau, Olivier, Martinet, Olivier, Martinez, Valérie, Martinot, Martin, Martres, Pascale, Marty, Sophie, Marty-Ane, Charles, Marzouk, Paul, Mascade, Géraldine, Masia, Florent, Masseron, Thierry, Masson, Loïc, Masson, Philippe, Matheron, Isabelle, Matica, Slavius, Matray, Olivier, Mattei, Marie-Françoise, Maubert, Bertrand, Maugein, Jeanne, Maureira, Juan-Pablo, May, Thierry, May, Adrien, Maze, Vincent, Meaudre Desgouttes, Eric, Mebazaa, Alexandre, Mechai, Frédéric, Medeau, Virginie, Megbemado, Richard, Mehri, Mona, Mein-Bottini, Myriam, Melis, Adrien, Mellier, Joelle, Ménager, Philippe, Ménard, Céline, Mendes-Martin, Lucile, Menguy, Anne-Claude, Menouar, Mohamed, Merabet, Taoufik, Mercury, Paul, Meregnani, Corinne, Mérigot, Philippe, Mermont, Sylvain, Merrouche, Yacine, Merville, Pierre-Gilles, Mesnage, Renaud, Mesnard, Louis, Messager, Aurélie, Messiaen, Thierry, Messika, Jonathan, Messner Pellenc, Patrick, Métenier, Hervé, Metton, Pierre, Meyer, Christian, Mialon, Michel, Miatello, Jordi, Michaud-herbst, Alban, Michault, Alain, Micheli, Sophie, Michon, Jocelyn, Baptiste Michot, Jean, Mielczarek, Severine, Mignart, Sophie, Mignaut, Virginie, Migraine Bouvagnet, Audrey, Mihout, Fabrice, Mille, Catherine, Millet, Olivier, Milpied, Noel, Mimoz, Olivier, Minet, Jacques, Minguet, Bertrand, Mohty, Mohamad, Moiton, Marie-Pierre, Monarchi, Richard, Monceau, Yannick, Monchi, Mehran, Monlun, Eric, Monsegu, Jacques, Montagne, Nathalie, Montcriol, Ambroise, Montmasson, Bernard, Mootien, Paramasiven, Moquet, Olivier, Morando, Virginie, Moreau, Anne-Sohie, Morel, Yves, Morelon, Emmanuel, Morin-Fatome, Armelle, Morincomme, Mathieu, Morlat, Philippe, Mosser, Laurent, Motard-Picheloup, Annie, Mottaz, Philippe, Moulinoux, Claire, Mouly, Laurence, Mourad, Georges, Mouries, Jean-Claude, Moussa, Hecham, Moustache, Audrey, Muir, Jean-François, Murbach, Valérie, N'guyen, Yohann, N'guyen, Jean-Claude, N'guyen-Khac, Florence, Nabholtz, Jean-Marc, Naceur, Tarik, Nakhleh, Jean, Nare, Aline, Nassif, Xavier, Nathan-Bonnet, Frédérique, Negrery, Huguette, Negrier, Claude, Neri, Dominique, Nesrine, Hakima, Neuwirth, Catherine, Ngami, Eugène, Carole Ngo Bell, Elisabeth, Nicobaharaye, Dieudonné, Nicolet, Laurent, Nicolet, Laurence, Nicolino, Marc, Niel, Philippe, Nikodijevic, Karine, Nkunzimana, Jean-Marie, Noel, Christian, Noirot, Alain, Noto, Philippe, Noulard, Marie-Noelle, Ntalu Nkato, Christophe, Nyunga, Martine, Obiols, Julien, Ochocki, Patrick, Odent, Sylvie, Olivier, Brigitte, Oliviero, Gérard, Ondze, Basile, Orléva, Oléna, Orode, Paul, Osman, Henri, Oswald, Eric, Otean, Paola, Ouazir, Abderkader, Ozanon, Christophe, Paccalin, Marc, Pages, Marie-Christine, Paindaveine, Bénédicte, Pangon, Béatrice, Pannecouck, Jean-Marie, Paquet, Jean-Christophe, Parent, Sabrina, Parisi-Duchene, Elisabeth, Pasche, Jérôme, Pasdeloup, Thierry, Patin, David, Patrigeon, René-Gilles, Patry, Isabelle, Paul, Jean-Gabriel, Pavel, Simona, Pavic, Michel, Pawlotsky, Jean-Michel, Payan, Christopher, Payen, Christiane, Péan, Yves, Péchinot, Frédérique, Péchinot, André, Pecquet, Matthieu, Pélaquier, Agnès, Peltier, Hervé, Penn, Pascale, Pennaforte, Jean-Loup, Perez, Didier, Périsson, Caroline, Perotin, Dominique, Perouse de Montclos, Michèle, Perreve, Sophie, Perronne, Christian, Perrotin, Dominique, Pesque, Valerie, Pestel-Caron, Martine, Pestre, Vincent, Petassou, Fabrice, Petit, Marie-Cécile, Petit Hoang, Camille, Petitjean, Philippe, Pettinelli, François, Peultier, Anne-Sophie, Piala, Jean-Marie, Pialoux, Gilles, Piau, Caroline, Picard, Aurélia, Picaud, Jean-Charles, Pichard, Eric, Pierre, Martin, Pierre, Fabrice, Pierrot, Paul, Piet, Emilie, Piffaut, Marie-Claude, Pigeon, Bertrand, Pignon, Carole, Pinon, Georges, Piquet, Jacques, Piriou, Vincent, Placidi, Eric, Plainfosse, Gillles, Plane, Christophe, Plantier, Isabelle, Claudiu-Plesa, Nicolai, Plésiat, Patrick, Plessis, Patrick, Plouzeau-Jayle, Chloé, Ploy, Marie-Cécile, Pochmalicki, Gilbert, Pofelski, Joanna, Poinsignon, Yves, Poirier, Anne-Sophie, Poitevin, Françoise, Pommier, Christian, Ponceau, Bénédicte, Poncelet, Christophe, Pop, Daniela, Porcheron, Martine, Pordes, Réginald, Porthault, Eric, Portneuf, Marc, Pottier, Anne, Pouedras, Pascal, Poulain, Jocelyne, Poulain, Gérard, Poupet, Hélène, Pouyanne, Julien, Pouzoullic, Marie, Poyart, Claire, Pozzetto, Bruno, Prazuck, Thierry, Pressac, Dominique, Prévost, Fabrice, Prince, Sylvie, Priollet, Pascal, Proost, Olivier, Protar, Daniel, Pujade Lauraine, Eric, Pujol, Antoine, Puybasset, Louis, Puyhardy, Jean, Quentin, Vincent, Quinsat, Denis, Rabier, Valérie, Radaoui, Fouzia, Radenac, Florian, Radenne, Sylvie, Raffenot, Didier, Raffi, François, Rahmani, Hassène, Ramanantsoa, Céline, Ranchon, Guillaume, Ranta, Dana, Raoult, Didier, Rasigade, Jean-Philippe, Rassiat, Emmanuel, Raulin, Olivia, Ravaud, Alain, Ravet, Nathalie, Razafimahefa, Hasinrina, Razafimahery, Mirana, Re, Daniel, Real, Philippe, Rebattu, Paul, Rebeyrotte, Catherine, Reboul, Pascal, Reboux, Anne-Hélène, Recule, Christine, Redonnet, Jean-Philippe, Redor, Alexis, Regouby, Yves, Rémy, Claude, Renard, Gisèle, Renard, Benoît, Renou, Frédéric, Repellin, Philippe, Reveil, Jean-Claude, Revel, Valérie, Reverseau, Anne, Revest, Mathieu, Rey, Philippe, Rey, Hyacine, Rey Zermati, Jany, Reyes Ortega, Guillermo, Reynaud, Alain, Reynes, Jacques, Rezgui, Nasseur, Riahi, Jacques, Ribes, David, Ribier, Arnaud, Richard, Christian, Richardin, Florence, Riche, Agnès, Richette, Pascal, Ridah, Khalid, Riegel, Philippe, Riehl, Frédéric, Rigaux, Françoise, Rioux, Christophe, Rival, Gilles, Rivière, Brigitte, Robert, Henri, Robert, René, Robillard, Pierre-Yves, Roblin, Mélanie, Roblot, Pascal, Roblot, France, Rogeaux, Olivier, Roger, Pierre-Marie, Rohmer-Heitz, Dominique, Rolland, Christophe, Roncato-Saberane, Mariam, Ronda, Isabelle, Rondepierre, Philippe, Roque-Afonso, Anne-Marie, Rosay, David, Rose, Christian, Roseau, Jean-Baptiste, Rosello, Sophie, Rosselli, Sylvène, Rossignol, Serge, Rostaing, Lionel, Roth, Christian, Rothe, Marie-Rose, Roubert, Xavier, Rouget, Sébastien, Rouidi, Ahmed, Roulier, Philippe, Rouquet, Yannick, Rouquette-Vincent, Isabelle, Roure Sobas, Chantal, Rousseau, Sylvaine, Rousseau, Florence, Roussel, Etienne, Roussel, Jean-Christian, Roussel, Christophe, Roussellier, Patricia, Roy, Christophe, Royer, Daniel, Roze, Jean-Christophe, Rozec, Bertrand, Ruimy, Raymond, Ruppé, Etienne, Ruyer, Olivier, Sabbat, Sébastien, Saghi, Tahar, Saigne, Christophe, Sakek, Necera, Salama, Gilles, Salanoubat, Celia, Salaun-Beretta, Guenaelle, Saliba, Elie, Salles, Gilles, Salmon, Odile, Louis Salomon, Jean, Salord, Jean-Michel, Salvucci, Marina, Samson, Thierry, Sanchez, Richard, Sansot, Dominique, Saplacan, Mihaela, Saroufim, Carlo, Sauder, Philippe, Sautereau, Denis, Savare, Ferdinand, Savatier, Rim, Scemla, Anne, Schendel, Adeline, Schmitt, Anna, Schmitt, François, Schmitt, Alain, Schneerson, Morgane, Schneider, Francis, Schved, Jean-François, Schwebel, Carole, Sebban, Anthony, Secher, Aline, Sédillot, Nicholas, Sedjelmaci, Yacine, Segonds, Christine, Seignovert, Camille, Seknazi, Corinne, Semenescu, Marius, Sément, Arnaud, Semet, Jean-Claude, Semet, Guy, Sennevile, Eric, Serier, Miloud, Serre, Arnaud, Seta, Nathalie, Seyrig, Jacques-Arnaud, Sgro, Eric, Sibony-Prat, Joyce, Sicsic, Jean-Luc, Sifaoui, Farid, Signouret, Thomas, Sigur, Nicolas, Silhadi, Souad, Siméoni, Umberto, Simian, Bernard, Similowski, Thomas, Simon, Georges, Simon, François, Simonin, Catherine, Sirbu, Cristina, Sire, Jean-Marie, Sivadon-Tardy, Valérie, Sivery, Bruno, Slama, Michel, Smati, Salim, Sobesky, Rodolphe, Sokeng-Affoule, Hélène, Sollet, Jean-Pierre, Sommabère, André, Sondag, Daniel, Soraudeau, Florence, Sotto, Albert, Soulie, Bruno, Souply, Laurent, Souquet, Jean-Christophe, Soury, Pierre, Souweine, Bertrand, Stahl, Jean-Paul, Steibach, Marie-Isabelle, Stephan, Robin, Stoclin, Annabelle, Stolidi, Philippe, Strock, Paul, Suatean, Diana, Subra, Jean-François, Sucin, Yves, Suel, Philippe, Sullice, Marc, Szwebel, Tali-Anne, Tacchini, Laurent, Talabani-Boizot, Hana, Talarmin, Jean-Philippe, Taleb, Fethi, Tamalet, Catherine, Tamion, Fabienne, Tandonnet, Olivier, Tankovic, Jacques, Tardy, Véronique, Tassot, Christelle, Taurin, Gregory, Taylor, Sabine, Tchenio, Xavier, Tebib, Jacques, Teillet, Laurent, Teixeira, Antonio, Terki, Mustapha, Tesseydre, Sonia, Texier, Jean-Claude, Texier, Anthony, Thellier, Jean-Paul, Thibaud, Didier, Thibault, Michel, Thibaut, Freddy, Thierry, Jacques, Thoinet, Sylvie, Thomas, Pierre, Thomas, René, Thomas, Yves, Thomas, Caroline, Thore, Jean, Thouret, Jean-Marc, Thouvenin, Maxime, Thuet, Francis, Tigaizin, Ahmed, Tigaud, Sylvestre, Tiry, Catherine, Tissieres, Pierre, Tissot, Alain, Tixier, Anne, Touati, Kamel, Toubia, Marie-Lina, Toullalan, Olivier, Tourani, Jean-Marc, Tourrand, Bernadette, Touze, Yvan, Trabelsi-Jnifen, Asma, Traissac, Laurent, Anh Tran, Tu, Tran, Vanessa, Tricoire, Joelle, Tronchon, Laurent, Trouiller, Sébastien, Trystram, David, Ahmed, Becaid, Tsouria, Tuca, Mirela, Turpin, Mathilde, Vache, Bernard, Vachée, Anne, Vaillant, Christine, Valadier, Patrick, Valayer, Patrick, Valette, Xavier, Vallet, Françis, Van de Velde, Florence, Vanden Einjden, Serge, Vandenesch, François, Vande-perre, Philippe, Varin, Marie-Christine, Vary, Gwenaelle, Vaschalde, Yvan, Vassallo, Matteo, Vasse, Marc, Vasseur, Manica, Vatan, Rémi, Vaucel, Jacques, Vergnaud, Michel, Verhaeghe, Annick, Vermesch-Langlin, Annie, Vernet, Guy, Vernet Garnier, Véronique, Verrier, Virginie, Vessieres, Annie, Vialette, Véronique, Viard, Jean-Paul, Vieillard Baron, Antoine, Vighetto, Alain, Villemain, Marc, Villers, Daniel, Vilque, Jean-Pierre, Vinay, Agnès, Vincent, Didier, Vincent, Pascal, Vincent, Colette, Vincent, Simon, Vinci, Clara, Viole, Didier, Violette, Jérémie, Viquesnel, Gerard, Virlouvet, Anne-Laure, Visentin, Séverine, Vittecoq, Daniel, Vodovar, Dominique, Vrigneaud, Laurence, Vu-Thien, Hoang, Vuotto, Fanny, Wafo, Estelle, Wagner, Michel, Walid, Nicola, Walter, Elisabeth, Watson, Sarah, Weinbreck, Pierre, Weinbronn, Eva, Weiss, Emmanuel, Weitten, Thierry, Welker, Yves, Westeel, Pierre-François, Wink, Olivier, Wintenberger, Claire, Woerther, Paul-Louis, Worcel, Isabelle, Wuillai, Anne, Wurmser, Marc, Xavier, Jacob, Yazdanpanah, Yazdan, Yehia, Aihem, Yvenou, Sterenn, Zagdoun, Elie, Zagozda, Dominique, Zame, Thierry-Pascal, Zamfiri, Oana, Zanaldi, Hélène, Zandecki, Marc, Zaoui, Eric, Zarrouk, Virginie, Zarski, Jean-Pierre, Zavadil, Patrick, Zeller, Valérie, Zerbib, Franck, Zerr, Vincent, Zgarni, Lémia, Zoulim, Fabien, Zoveda, Patrick, Zuber, Pierre, Zumbo, Christian, Charlier, Caroline, Perrodeau, Élodie, Leclercq, Alexandre, Cazenave, Benoît, Pilmis, Benoît, Henry, Benoît, Lopes, Amanda, Maury, Mylène M, Moura, Alexandra, Goffinet, François, Dieye, Hélène Bracq, Thouvenot, Pierre, Ungeheuer, Marie-Noëlle, Tourdjman, Mathieu, Goulet, Véronique, de Valk, Henriette, Lortholary, Olivier, Ravaud, Philippe, and Lecuit, Marc

Published
2017
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142. Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs

Author

Burke, Emily E., Chenoweth, Joshua G., Shin, Joo Heon, Collado-Torres, Leonardo, Kim, Suel-Kee, Micali, Nicola, Wang, Yanhong, Colantuoni, Carlo, Straub, Richard E., Hoeppner, Daniel J., Chen, Huei-Ying, Sellers, Alana, Shibbani, Kamel, Hamersky, Gregory R., Diaz Bustamante, Marcelo, Phan, BaDoi N., Ulrich, William S., Valencia, Cristian, Jaishankar, Amritha, Price, Amanda J., Rajpurohit, Anandita, Semick, Stephen A., Bürli, Roland W., Barrow, James C., Hiler, Daniel J., Page, Stephanie C., Martinowich, Keri, Hyde, Thomas M., Kleinman, Joel E., Berman, Karen F., Apud, Jose A., Cross, Alan J., Brandon, Nicholas J., Weinberger, Daniel R., Maher, Brady J., McKay, Ronald D. G., and Jaffe, Andrew E.

Published
2020
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143. Femtosecond Laser Ablation–Inductively Coupled Plasma Mass Spectrometry (fsLA-ICP-MS) for Direct Elemental Analysis of Rice.

Author

Kim, Seyeon, Shin, Hee-Chang, Kim, Hyoyoung, Hur, Suel Hye, Kim, Namkuk, Park, Sang Un, Kim, Ho Jin, and Kim, Yong-Kyoung

Subjects
FEMTOSECOND pulses, LASER ablation inductively coupled plasma mass spectrometry, INDUCTIVELY coupled plasma mass spectrometry, FEMTOSECOND lasers, ELEMENTAL analysis, TIME complexity, RICE
Abstract

Easy, safe, and rapid quantitative methods to determine trace elements in agricultural products are required for efficient food safety management. Microwave-assisted digestion is traditionally used for trace elements in agricultural samples and accurate results and high selectivity are obtained. However, this procedure involves sample preparation, mixing, and extraction, which increases the time and complexity. Here we present femtosecond laser ablation–inductively coupled plasma mass spectrometry (fsLA-ICP-MS) to quantify arsenic, cadmium, and lead in rice. The recoveries by fsLA-ICP-MS for As, Cd, and Pb were 118.1%, 96.9%, and 87.1%, respectively, and 102%, 96.9%, and 107% by ICP-MS. The results by these techniques correlated well (>0.94) with the previously determined concentrations. The results confirm that fsLA-ICP-MS may be used to quantify trace elements in rice and is a promising, inexpensive, and easy-to-use alternative to traditional methods for food analysis. [ABSTRACT FROM AUTHOR]

Published
2024
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146. Coatings Based on Gelatin and Chitosan in the Conservation of Papaya (Carica papaya L.) Minimally Processed

Author

Pereira, Kátia Gomes da Silva, Mônica Tejo Cavalcanti, Laesio Pereira Martinsa, Rita de Cássia Alves, Fernando Azevedo de Lucena, Max Suel Alves Santos, Samarone Xavier da Silva, Franciscleudo Bezerra da Costa, Inacia dos Santos Moreira, and Emmanuel Moreira

Subjects
blend, layer-by-layer, edible toppings, minimally processed, postharvest
Abstract

Minimally processed fruits undergo changes that require careful monitoring. This study aimed to assess the effectiveness of edible coatings based on chitosan and gelatin using various application techniques for minimally processed papayas. The treatments included: control (distilled water), 1% chitosan, 4% gelatin, 1% chitosan + 4% gelatin (blend), and 1% chitosan with a 4% gelatin undercoat (layer-by-layer). The coatings’ infrared spectroscopies (FTIR) were analyzed, and the fruits’ fresh mass, firmness, pulp color (L*, a*, b*, and hue angle), pH, titratable acidity, soluble solids, ascorbic acid, phenolic compounds, lycopene, β-carotene, total sugars, and catalase activity were measured. The results revealed that gelatin and the layer-by-layer treatment positively influenced the preservation of minimally processed papaya. These coatings effectively reduced fresh mass loss while maintaining firmness and the characteristic orange color of the mesocarp. Furthermore, the treated samples consistently exhibited low soluble solids content during the storage period, with minimal variations in acidity, thereby influencing the maturation process. Gelatin coatings demonstrated low polyphenol content, while the layer-by-layer treatment showed no significant changes in vitamin C levels. Lycopene and β-carotene levels remained stable throughout the storage period, with a slight increase observed in total sugars. Consequently, the application of gelatin polymers and the undercoat treatment (LBL) represents a viable alternative for extending the shelf life of minimally processed papayas for at least eight days.

Published
2023
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148. Pesquisa qualitativa no contexto da Educação no Brasil

Author

Marcos Suel Zanette

Subjects
Pesquisas em Educação, Pesquisa qualitativa, Entrevista., Theory and practice of education, LB5-3640
Abstract

RESUMO Neste artigo foi feita, a partir de dados historiográficos, uma investigação sobre o tema “pesquisa no contexto da educação brasileira”. Para a realização deste trabalho empírico bibliográfico, perpassou-se pelos textos publicados que versam sobre o início das pesquisas em Educação no Brasil e das reflexões sobre metodologias das pesquisas qualitativas nos trabalhos acadêmicos. O texto destaca que o dispositivo entrevista individual ou em grupo, como instrumento para construir achados de campo, é uma ferramenta apropriada para compreender os dizeres dos entrevistados no processo da descrição do objeto da investigação pedagógica em educação.

Published
2017
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149. Effect of an Organo-Modified Montmorillonite on the Barrier Properties of PET Nanocomposites Using a Polyester Ionomer as a Compatibilizing Agent

Author

Suel Eric Vidotti, Anne Cristine Chinellato, Guo-Hua Hu, and Luiz Antonio Pessan

Subjects
PET nanocomposite, Organoclay, Polyester ionomer compatibilizer, Barrier properties, Permeability, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Poly(ethylene terephthalate)/organically modified montmorillonite (PET/o-Mt) nanocomposites were prepared via melt intercalation in a twin-screw extruder using a polyester ionomer (PETi) as compatibilizer. The o-Mt content used was 0, 1, 3 or 5 wt% and the compatibilizer/o-Mt mass ratio was 0/1, 1/1 or 3/1. The main objective was to study the effects of the addition of o-Mt and compatibilizer on the barrier properties of PET/o-Mt nanocomposites. The nanocomposites showed a significant reduction in CO2 permeability of up to 50% when compared to the neat PET, without significant change in the CO2 solubility revealing the importance of the diffusional path imputed by the organoclay on the overall permeation process. Water vapor permeability was reduced for all nanocomposites, achieving up to 30% reduction for the nanocomposite containing a compatibilizer/o-Mt mass ratio of 1/1. Overall, the nanocomposite containing 5 wt% of organoclay and compatibilizer/o-Mt mass ratio of 1/1 showed the best barrier properties.

Published
2017
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